CN112994053B - Wind power consumption-oriented heat-electricity integrated system transmission and storage robust planning method - Google Patents

Wind power consumption-oriented heat-electricity integrated system transmission and storage robust planning method Download PDF

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CN112994053B
CN112994053B CN202110475209.3A CN202110475209A CN112994053B CN 112994053 B CN112994053 B CN 112994053B CN 202110475209 A CN202110475209 A CN 202110475209A CN 112994053 B CN112994053 B CN 112994053B
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wind power
heat
power
energy storage
wind
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CN112994053A (en
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杨东升
郑海洪
张化光
周博文
李广地
金硕巍
罗艳红
王迎春
闫士杰
杨波
柴琦
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Northeastern University China
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

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Abstract

The invention relates to a wind power consumption-oriented power transmission and storage robust planning method for a heat-electricity integrated system, which inhibits wind power rapid fluctuation and relieves transmission line blockage by configuring a heat storage electric boiler and an electricity energy storage device and increasing transmission capacity of a transmission line; providing a wind power uncertainty model and an energy storage system absorption wind power control strategy; aiming at minimizing the early investment cost and the system operation cost of the power transmission network, comprehensively considering the operation constraint of each unit in the system, the operation constraint of the energy storage system, the system electricity/heat balance and other constraint conditions, and establishing a wind power consumption-oriented heat-electricity integrated system energy transmission and storage robust planning model; and finally, solving the robust model by adopting a hierarchical iteration method to obtain the optimal position, capacity and power of the stored energy and the optimal planning scheme of the power transmission line, and improving the wind power consumption capacity of the power transmission network.

Description

Wind power consumption-oriented heat-electricity integrated system transmission and storage robust planning method
Technical Field
The invention relates to the technical field of joint scheduling of an electric power system and a thermodynamic system, in particular to a wind power consumption-oriented robust planning method for the energy transmission and storage of a heat-electricity integrated system.
Background
With the exhaustion of fossil energy in the world and the gradual deterioration of ecological environment, the development of renewable energy has become an important choice for each country. However, since clean energy such as wind power has the characteristics of strong volatility, high randomness and the like, the fact that a large amount of wind power enters a power grid inevitably changes the energy structure of the power grid and brings great threat to the safe operation of the power grid, and therefore the phenomenon of serious wind abandon is generated.
At present, the serious cause of wind abandon in the three north area of China mainly comprises two aspects, on one hand, the wind power plant is constructed remotely and is limited by the structure of a power transmission network, and a large amount of wind power cannot be transmitted to the interior of the power grid due to line blockage. On the other hand, the power grid system is limited by the climbing rate and the adjusting range of the unit, and cannot cope with the fluctuation of wind power. Meanwhile, during heat supply in the 'three north regions' of China, the peak load regulation capacity of a power grid system is further reduced by the operation mode of 'fixing the power by heat' of the cogeneration unit, so that the problem of wind abandonment is more serious.
At present, a method for improving the peak regulation capability of a unit in a power grid system mainly enhances the flexibility of the power grid system through an energy storage system and consumes more wind power resources. At present, most researches mainly consider the configuration of electric energy storage, however, the problems of low service life, high manufacturing cost, low efficiency and the like of the existing battery cannot be put into use on a large scale, meanwhile, the China 'three north region' mainly comprises two loads of electricity and heat, and the operation mode of a 'cogeneration unit' in the three north region 'for determining electricity by heat' can be decoupled by configuring a thermal energy storage device, so that the deep peak regulation of the unit is realized, and therefore, the configuration of an energy storage system needs to consider the configuration of two energy storage systems of heat storage and electricity storage, and has more significance.
In the problem of power transmission network line planning, a lot of researches are carried out, and through reasonable planning of power transmission network lines, the power grid structure of a power transmission line can be changed, the capacity of the power transmission line is increased, and therefore wind power is sent out in time. However, most of the existing power transmission network planning research oriented to wind power consumption does not consider the access of the energy storage system, and meanwhile, compared with power transmission line planning, the construction period of the energy storage system is shorter, so that the construction period can be effectively shortened by considering the combined planning of the power transmission line and the energy storage system, and considerable economic benefits are achieved.
Meanwhile, wind power has strong intermittence and volatility, the economical efficiency and the reliability of system configuration can be influenced, most of the optimized operation and the optimized energy storage configuration of the power transmission network are calculated by a deterministic wind power scene at present, and therefore the uncertainty of the wind power is fully considered in the planning of the power transmission network. At present, wind power uncertainty methods considered in a power transmission network are mainly divided into two methods. One is a stochastic programming method, which adopts Monte Carlo and Latin hypercube methods to generate and reduce wind power scenes, but in order to ensure the reliability of the model, a large number of scenes need to be considered, the calculation amount is large, and the complexity of the problem is increased; the other method is a robust planning method, and a model is generally established in the worst scene to carry out planning so as to ensure the stability of the system. Therefore, the method has important significance in considering the uncertainty and randomness of the wind power in the joint planning of the transmission network line and the energy storage system.
Aiming at the problems, the method has important significance for the research on the power transmission and storage robust planning of the heat-electricity integrated system, the blockage of the power transmission line can be relieved, the investment cost of the line and the energy storage is reduced, the deep peak regulation of a unit is realized, and the wind power permeability of the power transmission network is improved.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a wind power consumption-oriented robust planning method for the input and storage of a heat-electricity integrated system. The method comprises the steps of reasonably configuring a heat storage electric boiler and an electric energy storage device, increasing transmission capacity of a transmission line to restrain wind power rapid fluctuation and relieve transmission line blockage, simultaneously providing a wind power uncertainty model, establishing a heat-electricity integrated system transmission and storage robust planning model, and finally obtaining an energy storage optimal position, power and capacity and an optimal planning scheme of the transmission line by taking economy as an index.
The technical scheme adopted by the invention is as follows:
the invention provides a wind power consumption-oriented heat-electricity integrated system output and storage robust planning method, which comprises the following steps:
step S1: establishing a heat-electricity integrated system comprising a conventional thermal power generating unit, a cogeneration unit, a wind power generating unit, an electricity energy storage device and a heat storage electric boiler;
step S2: establishing a wind power uncertainty model, ensuring that a planning result is safe and stable and avoids over conservation by changing the number of uncertain collection endpoints, and simultaneously determining a wind power control strategy to be absorbed by an energy storage system;
and step S3: the method comprises the steps that the minimum sum of the early-stage investment cost and the system operation cost of a power transmission network is taken as an objective function, the operation constraints of all units in the system, the operation constraints of an energy storage system, the system electricity/heat balance and other constraint conditions are comprehensively considered, and a wind power consumption-oriented heat-electricity integrated system energy transmission and storage robust planning model is established;
and step S4: and solving the robust model based on a layered iteration method to obtain the optimal position, power and capacity of the stored energy and the optimal planning scheme of the power transmission line, and improving the wind power permeability of the power transmission network.
Further, in the step S1, the integrated thermal-electrical system mainly includes a power supply, an energy storage system, and a system load; the power supply part comprises 3 units of a conventional thermal power generating unit, a cogeneration unit and a wind generating set; the energy storage system comprises a heat storage electric boiler and an electric energy storage device, wherein the heat storage electric boiler comprises an electric boiler and a heat storage tank; the system load includes an electrical load and a thermal load.
Further, the step S2 specifically includes:
step S2.1: the wind power uncertain model expression is as follows:
Figure BDA0003047162390000031
in the formula:
Figure BDA0003047162390000032
the predicted value of the wind power plant at the node i at the moment t is obtained;
Figure BDA0003047162390000033
the upper limit of the upward fluctuation of the wind power of the node i at the time t is set; delta ofP w,i,t The lower limit of the downward fluctuation of the wind power of the node i at the moment t is defined; p w,i,t The actual power of the wind power plant of the node i at the moment t after uncertainty is considered;
Figure BDA0003047162390000034
andu w,i,t is a variable of 0, 1; when in use
Figure BDA0003047162390000035
When taking 1, P w,i,t Taking the wind power prediction power upper limit; when in useu w,i,t When taking 1, P w,i,t The lower limit of wind power prediction power is positioned; when the temperature is higher than the set temperature
Figure BDA0003047162390000036
u w,i,t While being 0,P w,i,t Then the predicted value is taken; f is a wind power uncertainty parameter;
step S2.2: wind power consumption strategy of energy storage system
The energy storage system comprises an electric energy storage device and a heat storage electric boiler; the specific control strategy is that whether waste wind exists or not is calculated according to a wind power predicted value, when the waste wind exists, an electric boiler and a cogeneration unit are started to simultaneously generate heat, one part of the generated heat is used for supplying heat load required by a heat supply network, the other part of the generated heat is stored by a heat storage tank, if the waste wind exists, the electric energy storage device needs to store redundant wind power, then whether the wind power actual power is equal to the wind power grid-connected power after the uncertainty of the wind power is considered is judged, and then the electric energy storage device carries out charging and discharging, so that the electric balance of the heat-electricity comprehensive system is ensured; when no abandoned wind is calculated, the heat storage tank releases heat to meet the heat load requirement, the electric energy storage device discharges to meet the electric load requirement, whether the wind power actual power is equal to the wind power grid-connected power after the wind power uncertainty is considered is judged, and then the electric energy storage device charges and discharges to ensure the electric balance of the heat-electricity integrated system;
further, the step S3 specifically includes:
establishing a wind power consumption-oriented heat-electricity integrated system transmission and storage determination planning model, wherein the total objective function of the system is as follows:
Figure BDA0003047162390000041
in the formula: c total The total cost of the integrated heat-electricity system; c inv Investment cost for the transmission line and the energy storage system; omega s A typical scene set; lambda [ alpha ] l The probability of occurrence of the first scene of the heat-electricity integrated system; c ope The operating cost of the heat-electricity integrated system;
step S3.1: investment cost of transportation and storage C inv ：
C inv ＝C line +C ess
In the formula: c line Investment cost for newly building a line; c ess The investment cost for newly building an energy storage system comprises a heat storage electric boiler and an electric energy storage device;
step S3.2: running cost C of the system ope ：
C ope ＝C gen +C chp +C qf
In the formula: c gen 、C chp 、C qf Respectively representing the running cost and the wind abandoning punishment cost of a conventional thermal power generating unit and a cogeneration unit;
step S3.3: system constraints
The model constraint of the heat-electricity integrated system mainly comprises an early-stage energy storage configuration constraint and a running constraint of the heat-electricity integrated system after configuration;
step S3.3.1: energy storage system configuration constraints;
step S3.3.2: determining operating constraints of the configured integrated thermoelectric system;
further, the step S4 specifically includes:
step S4.1: initializing an upper bound, a lower bound and iteration times of an original problem;
step S4.2: calculating a main investment problem of a storage and transmission system according to wind power prediction data and electricity (heat) load prediction data and a storage and transmission system investment cost formula, obtaining a line expansion decision, an energy storage device and power capacity, and updating the lower bound of the original problem;
step S4.3: calculating a sub-problem of the operation cost of the system under the wind power uncertain set according to the wind power uncertain model, and judging whether the sub-problem is feasible or not; if the operation is feasible, the next step is carried out; if not, adding an infeasible cutting plane to the main problem, skipping to the step S4.2, recalculating the main problem of the investment of the storage and transportation system according to the investment cost formula of the storage and transportation system, and updating the lower bound of the original problem;
step S4.4: calculating a system operation sub-problem according to a system operation cost formula under the condition of considering the wind power uncertainty set according to a wind power uncertainty model, and updating the upper bound of the original problem;
step S4.5: and judging whether the difference value between the upper bound and the lower bound meets the convergence condition, if so, outputting the optimal position, capacity and power of the stored energy and the optimal planning scheme of the power transmission line, if not, adding a feasible cutting plane to the main problem, skipping to the step S4.2, recalculating the main investment problem of the storage and transmission system according to the storage and transmission system investment cost formula, and updating the lower bound of the original problem.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention considers the configuration of two energy storage devices of electricity storage and heat storage and the planning of the power transmission line at the same time, can deal with the fluctuation of wind power resources, relieves the line blockage of the power transmission network, reduces the early investment cost of the power transmission network, and has more considerable economic benefit compared with the traditional method only considering the configuration of an energy storage system or the planning of the power transmission network;
2. according to the method, the characteristics of wind power uncertainty, volatility and the like are considered, a wind power uncertainty model is established, the planning model is prevented from being too conservative, and the economy of the planning model is guaranteed;
3. the method takes the minimum sum of the early investment cost and the system operation cost of the power transmission network as a target function, comprehensively considers the constraints of power transmission network electricity and heat balance, the model constraints of a conventional thermal power generating unit, a cogeneration unit, an electricity energy storage device, a heat storage electric boiler and the like, establishes a robust planning model, and simultaneously solves by adopting a layered iteration method, reduces the model dimension, improves the solving speed, finally ensures the optimal planning of a power transmission network line and the energy storage device, and simultaneously realizes the optimal operation of the system;
4. the method provides important guarantee for the planning of the power transmission network, improves the wind power consumption capability of the power transmission network, and can reduce the overall investment cost of the power transmission network system while ensuring the wind power consumption, safe and stable operation of the power transmission network.
Drawings
FIG. 1 is a system model schematic diagram of a wind power consumption oriented transmission and storage robust planning method for a heat-electricity integrated system of the invention;
FIG. 2 is a schematic diagram of a wind power uncertainty model for a wind power consumption-oriented robust planning method for the energy transmission and storage of a heat-power integrated system;
FIG. 3 is a schematic diagram of an energy storage and absorption wind power control strategy for a wind power absorption-oriented energy storage and storage robust planning method of a heat-electricity integrated system;
FIG. 4 is a schematic diagram of a planning model principle of a wind power consumption-oriented robust planning method for the output and storage of the heat-electricity integrated system;
FIG. 5 is a flow chart of a wind power consumption oriented robust planning method for the output and storage of the integrated thermal-electric system.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
A system model of a wind power consumption-oriented robust planning method for the transmission and storage of a heat-electricity integrated system is characterized in that a wind power uncertainty model and a wind power consumption and storage system consumption wind power control strategy are provided by reasonably configuring a heat storage electric boiler and an electricity energy storage device and increasing the transmission capacity of a transmission line to inhibit the rapid fluctuation of wind power and relieve the blockage of the transmission line, and a layered iteration method is adopted to calculate the optimal position, power and capacity of energy storage and the optimal planning scheme of the transmission line by taking the minimum sum of the early investment cost and the system operation cost of the transmission network as a target function. The method comprises the following specific steps with reference to the attached figures 1 to 5:
step S1: a heat-electricity integrated system comprising a conventional thermal power generating unit, a cogeneration unit, a wind power generating unit, an electricity energy storage device and a heat storage electric boiler is established.
The heat-electricity integrated system mainly comprises a power supply, an energy storage system and a system load, and the specific structure is shown in the attached figure 1.
The power supply part mainly comprises 3 units of a conventional thermal power generating unit, a cogeneration unit and a wind generating set; the energy storage system comprises a heat storage electric boiler and an electric energy storage device, wherein the heat storage electric boiler comprises two parts, an electric boiler and a heat storage tank. The system load comprises an electric load and a heat load, the electric load is supplied by a conventional thermal power generating unit, a cogeneration unit, a wind generating set and an electric energy storage device, and the heat load is satisfied by the cogeneration unit and a heat storage electric boiler.
Step S2: and establishing a wind power uncertainty model, ensuring that a planning result is safe and stable and avoids over conservation by changing the number of uncertain collection endpoints, and determining that an energy storage system consumes a wind power control strategy.
Step S2.1: establishing wind power uncertainty model
Because wind power output permeability is high in a power transmission network, and wind power volatility and intermittence are strong, the influence of wind power uncertainty on system planning is considered, the robust planning adopts a set mode to represent the uncertainty of variables, and a model of the robust planning is shown in the attached figure 2, and a concrete representation mode is shown as follows.
Figure BDA0003047162390000071
In the formula:
Figure BDA0003047162390000072
the predicted value of the wind power plant at the node i at the moment t is obtained;
Figure BDA0003047162390000073
for node i with wind power fluctuating upwards at time tAn upper limit; delta ofP w,i,t The lower limit of the downward fluctuation of the wind power of the node i at the time t is set; p w,i,t The actual power of the wind power plant of the node i at the moment t after uncertainty is considered;
Figure BDA0003047162390000074
andu w,i,t is a variable of 0, 1; when in use
Figure BDA0003047162390000075
When taking 1, P w,i,t Taking the wind power prediction power upper limit; when the temperature is higher than the set temperatureu w,i,t When taking 1, P w,i,t The lower limit of wind power prediction power is positioned; when the temperature is higher than the set temperature
Figure BDA0003047162390000076
u w,i,t While being 0,P w,i,t Then the predicted value is taken; and gamma is a wind power uncertainty parameter.
Step S2.2: providing an energy storage system wind power consumption strategy
In order to improve the wind power grid-connection capacity of the system and reasonably plan and configure the energy storage system, the specific operation control strategy of the energy storage system in the heat-electricity integrated system needs to be determined in advance, the energy storage system is adjusted to maintain the power (heat) balance of the power grid according to the proposed wind power uncertain model, and the specific control strategy of the energy storage system
The energy storage system comprises an electric energy storage device and a heat storage electric boiler. In order to reasonably configure the energy storage system and improve the wind power consumption capability of the power transmission network to the maximum extent, an operation control strategy of the energy storage system needs to be determined in advance. The wind power consumption control strategy of the energy storage system is shown in the attached figure 3. Firstly, calculating whether abandoned wind exists according to a wind power predicted value, when the abandoned wind exists, starting an electric boiler and a cogeneration unit to generate heat at the same time, wherein one part of the generated heat is used for supplying heat load required by a heat supply network, the other part of the generated heat is stored by a heat storage tank, if the abandoned wind exists, an electric energy storage device needs to store redundant wind power, then judging whether the actual wind power is equal to the grid-connected wind power after the uncertainty of the wind power is considered, and then charging and discharging are carried out on the electric energy storage device, so that the electric balance of the heat-electricity comprehensive system is ensured; when no abandoned wind is calculated, the heat storage tank releases heat to meet the heat load requirement, the electric energy storage device discharges to meet the electric load requirement, whether the wind power actual power is equal to the wind power grid-connected power after the wind power uncertainty is considered is judged, then the electric energy storage device charges and discharges, and the electric balance of the heat-electricity integrated system is guaranteed.
And step S3: the method aims at minimizing the early investment cost and the system operation cost of the power transmission network, comprehensively considers the operation constraints of all units in the system, the operation constraints of the energy storage system, the system electricity (heat) balance and other constraint conditions, and establishes a wind power consumption-oriented heat-electricity integrated system energy transmission and storage robust planning model. A schematic diagram of a thermal-electrical integrated system planning model is shown in fig. 4.
Firstly, establishing a wind power consumption-oriented heat-electricity integrated system storage and transportation determination planning model, wherein a total objective function of the system is as follows:
Figure BDA0003047162390000081
in the formula: c total The total cost of the system; c inv Investment costs for transmission lines and energy storage; omega s A typical scene set; lambda [ alpha ] l The occurrence probability of the first scene of the power transmission network is determined; c ope Is the operating cost of the system.
Step S3.1: the investment cost of the transmission and storage system comprises the investment cost of the energy storage system and the extended construction cost of the power transmission line, and the investment cost C of the transmission and storage is calculated according to the following formula inv ：
C inv ＝C line +C ess (3)
In the formula: c line Investment cost for newly building a line; c ess The energy storage system comprises a heat storage electric boiler and an electric energy storage device for the investment cost of newly building the energy storage system.
(1) Investment cost C of newly-built circuit line
Figure BDA0003047162390000082
In the formula:r is the capital discount rate; y is line The service life of the newly-built line is prolonged; omega line_bb A line set to be built is obtained; c. C line,ij Investment cost for building a new line between the nodes i and j; i is ij,k And establishing a 0-1 decision variable of the k line between the nodes i and j.
(2) Investment cost C of newly-built energy storage system ess
Figure BDA0003047162390000091
In the formula: y is ess The service life of the newly built energy storage system is prolonged; x is the number of soc,i Configuring a 0-1 decision variable of an electric energy storage device for a node i; x is the number of eb,i Configuring a 0-1 decision variable of the heat accumulation electric boiler for the node i; omega soc Is an energy storage device set to be built; omega eb Is an energy storage device set to be built; alpha is the unit power investment coefficient of the electric energy storage device; beta is the unit capacity investment coefficient of the electric energy storage device; epsilon is the unit power investment coefficient of the electric boiler; sigma is the unit power investment coefficient of the heat storage tank; rho is the unit capacity investment coefficient of the heat storage tank.
Figure BDA0003047162390000092
Figure BDA0003047162390000093
Continuous decision variables of power and capacity are respectively configured for the node i electric energy storage device;
Figure BDA0003047162390000094
power configured for node i electric boiler;
Figure BDA0003047162390000095
and (4) respectively determining continuous decision variables of power and capacity configured for the node i heat storage tank.
Step S3.2: in the aspect of operation of a power transmission network, the invention provides a heat-electricity combined power transmission operation optimization model containing a heat storage electric boiler and an electric energy storage device, which takes the minimum generating cost and the minimum waste wind cost of a unit as the target and comprehensively considersThe operating cost C of the system is calculated according to the following formula ope ：
C ope ＝C gen +C chp +C qf (6)
In the formula: c gen 、C chp 、C qf The operation cost and the wind abandon punishment cost of the conventional thermal power generating unit and the cogeneration unit are respectively.
(1) Operating cost C of conventional thermal power generating unit gen
The power generation cost of the conventional thermal power generating unit generally comprises the fuel cost and the start-stop cost at present:
Figure BDA0003047162390000096
in the formula: a is gen,i 、b gen,i 、c gen,i The operation cost coefficient of the node i conventional thermal power generating unit is obtained; p is gen,i,t The electric power of a conventional thermal power generating unit at a node i at a time t; u. of gen,i,t Starting and stopping a conventional thermal power generating unit at a node i at a time t; c gen,i The single start-stop cost of the conventional thermal power generating unit of the node i is calculated; omega gen The system is a conventional thermal power unit set.
(2) Cogeneration operating cost C chp
The cogeneration unit is a steam extraction type cogeneration unit, does not need to be shut down in order to meet heat supply, and then substitutes the electric heating output into the fuel cost of the conventional unit to calculate the fuel cost of the cogeneration unit.
P zh,i,t ＝P chp,i,t +C v,i H chp,i,t (8)
In the formula: p zh,i,t The equivalent electric output of the cogeneration unit connected with the node i at the moment t; p chp,i,t 、H chp,i,t Respectively the electric output and the thermal output of the joint i cogeneration unit at the moment t; c v,i The elastic coefficient of the electricity and the heat output of the cogeneration unit.
Figure BDA0003047162390000101
In the formula: a is chp,i 、b chp,i 、c chp,i The operation cost coefficient of the joint i cogeneration unit is obtained; omega chp Is a set of cogeneration units.
(3) Wind abandon penalty cost C qf
Figure BDA0003047162390000102
In the formula: omega w Is a wind power plant set; c. C w Punishing cost for unit power wind abandonment; p w,i,t Considering the actual power of uncertainty for the wind power plant of the node i at the time t;
Figure BDA0003047162390000103
and the actual grid-connected power of the node i wind power plant at the time t is obtained.
Step S3.3: system constraints
The model constraints of the heat-electricity integrated system mainly comprise early-stage energy storage configuration constraints and determined operation constraints of the heat-electricity integrated system after configuration.
Step S3.3.1: energy storage system configuration constraints
(1) Capacity, power constraints for electrical energy storage devices
Figure BDA0003047162390000104
In the formula:
Figure BDA0003047162390000105
respectively configuring the rated capacity upper and lower limits of the electric energy storage devices for the node i;
Figure BDA0003047162390000106
respectively configuring the rated power upper and lower limits of the electric energy storage device for the node i;
Figure BDA0003047162390000107
the system is configured with a maximum number of electrical energy storage devices.
(2) Capacity power constraint of heat storage electric boiler
Figure BDA0003047162390000111
In the formula:
Figure BDA0003047162390000112
the rated power upper and lower limits of the electric boiler configured for the node i are respectively set;
Figure BDA0003047162390000113
Figure BDA0003047162390000114
the upper limit and the lower limit of the rated power of the heat storage tanks configured for the node i are respectively set;
Figure BDA0003047162390000115
the upper and lower limits of rated capacity of the heat storage tanks configured for the node i are respectively set;
Figure BDA0003047162390000116
the maximum number of regenerative electric boilers configured for the system.
Step S3.3.2: operational constraints of the post-configuration thermoelectric integrated system are determined.
Determining the operation constraint of the configured thermoelectric integrated system mainly comprises the operation constraint, the power balance constraint, the power flow constraint and the like of each device in the system.
(1) Constraints of conventional thermal power generating units
The operation constraint of the conventional thermal power generating unit mainly comprises unit output upper and lower limit constraint, climbing constraint and start-stop constraint. The output upper and lower limit constraints and the climbing constraints of the conventional thermal power generating unit are shown in a formula (13).
Figure BDA0003047162390000117
In the formula:
Figure BDA0003047162390000118
P gen,i respectively representing the upper limit and the lower limit of the output of the node i machine set;
Figure BDA0003047162390000119
the upward slope climbing rate limit and the downward slope climbing rate limit of the node i machine set are respectively.
The conventional thermal power generating unit is started and stopped to restrain:
Figure BDA00030471623900001110
in the formula: TS (transport stream) gen,i 、TO gen,i Respectively represent the minimum shutdown/startup time of the conventional thermal power generating unit of the node.
(2) Cogeneration unit operation constraints
The operation constraints of the cogeneration unit mainly include electricity (heat) output constraints and climbing constraints of the cogeneration unit. Wherein, the electric (heat) output constraint and the climbing constraint of the cogeneration unit are shown in formula (15).
Figure BDA0003047162390000121
In the formula:
Figure BDA0003047162390000122
the upper limit of the thermal output of the joint i cogeneration unit is set; c m The heat-electricity ratio of the cogeneration unit;
Figure BDA0003047162390000123
P chp,i respectively is the upper limit and the lower limit of the power output of the joint i cogeneration unit;
Figure BDA0003047162390000124
upward and downward of the node i cogeneration unit respectivelyThe lower climbing limit.
(3) Thermal storage electric boiler operation constraint
The operation constraint of the heat accumulation electric boiler mainly comprises two parts: electric boiler operation restriction and heat accumulation tank operation restriction.
The electric boiler operation constraints are shown in equation (16).
Figure BDA0003047162390000125
In the formula: h eb,i,t The thermal power generated by the node t electric boiler at the time t; p eb,i,t The electric quantity consumed by the node i electric boiler at the time t is calculated; eta is the electric heating conversion rate of the electric boiler.
The operation constraint of the heat storage tank is shown in formula (17).
Figure BDA0003047162390000126
In the formula:
Figure BDA0003047162390000127
the heat storage state and the heat release state of the heat storage tank of the node i at the moment t are respectively set; s ht,i,t The heat storage capacity of the heat storage tank at the node i at the moment t is calculated;
Figure BDA0003047162390000128
and the heat storage power and the heat release power of the node i heat storage tank at the moment t are respectively. S ht,i,0 And S ht,i,T Indicating that the thermal power of the heat storage tank remains constant over a period.
(4) Electric energy storage device operation constraints
Figure BDA0003047162390000131
In the formula:
Figure BDA0003047162390000132
charging and discharging states of the node i electric energy storage device at the moment respectivelyState; e soc,i,t The electric quantity of the electric energy storage device at the moment is a node i;
Figure BDA0003047162390000133
the charging power and the discharging power of the node i electric energy storage device at the moment are respectively; e soc,i,0 And E soc,i,T Indicating that the electrical power of the electrical energy storage device remains constant over a period of time.
(4) Rotational back-up restraint
Figure BDA0003047162390000134
Figure BDA0003047162390000135
In the formula: delta P Wd And Δ P Wu The fluctuation amounts of the wind power in unit time are downward fluctuation and upward fluctuation respectively; delta P Ld And Δ P Lu The downward fluctuation amount and the upward fluctuation amount of the system load in unit time are respectively.
(5) Network flow constraints
For a heat supply network system, the section mainly considers a central heating mode, and neglects the loss of the heat supply network system, so the thermodynamic balance is constrained as follows.
Figure BDA0003047162390000136
In the formula: h load,t The predicted thermal load for the heat supply network at time t.
For the transmission network, the planning in this chapter mainly considers the distribution of active power, neglecting the transmission network loss, so that the sum of the injected active power of each node is equal to the sum of the outgoing active power, and the power balance constraint is as follows:
Figure BDA0003047162390000137
in the formula:P load,i,t the predicted electric load of the node i power grid at the time t;
Figure BDA0003047162390000138
the wind curtailment quantity of the wind power plant at the time t is a node i; omega Fbus 、Ω Tbus Respectively collecting the head end and the tail end of the line; p is ij,t The power is transmitted for the single line of branch i-j at time t.
And (3) line power flow constraint:
flow of the established lines:
Figure BDA0003047162390000141
and (3) the trend of the line to be built:
Figure BDA0003047162390000142
in the formula: omega line_b The established line set is obtained; omega line_bb Is a line set to be built; b ij Susceptance is carried out on a single line of a branch i-j; theta i,t 、θ j,t The voltage phase angle of the node i, j at time t, respectively.
Because the decision variable I exists in the power flow constraint formula (24) of the line to be built ij,k And a decision variable (θ) i,t -θ j,t ) Multiplication, so the constraint is a non-linear equation, we need to introduce a large set of real numbers M ij And converting the power flow constraint of the line to be built into the following steps:
Figure BDA0003047162390000143
branch non-out-of-limit constraint:
Figure BDA0003047162390000144
in the formula:
Figure BDA0003047162390000145
the maximum transmission power for a single line of branch i-j.
Node voltage phase angle constraint:
Figure BDA0003047162390000146
in the formula:
Figure BDA0003047162390000147
andθ i the maximum and minimum values of the phase angle of the node voltage are respectively. Theta ref,t To balance the voltage phase angle of the node at time t.
The established wind power consumption-oriented heat-electricity integrated system transmission and storage certainty planning model is converted into a standard mixed integer planning model, and a commercial solver can be called for quick calculation. However, due to some random variables having certain errors, the deterministic planning result may not be able to cope with some actual operating conditions, for example, the wind turbine generator output has certain uncertainty. Therefore, the robust planning method provided by the invention aims to consider the wind power uncertainty according to the formula (1) and ensure the minimization of the formula (2) in the worst wind power scene. Because the construction states of the power transmission line and the energy storage system are not influenced by wind power fluctuation, the investment decision of the power transmission line and the energy storage system is a first-stage variable of the robust planning model. And the output of each device of the thermal-electric integrated system is a second-stage variable of the robust planning model, and after the extension decision of the power transmission line and the position, the power and the capacity of the energy storage system are determined, the operation cost of the thermal-electric integrated system is minimized according to the wind power uncertainty model and the formula (6). Therefore, the deterministic programming model is converted into a robust programming model as in formula (28)
Figure BDA0003047162390000151
In the formula: u is an uncertain variable of the robust planning model, and the wind power output is represented in the section; x is a first-stage variable of the robust planning model, and the investment construction state of the power transmission line and the energy storage system is represented in the section; and y is a second-stage variable of the robust planning model, and represents the output condition of each device in the power grid system in this section.
And step S4: and solving the robust model based on a hierarchical iteration method to obtain the optimal position, capacity and power of the stored energy and the optimal planning scheme of the power transmission line, and improving the wind power consumption capability of the power transmission network.
And solving the model based on a hierarchical iteration method, and reducing the solving scale, as shown in the attached figure 5. In the specific solving process, an original problem is decomposed into a main problem and a sub problem, wherein the main problem is a line and energy storage investment problem, namely a first stage of robust planning, and a line extension decision, an energy storage position, capacity and power are preliminarily determined under prediction data. And the sub-problem is a power grid operation problem, is a second stage of robust planning, and after a line extension decision and an energy storage position, capacity and power are determined, an optimal operation decision scheme is obtained by calculating the operation cost of the system according to a wind power uncertainty model. The concrete model solving steps are as follows:
step S4.1: initializing an upper bound and a lower bound of an original problem, and setting iteration times;
step S4.2: and calculating the main investment problem of the storage and transmission system according to the wind power prediction data and the electricity (heat) load prediction data and the storage and transmission system investment cost formula, obtaining a line expansion decision and the energy storage device and power capacity, and updating the lower bound of the original problem.
Step S4.3: and (4) calculating the sub-problem of the operation cost of the system under the condition of considering the wind power uncertain set according to the wind power uncertain model, and judging whether the system is feasible or not. If the result is feasible, the next step is carried out; if not, adding an infeasible secant plane to the main problem, skipping to step 4.2, recalculating the main investment problem of the storage and transportation system according to the storage and transportation system investment cost formula, and updating the lower bound of the original problem.
Step S4.4: and under the condition of considering the wind power uncertainty set according to the wind power uncertainty model, calculating a system operation subproblem according to a system operation cost formula, and updating the upper bound of the original problem.
Step S4.5: and judging whether the difference value between the upper bound and the lower bound meets the convergence condition, if so, outputting the optimal position, capacity and power of the stored energy and the optimal planning scheme of the power transmission line, if not, adding a feasible cutting plane to the main problem, skipping to the step 4.2, recalculating the main investment problem of the storage and transmission system according to the storage and transmission system investment cost formula, and updating the lower bound of the original problem.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention by those skilled in the art should fall within the protection scope defined by the claims of the present invention without departing from the spirit of the present invention.

Claims (3)

1. A wind power consumption-oriented robust planning method for the transmission and storage of a heat-electricity integrated system is characterized by comprising the following steps:
step S1: establishing a heat-electricity integrated system comprising a conventional thermal power generating unit, a cogeneration unit, a wind power generating unit, an electricity energy storage device and a heat storage electric boiler;
step S2: establishing a wind power uncertainty model, ensuring that a planning result is safe and stable and avoids over conservation by changing the number of uncertain collection endpoints, and simultaneously determining a wind power control strategy to be absorbed by an energy storage system;
and step S3: the method comprises the steps that the minimum sum of the early-stage investment cost and the system operation cost of a power transmission network is taken as an objective function, the operation constraints of all units in the system, the operation constraints of an energy storage system, the system electricity/heat balance and other constraint conditions are comprehensively considered, and a wind power consumption-oriented heat-electricity integrated system energy transmission and storage robust planning model is established;
and step S4: solving the robust model based on a layered iteration method to obtain an optimal energy storage position, power and capacity and an optimal power transmission line planning scheme, and improving the wind power permeability of the power transmission network;
in the step S1, the heat-electricity integrated system mainly comprises a power supply, an energy storage system and a system load; the power supply part comprises 3 units of a conventional thermal power generating unit, a cogeneration unit and a wind generating set; the energy storage system comprises a heat storage electric boiler and an electric energy storage device, wherein the heat storage electric boiler comprises an electric boiler and a heat storage tank; the system load comprises an electrical load and a thermal load;
the step S2 specifically includes:
step S2.1: the wind power uncertain model expression is as follows:
Figure FDA0003698856680000011
in the formula:
Figure FDA0003698856680000012
the predicted value of the wind power plant at the node i at the moment t is obtained;
Figure FDA0003698856680000013
the upper limit of the upward fluctuation of the wind power of the node i at the moment t is defined; delta ofP w,i,t The lower limit of the downward fluctuation of the wind power of the node i at the moment t is defined; p w,i,t The actual power of the wind power plant of the node i at the moment t after uncertainty is considered;
Figure FDA0003698856680000014
andu w,i,t is a variable of 0, 1; when in use
Figure FDA0003698856680000021
When taking 1, P w,i,t Taking the wind power prediction power upper limit; when the temperature is higher than the set temperatureu w,i,t When taking 1, P w,i,t The lower limit of wind power prediction power is positioned; when in use
Figure FDA0003698856680000022
u w,i,t While being 0,P w,i,t Then the predicted value is taken; f is a wind power uncertainty parameter;
step S2.2: wind power consumption strategy of energy storage system
The energy storage system comprises an electric energy storage device and a heat storage electric boiler; the specific control strategy is that whether waste wind exists or not is calculated according to a wind power predicted value, when the waste wind exists, an electric boiler and a cogeneration unit are started to simultaneously generate heat, one part of the generated heat is used for supplying heat load required by a heat supply network, the other part of the generated heat is stored by a heat storage tank, if the waste wind exists, the electric energy storage device needs to store redundant wind power, then whether the wind power actual power is equal to the wind power grid-connected power after the uncertainty of the wind power is considered is judged, and then the electric energy storage device carries out charging and discharging, so that the electric balance of the heat-electricity comprehensive system is ensured; when no abandoned wind is calculated, the heat storage tank releases heat to meet the heat load requirement, the electric energy storage device discharges to meet the electric load requirement, whether the wind power actual power is equal to the wind power grid-connected power after the wind power uncertainty is considered is judged, then the electric energy storage device charges and discharges, and the electric balance of the heat-electricity integrated system is guaranteed.
2. The wind power consumption-oriented power-electricity integrated system output and storage robust planning method according to claim 1, characterized in that: the step S3 specifically includes:
establishing a wind power consumption-oriented heat-electricity integrated system transmission and storage determination planning model, wherein the total objective function of the system is as follows:
Figure FDA0003698856680000023
in the formula: c total The total cost of the integrated heat-electricity system; c inv Investment cost for the transmission line and the energy storage system; omega s A typical scene set; lambda [ alpha ] l The probability of occurrence of the first scene of the heat-electricity integrated system; c ope The operating cost of the heat-electricity integrated system;
step S3.1: investment cost of transportation and storage C inv ：
C inv ＝C line +C ess
In the formula: c line Investment cost for newly building a line; c ess The investment cost for newly building an energy storage system comprises a heat storage electric boiler and an electric energy storage device;
step S3.2: running cost C of the system ope ：
C ope ＝C gen +C chp +C qf
In the formula: c gen 、C chp 、C qf Respectively the running cost and the wind abandon punishment cost of a conventional thermal power generating unit and a cogeneration unit;
step S3.3: system constraints
The model constraint of the heat-electricity integrated system mainly comprises an early-stage energy storage configuration constraint and a running constraint of the heat-electricity integrated system after configuration;
step S3.3.1: energy storage system configuration constraints;
step S3.3.2: operational constraints of the post-configuration thermoelectric integrated system are determined.
3. The wind power consumption-oriented power-electricity integrated system output and storage robust planning method according to claim 1, characterized in that: the step S4 specifically includes:
step S4.1: initializing an upper bound, a lower bound and iteration times of an original problem;
step S4.2: calculating a main investment problem of the storage and transmission system according to wind power prediction and electric load prediction data and a storage and transmission system investment cost formula, obtaining a line expansion decision and an energy storage device and power capacity, and updating the lower bound of the original problem;
step S4.3: calculating a sub-problem of the operation cost of the system according to the wind power uncertainty model under the condition of considering the wind power uncertainty set, and judging whether the operation is feasible or not; if the operation is feasible, the next step is carried out; if not, adding an infeasible cutting plane to the main problem, skipping to the step S4.2, recalculating the main problem of the investment of the storage and transportation system according to the investment cost formula of the storage and transportation system, and updating the lower bound of the original problem;
step S4.4: under the wind power uncertainty set is considered according to the wind power uncertainty model, calculating a system operation sub-problem according to a system operation cost formula, and updating the upper bound of the original problem;
step S4.5: and judging whether the difference value between the upper bound and the lower bound meets the convergence condition, if so, outputting the optimal position, capacity and power of the stored energy and the optimal planning scheme of the power transmission line, if not, adding a feasible cutting plane to the main problem, skipping to the step S4.2, recalculating the main investment problem of the storage and transmission system according to the storage and transmission system investment cost formula, and updating the lower bound of the original problem.
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