CN111738502B - Multi-energy complementary system demand response operation optimization method for promoting surplus wind power consumption - Google Patents

Multi-energy complementary system demand response operation optimization method for promoting surplus wind power consumption Download PDF

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CN111738502B
CN111738502B CN202010541830.0A CN202010541830A CN111738502B CN 111738502 B CN111738502 B CN 111738502B CN 202010541830 A CN202010541830 A CN 202010541830A CN 111738502 B CN111738502 B CN 111738502B
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CN111738502A (en
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贠靖洋
郭梦婕
严正
程基峰
李明节
董存
范高锋
梁志峰
刘思扬
王跃峰
徐潇源
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Shanghai Jiaotong University
State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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Abstract

A demand response operation optimization method for a multi-energy complementary system for promoting surplus wind power consumption is characterized in that a comprehensive energy system model containing electricity and hydrogen production and a comprehensive energy system operation optimization operation model using an energy concentrator as an information receiving and processing and energy conversion carrier are established, and a comprehensive demand response mode based on demand response of power load and time-of-day electricity price is established to perform resource optimization configuration on the comprehensive energy system containing electricity and hydrogen production, so that the surplus wind power is effectively consumed and the total system operation cost is saved.

Description

Multi-energy complementary system demand response operation optimization method for promoting surplus wind power consumption
Technical Field
The invention relates to a technology in the field of new energy, in particular to a comprehensive demand response operation optimization method of an electricity-containing hydrogen production comprehensive energy system for promoting surplus wind power consumption.
Background
The comprehensive energy system for hydrogen production with electricity is a system which takes an electric power system as a core, consists of an energy supply network, an energy exchange link, an energy storage link, a comprehensive energy supply and utilization unit and a user energy utilization terminal, and realizes the production, supply and utilization of various forms of energy and the cooperative operation. The energy conversion can be realized by utilizing the forms of wind, light, gas, hydrogen and the like, and the high-efficiency multi-time utilization of the energy can be realized by utilizing the storage, supply and consumption of the energy such as electricity, heat and the like, so that the method is an important research direction for improving the utilization rate of clean energy and reducing the emission of carbon-containing and harmful gases at present.
In the prior art, aiming at the power demand response in the comprehensive energy system, the energy demand elasticity and load conversion substitution among various forms of energy at the demand side cannot be fully excavated, clean, environment-friendly and flexible hydrogen energy conversion and utilization are not involved, and the comprehensive energy system is limited to play a role in promoting surplus wind power consumption.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a demand response operation optimization method of a multi-energy complementary system for promoting surplus wind power consumption.
The invention is realized by the following technical scheme:
the invention relates to a demand response operation optimization method for a multi-energy complementary system for promoting surplus wind power consumption.
The comprehensive energy system model containing the electricity and the hydrogen has energy flow and load requirements in various forms, various coupling relations exist among the different energy forms, and mutual conversion is carried out in the comprehensive energy system in a composite working mode.
The composite working mode comprises the following steps: the system comprises a power generation mode, a heat generation mode, a hydrogen production mode, a power generation heat generation mode, a heat generation hydrogen production mode, an energy surplus hydrogen production mode and an extreme supply shortage mode.
The operation optimization operation model of the comprehensive energy system is as follows: an operation optimization operation model of the comprehensive energy system containing electricity to produce hydrogen.
The resource optimization configuration comprises the following steps: energy unit, load cell and energy hub, wherein: the energy unit includes but is not limited to wind power, photovoltaic, energy storage, CHP, and the load unit includes but is not limited to electrical load, hydrogen load.
Technical effects
The comprehensive energy system integrally solves the problems that the existing comprehensive energy system does not perform refined modeling on the production, transmission, storage and utilization of hydrogen energy, cannot fully excavate the demand response capability of users with different load types, and cannot ensure the system operation economy when the wind power fluctuation condition and the typical wind power daily output curve have great difference; according to the invention, through the comprehensive energy system optimization operation model which can consider the day-ahead time-of-use electricity price to automatically demand and respond to the comprehensive energy system for hydrogen production from electricity, and promote multi-layer and multi-way interaction between the energy supply side and the demand side, the physical model of the device for hydrogen production from electricity and fuel cells is introduced into the comprehensive energy system, and the comprehensive demand response mode is provided, so that all energy users participate in demand response, and integration of electricity, gas, heat and other forms of energy is realized. An energy hub model is constructed, two-way communication between a supply side and a demand side is promoted, and the energy hub model is also the center of interconversion of various energy sources. The energy concentrator can be used as an operation center for comprehensive demand response, can set a reasonable objective function, provides energy conversion and energy utilization plans for users, and extracts certain subsidies from the energy conversion and energy utilization plans.
Drawings
FIG. 1 is a schematic diagram of a comprehensive demand response physical architecture;
FIG. 2 is an energy hub physical model;
FIG. 3 is a diagram of a residential energy hub;
FIG. 4 is a diagram of a commercial consumer energy hub;
FIG. 5 is a block diagram of a heavy industry consumer energy hub;
FIG. 6 is an integrated energy system model containing electricity and hydrogen production with an energy hub;
FIG. 7 is a schematic view of a combined demand response;
FIG. 8 is a schematic diagram of an optimized solution for an integrated energy system containing electricity to produce hydrogen;
FIG. 9 is a graph of marginal cost of power generation for a hydrogen-containing integrated energy system;
FIG. 10 is a time-sharing price curve for three types of users;
FIG. 11 is a schematic diagram comparing wind power consumption at each time interval in mode 1;
FIG. 12 is a schematic diagram showing the comparison of the total system load at each time interval in mode 1;
FIG. 13 illustrates load curve changes before and after response to three types of user demands in mode 1;
FIG. 14 is a schematic diagram comparing wind power consumption at each time interval in the mode 2;
FIG. 15 is a comparison of the operation of the hydrogen-containing apparatus of the system before and after mode 2;
FIG. 16 is a schematic diagram illustrating the comparison of the total system load at each time interval in mode 2;
fig. 17 is a schematic diagram illustrating changes in input load curves of the energy concentrator before and after response to three types of user demands in the mode 2;
FIG. 18 shows patterns 2 with fA，fB，fCComparing schematic diagrams for the wind power consumption situation of each target time interval;
FIG. 19 pattern 2 with fB，fCThe output change schematic diagram of the system hydrogen-containing device before and after the objective function demand response;
FIG. 20 shows the equation f in mode 2A，fB，fCComparing schematic diagrams of system side power loads before and after target response;
FIG. 21 at fBA schematic diagram of the change of the user load curve before and after the response of the objective function demand;
FIG. 22 at fCA schematic diagram of the change of the user load curve before and after the demand response of the objective function;
FIG. 23 is a schematic illustration of wind turbine data according to an embodiment;
FIG. 24 is a schematic diagram of electrical load, thermal load, and hydrogen demand in an integrated energy system.
Detailed Description
As shown in fig. 1, for the present embodiment, a method for optimizing demand response operation of a multi-energy complementary system for promoting surplus wind power consumption includes the following steps:
step 1: according to the actual physical structure of the wind power hydrogen production-fuel cell device in the integrated energy system and the physical connection of the transmission system and the distribution system of the thermodynamic system, the multiple coupling relation and the load requirement between different energy forms are calculated, and a composite working mode of the integrated energy system containing the electric hydrogen production is provided, which specifically comprises the following steps:
a) and (3) generating mode: and when the heat load and the hydrogen load of the system can be met in the period t, the hydrogen storage is higher than the minimum limit, and the total generated power of the clean energy is smaller than the system load, the system is in a power generation mode.
b) A heat generation mode: when the electricity and hydrogen load of the system can be met in the period t, and the hydrogen storage is higher than the minimum limit, the heat generation of the photovoltaic photo-thermal system cannot meet the heat load requirement of the system, and the system is in a heat generation mode.
c) Hydrogen production mode: and when the electricity and heat loads of the system can be met in the period t, the hydrogen load requirement cannot be met or the hydrogen storage capacity is insufficient to the minimum limit, the system is in a hydrogen production mode.
d) And (3) a power generation hydrogen production mode: and when the heat load of the system is met in the period t, the total power generation power of the clean energy is smaller than the system load, and the hydrogen load cannot be met or the hydrogen storage capacity is insufficient to the minimum limit, the system is in a power generation and hydrogen production mode.
e) A power generation and heat generation mode: when the hydrogen load of the system can be met and the hydrogen storage is higher than the minimum limit at the time t, the total generating power of the clean energy is smaller than the system load and the heat generation of the photovoltaic photo-thermal system cannot meet the heat load demand of the system, the system is in a power generation and heat generation mode.
f) And (3) a heat production hydrogen production mode: when the electrical load of the system can be met in a period t, the hydrogen load demand cannot be met or the hydrogen storage capacity is insufficient and the minimum limit is met, and the heat generation of the photovoltaic photo-thermal system cannot meet the heat load demand of the system, the system is in a heat generation hydrogen production mode.
g) And (3) an energy surplus hydrogen production mode: when the electric load, the heat load and the hydrogen load can all be met in the period t and the hydrogen storage is lower than the maximum storage limit, the system is in the energy surplus hydrogen production mode.
h) Extreme starvation mode: when the electric, thermal and hydrogen loads are all in short supply for the period t, the system is in an extreme short supply mode.
The summary of the composite operation mode is shown in table 1 and table 2.
TABLE 1 comprehensive energy system operating scenario for hydrogen production with electricity
Figure RE-GDA0002581227430000031
Figure RE-GDA0002581227430000041
TABLE 2 TABLE 1 symbols detailed meanings
Figure RE-GDA0002581227430000042
And 2, step: based on the complementarity of the comprehensive energy system, a comprehensive demand response mode is designed, namely, a user can replace electric energy with low-price energy during the peak period of electricity utilization, the energy supply pressure of the energy supply side is reduced, and the energy utilization cost of the energy utilization side is saved. For example, if the electrical load is large at a certain period of time, the power supply is insufficient, but the hydrogen supply is surplus, the fuel cell can be used for converting the surplus hydrogen into electric energy and conveying the electric energy to the user side; if the power supply is abundant in a certain period of time in winter, but the heat demand is large, the heat price is high, and a user can select to replace direct heat utilization by electric heating devices such as a heat pump, a central air conditioner and an electric heater so as to reduce the heat load burden. The comprehensive demand response physical construction schematic diagram is shown in fig. 1.
And step 3: the energy hub model is established as an independently operating third party authority, playing the role of an intermediary between the supply side and the demand side, similar to the load aggregators in traditional demand responses. In the traditional demand response, a load aggregator is used as an important intermediate link in the demand response process, so that the load aggregator not only bears the work of managing and integrating user side resources, but also can promote the two-way communication between a supply side and a demand side. In the integrated demand response, the energy hub not only undertakes the above-mentioned work of the load aggregator, but more importantly, it is the center of interconversion of the various energy sources.
As shown in fig. 2, the energy hub model refers to: the hydrogen energy, the electric energy and the heat energy from the supply side are respectively converted into the hydrogen, cold and heat requirements of the user side through devices such as a transformer, a fuel cell, a heat pump and the like. The energy hub is used as an operation center for comprehensive demand response, can set reasonable targets, provides energy conversion and energy utilization plans for users, and extracts certain subsidies from the energy conversion and energy utilization plans. The existence of the energy concentrator ensures the safety and fairness of the system operation, and simultaneously, as a manager of the system, the energy concentrator is also an information gathering center and provides data support for the operation and the expansion of the comprehensive energy system.
And 4, step 4: the energy hub model is utilized to model different types of users, then the transferable load and the transferable load are introduced into the model, an optimization model of comprehensive demand response of the comprehensive energy system containing the electricity to produce the hydrogen is established, and the coordination and optimization of the operation modes of the energy supply side and the user side are realized.
The energy coupling matrix is a mathematical representation for realizing interconversion of different types of energy in the energy concentrator, the essence of the energy coupling matrix is to describe a functional relationship between multi-type energy input and multi-type energy output in a system containing the multi-type energy, and the specific input and output relationship is expressed as follows:
Figure RE-GDA0002581227430000051
wherein: l is a radical of an alcoholα，Lβ，LωEnergy output in different forms of energy; cαα，Cβα…， CωωAnd the coupling factors are respectively coupling factors between various types of energy sources, namely steady state comprehensive conversion coefficients between the input and the output of the various types of energy sources.
The expressions of the energy sources are respectively as follows:
Figure RE-GDA0002581227430000052
the modeling of the different types of users is that: respectively establishing a residential user energy hub model, a commercial user energy hub model and a heavy industry user energy hub model according to specific energy use habits and facility types of users, wherein:
the energy hub model of the residential users is as follows: because the residential area of the resident user is limited, and the energy concentrator is not suitable for installing large-scale energy conversion equipment, when the energy concentrator of each user unit in the model comprises a micro fuel cell device and an electric heater, the conversion from hydrogen energy to electric energy and the conversion from electric energy to heat energy can be realized. The structure of the energy hub is shown in figure 3.
When the energy conversion efficiency of the micro fuel cell and the electric heater in the energy concentrator of the residential user is constant, the concept of energy distribution coefficient is introduced according to the law of energy conservation, and the concept of energy distribution coefficient is provided
Figure RE-GDA0002581227430000053
Figure RE-GDA0002581227430000054
Wherein:
Figure RE-GDA0002581227430000055
indicating the electric energy required by the electric heater;
Figure RE-GDA0002581227430000056
representing the hydrogen energy required to supply the micro fuel cell;
Figure RE-GDA0002581227430000057
a hydrogen load, a heat load, and an electric load that are actually supplied to the residential users by the energy hub, respectively;
Figure RE-GDA0002581227430000058
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure RE-GDA0002581227430000059
the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy are respectively;
Figure RE-GDA00025812274300000510
respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the energy hub of the residential user and the comprehensive energy system.
In conjunction with the energy coupling matrix, the energy hub model for the residential user can be based on the following matrix:
Figure RE-GDA0002581227430000061
wherein:
Figure RE-GDA0002581227430000062
indicating the electric energy required by supplying the electric heater;
Figure RE-GDA0002581227430000063
represents the hydrogen energy required to supply the micro fuel cell;
Figure RE-GDA0002581227430000064
a hydrogen load, a heat load, and an electric load that are actually supplied to the residential users by the energy hub, respectively;
Figure RE-GDA0002581227430000065
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure RE-GDA0002581227430000066
the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy are respectively;
Figure RE-GDA0002581227430000067
respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the energy hub of the residential user and the comprehensive energy system.
The commercial user energy hub model is as follows: compared with the resident users, the commercial users have more population, higher total energy consumption and relatively stable daily energy plan, but can adjust the load according to actual conditions, and the energy supply area of a single user is larger than that of the resident users. Therefore, in the present model, each energy concentrator of the user unit includes a micro fuel cell device and a central air conditioning device to satisfy the requirement of large-area heating, and the structure of the energy concentrator is shown in fig. 4.
When the energy conversion efficiency of the fuel cell and the central air conditioner in the energy concentrator of the residential user is constant and is combined with the energy coupling matrix, the energy concentrator model of the commercial user can be expressed by the following expression and matrix:
Figure RE-GDA0002581227430000068
Figure RE-GDA0002581227430000069
wherein:
Figure RE-GDA00025812274300000610
the electric energy is needed for supplying the central air conditioner;
Figure RE-GDA00025812274300000611
to supply the hydrogen energy required by the fuel cell;
Figure RE-GDA00025812274300000612
Figure RE-GDA00025812274300000613
hydrogen load, heat load, and electrical load, respectively, that are actually supplied to the commercial customer by the energy hub;
Figure RE-GDA00025812274300000614
the energy distribution proportion of hydrogen energy and electric energy is respectively;
Figure RE-GDA00025812274300000615
the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy are respectively;
Figure RE-GDA00025812274300000616
the energy interaction quantity of the commercial user energy concentrator and the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the comprehensive energy system are respectively.
The heavy industry user energy hub model is as follows: compared with residential and commercial users, the heavy industrial users have large and strict requirements on electric energy and heat energy because the heavy industrial users include large industrial equipment operating for a long time, and most of the heavy industrial users need to include a chemical reaction process in the production and manufacturing process, and the reaction temperature during operation is strict. Meanwhile, as the sudden power failure event can cause great economic loss to the production process and the durability of equipment, and partial heavy industrial users are considered to take hydrogen as a raw material to participate in production, the energy concentrator of each user unit in the model comprises a fixed fuel cell device, a heat pump device and a hydrogen storage device so as to meet the requirements of large-area energy supply and heating and hydrogen energy raw material storage. The energy hub architecture of a heavy industrial user is shown in fig. 5.
The energy conversion efficiency of the fuel cell and the electric heater in the heavy industry user energy concentrator is constant, and when the hydrogen storage device stores hydrogen, the proportional coefficient of the consumed power of the hydrogen compressor in unit time and the stored amount of the hydrogen is constant, the invention has the following steps:
Figure RE-GDA0002581227430000071
combining an energy coupling matrix and improving, adding an energy storage unit, wherein an energy hub model of a heavy industrial user can be represented by the following matrix expression:
Figure RE-GDA0002581227430000072
wherein:
Figure RE-GDA0002581227430000073
the electric energy required by heat supply of the heat pump is provided;
Figure RE-GDA0002581227430000074
hydrogen energy required by the micro fuel cell is supplied; k is a radical of formulageΔvgConsuming electrical energy for the hydrogen compressor;
Figure RE-GDA0002581227430000075
Figure RE-GDA0002581227430000076
a hydrogen load, a heat load, and an electric load, which are actually supplied to the heavy industrial users by the energy hub, respectively;
Figure RE-GDA0002581227430000077
the hydrogen energy and the electric energy are respectively distributed according to the proportion;
Figure RE-GDA0002581227430000078
respectively representing the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy; k is a radical ofgeThe power consumption for compressing the unit volume of hydrogen;
Figure RE-GDA0002581227430000079
and respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the heavy industrial user energy hub and the comprehensive energy system.
And 5: and establishing an integrated energy system model containing the energy concentrator and used for hydrogen production with electricity. FIG. 6 shows an integrated model of an integrated energy system including a load side energy hub and an electrical hydrogen plant. The energy supply side comprises a thermal power generating unit, a photovoltaic photo-thermal device, a CHP unit, a wind power generating unit, a water electrolysis device, a hydrogen storage device and a fuel cell, and provides electric energy, heat energy and hydrogen energy for the side load of the system; the system side load is automatically responded, distributed and converted by the energy hub, and the actual electric load, heat load and hydrogen load requirements of the user side are met. After the comprehensive demand response process is implemented, the system side load is the input quantity of each type of energy of the user energy hub, and the user side actual load is the output quantity of each type of energy of the energy hub.
The energy concentrator is used as an intermediate hub for realizing loads of an energy supply side and a user side, can receive and process energy information, and realizes coordination transfer and energy conversion of various types of energy according to a price mechanism and a response signal provided by a market.
And 6: a comprehensive demand response constraint including an energy hub is established. In the comprehensive energy system containing the wind power hydrogen production-fuel cell device, the user side comprises different types of energy hubs, so that the demand response of traditional power users can be expanded to the comprehensive demand response of different types of users. Traditional demand response behaviors have dominated the user's response to electrical load on a time scale, including user shedding unnecessary load at peak/peak times and user shifting part of their load from peak/peak times to off-peak times; in the comprehensive demand response, the user can respond to different types of loads through reduction and transfer on a time scale, and can also respond to partial energy of the loads through energy form conversion, for example, the user can use an electric heater to provide heat load when the heat supply price is high, or use a fuel cell to supply power when the electricity price is high and the hydrogen price is low. The relationship between the conventional demand response and the integrated demand response is shown in fig. 7.
According to the model, various transferable loads are considered, and the energy transfer model of the energy system based on comprehensive demand response is obtained as follows:
Figure RE-GDA0002581227430000081
wherein: l isg,t，Lh,t，Le,tActual hydrogen, heat and electricity load values of the user at t time after the comprehensive demand response is finished are respectively obtained;
Figure RE-GDA0002581227430000082
respectively predicting values of hydrogen load, heat load and electric load of a user at t time before response; Δ Lgz,t，ΔLhz,t，ΔLez,tThe variation of hydrogen, heat and electric loads can be transferred in the t period, if the variation is positive, the charge is transferred to the t period, and if the variation is negative, the load is transferred from the t period.
The transferable three types of load constraints of various users, namely, the comprehensive demand response constraint, the user satisfaction constraint and the day-ahead time-of-use electricity price constraint are respectively as follows:
Figure RE-GDA0002581227430000083
Figure RE-GDA0002581227430000084
wherein:
Figure RE-GDA0002581227430000085
the variable quantity of the transferable electric load of the x-th class user at the time t;
Figure RE-GDA0002581227430000086
the hydrogen load proportionality coefficient can be transferred for x-type users in a transferable period;
Figure RE-GDA0002581227430000087
a scaling factor for the transferable thermal load amount for class x users during the transferable period;
Figure RE-GDA0002581227430000088
transferable electric load scale factor for the transferable time period of the x-class users;
Figure RE-GDA0002581227430000089
is the time period during which there is a transferable electrical load.
And combining the comprehensive demand response energy reduction model with the user energy concentrator model to obtain an optimization model of the comprehensive demand response of the comprehensive energy system containing the electricity for hydrogen production, wherein the optimization model comprises the following steps:
Figure RE-GDA00025812274300000810
Figure RE-GDA00025812274300000811
wherein:
Figure RE-GDA00025812274300000812
respectively is the upper limit of the reducible load amount of the x-th class users at the time t;
Figure RE-GDA00025812274300000813
the interval of the time period can be reduced; x belongs to { r, b, id }, wherein r represents a residential user, b represents a commercial user, and id represents a heavy industrial user; and the system provides power to the user in one direction.
Figure RE-GDA0002581227430000091
The proportions of the hydrogen energy and the electric energy are respectively distributed for the resident users,
Figure RE-GDA0002581227430000092
the proportions of the hydrogen energy and the electric energy are respectively distributed for commercial users,
Figure RE-GDA0002581227430000093
the proportions of the hydrogen energy and the electric energy are respectively distributed for heavy industrial users.
Figure RE-GDA0002581227430000094
Figure RE-GDA0002581227430000095
Hydrogen power and electric power consumed by residential users respectively,
Figure RE-GDA0002581227430000096
hydrogen power and electric power consumed by commercial users respectively,
Figure RE-GDA0002581227430000097
hydrogen power and electric power consumed by heavy industrial users, respectively.
Figure RE-GDA0002581227430000098
For the x-th class of users at time t the variation of the electrical load can be transferred,
Figure RE-GDA0002581227430000099
the class x users may shift the amount of change in thermal load for time t,
Figure RE-GDA00025812274300000910
the x-th class of users may shift the amount of change in hydrogen load for time t.
Figure RE-GDA00025812274300000911
Predicted values of hydrogen, heat and electric loads of the x-th class users at the time t before response are respectively obtained.
Figure RE-GDA00025812274300000912
To supply hydrogen energy for the micro fuel cell; k is a radical of formulageΔvgConsuming electrical energy for the hydrogen compressor;
Figure RE-GDA00025812274300000913
hydrogen load, heat load, electric load which are actually supplied to heavy industrial users by the energy hub;
Figure RE-GDA00025812274300000914
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure RE-GDA00025812274300000915
respectively representing the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy; k is a radical ofgeThe power consumption for compressing the unit volume of hydrogen;
Figure RE-GDA00025812274300000916
and respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the heavy industrial user energy hub and the comprehensive energy system.
And 7: user satisfaction constraints are established. The comprehensive demand response process can change the original energy utilization habits of users to different degrees, and the transfer and reduction of different kinds of energy can cause the satisfaction degree of the users to be reduced. Satisfaction degree coefficients of electricity, heat and hydrogen of user types x are respectively defined
Figure RE-GDA00025812274300000917
And the ratio of the change quantity of the electricity, heat and hydrogen load after the comprehensive demand response is implemented to the initial quantity before the response in a time period is in a linear relation, and the expressions are respectively as follows:
Figure RE-GDA00025812274300000918
Figure RE-GDA00025812274300000919
wherein:
Figure RE-GDA00025812274300000920
the minimum satisfaction limiting coefficients for electricity, heat and hydrogen for the user types x are different, and the minimum satisfaction requirements of different types of customers are different.
Figure RE-GDA00025812274300000921
The xth class user may divert the amount of change in the electrical load for time t,
Figure RE-GDA00025812274300000922
a class x user may divert the amount of change in thermal load for time t,
Figure RE-GDA00025812274300000923
the variation of the hydrogen load may be transferred for the xth class of users at time t.
Figure RE-GDA00025812274300000924
Respectively predicting values of hydrogen load, heat load and electric load of the x-th class user at the time t before response;
and 8: and establishing day-ahead time-of-day electricity price constraint. The model introduces a day-ahead time-of-use electricity price mechanism, and forecasts values of hydrogen, heat and electricity loads of users at t time intervals before response
Figure RE-GDA00025812274300000925
And (4) setting the time-of-use electricity price of each time period according to the marginal cost of the power generation of the comprehensive energy system after the initial distribution.
The marginal power generation cost refers to the production cost generated by adding one unit of generated energy under the condition of the current unit output. Since the system is intended to promote the consumption of renewable energy and the CHP unit exists in the system as a standby unit of heat energy, the power generation cost of the system in the t period is composed of the power generation cost of the thermal power unit in the t period. The total power generation cost is as follows:
Figure RE-GDA0002581227430000101
wherein: the power generation cost of the ith thermal power generation cost in the t period is as follows: f. ofi(Pi,t)＝ai+biPi,t+ciPi,t 2，Pi,tAs a generator output value, ai，biAnd ciThe coefficients of the constant term, the first term and the second term of the generator cost function are constants respectively. u. ui,tThe starting and stopping states of the generator are variable 0-1. Si,tIs the start-up and shut-down cost of the generator. Incremental cost lambda of ith thermal generator seti,e,tAs the first derivative of the cost function fi (Pi, t):
Figure RE-GDA0002581227430000102
according to the equal micro-increment rate criterion, all the running generator sets in the energy system have the minimum total energy loss and the highest economical efficiency when running at the equal energy consumption micro-increment rate. In the comprehensive energy system, the running cost coefficients of all the units are different, and the marginal cost of the power generation side is the incremental cost average value of the real-time running units, namely: lambda [ alpha ]ge,t＝Avg{λi,e,t,i∈Nrun,t}, in which: and Nrun, t is the number set of the running unit at the time t. According to the marginal cost, the price of the electricity price of the xth user in time-of-use before the time t day is set as follows:
Figure RE-GDA0002581227430000103
wherein:
Figure RE-GDA0002581227430000104
the premium factor of the power generation side for the x-th class users.
And step 9: establishing system electric power balance constraint, thermodynamic balance constraint and hydrogen balance constraint conditions in the system balance constraint model as follows:
Figure RE-GDA0002581227430000105
wherein: n is a radical of hydrogenWThe number of wind generating sets in the comprehensive energy system; n is a radical ofVThe number of photovoltaic photo-thermal units;
Figure RE-GDA0002581227430000106
the output power of the wind turbine generator i in the time period t is obtained;
Figure RE-GDA0002581227430000107
the output power of the photovoltaic cell i in the t period; pe,tThe power absorbed by the electrohydrogen production device in the time period t; pf,tPower discharged for the fuel cell during the time period t; p isload,tThe total load of the integrated energy system in the time period t. VH,tHydrogen capacity in the hydrogen storage device for a period of time t; vHload,tIs the hydrogen load demand over time t. HL,tThe heat load of the comprehensive energy system at the time t is realized; etaheatThe heat energy utilization ratio for the heating network;
Figure RE-GDA0002581227430000108
the thermal output of the photovoltaic and photo-thermal unit in the period of t and Hloss,tAnd the heat power loss of the pipeline in the t period.
Step 10: establishing the operation constraint of a comprehensive energy system containing wind power hydrogen production, which specifically comprises the following steps:
i) wind power hydrogen production-fuel cell device constraint: in the wind power hydrogen production-fuel cell device, the water electrolysis process absorbs power and generates hydrogen, and the relationship between the absorbed power and the hydrogen output is as follows: pe,t＝ηeVHe,tWherein: p ise，tThe power absorbed during electrolysis of water for a period of time t, including rectifier losses and hydrogen compression power consumption; etaeThe power consumed to produce a unit volume of hydrogen.
The fuel cell consumes hydrogen and outputs power, and the relationship between hydrogen consumption and output power is: pf,t＝ηfVHf,tWherein: pf, t is the output power of the fuel cell for the period t taking into account the inverter losses; etafThe power released to consume a unit volume of hydrogen; VHf, t is the volume of hydrogen consumed by the fuel cell during time t.
In the operation constraint of the comprehensive energy system containing wind power hydrogen production, the electric hydrogen production device only produces hydrogen when wind power is abundant or hydrogen reserves are insufficient to meet the load, and the fuel cell only generates power when wind power is completely consumed, so that the requirements are met: w is ae,iue,t+wf, iuf,t≤1，
Figure RE-GDA0002581227430000111
Wherein: w is ae，t、wf，tFor the initialization state parameters of the electric hydrogen production device and the fuel cell device, 0 represents that the electric hydrogen production device is in a forced shutdown state, 1 represents that the electric hydrogen production device is in an adjustable working state, and the initialization parameters are obtained by an initialization assignment process; u. ofe，t，uf，tThe variable is the operation state 0-1 variable of the electric hydrogen production device and the fuel cell, 0 represents that the electric hydrogen production device is in a shutdown state, and 1 represents that the electric hydrogen production device is in a working state;
Figure RE-GDA0002581227430000112
and
Figure RE-GDA0002581227430000113
the maximum values of the consumed power of the electrolysis device and the output power of the fuel cell are respectively;
Figure RE-GDA0002581227430000114
and
Figure RE-GDA0002581227430000115
respectively, the minimum value of the electrolyzer consumed power and the fuel cell output power.
ii) the storage equilibrium constraint for hydrogen is:
Figure RE-GDA0002581227430000116
wherein: vH，tHydrogen capacity in the hydrogen storage device for a period of t; vHload,tIs the hydrogen load demand over time t.
The storable amount of hydrogen and the power constraints of the wind turbine are:
Figure RE-GDA0002581227430000117
Figure RE-GDA0002581227430000118
wherein:
Figure RE-GDA0002581227430000119
is the maximum hydrogen storage capacity;
Figure RE-GDA00025812274300001110
the maximum output power of the ith wind turbine generator is set;
Figure RE-GDA00025812274300001111
the maximum output power of the ith photovoltaic cell.
iii) thermodynamic system constraints: the total heat output balance constraint of this thermal power grid is:
Figure RE-GDA00025812274300001112
wherein: hL，tThe heat load of the comprehensive energy system at the time t is achieved; etaheatThe heat energy utilization ratio for the heating network;
Figure RE-GDA00025812274300001113
thermal output of photovoltaic and photothermal unit at t time period, Hloss，tThe thermal power loss of the pipeline in the t period.
The thermal system meets the heat load requirement through a fuel cell and a photovoltaic photo-thermal system. The traditional gas turbine cogeneration operation mode has two working states including 'fixing power by heat' and 'fixing heat by electricity', the invention aims to increase the consumption of clean energy, and the heat-electricity demand ratio of the invention is obviously smaller than the rated heat-electricity ratio of a fuel cell, so when a fuel cell device and a CHP unit are both in a 'fixing heat by electricity' mode, the constraint conditions are as follows: hf,t＝KfPf,t，Hchp,t＝KchpPchp,t，
Figure RE-GDA00025812274300001114
Which are the thermoelectric ratio constraint of the fuel cell, the thermoelectric ratio constraint of the CHP unit, and the upper and lower limit constraints of the output of the fuel cell, respectively. Kf is the thermoelectric ratio, Kchp is the thermoelectric ratio of the CHP unit,
Figure RE-GDA00025812274300001115
is the minimum value of the output force of the fuel cell,
Figure RE-GDA00025812274300001116
is the maximum fuel cell output.
The thermodynamic system transfers heat through water, and the heat energy flows through a heat source j and has the mass Qsh，jWater temperature T of return waterh，j，tRaising the temperature to the water supply temperature Tg，j，tAnd delivered to a thermal load; the water with the heat load quality QL flows through the water supply temperature TgL，tReducing to the return water temperature ThL，tThen the heat absorbed by the heat load nodePower HL，tSatisfies the following conditions: hL,tΔt＝cwQL(TgL,t-ThL,t)，ηheatHj,tΔt＝cwQsh,j(Tg,j,t-Th,j,t) Wherein: c. CwIs the specific heat capacity of water. And at the heat source, the return water temperature of the heat load point in the previous period is the return water temperature of each heat source in the next period, and then: t is a unit ofhj,t＝ThL,t-1。
The hot water capacity balance constraint and the hot water mix temperature balance constraint at the heat load point are as follows, where NRThe total number of heat sources:
Figure RE-GDA0002581227430000121
thermal power loss exists in the thermal power transmission process of the thermodynamic system: hloss,tΔt＝λwQL(Tg,t-T0,t) Wherein: t is0，tIs the ambient temperature at time t; lambda [ alpha ]wThe heat transfer coefficient from the point of the heat source to the heat exchange station. The coefficient is linear with the node distance, when the distances between each heat source and the nodes of the heat exchange station are equal in the model, namely lambdawIs a fixed constant.
In addition, during the pipeline transportation process, the supply water temperature and the return water temperature are limited by the allowable value of the pipeline transportation equipment:
Figure RE-GDA0002581227430000122
wherein:
Figure RE-GDA0002581227430000123
the minimum temperature limit values of the water supply pipeline and the water return pipeline are respectively set;
Figure RE-GDA0002581227430000124
the maximum temperature limit values of the water supply pipeline and the water return pipeline are respectively.
iv) CHP train constraints: the comprehensive energy system comprises a CHP unit to meet the heat energy supply of the system in the heat consumption peak period, and the constraint conditions are as follows:
Figure RE-GDA0002581227430000125
it is the power limit restraint of CHP unit and the climbing restraint of CHP unit respectively, wherein:
Figure RE-GDA0002581227430000126
and
Figure RE-GDA0002581227430000127
respectively the minimum output and the maximum output of the CHP unit;
Figure RE-GDA0002581227430000128
and
Figure RE-GDA0002581227430000129
the power limit of the upper and lower climbing of the CHP unit is respectively.
v) photovoltaic photo-thermal unit constraint: the photovoltaic photo-thermal unit consists of a photovoltaic device and a photo-thermal device. The photovoltaic device can convert the absorbed solar energy into electric energy; the photo-thermal device concentrates direct solar energy to the heat-conducting medium to heat so as to provide thermal power for the system, and the thermoelectric ratio of the photo-thermal device is Kv. Because the primary energy is solar energy, the operation of the system is cleaner and more environment-friendly than that of the traditional CHP unit. The output thermoelectric ratio constraint is as follows:
Figure RE-GDA00025812274300001210
vi) thermal power generating set constraint: the comprehensive energy system of the invention comprises devices such as a wind power hydrogen production-fuel cell and the like, and also comprises a traditional thermal power generating unit, and the constraint conditions are as follows:
Figure RE-GDA00025812274300001211
ui,tPi min≤Pi,t≤ui,tPi max，
Figure RE-GDA0002581227430000131
it is respectively the rotation standby restraint of the thermal power unit, the upper and lower limit restraint of the output power of the thermal power unit, the upward climbing restraint and the downward climbing restraint of the thermal power unitBundle, cold-hot start constraint, wherein: rt is the total standby power of the system;
Figure RE-GDA0002581227430000132
and
Figure RE-GDA0002581227430000133
the maximum output power and the minimum output power of the unit i are respectively; pup, i is the rise power limit of the unit i; pstart, i is the starting power limit of the unit i; pbrown, i is the power reduction limit of the unit i; pshut, i is the shutdown power limit of the unit i;
Figure RE-GDA0002581227430000134
the minimum starting time of the unit i is set;
Figure RE-GDA0002581227430000135
the minimum shutdown time of the unit i.
Step 11: and constructing an objective function. The invention models the comprehensive energy system of the hydrogen production device containing the electricity considering the comprehensive demand response, considers the influence of the introduced comprehensive demand response on the optimized operation of the whole system, and respectively establishes to minimize the social total cost (hereinafter referred to as an objective function f)A) Minimizing the user energy cost (hereinafter referred to as objective function f)B) And minimizing the energy supply side operating cost (hereinafter referred to as objective function f)C) The optimization model of (1).
The objective function is as follows: min frun＝fc+fchp+fd+feWherein: f. ofcF, total operating cost of the thermal power generating unitdRunning cost of the compression apparatus, fchpCost of coal for CHP units, feIs the transmission cost of hydrogen and heat pipeline media, wherein:
Figure RE-GDA0002581227430000136
Figure RE-GDA0002581227430000137
wherein: t, i and j are respectively time interval, thermal power generating unit and photovoltaic photo-thermal deviceNumbering; t is an optimization period; n is a radical ofGThe number of the thermoelectric generator sets in the comprehensive energy system; p isi,tThe output power of the thermal power generating unit i in the t time period is obtained; u. ofi,tIs a variable of 0 to 1 of the running state of the unit i in the period t; c. CchpThe unit coal consumption of CHP unit power generation; hchpT is the thermal output of the CHP unit when the CHP unit operates in the time period t; c. CHUnit gas compression cost for the compressor; vHe,tVolume of hydrogen produced by the electrolyzer for period t; c. CtHydrogenIs the transmission cost per unit of hydrogen; vHload,tTotal volume of hydrogen supplied to the load for time period t; c. CtHeatUnit transmission cost of heat power of a heat source; hf,tThermal power released by the fuel cell when combusting hydrogen over a period of time t; hchpT is the thermal power released by the CHP unit when the CHP unit operates in the t period; hG,j,tThermal power released by the jth photovoltaic photo-thermal device in a t period; n is a radical ofVThe number of photovoltaic optothermal devices in the system; f. ofi(Pi,t) The power generation cost of the thermal power generating unit is as follows: f. ofi(Pi,t)＝ai+biPi,t+ciPi,t 2Wherein: a is ai,bi,ciThe power generation cost coefficient of the unit i and the starting cost of the unit i in the period t
Figure RE-GDA0002581227430000138
Wherein:
Figure RE-GDA0002581227430000139
minimum downtime of unit i, Ti,tThe time of continuous operation or continuous shutdown of the unit i in the T-th time period is positive when the unit i is in continuous operation time and negative when the unit i is in continuous shutdown time, and Tcold,iIs the cold start time of unit i.
(1) Taking into account supply side energy purchase yield finThe total running cost of the comprehensive energy system of the hydrogen production device containing the electricity is as follows: fg＝fc+fchp+fd+fe，fcThe method comprises the following steps of (1) setting the total operation cost of the thermal power generating unit:
Figure RE-GDA0002581227430000141
fchpfor CHP unit coal cost:
Figure RE-GDA0002581227430000142
fdfor hydrogen-containing plant operating costs:
Figure RE-GDA0002581227430000143
fefor heat distribution pipeline medium transmission cost:
Figure RE-GDA0002581227430000144
(2) the system considers the time-of-use electricity price, the heat energy and the supply price of the hydrogen energy of the electric energy, and the price curves of the electricity, the heat and the hydrogen energy are different according to different user types. The energy concentrator can automatically reduce and transfer energy according to various energy price signals and can convert different energy according to contained equipment. The user energy cost price is:
Figure RE-GDA0002581227430000145
wherein:
Figure RE-GDA0002581227430000146
Figure RE-GDA0002581227430000147
the electricity purchase prices of residents, commercial and heavy industrial users in the time period t are respectively;
Figure RE-GDA0002581227430000148
the heat supply price of the system for the residents, the businesses and the heavy industrial users in the period t;
Figure RE-GDA0002581227430000149
the hydrogen purchase price is the hydrogen purchase price of residents, businesses and heavy industrial users in the period t.
Based on the comprehensive energy system scene of the embodiment, a simulation platform is built according to the method designed by the invention, and the multi-energy complementation of hydrogen production containing electricity designed by the invention is testedThe system integrates the performance of the demand response model. The computer configuration environment relied on in this embodiment is as follows:
software/hardware Version/model
Operating system Windows 10
Memory device 8GB RAM
CPU Intel Core i5-8400 [email protected]
Matlab R2014a
In this embodiment, the background of the reoebel energy source reconstruction industrial park in inner Mongolia of China is used as a reference, and the comprehensive energy system of the test example comprises: 2 wind power generation units, 1 electric hydrogen production unit, 1 fuel cell, 1 hydrogen storage unit, 1 solar photovoltaic photo-thermal device, 10 thermal power generation units and 1 heat exchange station. The period T of the optimization solution is 24h, and the time interval delta T is 1 h. In the morning, 0:00-1:00 is set as the 1 st time period, and 23:00-24:00 is the 24 th time period. The data of the wind power generating set is shown in fig. 23, the electric load, the heat load and the hydrogen demand in the comprehensive energy system are shown in fig. 24, and the power generation cost parameters of the thermal power generating set are shown in table a.
TABLE A Power Generation cost parameter of thermal power generating Unit
Figure RE-GDA00025812274300001410
Figure RE-GDA0002581227430000151
The first step is that the predicted value is based on the load of each user
Figure RE-GDA0002581227430000152
For setting up devices for producing hydrogen containing electricityThe comprehensive energy system optimization operation model takes the lowest total operation cost of the comprehensive energy system as a target function, and takes the operation constraint of the comprehensive energy system containing the wind power hydrogen production established in the step 10 in the invention content as a constraint condition.
The second step: and calling GUROBI 8.0.1 software through a MATLAB 2014a platform to solve the target function. And obtaining a system operation mode before response according to the solution result, and calculating time-sharing price information of each user energy according to the time-sharing price information, including unit marginal cost and various user energy price curves.
Solving to obtain the marginal cost of power generation of each unit of the system, counting the sum of the marginal cost of the power generation units and the number of the units in operation, obtaining the average value of the marginal cost of power generation of the units as the marginal cost of power generation of the system according to an equal differential rate criterion, and drawing a curve of the marginal cost of power generation of the hydrogen-containing comprehensive energy system as shown in fig. 9.
Setting the premium coefficient of the user general class according to the marginal cost of power generation of the system, and setting the premium coefficient of the user general class according to the marginal cost of power generation of the system
Figure RE-GDA0002581227430000153
And (3) solving time-of-use electricity price curves of various users, and setting hydrogen peak-valley prices and thermal power peak-valley prices of various users based on the time-of-use electricity price curves, as shown in table 3. According to the characteristics of electricity, heat and hydrogen demand of users in different time periods, peak-valley time periods of heat supply and hydrogen supply prices are set, and specific energy time-sharing price curves of three types of users are shown in fig. 10.
TABLE 3 statistical table of overflow price coefficient and energy consumption price of various users
Figure RE-GDA0002581227430000154
The third step: the transferable coefficients and the transferring time periods of the loads of various types of users are set as shown in table 4.
TABLE 4 transferable coefficients and transferring periods of various user loads
Figure RE-GDA0002581227430000155
The fourth step: and setting three objective functions and two operation modes, and respectively carrying out solution and result comparison analysis.
The comprehensive energy system of the hydrogen production plant containing the electricity is modeled by considering the comprehensive demand response, and considering the influence of the introduced comprehensive demand response on the optimized operation of the whole system, an optimized model is respectively established by minimizing the social total cost (hereinafter referred to as an objective function fA), minimizing the user energy cost (hereinafter referred to as an objective function fB) and minimizing the energy supply side operation cost (hereinafter referred to as an objective function fC). The three objective functions are embodied in the same way as the step 11 of the summary of the invention, and are respectively realized in the actual solution by adding three types of energy hubs. The integrated demand response operation mode 1 (hereinafter, referred to simply as mode 1) is set as an integrated demand response considering only the transferable loads, and the integrated demand response operation mode 2 (hereinafter, referred to simply as mode 2) is set as an integrated demand response comprehensively considering the transferable and transferable loads.
And respectively solving the optimization model by taking the minimized social total cost as a target in the mode 1 and the mode 2 and taking the comprehensive demand response constraint, the user satisfaction constraint, the day-ahead time-of-day electricity price constraint, the system balance constraint and the comprehensive energy system operation constraint containing wind power hydrogen production of the energy hub established in the steps 3-10 as constraint conditions to obtain an optimization solution result.
In the mode 2, the system is subjected to comprehensive demand response of the mode 2 by respectively aiming at minimizing the total cost of energy consumption (fB) for users and the total cost of running on the energy supply side (fC), and the result is compared with the goal of minimizing the total social cost (fA) in the mode 2.
The total operating cost of each system obtained by solving in the mode 1 is shown in table 5, and the comparison situation of the wind power consumption situation at each time interval is shown in fig. 11. As can be seen from table 5, the total social cost is reduced by 35914 $beforeand after the implementation mode 1, where the user energy cost is reduced by 2651$, and the energy supply cost on the energy supply side of the integrated energy system is reduced by 33263$, from which it is seen that the reduction of the total social cost can be effectively achieved by introducing the transferable load demand response, and in the case of implementation time-of-use electricity prices, both the user energy cost and the system energy supply side cost can be reduced.
As can be seen from fig. 11, in the mode 1, the wind power consumption of the system 4 is significantly increased in a period, and compared with the mode 1 in which the demand response is not considered, the total wind power consumption of each period is increased by 1435.3MW, it is known that the wind curtailment rate of the system can be effectively reduced by introducing the mode 1, and the clean energy consumption is increased.
TABLE 5 Total cost ($) of each operation of the integrated energy system in mode 1
Figure RE-GDA0002581227430000161
Fig. 12 is a comparison curve of the total load of the system before and after the introduction of the comprehensive demand response in the mode 1, fig. 13 is a change situation of the electric, thermal, and hydrogen loads of each type of user before and after the introduction of the comprehensive demand response in the mode 1, and tables 4 to 5 are energy cost and satisfaction situations of each type of user before and after the demand response in the mode 1. From fig. 12, after introducing mode 1, the load of the system is significantly reduced in 11-13 original peak periods, and the total load peak-valley difference of the user is reduced from 800MW to 757MW by increasing the load in 1-3, 17-19, 23-24 original valley periods, which is caused by the energy hub shifting the peak period load to the valley period, so that introducing mode 1 can realize peak clipping and valley filling to the system load.
TABLE 6 energy cost and satisfaction for various users before and after demand response in mode 1
Figure RE-GDA0002581227430000162
Figure RE-GDA0002581227430000171
In fig. 13, three types of users have different degrees of response due to the difference in the transferable coefficients of the various types of loads. Wherein the electrical load curve in fig. 13c) varies most significantly for heavy industrial users with a transferable electrical load factor of 20%; the transferable electrical load factor of the commercial user is only 5%, the electrical load curve in fig. 13b) changes the least, and is closest to the original predicted load curve. As can be seen from table 6, the energy cost reduction can be achieved at the sacrifice of the satisfaction degree after the response of the various users in the mode 1, wherein the commercial user reduction cost ratio is 0.22% and the power consumption satisfaction degree is the highest, and the heavy industry user reduction cost ratio is 0.6% and the power consumption satisfaction degree is the lowest.
Analysis of optimized results in mode 2 with the goal of minimizing the total social cost
In order to make the calculation result more intuitive, the invention sets the energy conversion coefficient between each type to be 1, namely, the energy between each type can realize complete conversion, and the transfer coefficients of different types of energy in the comprehensive demand response process are the same as the above. The effect after the contrast mode 2 response relative to before the response and after the mode 1 response is analyzed. In the mode 2, the total operating costs of the system before and after the comprehensive demand response is introduced are shown in table 7, and the wind power consumption ratio in each time period is shown in fig. 13.
TABLE 7 Total cost ($) of operation of the integrated energy system before and after different mode response
Figure RE-GDA0002581227430000172
As can be seen from FIG. 14, in the mode 2, the wind power consumption of the system in a plurality of periods is increased obviously, and compared with the mode 2 without considering the comprehensive demand response, the wind power consumption of each period is increased by 2036.6 MW; compared with the mode 1, the mode 2 consumes more wind power 601.3MW than the mode 1 in FIG. 11. As can be seen from fig. 15, the electrolytic devices in the system after the mode 2 is introduced have significantly improved working efficiency at 4, 6, and 22, and provide more hydrogen reserve for the system by consuming surplus wind electricity, which is caused by the energy hub automatically converting part of the hydrogen into electricity when the hydrogen price is lower than the electricity price; the fuel cell in the comprehensive energy system releases increased power in 6-9 and 12-17 hours, and clean electric energy and heat energy are provided for the system, so that the operation cost of the traditional thermal power generating unit and the CHP unit is reduced. Therefore, the introduction of the convertible comprehensive demand response can effectively enhance the clean energy consumption capability of the system and reduce the wind curtailment rate of the system.
Fig. 16 is a total load comparison curve of the integrated demand response system introduced in the mode 2, fig. 17 is a change situation of electric, thermal, and hydrogen loads before and after the integrated demand response is introduced for three types of users in the mode 2, table 8 is a total energy conversion amount of the user-side energy hub between different types of energy in the mode 2, and table 9 is a situation of energy cost and satisfaction of various types of users before and after the integrated demand response is introduced for three types of users in the mode 2. As can be seen from Table 8, in mode 2, the residential, commercial and heavy industrial users all transfer part of the different kinds of loads after response, and the total power is converted into 418MW and the total power is converted into 276.8 MW.
TABLE 8 Total load transfer for subscriber-side energy concentrator in mode 2
Figure RE-GDA0002581227430000173
Figure RE-GDA0002581227430000181
As can be seen from fig. 16, the peak-to-valley load of the system after the demand response is introduced in the mode 2 is reduced by 755.5MW compared with that before the demand response is not responded, which is basically equal to the reduction amount in the mode 1, and as can be seen from fig. 17, the electrical loads of various users are obviously reduced at the time 22, because the price of hydrogen is lower than that of electricity during the time 22, and the energy hub automatically converts the hydrogen energy into the electrical energy to reduce the supply pressure on the energy supply side of the integrated energy system. Compared with fig. 16 and 12, after various users respond in the mode 2, the jitter frequency of the electric load curve is higher than that in the mode 1, and the hydrogen load curve and the thermal load curve are changed to a greater extent, except for the increase of the load capacity caused by temporary shortage of wind power and the limited climbing constraint of the thermal power unit at the time of 21, the various load curves are reduced at the rest wave crests, and are improved at the wave troughs; from table 9, it can be seen that the cost of the residential, commercial, and heavy industrial users in the mode 2 is reduced by 0.34%, 0.29%, and 1.0% respectively after the responses, compared with the results after the responses in the mode 1, the user energy cost in the mode 2 is lower and the satisfaction degree is higher, so that the user satisfaction degree can be improved while the user energy cost is reduced by introducing the mode 2, because the mode 2 introduces the interconversion between loads, enhances the coupling relationship between multiple energies, preferentially selects low-price energy to satisfy the same effect, and improves the diversity and sensitivity of the comprehensive demand response.
TABLE 9 energy costs ($) and satisfaction degree for various users before and after different mode responses
Figure RE-GDA0002581227430000182
Mode 2 optimization result analysis comparison under three targets
And respectively aiming at minimizing the total cost of energy for a user (fB) and the total cost of running of an energy supply side (fC), carrying out comprehensive demand response of a mode 2 on the system, wherein the transfer coefficient and the time interval of different types of energy sources in the system and the conversion coefficient between the energy sources are the same as those set before, and comparing the result with the goal of minimizing the total social cost (fA) in the mode 2.
In the mode 2, the total operating costs of the system before and after the system introduces the comprehensive demand response by respectively taking fA, fB and fC as targets are shown in table 10, the wind power consumption condition pair in each time period is shown in fig. 18, and the output change of the hydrogen-containing device of the system before and after the demand response is shown in fig. 19.
TABLE 10 statistics of the results of the three objective function responses before and after
Figure RE-GDA0002581227430000183
Figure RE-GDA0002581227430000191
As can be seen from Table 10, the values are given in fA，fB，fCAfter the target response, the energy consumption cost of the system is reduced, and f is used for reducingA，fCThe total social cost and the energy supply cost of the system are obviously reduced after the target response is carried out, and f is usedBThe total social cost of the system is increased after the target response, mainly reflected in the increased cost of the energy supplier of the system, because the target fBOnly the energy cost of the user is considered, and the energy hub can not preferentially consume the surplus new energy of the system only according to the transferable and transferable load of the user energy price minimum response. Combine FIG. 18 and FIG. 19, take fCWhen the system is a target function, the wind power consumption capacity of the system is the strongest, the total consumption is 15139MW, the wind abandon rate is reduced by 1419MW compared with that of the system before response, the input power of an electrolysis device in a hydrogen-containing device of the system is increased by 84MW, the output power of a fuel cell is increased by 84MW, hydrogen is produced by the system for consuming surplus wind power, only the gas compression cost exists, and the extra hydrogen is completely input into the system for power supply and heat supply, so that the original power generation and heat generation cost is reduced; with fBWhen the response energy supply system is a target function, the wind power consumption capacity of the system is weakest after response, only 12032MW is consumed, compared with the wind abandon rate before response, 1688KW is increased, the medium fuel cell of the electrolysis device in the energy supply system does not output power after response, and hydrogen produced by wind power is input into the energy concentrator to meet the hydrogen load demand and the hydrogen-to-electricity process in the convertible load.
FIG. 20 shows the values of f in the pattern 2A，fB，fCThe total load comparison curve of the comprehensive demand response system is introduced for the target, and f is respectively used for various users in fig. 21 and 22B，fCThe change of the electrical, thermal and hydrogen load before and after the introduction of the comprehensive demand response for the objective function is shown in Table 11 for three types of usersA，fB，fCThe energy cost and satisfaction degree of various users before and after the comprehensive demand response is introduced for the target.
From FIG. 20 it can be seen that fA，fCThe response curves trend substantially the same, with fB at 9, 14, 20-22 the load curve trend is opposite to the original load trend before response, due to the automatic allocation of the energy hub targeting the minimum total energy cost for the user when the hydrogen price is lower than the electricity price. As can be seen from tables 11, 21 and 22, f isBThe overall satisfaction coefficient of the user is the lowest when the function is an objective function, and f is usedAThe overall satisfaction factor of the user is the highest for the objective function, which isSince only fBThe targeted energy hub will invoke all user-adjustable loads at the expense of user mass satisfaction to achieve cost reduction, and fA，fCResponse is made from the standpoint of system power side operating costs and overall planning. Compare with fBIn f withCThe energy supply side operation total cost is more economic benefits for the social total cost, the consumption of clean energy can be greatly improved, the unit start-stop cost of the system is reduced, the total cost is reduced by 178927 dollars, and meanwhile, the peak-valley difference of electricity consumption of a user is reduced by 43.16MW through matching with the system, so that certain economic benefits are obtained, and the cost of specific energy saving is 11881 dollars.
Table 11 user satisfaction and energy cost ($) before and after different mode responses
Figure RE-GDA0002581227430000192
Comprehensive comparison fA，fB，fCIt can be seen that the three objective functions are substantially obtained by adding the energy cost of the user side and the operation cost of the energy supply side according to different weighting coefficients, and the specific implementation objective in the practical situation is determined by the provider of the operation strategy of the energy hub, and the benefit distribution ratio between the user side and the energy supply side can be changed by changing the weighting coefficients of the energy cost of the user side and the operation cost of the energy supply side.
In consideration of the future development trend of hydrogen and the application of the wind power hydrogen production device in a comprehensive energy system, the invention meets the requirements of electric power, hydrogen and heat load through the mutual conversion among various energy sources. Compared with the conventional natural gas, hydrogen serving as a clean carbon-free secondary energy source can be produced when new energy is abundant and exists in the system in the form of energy storage, and can output power for the system through a fuel cell when the new energy is in a valley or in a low load. The invention considers the influence of peak-valley electricity price, provides an electricity-containing hydrogen production comprehensive energy system model under the power demand response, and adopts electric quantity electricity price elastic matrix modeling and solving. The users are divided into extremely flexible and heavy industrial users, relatively flexible industrial users, general commercial users and residential users according to the user energy consumption characteristics and different response degrees of the user energy consumption characteristics to price signals. Further, a comprehensive demand response model of the hydrogen-containing comprehensive energy system is established based on a day-ahead time-of-use electricity price solving algorithm of the power generation marginal cost, and an energy hub is used as an information receiving and processing and energy conversion carrier, so that automatic response of electricity, heat and hydrogen is realized for various users. Compared with the traditional peak-valley electricity price type demand response, the model can calculate the day-ahead time-of-day electricity price curve according to the predicted wind, light and user load data, and automatically realize the time transfer of various types of loads and the conversion among different energy sources. By changing the weight ratio of the energy supply side and the user side in the objective function, adjustment of the economic cost allocation can be realized. Meanwhile, the energy concentrator is used as a control carrier, so that monitoring, collection and statistics of energy information are completed, and the effectiveness and fairness of automatic demand response are guaranteed.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (8)

1. A demand response operation optimization method for a multi-energy complementary system for promoting surplus wind power consumption is characterized in that a comprehensive energy system model containing electricity and hydrogen production and a comprehensive energy system operation optimization operation model using an energy concentrator as an information receiving and processing and energy conversion carrier are established, and a comprehensive demand response mode based on demand response of power load and day-ahead time-of-use electricity price is established to perform resource optimization configuration on the comprehensive energy system containing electricity and hydrogen production, so that the effective consumption of surplus wind power and the total cost saving of system operation are realized, and the method specifically comprises the following steps:
step 1: according to the actual physical structure of the wind power hydrogen production-fuel cell device in the integrated energy system, the physical connection of a transmission system and a distribution system of a thermodynamic system, and the multiple coupling relationship and load requirements among different energy forms, a composite working mode of the integrated energy system containing the electricity for hydrogen production is provided;
and 2, step: based on the complementarity of the comprehensive energy system, a comprehensive demand response mode is designed, namely, a user can replace electric energy with low-price energy in the peak period of electricity utilization, the energy supply pressure of an energy supply side is reduced, and the energy utilization cost of the energy utilization side is saved;
and step 3: establishing an energy hub model;
and 4, step 4: modeling different types of users by utilizing an energy hub model, introducing a transferable load and a transferable load into the model, and establishing an optimization model of comprehensive demand response of the comprehensive energy system containing electricity and hydrogen;
and 5: sequentially establishing an electric power-containing hydrogen production comprehensive energy system model containing an energy concentrator, comprehensive demand response constraint containing the energy concentrator, user satisfaction constraint, day-ahead time-of-use electricity price constraint, system balance constraint, system electric power balance constraint and comprehensive energy system operation constraint containing wind power hydrogen production in the model, and constructing a target function;
and 6: solving the objective function to obtain a system operation mode before response, calculating energy time-sharing price information of each user according to the system operation mode, setting load transferable coefficients and transferring time periods of various users and realizing optimization;
the energy hub model is used for modeling different types of users, namely, according to an energy hub serving as an operation center for comprehensive demand response, hydrogen energy, electric energy and heat energy from a supply side are converted into hydrogen, cold and heat demands of a user side through a transformer, a fuel cell and a heat pump device respectively, and the input and output relations of the energy hub are represented as follows:
Figure FDA0003626875140000011
wherein: l isα，Lβ，LωEnergy output in different energy forms; cαα，Cβα…，CωωCoupling factors among various types of energy sources, namely steady-state comprehensive conversion coefficients among input and output of various types of energy sources;
respectively establishing a residential user energy hub model, a commercial user energy hub model and a heavy industrial user energy hub model according to the specific energy habits and facility types of users, wherein:
the energy hub model of the residential users is as follows:
Figure FDA0003626875140000021
wherein:
Figure FDA0003626875140000022
indicating the electric energy required by supplying the electric heater;
Figure FDA0003626875140000023
representing the hydrogen energy required to supply the micro fuel cell;
Figure FDA0003626875140000024
a hydrogen load, a heat load, and an electric load, which are actually supplied to the residential users by the energy hub, respectively;
Figure FDA0003626875140000025
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure FDA0003626875140000026
the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy are respectively;
Figure FDA0003626875140000027
respectively representing energy interaction quantities of a hydrogen energy system, a thermodynamic system and a power grid in the energy hub of the residential user and the comprehensive energy system;
the energy hub model for the business user is:
Figure FDA0003626875140000028
Figure FDA0003626875140000029
wherein:
Figure FDA00036268751400000210
the electric energy is needed for supplying the central air conditioner;
Figure FDA00036268751400000211
hydrogen energy required by the fuel cell is supplied;
Figure FDA00036268751400000212
a hydrogen load, a heat load, and an electrical load that are actually supplied to the commercial customer by the energy hub, respectively;
Figure FDA00036268751400000213
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure FDA00036268751400000214
the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy are respectively;
Figure FDA00036268751400000215
energy interaction quantities of a hydrogen energy system, a thermodynamic system and a power grid in the commercial user energy hub and the comprehensive energy system are respectively;
the heavy industry user energy hub model is as follows:
Figure FDA00036268751400000216
wherein:
Figure FDA00036268751400000217
the electric energy required by heat supply of the heat pump is provided;
Figure FDA00036268751400000218
to supply hydrogen energy for the micro fuel cell; k is a radical ofgeΔvgConsuming electrical energy for the hydrogen compressor;
Figure FDA00036268751400000219
a hydrogen load, a heat load, and an electric load, which are actually supplied to the heavy industrial users by the energy hub, respectively;
Figure FDA00036268751400000220
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure FDA00036268751400000221
respectively representing the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy; k is a radical ofgeThe power consumption for compressing the unit volume of hydrogen;
Figure FDA00036268751400000222
and respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the heavy industrial user energy hub and the comprehensive energy system.
2. The method for optimizing demand response operation of a multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the comprehensive energy system model for hydrogen production with electricity has energy flow and load demands in various forms, various coupling relations exist among different energy forms, and mutual conversion is carried out in the comprehensive energy system in a composite working mode.
3. The method for optimizing demand response operation of a multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the composite working mode comprises: the system comprises a power generation mode, a heat generation mode, a hydrogen production mode, a power generation heat generation mode, a heat generation hydrogen production mode, an energy surplus hydrogen production mode and an extreme supply shortage mode.
4. The method for optimizing the demand response operation of the multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the optimization model of the comprehensive demand response of the comprehensive energy system for hydrogen production by electricity comprises the following steps:
Figure FDA0003626875140000031
Figure FDA0003626875140000032
wherein:
Figure FDA0003626875140000033
respectively is the upper limit of the reducible load amount of the x-th class users at the time t;
Figure FDA0003626875140000034
the interval of the time period can be reduced; x belongs to { r, b, id }, wherein r represents a residential user, b represents a commercial user, and id represents a heavy industrial user; and the system provides power to the user in one direction;
Figure FDA0003626875140000035
the proportions of the hydrogen energy and the electric energy are respectively distributed for the resident users,
Figure FDA0003626875140000036
the proportions of the hydrogen energy and the electric energy are respectively distributed for commercial users,
Figure FDA0003626875140000037
the proportions of the hydrogen energy and the electric energy are respectively distributed for heavy industrial users;
Figure FDA0003626875140000038
hydrogen power and electric power consumed by residential users respectively,
Figure FDA0003626875140000039
hydrogen power and electric power consumed by commercial users respectively,
Figure FDA00036268751400000310
hydrogen power and electric power consumed by heavy industrial users respectively;
Figure FDA00036268751400000311
the xth class user may divert the amount of change in the electrical load for time t,
Figure FDA00036268751400000312
a class x user may divert the amount of change in thermal load for time t,
Figure FDA00036268751400000313
the variable quantity of transferable hydrogen load for the xth user at time t;
Figure FDA00036268751400000314
respectively predicting values of hydrogen load, heat load and electric load of the x-th class user at the time t before response;
Figure FDA00036268751400000315
hydrogen energy required by the micro fuel cell is supplied; k is a radical ofgeΔvgConsuming electrical energy for the hydrogen compressor;
Figure FDA00036268751400000316
hydrogen load, heat load, electric load which are actually supplied to heavy industrial users by the energy hub;
Figure FDA00036268751400000317
the distribution proportion of the hydrogen energy and the electric energy is respectively;
Figure FDA00036268751400000318
respectively representing the energy conversion coefficient from hydrogen energy to electric energy and the energy conversion coefficient from electric energy to heat energy; k is a radical of formulageThe power consumption for compressing the unit volume of hydrogen;
Figure FDA00036268751400000319
Figure FDA00036268751400000320
and respectively representing the energy interaction quantity of a hydrogen energy system, a thermodynamic system and a power grid in the heavy industrial user energy hub and the comprehensive energy system.
5. The method for optimizing the demand response operation of the multi-energy complementary system for promoting surplus wind power consumption according to claim 4, wherein a power supply side in the comprehensive energy system model containing the energy hub and hydrogen production containing electricity consists of a thermal power generating unit, a photovoltaic photo-thermal device, a CHP unit, a wind power generating unit, a water electrolysis device, a hydrogen storage device and a fuel cell, and provides electric energy, heat energy and hydrogen energy for a side load of the system; the system side load is automatically responded, distributed and converted by the energy concentrator, and the actual electric load, heat load and hydrogen load requirements of a user side are met; after the comprehensive demand response process is implemented, the system side load is the input quantity of various types of energy of the user energy hub, and the user side actual load is the output quantity of various types of energy of the energy hub.
6. The method for optimizing demand response operation of a multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the operation constraints of the integrated energy system comprise: the method comprises the following steps of wind power hydrogen production-fuel cell device constraint, hydrogen storage balance constraint, thermodynamic system constraint, CHP unit constraint, photovoltaic photo-thermal unit constraint and thermal power generator unit constraint.
7. The method for optimizing demand response operation of the multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the comprehensive demand response constraint, the user satisfaction constraint and the day-ahead time-of-use electricity price constraint are respectively as follows:
Figure FDA0003626875140000041
wherein:
Figure FDA0003626875140000042
the xth class user may divert the amount of change in the electrical load for time t,
Figure FDA0003626875140000043
the hydrogen load scaling factor may be transferred for class x users during the transferable period,
Figure FDA0003626875140000044
a scaling factor for the amount of thermal load that class x users can transfer during the transferable period,
Figure FDA0003626875140000045
an electrical load scaling factor may be transferred for a class x user transferable period,
Figure FDA0003626875140000046
is the time period during which there is a transferable electrical load.
8. The method for optimizing demand response operation of a multi-energy complementary system for promoting surplus wind power consumption according to claim 1, wherein the objective function is as follows: min frun＝fc+fchp+fd+feWherein: f. ofcF, total operating cost of the thermal power generating unitdRunning cost of the compression apparatus, fchpCost of coal for CHP units, feIs the transmission cost of hydrogen and heat pipeline media, wherein:
Figure FDA0003626875140000047
Figure FDA0003626875140000048
wherein: t, i and j are respectively the numbers of a time interval, a thermal power generating unit and a photovoltaic photo-thermal device; t is an optimization period; n is a radical ofGThe number of the thermoelectric generator sets in the comprehensive energy system; pi,tThe output power of the thermal power generating unit i in the t period is obtained; u. ofi,tIs a variable of 0 to 1 of the running state of the unit i in the period t; c. CchpThe unit coal consumption for generating electricity of the CHP unit; hchpT is the thermal output of the CHP unit when the CHP unit operates in the time period t; c. CHIs the unit gas compression cost of the compressor; vHe,tFor electrolysis of t time periodThe volume of hydrogen produced by the device; c. CtHydrogenThe transport cost per unit of hydrogen; vHload,tTotal volume of hydrogen supplied to the load for time period t; c. CtHeatUnit transmission cost of heat source heat power; hf,tThermal power released by the fuel cell when combusting hydrogen over a period of time t; hchpT is the thermal power released by the CHP unit when the CHP unit operates in the period t; hG,j,tThermal power released by the jth photovoltaic photo-thermal device in a t period; n is a radical ofVThe number of photovoltaic photo-thermal devices in the system; f. ofi(Pi,t) The power generation cost of the thermal power generating unit is as follows: f. ofi(Pi,t)＝ai+biPi,t+ciPi,t 2Wherein: a is ai,bi,ciThe power generation cost coefficient of the unit i and the starting cost of the unit i in the period t
Figure FDA0003626875140000051
Wherein:
Figure FDA0003626875140000052
minimum downtime of unit i, Ti,tThe continuous operation time or continuous shutdown time of the unit i in the T-th time period is positive when the unit i is in continuous operation time and negative when the unit i is in continuous shutdown time, and Tcold,iIs the cold start time of unit i.
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CN112270096B (en) * 2020-10-29 2022-12-16 国网甘肃省电力公司电力科学研究院 Flexible resource contribution degree solving method for promoting new energy consumption
CN113410856B (en) * 2020-11-04 2022-11-04 清华四川能源互联网研究院 Combined system and method for delaying performance attenuation of energy storage electric power auxiliary service system
CN112510736A (en) * 2020-11-09 2021-03-16 国网甘肃省电力公司电力科学研究院 Wind-fire coupling multi-energy system based on hydrogen energy
CN112434915B (en) * 2020-11-09 2023-06-30 沈阳工程学院 Regional comprehensive energy system flexibility optimal configuration method for abandoned wind digestion
CN112491147A (en) * 2020-11-12 2021-03-12 青海大学 Hydrogen energy storage comprehensive energy configuration system and method
CN112952805A (en) * 2021-02-08 2021-06-11 国网江苏省电力有限公司电力科学研究院 Electric hydrogen energy system scheduling method considering flexible hydrogen demand
CN112989594B (en) * 2021-03-09 2023-05-19 南方电网科学研究院有限责任公司 Comprehensive energy system operation optimization method considering hydrogen energy
CN113807884B (en) * 2021-08-20 2024-05-14 国网浙江省电力有限公司经济技术研究院 Method and device for determining power grid access capacity of park comprehensive energy system
CN113867291B (en) * 2021-10-08 2023-11-03 润泰新能源集团有限公司 Energy storage heat exchange optimization scheduling method
CN113946981B (en) * 2021-11-17 2023-06-20 国网四川省电力公司电力科学研究院 Site selection and volume determination method and system for accessing hydro-electric hydrogen production load into power grid
CN114595584B (en) * 2022-03-14 2023-06-30 南方电网数字电网研究院有限公司 Multi-energy complementary regional terminal energy utilization configuration method and device
CN115864484B (en) * 2022-11-23 2024-04-09 国网湖北综合能源服务有限公司 Power energy control method for multi-energy complementary direct current micro-grid
CN116128163B (en) * 2023-04-13 2023-06-30 国网天津静海供电有限公司 Comprehensive energy optimization method and device considering green hydrogen production and storage and user satisfaction

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109727158A (en) * 2019-01-25 2019-05-07 燕山大学 A kind of electric heating integrated energy system dispatching method based on the weak robust optimization of improvement
CN110443410A (en) * 2019-07-10 2019-11-12 国网福建省电力有限公司 A kind of running optimizatin method of region multi-energy system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109727158A (en) * 2019-01-25 2019-05-07 燕山大学 A kind of electric heating integrated energy system dispatching method based on the weak robust optimization of improvement
CN110443410A (en) * 2019-07-10 2019-11-12 国网福建省电力有限公司 A kind of running optimizatin method of region multi-energy system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
含风电制氢装置的综合能源***优化运行;郭梦婕 等;《中国电力》;20200131;第53卷(第1期);摘要、正文第1-2部分 *
考虑能源子***与储能的综合能源***优化分析;钟永洁 等;《电力建设》;20190831;第40卷(第8期);摘要、第1部分 *

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