CN104616208A - Model predication control based cooling heating and power generation type micro-grid operation method - Google Patents

Abstract

The invention discloses a model predication control based cooling heating and power generation type micro-grid operation method. The method comprises the steps of building a predication model to predicate the wind power, photovoltaic power and cooling heating power generation load power data within a control time domain in the future; solving a rolling optimizing model at every moment according to the latest predication result and the real-time operation state of each device; calculating the force output of each device at the following time quantum; re-calculating the rolling optimizing model at the next time according to the latest predication result, monitoring the actual wind power value, photovoltaic value, cooling load value, heating load value and power generation load value on real time; updating the historic data; solving and feeding back to correct the model at every 5 minutes to obtain the adjustment of each device; distributing to each device for adjusting until reaching the next rolling optimizing time. With the adoption of the method, the influence of inaccurate predication on the optimal operation of the system can be removed well, thus the system operation risk is reduced, and the system operation stability is improved; meanwhile, the economy of the operation of a cooling heating and power generation type micro-grid can be increased.

Description

A kind of supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control

Technical field

The invention belongs to cold, heat and power triple supply system field, specifically, relate to a kind of supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control.

Background technology

At present, take natural gas as the clean energy resource of representative, use with regenerative resource and be combined with each other, and utilize generator waste heat overbottom pressure, together constitute supply of cooling, heating and electrical powers type micro-capacitance sensor, become the outer fast-developing cleaning new energy industry of Now Domestic.Supply of cooling, heating and electrical powers type micro-grid system is arranged on user side nearby with various ways such as small-scale, low capacity, modularization and distributings, the energy supply system of user to cold energy, heat energy, electrical energy demands can be met simultaneously, save tradition and concentrate the initial outlay cost of energy induction system and reduce energy loss in transmitting procedure.Supply of cooling, heating and electrical powers type micro-grid system take clean energy resource as main fuel, can reduce the pollutant emissions such as oxides of nitrogen, sulphuric dioxide, solid particle, greatly reduces the pressure that environment worsens.

Supply of cooling, heating and electrical powers type micro-capacitance sensor optimizing operation method is basis operation plan instruction operation a few days ago mostly, can realize the economical operation of system to a certain extent.But, exert oneself due to renewable power supply and there is the feature such as undulatory property, intermittence, add that the electricity consumption behavior of user has more randomness, often there is deviation in the predicted value of load and renewable power supply power and actual value, cause actual conditions often to depart from operation plan a few days ago, have a strong impact on supply of cooling, heating and electrical powers type micro-capacitance sensor optimizing operation.

Summary of the invention

Technical matters: technical matters to be solved by this invention is: a kind of supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control is provided, the impact because forecasting inaccuracy causes system cloud gray model can be eliminated well, ensure what system operating instructions always calculated in the optimization of up-to-date information, reduce the risk of system cloud gray model, improve the stability of system cloud gray model, improve the economy that supply of cooling, heating and electrical powers type micro-capacitance sensor runs simultaneously.

Technical scheme: for solving the problems of the technologies described above, a kind of supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control that the present invention proposes, comprises the following steps:

Step 10) set up parametric prediction model, comprise wind-powered electricity generation forecast model, photovoltaic forecast model, cooling load prediction model, heat load prediction model and electric load forecast model; According to each parametric prediction model, in the k moment, according to n the historical data gathered before the k moment, utilize each parametric prediction model, following wind power, photovoltaic power, refrigeration duty power, thermal load power and the electric load power controlled in time domain M of prediction; Historical data comprises wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power;

Step 20) according to step 10) control in time domain M wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power in future of obtaining, set up such as formula the rolling optimization model shown in (1) to formula (12):

First determine with micro-grid system operating cost minimum for objective function, shown in (1):

$\mathrm{MinC}=\underset{t=k+1}{\overset{k+M}{\mathrm{\Σ}}}{C}_{\mathrm{ng}}^t+C_{\mathrm{om}}^t+C_{\mathrm{eb}}^t$ Formula (1)

In formula, C represents system operation cost; K represents current time; M represents control time domain; the fuel cost of expression system t period; the operation expense of expression system t period; represent t period and the mutual cost of electrical network;

Then determine constraint condition, comprise cold energy balance, thermal energy balance, electric energy balance and equipment and run constraint condition:

Cold energy equilibrium constraint is determined according to formula (5):

$P_{\mathrm{ac}}^t\·{\mathrm{COP}}_{\mathrm{ac}}+P_{\mathrm{ec}}^t\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c^t$ Formula (5)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; represent t cooling load of the air-conditioning system power, unit: kW;

Thermal energy equilibrium constraint is determined according to formula (6):

$P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+P_b^t-(P_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t)=P_{\mathrm{ac}}^t+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}$ Formula (6)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger;

Electric energy balance constraint condition is determined according to formula (7):

$P_{\mathrm{pv}}^t+P_{\mathrm{wt}}^t+P_{\mathrm{mt}}^t+P_g^t-(P_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t)=P_{\mathrm{ec}}^t+P_{\mathrm{el}}^t$ Formula (7)

In formula, represent the predicted value of photovoltaic t period; represent the predicted value of wind-powered electricity generation t period; represent the electric power of miniature gas turbine t period, unit: kW; expression system t period and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; represent t period system electric load power, unit: kW;

Determine that miniature gas turbine runs constraint condition according to formula (801) and formula (802), its Chinese style (801) is miniature gas turbine running status constraint condition; Formula (802) represents gas turbine unit Climing constant condition, comprises Unit Commitment Climing constant and runs Climing constant continuously:

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }$ Formula (801)

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^d+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{off}}\≤P_{\mathrm{mt}}^t-P_{\mathrm{mt}}^{t-1}\≤U_{\mathrm{mt}}^{t-1}\·P_{\mathrm{mt}}^u+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{on}}$ Formula (802)

In formula (801), represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine is shut down; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum when continuous running status of micro-gas-turbine unit: kW; represent miniature gas turbine t-1 period running status variable; to represent when micro-gas-turbine unit is shut down maximum falls power, unit: kW; represent the electric power of miniature gas turbine t-1 period, unit: kW; represent most the increase power of micro-gas-turbine unit when continuous running status, unit: kW; represent the power that increases most when micro-gas-turbine unit starts, unit: kW;

The constraint condition that gas fired-boiler runs is determined according to formula (9):

$P_b^{\min }\≤P_b^t\≤P_b^{\max }$ Formula (9)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW;

The constraint condition of the mutual power of electrical network is determined according to formula (10):

$P_g^{\min }\≤P_g^t\≤P_g^{\max }$ Formula (10)

In formula, the lower limit of expression system and the mutual power of major network, unit kW; the upper limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW;

The constraint condition that accumulator runs is determined according to formula (11):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t\≤0\\ 0\≤P_{c,\mathrm{bt}}^t\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ U_{\mathrm{disc},\mathrm{bt}}^t+U_{c,\mathrm{bt}}^t\≤1\\ W_{\mathrm{bt}}^{t+1}=W_{\mathrm{bt}}^t\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}{P}_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·\mathrm{\Δt}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t+1}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (11)

In formula, represent the discharge condition of accumulator t period, represent battery discharging; represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; represent the charge power of accumulator t period, unit: kW; represent the charged state of accumulator t period, represent charge in batteries; represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; represent the energy of t+1 period in accumulator, unit: kWh; represent the energy of t period in accumulator, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t represents the time interval;

The constraint condition that heat storage tank runs is determined according to formula (12):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t\≤0\\ 0\≤P_{c,\mathrm{tst}}^t\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ U_{\mathrm{disc},\mathrm{tst}}^t+U_{c,\mathrm{tst}}^t\≤1\\ W_{\mathrm{tst}}^{t+1}=W_{\mathrm{tst}}^t\·(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}{P}_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·\mathrm{\Δt}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (12)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent the accumulation of heat power upper limit of heat storage tank, unit kW; represent the heat release power of heat storage tank t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; represent the energy of t+1 period in heat storage tank, unit: kWh; represent the energy of t period in heat storage tank, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh;

In each moment, according to step 10) the up-to-date refrigeration duty that obtains, thermal load and electric load predict the outcome and miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the running status that energy storage device is real-time, Yalmip optimization tool is adopted to solve rolling optimization model, measuring and calculating miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device will control exerting oneself of time domain M period in future, by the miniature gas turbine of first period in the following M period, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, each equipment is delivered in the instruction of exerting oneself of energy storage device,

Step 30) monitoring real time data, and upgrade historical data: monitoring is obtained the wind power in each moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value, replaced the wind power in a upper moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value;

Step 40) set up feedback compensation model, the actual of equipment such as real-time correction miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device are exerted oneself: the actual value of Real-Time Monitoring wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power, and the historical data upgrading wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load; Feedback compensation model is such as formula shown in (13) to formula (21):

Set up such as formula shown in (13) with the minimum correction function for objective function of relative adjustment amount:

$\begin{array}{c}\mathrm{Min\; AD}=w_1\·\left(\right|{\mathrm{\ΔP}}_{\mathrm{mt}}|/P_{\mathrm{mt}}^r+|{\mathrm{\ΔP}}_{\mathrm{ec}}|/P_{\mathrm{ec}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{bt}}|/P_{c,\mathrm{bt}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc}.\mathrm{bt}}|/P_{\mathrm{disc},\mathrm{bt}}^r+|{\mathrm{\ΔP}}_g|/P_g^r)\\ +w_2\·\left(\right|{\mathrm{\ΔP}}_b|/P_b^r+|{\mathrm{\ΔP}}_{\mathrm{ac}}|/P_{\mathrm{ac}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{tst}}|/P_{c,\mathrm{tst}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}|/P_{\mathrm{disc},\mathrm{tst}}^r)\end{array}$ Formula (13)

In formula, AD represents overall relative adjustment amount; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the rated power that miniature gas turbine exports, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; represent the rated power of electric refrigerating machine machine input, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the rated power of charge in batteries, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the rated power of battery discharging, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; expression system and the mutual rated power of major network, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent that gas fired-boiler exports rated power, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input, unit: kW; represent the rated power of adsorbent refrigerator input, unit: kW; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the rated power of heat storage tank accumulation of heat, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the rated power of heat storage tank heat release, unit: kW; w ₁represent the weight coefficient relevant to electric energy, w ₂represent the weight coefficient relevant to cold and hot energy;

Set up such as formula the cold energy equilibrium constraint shown in (14):

$(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})\·{\mathrm{COP}}_{\mathrm{ac}}+(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}})\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c$ Formula (14)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; Q _cfor real-time cooling load of the air-conditioning system power, unit: kW;

Set up such as formula the thermal energy equilibrium constraint shown in (15):

$(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+(P_b^t+{\mathrm{\ΔP}}_b)-(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}+P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})=(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})+Q_h/{\mathrm{\η}}_{\mathrm{he}}$ Formula (15)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kW; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input; η _herepresent effectiveness of heat exchanger; Q _hfor real-time system heat load power, unit: kW;

Set up such as formula the electric energy balance constraint condition shown in (16):

$P_{\mathrm{pv}}+P_{\mathrm{wt}}+(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})+(P_g^t+{\mathrm{\ΔP}}_g)-(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}+P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})=(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}})+P_{\mathrm{el}}$ Formula (16)

In formula, P _pvrepresent real-time photovoltaic power, unit: kW; P _wtrepresent real-time wind power, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; expression system t period and the mutual power of major network, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent accumulator t period discharge power, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; P _elrepresent real-time system electric load power, unit: kW;

Set up the constraint condition run such as formula the miniature gas turbine shown in (17):

$\begin{array}{c}{U}_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }\\ U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{d^{\′}}\≤{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{u^{\′}}\end{array}$ Formula (17)

In formula, represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine does not run; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum in short-term when continuous running status of micro-gas-turbine unit: kW; represent in short-term most the increase power of micro-gas-turbine unit when continuous running status, unit: kW;

Set up the constraint condition run such as formula the gas fired-boiler shown in (18):

$P_b^{\min }\≤P_b^t+P_b\≤P_b^{\max }$ Formula (18)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW;

Set up the constraint condition such as formula the mutual power of electrical network shown in (19):

formula (19)

In formula, the lower limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; the upper limit of expression system and the mutual power of major network, unit: kW;

Set up the constraint condition run such as formula the accumulator shown in (20):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}}\≤0\\ 0\≤P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ W_{\mathrm{bt}}^{t^{\′}+1}=W_{\mathrm{bt}}^{t^{\′}}\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}})+(P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t^{\′}+1}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (20)

In formula, represent the discharge condition of accumulator t period, represent battery discharging, represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the charge power of accumulator t period, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the charged state of accumulator t period, represent charge in batteries, represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; energy before expression feedback compensation in accumulator, unit: kWh; represent the energy in the accumulator after feedback compensation, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t '=1/12h;

Set up the constraint condition run such as formula the heat storage tank shown in (21):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}\≤0\\ 0\≤P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ W_{\mathrm{tst}}^{t^{\′}+1}=W_{\mathrm{tst}}^{t^{\′}}\·(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}})+(P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t^{\′}+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (21)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent charge in batteries power upper limit, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; energy before expression feedback compensation in heat storage tank, unit: kWh; represent the energy in the heat storage tank after feedback compensation, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh;

Finally, Yalmip optimization tool is adopted to solve feedback compensation model, obtain the adjustment amount that miniature gas turbine is exerted oneself, gas fired-boiler is exerted oneself, adsorbent refrigerator power input, electric refrigerating machine power input, accumulator cell charging and discharging power, heat storage tank store the mutual power of heat release power, system and electrical network, these adjustment amounts are issued to respectively miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, accumulator, heat storage tank equipment adjusts; Within every 5 minutes, perform a step 30) and step 40), until be finished in control cycle Δ t.

Step 50) enter subsequent time, return step 10), until micro-capacitance sensor out of service.

Further, described step 20) in,

$C_{\mathrm{ng}}^t=\mathrm{\Δt}\·[R_{\mathrm{ng}}(P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}+P_b^t/{\mathrm{\η}}_b)/H_{\mathrm{ng}}]$ Formula (2)

In formula, △ t represents the time interval; R _ngrepresent Gas Prices, unit: $/m ³; represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; represent the power of gas fired-boiler t period, unit: kW; η _brepresent the efficiency of gas fired-boiler; H _ngrepresent heating value of natural gas;

$\begin{array}{c}{C}_{\mathrm{om}}^t=\mathrm{\Δt}\·[P_{\mathrm{mt}}^t\·K_{\mathrm{om},\mathrm{mt}}+P_b^t\·K_{\mathrm{om},b}+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}\·K_{\mathrm{om},\mathrm{he}}\\ +P_{\mathrm{ac}}^t\·K_{\mathrm{om},\mathrm{ac}}+P_{\mathrm{ec}}^t\·K_{\mathrm{om},\mathrm{ec}}+P_{\mathrm{pv}}^t\·K_{\mathrm{om},\mathrm{pv}}+P_{\mathrm{wt}}^t\·K_{\mathrm{om},\mathrm{wt}}\\ +(P_{c,\mathrm{bt}}-P_{\mathrm{disc},\mathrm{bt}}^t)\·K_{\mathrm{om},\mathrm{bt}}+(P_{c,\mathrm{tst}}^t-P_{\mathrm{disc},\mathrm{tst}}^t)\·K_{\mathrm{om},\mathrm{tst}}]\end{array}$ Formula (3)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; K _{om, mt}represent miniature gas turbine operation and maintenance cost, unit: $/kWh; represent the power of gas fired-boiler t period, unit: kW; K _{om, b}represent gas fired-boiler operation and maintenance cost, unit: $/kWh; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger; K _{om, he}represent heat exchanger operation and maintenance cost, unit: $/kWh; represent the power input of adsorbent refrigerator t period, unit: kW; K _{om, ac}represent adsorbent refrigerator operation and maintenance cost, unit: $/kWh; represent the power input of electric refrigerating machine t period, unit: kW; K _{om, ec}represent electric refrigerating machine operation and maintenance cost, unit: $/kWh; represent the predicted value of photovoltaic t period; K _{om, pv}represent photovoltaic cell maintenance cost unit: $/kWh; represent the predicted value of wind-powered electricity generation t period; K _{om, wt}represent blower fan maintenance cost unit: $/kWh; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; K _{om, bt}represent accumulator operation and maintenance cost, unit: $/kWh; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; K _{om, tst}represent heat storage tank operation and maintenance cost, unit: $/kWh;

$C_{\mathrm{eb}}^t=\mathrm{\Δt}\·[(R_p^t+\mathrm{\α}{R}_s^t)/2\·P_g^t+(R_p^t-\mathrm{\α}{R}_s^t)/2\·|P_g^t\left|\right]$ Formula (4)

In formula, the expression system t period from the price of major network power purchase, unit: $/kWh; the expression system t period is to the price of major network sale of electricity; α be 0 or 1, α=1 represent that micro-capacitance sensor can to major network sale of electricity, α=0 represents and does not allow micro-capacitance sensor to major network sale of electricity; expression system t period and the mutual power of major network, unit: kW, represent from major network power purchase, represent to major network sale of electricity.

Beneficial effect: compared with prior art, the present invention has the following advantages:

The supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control that the present invention proposes, first the corresponding forecast model of wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load is set up, according to up-to-date wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, electric load historical data, prediction will control wind power in time domain M, photovoltaic power, cool and thermal power load power data future, each moment, according to the up-to-date refrigeration duty obtained, thermal load and electric load predict the outcome and miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the running status that energy storage device etc. are real-time, Yalmip optimization tool is adopted to solve this rolling optimization model, calculate miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the equipment such as energy storage device are exerted oneself the following M period, but miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the equipment such as energy storage device only perform the instruction of first period, predict the outcome according to up-to-date again to subsequent time, recalculate rolling optimization model, circulation like this is carried out, this ensure that system call instruction is all calculating on the basis of up-to-date information, thus make each equipment run the actual optimum of maintenance, Real-Time Monitoring wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, the actual value of electric load, and upgrade wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, the historical data of electric load, Yalmip optimization tool within every 5 minutes, is adopted to solve feedback compensation model, obtain miniature gas turbine to exert oneself, gas fired-boiler is exerted oneself, adsorbent refrigerator power input, electric refrigerating machine power input, accumulator cell charging and discharging power, heat storage tank stores heat release power, the adjustment amount of system and the mutual power of electrical network etc., these adjustment amounts are issued to miniature gas turbine respectively, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, accumulator, the equipment such as heat storage tank adjust, until the next rolling optimization moment.The inventive method can eliminate the impact because forecasting inaccuracy causes system optimized operation well, ensure what system operating instructions always calculated in the optimization of up-to-date information, reduce the risk of system cloud gray model, improve the stability of system cloud gray model, improve the economy that supply of cooling, heating and electrical powers type micro-capacitance sensor runs simultaneously.

Accompanying drawing explanation

Fig. 1 is supply of cooling, heating and electrical powers type micro-capacitance sensor structural representation in the present invention.

Fig. 2 is Systematical control block diagram of the present invention.

Fig. 3 is process flow diagram of the present invention.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with accompanying drawing and case study on implementation, the present invention is in depth described in detail.Should be appreciated that concrete case study on implementation described herein is only in order to explain the present invention, and be not used in restriction invention.

The present invention relates to a kind of supply of cooling, heating and electrical powers type micro-capacitance sensor optimizing operation method based on Model Predictive Control, belong to cold, heat and power triple supply system field, is supply of cooling, heating and electrical powers type micro-capacitance sensor structural representation as shown in Figure 1.Supply of cooling, heating and electrical powers type micro-capacitance sensor comprises photovoltaic cell, blower fan, accumulator, miniature gas turbine, gas fired-boiler, electric refrigerating machine, Absorption Refrigerator, heat interaction device and heat storage tank, there is cold energy stream in depositing in system, thermal energy stream, electric flux stream and natural gas flow.The inventive method mainly comprises three parts: prediction module, rolling optimization module and feedback compensation module.

As shown in Figure 3, the supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control of the present invention, comprises the following steps:

Step 10) set up parametric prediction model, comprise wind-powered electricity generation forecast model, photovoltaic forecast model, cooling load prediction model, heat load prediction model and electric load forecast model; According to each parametric prediction model, in the k moment, according to n the historical data gathered before the k moment, utilize each parametric prediction model, following wind power, photovoltaic power, refrigeration duty power, thermal load power and the electric load power controlled in time domain M of prediction; Historical data comprises wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power.

Step 20) according to step 10) control in time domain M wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power in future of obtaining, set up such as formula the rolling optimization model shown in (1) to formula (12).

First determine with micro-grid system operating cost minimum for objective function, shown in (1):

$\mathrm{MinC}=\underset{t=k+1}{\overset{k+M}{\mathrm{\Σ}}}{C}_{\mathrm{ng}}^t+C_{\mathrm{om}}^t+C_{\mathrm{eb}}^t$

In formula, C represents system operation cost; K represents current time; M represents control time domain; the fuel cost of expression system t period; the operation expense of expression system t period; represent t period and the mutual cost of electrical network.

$C_{\mathrm{ng}}^t=\mathrm{\Δt}\·[R_{\mathrm{ng}}(P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}+P_b^t/{\mathrm{\η}}_b)/H_{\mathrm{ng}}]$ Formula (2)

In formula, △ t represents the time interval; R _ngrepresent Gas Prices, unit: $/m ³; represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; represent the power of gas fired-boiler t period, unit: kW; η _brepresent the efficiency of gas fired-boiler; H _ngrepresent heating value of natural gas, H _ng=9.78kWh/m ³.As preferably, △ t=0.25h.

$\begin{array}{c}{C}_{\mathrm{om}}^t=\mathrm{\Δt}\·[P_{\mathrm{mt}}^t\·K_{\mathrm{om},\mathrm{mt}}+P_b^t\·K_{\mathrm{om},b}+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}\·K_{\mathrm{om},\mathrm{he}}\\ +P_{\mathrm{ac}}^t\·K_{\mathrm{om},\mathrm{ac}}+P_{\mathrm{ec}}^t\·K_{\mathrm{om},\mathrm{ec}}+P_{\mathrm{pv}}^t\·K_{\mathrm{om},\mathrm{pv}}+P_{\mathrm{wt}}^t\·K_{\mathrm{om},\mathrm{wt}}\\ +(P_{c,\mathrm{bt}}-P_{\mathrm{disc},\mathrm{bt}}^t)\·K_{\mathrm{om},\mathrm{bt}}+(P_{c,\mathrm{tst}}^t-P_{\mathrm{disc},\mathrm{tst}}^t)\·K_{\mathrm{om},\mathrm{tst}}]\end{array}$ Formula (3)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; K _{om, mt}represent miniature gas turbine operation and maintenance cost, unit: $/kWh; represent the power of gas fired-boiler t period, unit: kW; K _{om, b}represent gas fired-boiler operation and maintenance cost, unit: $/kWh; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger; K _{om, he}represent heat exchanger operation and maintenance cost, unit: $/kWh; represent the power input of adsorbent refrigerator t period, unit: kW; K _{om, ac}represent adsorbent refrigerator operation and maintenance cost, unit: $/kWh; represent the power input of electric refrigerating machine t period, unit: kW; K _{om, ec}represent electric refrigerating machine operation and maintenance cost, unit: $/kWh; represent the predicted value of photovoltaic t period; K _{om, pv}represent photovoltaic cell maintenance cost unit: $/kWh; represent the predicted value of wind-powered electricity generation t period; K _{om, wt}represent blower fan maintenance cost unit: $/kWh; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; K _{om, bt}represent accumulator operation and maintenance cost, unit: $/kWh; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; K _{om, tst}represent heat storage tank operation and maintenance cost, unit: $/kWh.

$C_{\mathrm{eb}}^t=\mathrm{\Δt}\·[(R_p^t+\mathrm{\α}{R}_s^t)/2\·P_g^t+(R_p^t-\mathrm{\α}{R}_s^t)/2\·|P_g^t\left|\right]$ Formula (4)

In formula, the expression system t period from the price of major network power purchase, unit: $/kWh; the expression system t period is to the price of major network sale of electricity; α be 0 or 1, α=1 represent that micro-capacitance sensor can to major network sale of electricity, α=0 represents and does not allow micro-capacitance sensor to major network sale of electricity; expression system t period and the mutual power of major network, unit: kW, represent from major network power purchase, represent to major network sale of electricity.

Then determine constraint condition, comprise cold energy balance, thermal energy balance, electric energy balance and equipment and run constraint condition.

Cold energy equilibrium constraint is determined according to formula (5):

$P_{\mathrm{ac}}^t\·{\mathrm{COP}}_{\mathrm{ac}}+P_{\mathrm{ec}}^t\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c^t$ Formula (5)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; represent t cooling load of the air-conditioning system power, unit: kW.

Thermal energy equilibrium constraint is determined according to formula (6):

$P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+P_b^t-(P_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t)=P_{\mathrm{ac}}^t+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}$ Formula (6)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger.

Electric energy balance constraint condition is determined according to formula (7):

$P_{\mathrm{pv}}^t+P_{\mathrm{wt}}^t+P_{\mathrm{mt}}^t+P_g^t-(P_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t)=P_{\mathrm{ec}}^t+P_{\mathrm{el}}^t$ Formula (7)

In formula, represent the predicted value of photovoltaic t period; represent the predicted value of wind-powered electricity generation t period; represent the electric power of miniature gas turbine t period, unit: kW; expression system t period and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; represent t period system electric load power, unit: kW.

Determine that miniature gas turbine runs constraint condition according to formula (801) and formula (802), its Chinese style (801) is miniature gas turbine running status constraint condition; Formula (802) represents gas turbine unit Climing constant condition, comprises Unit Commitment Climing constant and runs Climing constant continuously:

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }$ Formula (801)

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^d+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{off}}\≤P_{\mathrm{mt}}^t-P_{\mathrm{mt}}^{t-1}\≤U_{\mathrm{mt}}^{t-1}\·P_{\mathrm{mt}}^u+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{on}}$ Formula (802)

In formula (801), represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine is shut down; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum when continuous running status of micro-gas-turbine unit: kW; represent miniature gas turbine t-1 period running status variable; to represent when micro-gas-turbine unit is shut down maximum falls power, unit: kW; represent the electric power of miniature gas turbine t-1 period, unit: kW; represent most the increase power of micro-gas-turbine unit when continuous running status, unit: kW; represent the power that increases most when micro-gas-turbine unit starts, unit: kW.

The constraint condition that gas fired-boiler runs is determined according to formula (9):

$P_b^{\min }\≤P_b^t\≤P_b^{\max }$ Formula (9)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW.

The constraint condition of the mutual power of electrical network is determined according to formula (10):

$P_g^{\min }\≤P_g^t\≤P_g^{\max }$ Formula (10)

In formula, the lower limit of expression system and the mutual power of major network, unit kW; the upper limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW.

The constraint condition that accumulator runs is determined according to formula (11):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t\≤0\\ 0\≤P_{c,\mathrm{bt}}^t\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ U_{\mathrm{disc},\mathrm{bt}}^t+U_{c,\mathrm{bt}}^t\≤1\\ W_{\mathrm{bt}}^{t+1}=W_{\mathrm{bt}}^t\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}{P}_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·\mathrm{\Δt}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t+1}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (11)

In formula, represent the discharge condition of accumulator t period, represent battery discharging; represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; represent the charge power of accumulator t period, unit: kW; represent the charged state of accumulator t period, represent charge in batteries; represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; represent the energy of t+1 period in accumulator, unit: kWh; represent the energy of t period in accumulator, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t represents the time interval.

The constraint condition that heat storage tank runs is determined according to formula (12):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t\≤0\\ 0\≤P_{c,\mathrm{tst}}^t\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ U_{\mathrm{disc},\mathrm{tst}}^t+U_{c,\mathrm{tst}}^t\≤1\\ W_{\mathrm{tst}}^{t+1}=W_{\mathrm{tst}}^t\·(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}{P}_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·\mathrm{\Δt}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (12)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent the accumulation of heat power upper limit of heat storage tank, unit kW; represent the heat release power of heat storage tank t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; represent the energy of t+1 period in heat storage tank, unit: kWh; represent the energy of t period in heat storage tank, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh.

In each moment, according to step 10) the up-to-date refrigeration duty that obtains, thermal load and electric load predict the outcome and miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the running status that energy storage device is real-time, Yalmip optimization tool is adopted to solve rolling optimization model, measuring and calculating miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device will control exerting oneself of time domain M period in future, by the miniature gas turbine of the first period in the following M period, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, each equipment is delivered in the instruction of exerting oneself of energy storage device.

Step 30) monitoring real time data, and upgrade historical data: monitoring is obtained the wind power in each moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value, replaced the wind power in a upper moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value.

Step 40) set up feedback compensation model, the actual of equipment such as real-time correction miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device are exerted oneself: the actual value of Real-Time Monitoring wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power, and the historical data upgrading wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load; Feedback compensation model is such as formula shown in (13) to formula (21).

Set up such as formula shown in (13) with the minimum correction function for objective function of relative adjustment amount:

$\begin{array}{c}\mathrm{Min\; AD}=w_1\·\left(\right|{\mathrm{\ΔP}}_{\mathrm{mt}}|/P_{\mathrm{mt}}^r+|{\mathrm{\ΔP}}_{\mathrm{ec}}|/P_{\mathrm{ec}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{bt}}|/P_{c,\mathrm{bt}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc}.\mathrm{bt}}|/P_{\mathrm{disc},\mathrm{bt}}^r+|{\mathrm{\ΔP}}_g|/P_g^r)\\ +w_2\·\left(\right|{\mathrm{\ΔP}}_b|/P_b^r+|{\mathrm{\ΔP}}_{\mathrm{ac}}|/P_{\mathrm{ac}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{tst}}|/P_{c,\mathrm{tst}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}|/P_{\mathrm{disc},\mathrm{tst}}^r)\end{array}$ Formula (13)

In formula, AD represents overall relative adjustment amount; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the rated power that miniature gas turbine exports, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; represent the rated power of electric refrigerating machine machine input, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the rated power of charge in batteries, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the rated power of battery discharging, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; expression system and the mutual rated power of major network, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent that gas fired-boiler exports rated power, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input, unit: kW; represent the rated power of adsorbent refrigerator input, unit: kW; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the rated power of heat storage tank accumulation of heat, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the rated power of heat storage tank heat release, unit: kW; w ₁represent the weight coefficient relevant to electric energy, w ₂represent the weight coefficient relevant to cold and hot energy.

Set up such as formula the cold energy equilibrium constraint shown in (14):

$(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})\·{\mathrm{COP}}_{\mathrm{ac}}+(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}})\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c$ Formula (14)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; Q _cfor real-time cooling load of the air-conditioning system power, unit: kW.

Set up such as formula the thermal energy equilibrium constraint shown in (15):

$(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+(P_b^t+{\mathrm{\ΔP}}_b)-(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}+P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})=(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})+Q_h/{\mathrm{\η}}_{\mathrm{he}}$ Formula (15)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kW; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; △ P _acrepresent the adjustment amount of adsorbent refrigerator power input; η _herepresent effectiveness of heat exchanger; Q _hfor real-time system heat load power, unit: kW.

Set up such as formula the electric energy balance constraint condition shown in (16):

$P_{\mathrm{pv}}+P_{\mathrm{wt}}+(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})+(P_g^t+{\mathrm{\ΔP}}_g)-(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}+P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})=(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}})+P_{\mathrm{el}}$ Formula (16)

In formula, P _pvrepresent real-time photovoltaic power, unit: kW; P _wtrepresent real-time wind power, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; expression system t period and the mutual power of major network, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent accumulator t period discharge power, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; △ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; P _elrepresent real-time system electric load power, unit: kW.

Set up the constraint condition run such as formula the miniature gas turbine shown in (17):

$\begin{array}{c}{U}_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }\\ U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{d^{\′}}\≤{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{u^{\′}}\end{array}$ Formula (17)

In formula, represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine does not run; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; △ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum in short-term when continuous running status of micro-gas-turbine unit: kW; represent in short-term most the increase power of micro-gas-turbine unit when continuous running status, unit: kW.

Set up the constraint condition run such as formula the gas fired-boiler shown in (18):

$P_b^{\min }\≤P_b^t+P_b\≤P_b^{\max }$ Formula (18)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; △ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW.

Set up the constraint condition such as formula the mutual power of electrical network shown in (19):

formula (19)

In formula, the lower limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW; △ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; the upper limit of expression system and the mutual power of major network, unit: kW.

Set up the constraint condition run such as formula the accumulator shown in (20):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}}\≤0\\ 0\≤P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ W_{\mathrm{bt}}^{t^{\′}+1}=W_{\mathrm{bt}}^{t^{\′}}\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}})+(P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t^{\′}+1}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (20)

In formula, represent the discharge condition of accumulator t period, represent battery discharging, represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; △ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the charge power of accumulator t period, unit: kW; △ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the charged state of accumulator t period, represent charge in batteries, represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; energy before expression feedback compensation in accumulator, unit: kWh; represent the energy in the accumulator after feedback compensation, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t '=1/12h.

Set up the constraint condition run such as formula the heat storage tank shown in (21):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}\≤0\\ 0\≤P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ W_{\mathrm{tst}}^{t^{\′}+1}=W_{\mathrm{tst}}^{t^{\′}}\·(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}})+(P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t^{\′}+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (21)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent charge in batteries power upper limit, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; △ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; △ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; energy before expression feedback compensation in heat storage tank, unit: kWh; represent the energy in the heat storage tank after feedback compensation, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh.

Finally, Yalmip optimization tool is adopted to solve feedback compensation model, obtain the adjustment amount that miniature gas turbine is exerted oneself, gas fired-boiler is exerted oneself, adsorbent refrigerator power input, electric refrigerating machine power input, accumulator cell charging and discharging power, heat storage tank store the mutual power of heat release power, system and electrical network, these adjustment amounts are issued to respectively miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, accumulator, heat storage tank equipment adjusts; Within every 5 minutes, perform a step 30) and step 40), until be finished in control cycle Δ t.The time interval of rolling optimization is Δ t=0.25h, and the time interval of feedback compensation is Δ t '=1/12h, and feedback compensation is the correction to rolling optimization result, will do 3 feedback compensations within the time interval of a rolling optimization.

Step 50) enter subsequent time, return step 10), until micro-capacitance sensor out of service.

Step 10 of the present invention) in, wind-powered electricity generation forecast model and photovoltaic forecast model adopt document " the wind energy turbine set short term power forecast model of Kalman filtering correction " (Zhao Pan, Dai Yiping, Xia Junrong etc. the wind energy turbine set short term power forecast model [J] of Kalman filtering correction. XI AN JIAOTONG UNIVERSITY Subject Index, 2011, (5): 47-51.) in forecast model.Cooling load prediction model, heat load prediction model and electric load forecast model all adopt document " application of Nonparametric Autoregressive method in short-term electric load prediction " (Zhao Yuan, Zhang Xiafei, Xie Kaigui. the application of Nonparametric Autoregressive method in short-term electric load prediction [J]. High-Voltage Technology, 2011, (2): 429-435.) in forecast model.

In step 20) in, at each moment k, according to step 10) the up-to-date refrigeration duty that obtains, thermal load and electric load predict the outcome and miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the running status that energy storage device is real-time, Yalmip optimization tool is adopted to solve rolling optimization model, measuring and calculating miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device will control exerting oneself of time domain M period in future, by the miniature gas turbine of first period in the following M period, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, each equipment is delivered in the instruction of exerting oneself of energy storage device.Predict the outcome according to up-to-date to subsequent time again, recalculate rolling optimization model, so circulation is carried out.This ensure that system call instruction is all calculating on the basis of up-to-date information.

Step 30) in, the actual value of Real-Time Monitoring wind power, photovoltaic power, refrigeration duty, thermal load and electric load, and the historical data upgrading wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load.The predicted value of wind power, photovoltaic power, refrigeration duty, thermal load and electric load and actual value are often different, need to pass through feedback compensation, the actual of equipment such as real-time correction miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device are exerted oneself, feedback compensation is the small adjustment to rolling optimal dispatching instruction, in order to revise the error brought because ex ante forecasting is inaccurate, feedback compensation model is the Optimized model of a quiet hour section.Exerting oneself on predicted data basis of each equipment that rolling optimization obtains.When actual motion, predicted value is different with actual value.If each equipment runs according to the result of rolling optimization, just system cloud gray model cannot be met, so will revise exerting oneself of each equipment according to actual value, namely feedback compensation.

Fig. 2 is the Systematical control block diagram of the inventive method, X in figure _kthe predicted value of kth moment to wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, the following M time domain of electric load; X is wind-powered electricity generation, photovoltaic, refrigeration duty, heat are carved, the Real-Time Monitoring value of electricity; U _k+1be that each facilities plan of first period of kth moment rolling optimization result is exerted oneself instruction, comprise Gas Turbine Output, gas fired-boiler is exerted oneself, adsorbent refrigerator, electric refrigerating machine power input, accumulator cell charging and discharging power, heat storage tank stores heat release power, system and the mutual power of electrical network etc.; △ u is the Gas Turbine Output after Real-time Feedback corrects, and gas fired-boiler is exerted oneself, adsorbent refrigerator, electric refrigerating machine power input, accumulator cell charging and discharging power, and heat storage tank stores heat release power, the adjustment amount of system and the mutual power of electrical network; for each Gas Turbine Output, gas fired-boiler is exerted oneself, adsorbent refrigerator, electric refrigerating machine power input, accumulator cell charging and discharging power, and heat storage tank stores heat release power, system and real-time the exerting oneself of the mutual power of electrical network.

First method of the present invention sets up the corresponding forecast model of wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load, and according to up-to-date historical data, prediction is following controls wind power, photovoltaic power, cool and thermal power load power data in time domain M; Each moment, according to up-to-dately predicting the outcome and each equipment real-time running state of obtaining, Yalmip optimization tool is adopted to solve this rolling optimization model, calculate each equipment exerting oneself in the following M period, but only perform the instruction of first period, predict the outcome according to up-to-date again to subsequent time, recalculate rolling optimization model, so circulate; The actual value of Real-Time Monitoring wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, electric load, and upgrade the historical data of wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load, electric load, within every 5 minutes, solve feedback compensation model, obtain the adjustment amount of each equipment, and be issued to each equipment respectively and adjust, until the next rolling optimization moment.The inventive method can eliminate the impact because forecasting inaccuracy causes system optimized operation well, ensure what system operating instructions always calculated in the optimization of up-to-date information, reduce the risk of system cloud gray model, improve the stability of system cloud gray model, improve the economy that supply of cooling, heating and electrical powers type micro-capacitance sensor runs simultaneously.

The above is only the preferred embodiment of the present invention; it is noted that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (3)

1., based on a supply of cooling, heating and electrical powers type micro-capacitance sensor operation method for Model Predictive Control, it is characterized in that, this operation method comprises the following steps:

Step 10) set up parametric prediction model, comprise wind-powered electricity generation forecast model, photovoltaic forecast model, cooling load prediction model, heat load prediction model and electric load forecast model; According to each parametric prediction model, in the k moment, according to n the historical data gathered before the k moment, utilize each parametric prediction model, following wind power, photovoltaic power, refrigeration duty power, thermal load power and the electric load power controlled in time domain M of prediction; Historical data comprises wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power;

Step 20) according to step 10) control in time domain M wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power in future of obtaining, set up such as formula the rolling optimization model shown in (1) to formula (12):

First determine with micro-grid system operating cost minimum for objective function, shown in (1):

$\mathrm{MinC}=\underset{t=k+1}{\overset{k+M}{\mathrm{\Σ}}}{C}_{\mathrm{ng}}^t+C_{\mathrm{om}}^t+C_{\mathrm{eb}}^t$ Formula (1)

In formula, C represents system operation cost; K represents current time; M represents control time domain; the fuel cost of expression system t period; the operation expense of expression system t period; represent t period and the mutual cost of electrical network;

Then determine constraint condition, comprise cold energy balance, thermal energy balance, electric energy balance and equipment and run constraint condition:

Cold energy equilibrium constraint is determined according to formula (5):

$P_{\mathrm{ac}}^t\·{\mathrm{COP}}_{\mathrm{ac}}+P_{\mathrm{ec}}^t\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c^t$ Formula (5)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; represent t cooling load of the air-conditioning system power, unit: kW;

Thermal energy equilibrium constraint is determined according to formula (6):

$P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+P_b^t-(P_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t)=P_{\mathrm{ac}}^t+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}$ Formula (6)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger;

Electric energy balance constraint condition is determined according to formula (7):

$P_{\mathrm{pv}}^t+P_{\mathrm{wt}}^t+P_{\mathrm{mt}}^t+P_g^t-(P_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t)=P_{\mathrm{ec}}^t+P_{\mathrm{el}}^t$ Formula (7)

In formula, represent the predicted value of photovoltaic t period; represent the predicted value of wind-powered electricity generation t period; represent the electric power of miniature gas turbine t period, unit: kW; expression system t period and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; represent t period system electric load power, unit: kW;

Determine that miniature gas turbine runs constraint condition according to formula (801) and formula (802), its Chinese style (801) is miniature gas turbine running status constraint condition; Formula (802) represents gas turbine unit Climing constant condition, comprises Unit Commitment Climing constant and runs Climing constant continuously:

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }$ Formula (801)

$U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^d+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{off}}\≤P_{\mathrm{mt}}^t-P_{\mathrm{mt}}^{t-1}\≤U_{\mathrm{mt}}^{t-1}\·P_{\mathrm{mt}}^u+(U_{\mathrm{mt}}^t-U_{\mathrm{mt}}^{t-1})\·P_{\mathrm{mt}}^{\mathrm{on}}$ Formula (802)

In formula (801), represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine is shut down; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum when continuous running status of micro-gas-turbine unit: kW; represent miniature gas turbine t-1 period running status variable; to represent when micro-gas-turbine unit is shut down maximum falls power, unit: kW; represent the electric power of miniature gas turbine t-1 period, unit: kW; represent most the increase power of micro-gas-turbine unit when continuous running status, unit: kW; represent the power that increases most when micro-gas-turbine unit starts, unit: kW;

The constraint condition that gas fired-boiler runs is determined according to formula (9):

$P_b^{\min }\≤P_b^t\≤P_b^{\max }$ Formula (9)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW;

The constraint condition of the mutual power of electrical network is determined according to formula (10):

$P_g^{\min }\≤P_g^t\≤P_g^{\max }$ Formula (10)

In formula, the lower limit of expression system and the mutual power of major network, unit kW; the upper limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW;

The constraint condition that accumulator runs is determined according to formula (11):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t\≤0\\ 0\≤P_{c,\mathrm{bt}}^t\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ U_{\mathrm{disc},\mathrm{bt}}^t+U_{c,\mathrm{bt}}^t\≤1\\ W_{\mathrm{bt}}^{t+1}=W_{\mathrm{bt}}^t\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}{P}_{c,\mathrm{bt}}^t+P_{\mathrm{disc},\mathrm{bt}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·\mathrm{\Δt}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t+}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (11)

In formula, represent the discharge condition of accumulator t period, represent battery discharging; represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; represent the charge power of accumulator t period, unit: kW; represent the charged state of accumulator t period, represent charge in batteries; represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; represent the energy of t+1 period in accumulator, unit: kWh; represent the energy of t period in accumulator, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t represents the time interval;

The constraint condition that heat storage tank runs is determined according to formula (12):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t\≤0\\ 0\≤P_{c,\mathrm{tst}}^t\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ U_{\mathrm{disc},\mathrm{tst}}^t+U_{c,\mathrm{tst}}^t\≤1\\ W_{\mathrm{tst}}^{t+1}=W_{\mathrm{tst}}^t\·(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}{P}_{c,\mathrm{tst}}^t+P_{\mathrm{disc},\mathrm{tst}}^t/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·\mathrm{\Δt}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (12)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent the accumulation of heat power upper limit of heat storage tank, unit kW; represent the heat release power of heat storage tank t period, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; represent the energy of t+1 period in heat storage tank, unit: kWh; represent the energy of t period in heat storage tank, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh;

In each moment, according to step 10) the up-to-date refrigeration duty that obtains, thermal load and electric load predict the outcome and miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, the running status that energy storage device is real-time, Yalmip optimization tool is adopted to solve rolling optimization model, measuring and calculating miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device will control exerting oneself of time domain M period in future, by the miniature gas turbine of first period in the following M period, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, each equipment is delivered in the instruction of exerting oneself of energy storage device,

Step 30) monitoring real time data, and upgrade historical data: monitoring is obtained the wind power in each moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value, replaced the wind power in a upper moment, photovoltaic power, refrigeration duty power, thermal load power and electric load power actual value;

Step 40) set up feedback compensation model, the actual of equipment such as real-time correction miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, energy storage device are exerted oneself: the actual value of Real-Time Monitoring wind power, photovoltaic power, refrigeration duty power, thermal load power and electric load power, and the historical data upgrading wind-powered electricity generation, photovoltaic, refrigeration duty, thermal load and electric load; Feedback compensation model is such as formula shown in (13) to formula (21):

Set up such as formula shown in (13) with the minimum correction function for objective function of relative adjustment amount:

$\begin{array}{c}\mathrm{MinAD}=w_1\·\left(\right|{\mathrm{\ΔP}}_{\mathrm{mt}}|/P_{\mathrm{mt}}^r+|{\mathrm{\ΔP}}_{\mathrm{ec}}|/P_{\mathrm{ec}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{bt}}|/P_{c,\mathrm{bt}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}}|/P_{\mathrm{disc},\mathrm{bt}}^r+|{\mathrm{\ΔP}}_g|/P_g^r)\\ +w_2\·\left(\right|{\mathrm{\ΔP}}_b|/P_b^r+|{\mathrm{\ΔP}}_{\mathrm{ac}}|/P_{\mathrm{ac}}^r+|{\mathrm{\ΔP}}_{c,\mathrm{tst}}|/P_{c,\mathrm{tst}}^r+|{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}|/P_{\mathrm{disc},\mathrm{tst}}^r)\end{array}$ Formula (13)

In formula, AD represents overall relative adjustment amount; Δ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the rated power that miniature gas turbine exports, unit: kW; Δ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; represent the rated power of electric refrigerating machine machine input, unit: kW; Δ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the rated power of charge in batteries, unit: kW; Δ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the rated power of battery discharging, unit: kW; Δ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; expression system and the mutual rated power of major network, unit: kW; Δ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent that gas fired-boiler exports rated power, unit: kW; Δ P _acrepresent the adjustment amount of adsorbent refrigerator power input, unit: kW; represent the rated power of adsorbent refrigerator input, unit: kW; Δ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the rated power of heat storage tank accumulation of heat, unit: kW; Δ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the rated power of heat storage tank heat release, unit: kW; w ₁represent the weight coefficient relevant to electric energy, w ₂represent the weight coefficient relevant to cold and hot energy;

Set up such as formula the cold energy equilibrium constraint shown in (14):

$(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})\·{\mathrm{COP}}_{\mathrm{ac}}+(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}}^p)\·{\mathrm{COP}}_{\mathrm{ec}}=Q_c$ Formula (14)

In formula, represent the power input of adsorbent refrigerator t period, unit: kW; Δ P _acrepresent the adjustment amount of adsorbent refrigerator power input; COP _acrepresent the coefficient of refrigerating performance of adsorbent refrigerator; represent the power input of electric refrigerating machine t period, unit: kW; Δ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; COP _ecrepresent the coefficient of refrigerating performance of electric refrigerating machine; Q _cfor real-time cooling load of the air-conditioning system power, unit: kW;

Set up such as formula the thermal energy equilibrium constraint shown in (15):

$(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})/{\mathrm{\η}}_{\mathrm{mt}}\·(1-{\mathrm{\η}}_{\mathrm{mt}}-{\mathrm{\η}}_{\mathrm{loss}})\·{\mathrm{\η}}_{\mathrm{hr}}+(P_b^t+{\mathrm{\ΔP}}_b)-(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}+P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})=(P_{\mathrm{ac}}^t+{\mathrm{\ΔP}}_{\mathrm{ac}})+Q_h/{\mathrm{\η}}_{\mathrm{he}}$ Formula (15)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; Δ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; η _lossrepresent the gas turbine energy proportion of goods damageds; η _hrrepresent waste-heat recoverer efficiency; represent the power of gas fired-boiler t period, unit: kW; Δ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kW; Δ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; Δ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the power input of adsorbent refrigerator t period, unit: kW; Δ P _acrepresent the adjustment amount of adsorbent refrigerator power input; η _herepresent effectiveness of heat exchanger; Q _hfor real-time system heat load power, unit: kW;

Set up such as formula the electric energy balance constraint condition shown in (16):

$P_{\mathrm{pv}}+P_{\mathrm{wt}}+(P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}})+(P_g^t+{\mathrm{\ΔP}}_g)-(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}+P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})=(P_{\mathrm{ec}}^t+{\mathrm{\ΔP}}_{\mathrm{ec}})+P_{\mathrm{el}}$ Formula (16)

In formula, P _pvrepresent real-time photovoltaic power, unit: kW; P _wtrepresent real-time wind power, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; Δ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; expression system t period and the mutual power of major network, unit: kW; Δ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; represent the charge power of accumulator t period, unit: kW; Δ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent accumulator t period discharge power, unit: kW; Δ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the power input of electric refrigerating machine t period, unit: kW; Δ P _ecrepresent the adjustment amount of electric refrigerating machine machine power input, unit: kW; P _elrepresent real-time system electric load power, unit: kW;

Set up the constraint condition run such as formula the miniature gas turbine shown in (17):

$\begin{array}{c}{U}_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\min }\≤P_{\mathrm{mt}}^t+{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{\max }\\ U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{d^{\′}}\≤{\mathrm{\ΔP}}_{\mathrm{mt}}\≤U_{\mathrm{mt}}^t\·P_{\mathrm{mt}}^{u^{\′}}\end{array}$ Formula (17)

In formula, represent miniature gas turbine t period running status variable, represent that miniature gas turbine runs, represent that miniature gas turbine does not run; represent the lower limit that miniature gas turbine is exerted oneself, unit: kW; represent the electric power of miniature gas turbine t period, unit: kW; Δ P _mtrepresent the adjustment amount that miniature gas turbine is exerted oneself, unit: kW; represent the upper limit that miniature gas turbine is exerted oneself, unit: kW; represent that unit falls power, in maximum in short-term when continuous running status of micro-gas-turbine unit: kW; represent in short-term most the increase power of micro-gas-turbine unit when continuous running status, unit: kW;

Set up the constraint condition run such as formula the gas fired-boiler shown in (18):

$P_b^{\min }\≤P_b^t+P_b\≤P_b^{\max }$ Formula (18)

In formula, represent the lower limit that gas fired-boiler is exerted oneself, unit: kW; represent the power of gas fired-boiler t period, unit: kW; Δ P _brepresent the adjustment amount that gas fired-boiler is exerted oneself, unit: kW; represent the upper limit that gas fired-boiler is exerted oneself, unit: kW;

Set up the constraint condition such as formula the mutual power of electrical network shown in (19):

formula (19)

In formula, the lower limit of expression system and the mutual power of major network, unit: kW; expression system t period and the mutual power of major network, unit: kW; Δ P _gthe adjustment amount of expression system and the mutual power of major network, unit: kW; the upper limit of expression system and the mutual power of major network, unit: kW;

Set up the constraint condition run such as formula the accumulator shown in (20):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}}\≤0\\ 0\≤P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}}\≤U_{c,\mathrm{bt}}^t\·P_{\mathrm{bt}}^{\max }\\ W_{\mathrm{bt}}^{t^{\′}+1}=W_{\mathrm{bt}}^{t^{\′}}\·(1-{\mathrm{\σ}}_{\mathrm{bt}})+({\mathrm{\η}}_{c,\mathrm{bt}}(P_{c,\mathrm{bt}}^t+{\mathrm{\ΔP}}_{c,\mathrm{bt}})+(P_{\mathrm{disc},\mathrm{bt}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{bt}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{bt}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{bt}}^{\min }\≤W_{\mathrm{bt}}^{t^{\′}+1}\≤W_{\mathrm{bt}}^{\max }\end{array}\right.$ Formula (20)

In formula, represent the discharge condition of accumulator t period, represent battery discharging, represent that accumulator does not charge also not discharge; represent charge in batteries power upper limit, unit: kW; represent accumulator t period discharge power, unit: kW; Δ P _{disc, bt}represent the adjustment amount of battery discharging power, unit: kW; represent the charge power of accumulator t period, unit: kW; Δ P _{c, bt}represent the adjustment amount of charge in batteries power, unit: kW; represent the charged state of accumulator t period, represent charge in batteries, represent that accumulator does not charge also not discharge; represent battery discharging power upper limit, unit: kW; energy before expression feedback compensation in accumulator, unit: kWh; represent the energy in the accumulator after feedback compensation, unit: kWh; σ _btrepresent the self-energy proportion of goods damageds of accumulator; η _{c, bt}represent the charge efficiency of accumulator; η _{disc, bt}represent battery discharging efficiency; represent the lower limit of accumulator storage power, unit: kWh; represent the upper limit of accumulator storage power, unit: kWh; Δ t '=1/12h;

Set up the constraint condition run such as formula the heat storage tank shown in (21):

$\left\{\begin{array}{c}{U}_{\mathrm{disc},\mathrm{tst}}^t\·P_{\mathrm{bt}}^{\min }\≤P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}}\≤0\\ 0\≤P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}}\≤U_{c,\mathrm{tst}}^t\·P_{\mathrm{tst}}^{\max }\\ W_{\mathrm{tst}}^{t^{\′}+1}=W_{\mathrm{tst}}^{t^{\′}}(1-{\mathrm{\σ}}_{\mathrm{tst}})+({\mathrm{\η}}_{c,\mathrm{tst}}(P_{c,\mathrm{tst}}^t+{\mathrm{\ΔP}}_{c,\mathrm{tst}})+(P_{\mathrm{disc},\mathrm{tst}}^t+{\mathrm{\ΔP}}_{\mathrm{disc},\mathrm{tst}})/{\mathrm{\η}}_{\mathrm{disc},\mathrm{tst}})\·{\mathrm{\Δt}}^{\′}\\ W_{\mathrm{tst}}^{\min }\≤W_{\mathrm{tst}}^{t^{\′}+1}\≤W_{\mathrm{tst}}^{\max }\end{array}\right.$ Formula (21)

In formula, represent the heat release state of heat storage tank t period, represent heat storage tank heat release, represent heat storage tank not heat release also not accumulation of heat; represent charge in batteries power upper limit, unit: kW; represent the heat release power of heat storage tank t period, unit: kW; Δ P _{disc, tst}represent the adjustment amount of heat storage tank heat release power, unit: kW; represent the accumulation of heat power of heat storage tank t period, unit: kWh; Δ P _{c, tst}represent the adjustment amount of heat storage tank accumulation of heat power, unit: kW; represent the heat storage state of heat storage tank t period, represent heat storage tank accumulation of heat, represent heat storage tank not heat release also not accumulation of heat; represent the heat release power upper limit of heat storage tank, unit: kW; energy before expression feedback compensation in heat storage tank, unit: kWh; represent the energy in the heat storage tank after feedback compensation, unit: kWh; σ _tstrepresent the self-energy proportion of goods damageds of heat storage tank; η _{c, tst}represent the heat storage efficiency of heat storage tank; η _{disc, tst}represent the efficiency of heat storage tank release heat; represent the lower limit of heat storage tank storage power, unit: kWh; represent the upper limit of heat storage tank storage power, unit: kWh;

Finally, Yalmip optimization tool is adopted to solve feedback compensation model, obtain the adjustment amount that miniature gas turbine is exerted oneself, gas fired-boiler is exerted oneself, adsorbent refrigerator power input, electric refrigerating machine power input, accumulator cell charging and discharging power, heat storage tank store the mutual power of heat release power, system and electrical network, these adjustment amounts are issued to respectively miniature gas turbine, gas fired-boiler, adsorbent refrigerator, electric refrigerating machine, accumulator, heat storage tank equipment adjusts; Within every 5 minutes, perform a step 30) and step 40), until be finished in control cycle Δ t;

Step 50) enter subsequent time, return step 10), until micro-capacitance sensor out of service.

2., according to the supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control according to claim 1, it is characterized in that, described step 20) in,

$C_{\mathrm{ng}}^t=\mathrm{\Δt}\·\left[(R_{\mathrm{ng}}(P_{\mathrm{mt}}^t/{\mathrm{\η}}_{\mathrm{mt}}+P_b^t/{\mathrm{\η}}_b)/H_{\mathrm{ng}})\right]$ Formula (2)

In formula, Δ t represents the time interval; R _ngrepresent Gas Prices, unit: $/m ³; represent the electric power of miniature gas turbine t period, unit: kW; η _mtrepresent the efficiency of miniature gas turbine; P _b ^trepresent the power of gas fired-boiler t period, unit: kW; η _brepresent the efficiency of gas fired-boiler; H _ngrepresent heating value of natural gas;

$\begin{array}{c}{C}_{\mathrm{om}}^t=\mathrm{\Δt}\·[P_{\mathrm{mt}}^t\·K_{\mathrm{om},\mathrm{mt}}+P_b^t\·K_{\mathrm{om},b}+Q_h^t/{\mathrm{\η}}_{\mathrm{he}}\·K_{\mathrm{om},\mathrm{he}}\\ +P_{\mathrm{ac}}^t\·K_{\mathrm{om},\mathrm{ac}}+P_{\mathrm{ec}}^t\·K_{\mathrm{om},\mathrm{ec}}+P_{\mathrm{pv}}^t\·K_{\mathrm{om},\mathrm{pv}}+P_{\mathrm{wt}}^t\·K_{\mathrm{om},\mathrm{wt}}\\ +(P_{c,\mathrm{bt}}^t-P_{\mathrm{disc},\mathrm{bt}}^t)\·K_{\mathrm{om},\mathrm{bt}}+(P_{c,\mathrm{tst}}^t-P_{\mathrm{disc},\mathrm{tst}}^t)\·K_{\mathrm{om},\mathrm{tst}]}\end{array}$ Formula (3)

In formula, represent the electric power of miniature gas turbine t period, unit: kW; K _{om, mt}represent miniature gas turbine operation and maintenance cost, unit: $/kWh; represent the power of gas fired-boiler t period, unit: kW; K _{om, b}represent gas fired-boiler operation and maintenance cost, unit: $/kWh; represent the thermal load power of t period system, unit: kW; η _herepresent effectiveness of heat exchanger; K _{om, he}represent heat exchanger operation and maintenance cost, unit: $/kWh; represent the power input of adsorbent refrigerator t period, unit: kW; K _{om, ac}represent adsorbent refrigerator operation and maintenance cost, unit: $/kWh; represent the power input of electric refrigerating machine t period, unit: kW; K _{om, ec}represent electric refrigerating machine operation and maintenance cost, unit: $/kWh; represent the predicted value of photovoltaic t period; K _{om, pv}represent photovoltaic cell maintenance cost unit: $/kWh; represent the predicted value of wind-powered electricity generation t period; K _{om, wt}represent blower fan maintenance cost unit: $/kWh; represent the charge power of accumulator t period, unit: kW; represent accumulator t period discharge power, unit: kW; K _{om, bt}represent accumulator operation and maintenance cost, unit: $/kWh; represent the accumulation of heat power of heat storage tank t period, unit: kWh; represent the heat release power of heat storage tank t period, unit: kW; K _{om, tst}represent heat storage tank operation and maintenance cost, unit: $/kWh;

$C_{\mathrm{eb}}^t=\mathrm{\Δt}\·[(R_p^t+\mathrm{\α}{R}_s^t)/2\·P_g^t+(R_p^t-\mathrm{\α}{R}_s^t)/2\·|P_g^t\left|\right]$ Formula (4)

In formula, the expression system t period from the price of major network power purchase, unit: $/kWh; the expression system t period is to the price of major network sale of electricity; α be 0 or 1, α=1 represent that micro-capacitance sensor can to major network sale of electricity, α=0 represents and does not allow micro-capacitance sensor to major network sale of electricity; expression system t period and the mutual power of major network, unit: kW, represent from major network power purchase, represent to major network sale of electricity.

3., according to the supply of cooling, heating and electrical powers type micro-capacitance sensor operation method based on Model Predictive Control according to claim 2, it is characterized in that, described step 20) in, Δ t=0.25h, H _ng=9.78kWh/m ³.