CN108988328B - Power system power generation side resource allocation optimization method - Google Patents

Power system power generation side resource allocation optimization method Download PDF

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CN108988328B
CN108988328B CN201810857052.9A CN201810857052A CN108988328B CN 108988328 B CN108988328 B CN 108988328B CN 201810857052 A CN201810857052 A CN 201810857052A CN 108988328 B CN108988328 B CN 108988328B
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power
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CN108988328A (en
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张维静
汪洋
李成仁
高效
邹鹏
刘秉祺
张天宇
尤培培
柯美锋
吴慧莹
王莹
周树鹏
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Tsinghua University
State Grid Energy Research Institute Co Ltd
Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
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Tsinghua University
State Grid Energy Research Institute Co Ltd
Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
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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
    • H02J3/008—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
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • 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]
    • 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 provides a power system power generation side resource allocation optimization method, and belongs to the field of optimization of power system power generation side resource allocation. Firstly, establishing and constructing a power system power generation side resource allocation optimization model based on a Nash-Guno equilibrium model, wherein the model is composed of an objective function and constraint conditions, and the technical constraints and market clearing conditions of market participants are considered; and optimizing the power generation resource allocation according to the technical constraints provided by different power generators to obtain a resource optimization allocation result. The method is used for optimizing the resource allocation of the power generation side of the power system, improving the consumption of renewable energy sources and improving the operation efficiency of the power system.

Description

Power system power generation side resource allocation optimization method
Technical Field
The invention provides a power system power generation side resource allocation optimization method, and belongs to the field of optimization of power system power generation side resource allocation.
Background
With the advancement of the electric power market reform, the marketization level is gradually improved, and the optimization of the unit output and the resource allocation is an important target of the electric power market participants. On the power generation side of the power system, power generators participate in market competition, and through optimization decision, the maximum optimization of resources is realized in the game process. The renewable energy power generation is greatly influenced by weather, has the characteristics of intermittence, volatility and randomness, influences the reliability of a power system, and the contradiction between the renewable energy and the power system is aggravated as the proportion of the renewable energy is increased day by day. The contradiction between the output of renewable energy and the stability of the power system can be effectively relieved by the flexible adjusting characteristic of the energy storage system, an important adjusting effect is achieved on the power generation side, and the overall resource optimization configuration of the power system is more complex when the energy storage system participates in the competition of the power generation side.
Resource allocation of a power generation side of a power system is a research focus of scholars at home and abroad, and the scholars propose a plurality of optimization methods in the past decade. However, as the power industry develops, especially as the degree of electric power field increases, the requirements for optimizing the precision and speed of resource allocation also increase. Most of the research is to realize the optimal allocation of resources by means of market through the transfer of power generation rights. In the trading of power generation rights, power generators maximize benefits of the power generators, and continuously adjust competitive strategies of the power generators by considering production capacity, operation strategies and market changes of the power generators, so that unreasonable resource distribution is possibly caused, and cooperation among the power generators is difficult to form. In the power generation right transaction, when the number of transferors is large, a cooperative organization is difficult to form, each transaction subject is on the premise of own benefits, and in order to minimize the benefit loss of the transferors, a non-cooperative game of prisoner predicament is formed among the transferors, so that the redundancy of a power system is excessive, the resource allocation efficiency is low, the development of the current power market is difficult to adapt, and the operation efficiency of the power system is influenced.
The gulo model is a common model for analyzing the oligopolistic competition, a generator determines the type to participate in the power generation side in a power system to form a typical oligopolistic competition, and the output of the generator is used as a competitive bidding mode in a power market. Nash equilibrium is a combination of strategies chosen for all market participants, where the strategy chosen by each participant must be an optimal reaction to the strategy of the other participants, and no participant is willing to abandon his defined strategy alone. The Nash-Guno equilibrium model is generally applied to the electric power market considering futures contracts, and can effectively solve the problem of resource optimization configuration of power generators based on futures and option trading.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a power generation side resource allocation optimization method of a power system. The method is used for optimizing the resource allocation of the power generation side of the power system, improving the consumption of renewable energy sources and improving the operation efficiency of the power system.
The invention provides a power system power generation side resource allocation optimization method, which is characterized by comprising the following steps:
1) constructing a power system power generation side resource allocation optimization model, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
1-1) determining an objective function of the model, wherein an expression is shown as a formula (1):
Figure GDA0002584001100000021
in the formula,
Figure GDA0002584001100000022
is an optimized objective function of the whole power generation system, namely the output of the ith power generation unit in the energy storage system, the thermal power generation unit, the hydroelectric power generation unit and the renewable energy power generation unit at the moment t and the corresponding power generatorThe gains brought by the reserve capacity and peak shaving capacity of the group;
Figure GDA0002584001100000023
the output of the type generating set is determined at the ith station at the moment t,
Figure GDA0002584001100000024
the ith station determines the spare capacity of the type generating set at the time t,
Figure GDA0002584001100000025
and determining the peak shaving capacity of the type generator set at the ith station at the time t. E represents the output of the unit, R represents the reserve capacity of the unit, F represents the peak shaving capacity of the unit, T represents 24 hours a day, and N represents the total number of market participants; α (t) and β (t) are coefficients corresponding to the slope and intercept, respectively, of the anti-demand function at time t, λR(t) represents the price of the alternate market at time t,
Figure GDA0002584001100000026
representing the peak shaver capacity price at time t,
Figure GDA0002584001100000027
representing peak shaving use price at time t, thetaXiIndicating the determined category of the ith station; peak shaving ratio of generator set, CTiRepresenting the power generation cost coefficient of the ith thermal generator set;
1-2) determining the constraint conditions of the model, specifically as follows:
1-2-1) market clearing constraints, the expression is as follows:
Figure GDA0002584001100000031
in the formula, ES represents the number of energy storage systems, TP represents the number of thermal power generating units, HP represents the number of hydroelectric generating units, and RE represents the number of renewable energy generating units; si represents i units of the energy storage system for power generation, Ti represents i units of the thermal power generation, Hi represents i units of the hydraulic power generation, Ri represents renewable energyI units for generating power; q. q.sD(t) is the total power demand at time t, λE(t) is market price of electrical energy at time t;
1-2-2) energy storage system technical constraint, the expression is as follows:
Figure GDA0002584001100000032
Figure GDA0002584001100000033
Figure GDA0002584001100000034
in the formula (3), the reaction mixture is,
Figure GDA0002584001100000035
is the power generation output of the ith unit of the energy storage system at the moment t,
Figure GDA0002584001100000036
and
Figure GDA0002584001100000037
the discharge output and the charge input of the ith unit of the energy storage system at the moment t are respectively,
Figure GDA0002584001100000038
and
Figure GDA0002584001100000039
all are binary variables which respectively represent the discharge state and the charge state of the ith unit of the energy storage system at the moment t, and q isSimaxThe maximum output of the ith unit of the energy storage system;
in the formula (4), the reaction mixture is,
Figure GDA00025840011000000310
is the reserve capacity of the ith unit of the energy storage system at the moment t,
Figure GDA00025840011000000311
the frequency modulation capacity of the ith unit of the energy storage system at the moment t;
in the formula (5), h is the number of hours of the energy storage system, ESi(t) the energy stored by the ith unit of the energy storage system at the moment t;
1-2-3) thermal power generating unit constraint, wherein the expression is as follows:
Figure GDA0002584001100000041
Figure GDA0002584001100000042
in the formula (6), the reaction mixture is,
Figure GDA0002584001100000043
is the power generation output of the ith thermal power generating unit at the moment t,
Figure GDA0002584001100000044
is the spare capacity of the ith thermal power generating unit at the moment t,
Figure GDA0002584001100000045
is the frequency modulation capacity q of the ith thermal power generating unit at the moment tTimaxIs the maximum limit value of the power generation of the ith thermal power generating unit, qTiminThe minimum limit value of the power generation of the ith thermal power generating unit;
in the formula (7), the reaction mixture is,
Figure GDA0002584001100000046
is the upper limit of the ramp rate of the ith thermal power generating unit,
Figure GDA0002584001100000047
is the lower limit of the ramp rate of the ith thermal power generating unit; t is tRIs a standby response time limit, tFIs the peak shaver response time limit;
1-2-4) hydroelectric generating set constraints, the expression is as follows:
Figure GDA0002584001100000048
Figure GDA0002584001100000049
in the formula (8), the reaction mixture is,
Figure GDA00025840011000000410
is the power generation output of the ith hydroelectric generating set at the moment t,
Figure GDA00025840011000000411
is the reserve capacity of the ith hydroelectric generating set at the moment t,
Figure GDA00025840011000000412
is the frequency modulation capacity of the ith hydroelectric generating set at the moment t, qHimaxAnd q isHiminThe maximum limit value and the minimum limit value of the power generation of the ith hydroelectric generating set are respectively set;
in the formula (9), EHimaxThe maximum hydropower output which can be provided by the ith hydroelectric generating set in one day;
1-2-5) renewable energy power generation constraints, the expression is as follows:
Figure GDA00025840011000000413
in the formula (10), qRimax(t) is the output upper limit of the ith renewable energy power generator set at the moment t, qRimin(t) the lower limit of the output of the ith renewable energy power generator set at the moment t;
2) solving the model established in the step 1) to respectively obtain the output, reserve capacity and peak regulation capacity of the energy storage system, the thermal power generating unit, the hydroelectric generating unit and the renewable energy power generation, namely solving
Figure GDA0002584001100000051
And finishing the optimization of the resource allocation of the power generation side of the power system.
The invention has the technical characteristics and beneficial effects that:
1. the invention constructs an objective function based on a Nash-Guno equilibrium model, considers the technical constraints of market participants and market clearing conditions, and is beneficial to reasonably distributing power resources.
2. According to technical constraints provided by different power generators, the power generation resource allocation is optimized, so that the power generators can cooperate better, and the influence caused by the redundancy of a power system is reduced.
3. The invention provides corresponding power generation strategies for different types of power generators, improves the utilization rate of different power generation equipment, and further promotes the operation efficiency of the power system.
Detailed Description
The present invention provides a method for optimizing resource allocation on a power generation side of a power system, and the present invention is further described in detail with reference to specific embodiments. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides an optimization method for resource allocation on a power generation side of a power system, which is an optimization method based on a Nash-Guno equilibrium model.
Nash-Guno equilibrium refers to the situation in gaming where, for each market participant, the participant cannot improve on his own, as long as the other competitors do not change the strategy. When nash equilibrium exists, each participant has only a limited number of policy choices and allows for a mixed policy. In the power generation market of a power system, an energy storage system, a thermal power generating unit, a hydroelectric generating unit and renewable energy are participants of the market, the upper layer of the established traditional Nash-Guno model aims at the respective profit maximization and technical constraint of four participants, and the lower layer of the traditional Nash-Guno model aims at providing clear market conditions.
According to the method, the energy storage system is considered to participate in the power generation side of the power system, and system resources are optimally configured for different power generation side participants by reconstructing a Nash-Guno balance model, so that the operation efficiency of the power market is improved.
The invention provides a power generation side resource allocation optimization method of a power system, which comprises the following steps:
1) the method comprises the following steps of constructing a power system power generation side resource allocation optimization model, wherein the model consists of an objective function and constraint conditions, and specifically comprises the following steps:
1-1) determining an objective function of the model, wherein an expression is shown as a formula (1):
Figure GDA0002584001100000061
formula (1) represents the total benefit brought by the total electric energy output, the reserve capacity and the peak shaving capacity of the system at the time t under the condition that the technical constraints of the energy storage system, the thermal power, the hydropower and the renewable energy power generation are not exceeded. Wherein,
Figure GDA0002584001100000062
the method is an optimization objective function of the whole power generation system, namely the output of the ith power generation unit in the energy storage system, the thermal power generation unit, the hydroelectric power generation unit and the renewable energy power generation unit at the time t, and the corresponding benefits brought by the reserve capacity and the peak shaving capacity of the corresponding power generation unit.
To the left of the equation is the overall optimization objective, i.e. the respective profits of the market participants,
Figure GDA0002584001100000063
the method includes the steps that the output of a power generating set of the type (Xi, the value range of which is the energy storage system ES, the thermal power TP, the hydropower HP and the renewable energy RE) is determined at the ith time (in the embodiment, the types of the power generating set participating in the power generation side of the power system include an energy storage system, thermal power generation, hydroelectric power generation and renewable energy power generation);
Figure GDA0002584001100000064
the ith station determines the spare capacity of the type generating set at the time t,
Figure GDA0002584001100000065
the peak shaving capacity of the type generator set is determined by the ith station at the time T, E represents the output of the generator set, R represents the spare capacity of the generator set, F represents the peak shaving capacity of the generator set, T represents 24 hours a day, and N represents the total number of market participants. α (t) and β (t) are the slope and cutoff of the inverse demand function at time t, respectivelyFrom the corresponding coefficient. Lambda [ alpha ]R(t) represents the price of the alternate market at time t,
Figure GDA0002584001100000066
representing the peak shaver capacity price at time t,
Figure GDA0002584001100000067
representing peak shaving use price at time t, thetaXiThe method comprises the steps of (1) representing the ith determined type (the preferable range of X is an energy storage system S, a thermal power generating unit T, a hydroelectric generating unit H and a renewable energy generating unit R); peak shaving ratio of generator set, CTiAnd the power generation cost coefficient of the ith thermal generator set is shown.
1-2) determining the constraint conditions of the model, specifically as follows:
1-2-1) market clearing constraints, the expression is as follows:
Figure GDA0002584001100000071
in the first equation of the equation (2), the left side of the equation is the output of all market participants at the time t, and the right side of the equation is the total output of the energy storage system, the thermal power generating unit, the hydroelectric generating unit and the renewable energy generating unit at the time t. The energy storage system comprises an ES, a TP, a HP, a hydroelectric generating set and a RE, wherein the ES represents the number of the energy storage systems, the TP represents the number of the thermal generating sets, the HP represents the number of the hydroelectric generating sets, and the RE represents the number of the renewable energy generating sets; si denotes i units of the energy storage system, Ti denotes i units of the thermal power generation, Hi denotes i units of the hydraulic power generation, and Ri denotes i units of the renewable energy power generation.
In the second equation of the formula (2), qD(t) is the total demand for power at time t.
In the third equation of equation (2), λE(t) is the market price of electrical energy at time t.
The market clearing constraint covers a multi-period power balance constraint and a linear inverse demand function. When the anti-demand function is reduced, different generators need to consider the strategy of competitors to determine the pricing of the generators, so that the gains of the generators are maximized.
1-2-2) energy storage system technical constraint, the expression is as follows:
Figure GDA0002584001100000072
Figure GDA0002584001100000073
Figure GDA0002584001100000074
in the formula (3), the reaction mixture is,
Figure GDA0002584001100000075
is the power generation output of the ith unit of the energy storage system at the moment t,
Figure GDA0002584001100000076
and
Figure GDA0002584001100000077
the discharge output and the charge input of the ith unit of the energy storage system at the moment t are respectively,
Figure GDA0002584001100000078
and
Figure GDA0002584001100000079
all are binary variables which respectively represent the discharge state and the charge state of the ith unit of the energy storage system at the moment t, and q isSimaxIs the maximum output of the ith unit of the energy storage system.
In the formula (4), the reaction mixture is,
Figure GDA0002584001100000081
is the reserve capacity of the ith unit of the energy storage system at the moment t,
Figure GDA0002584001100000082
and the frequency modulation capacity of the ith unit of the energy storage system at the moment t.
In formula (5), h is the hour of operation of the energy storage systemNumber, ESiAnd (t) is the energy stored by the ith unit of the energy storage system at the moment t.
According to the formulas (3), (4) and (5), the energy storage system is subject to technical constraints including charge and discharge limit constraints, capacity constraints and available energy constraints.
1-2-3) thermal power generating unit constraint, wherein the expression is as follows:
Figure GDA0002584001100000083
Figure GDA0002584001100000084
in the formula (6), the reaction mixture is,
Figure GDA0002584001100000085
is the power generation output of the ith thermal power generating unit at the moment t,
Figure GDA0002584001100000086
is the spare capacity of the ith thermal power generating unit at the moment t,
Figure GDA0002584001100000087
is the frequency modulation capacity q of the ith thermal power generating unit at the moment tTimaxIs the maximum limit value of the power generation of the ith thermal power generating unit, qTiminAnd the minimum limit value of the power generation of the ith thermal power generating unit.
In the formula (7), the reaction mixture is,
Figure GDA0002584001100000088
is the upper limit of the ramp rate of the ith thermal power generating unit,
Figure GDA0002584001100000089
is the lower limit of the ramp rate of the ith thermal power generating unit; t is tRIs a standby response time limit, tFIs the peak shaver response time limit.
According to the formula (6) and the formula (7), the thermal power generating unit is subjected to the technical constraints of capacity constraint and climbing constraint.
1-2-4) hydroelectric generating set constraints, the expression is as follows:
Figure GDA00025840011000000810
Figure GDA00025840011000000811
in the formula (8), the reaction mixture is,
Figure GDA0002584001100000091
is the power generation output of the ith hydroelectric generating set at the moment t,
Figure GDA0002584001100000092
is the reserve capacity of the ith hydroelectric generating set at the moment t,
Figure GDA0002584001100000093
is the frequency modulation capacity of the ith hydroelectric generating set at the moment t, qHimaxAnd q isHiminThe maximum limit value and the minimum limit value of the power generation of the ith hydroelectric generating set are respectively.
In the formula (9), EHimaxIs the maximum hydroelectric output that the ith hydroelectric generating set can provide in a day.
According to the formula (8) and the formula (9), the technical constraints of the hydroelectric generating set are capacity constraint and water resource available energy constraint.
1-2-5) renewable energy power generation constraints, the expression is as follows:
Figure GDA0002584001100000094
in the formula (10), qRimax(t) is the output upper limit of the ith renewable energy power generator set at the moment t, qRiminAnd (t) is the lower output limit of the ith renewable energy power generator set at the moment t.
As can be seen from equation (10), the technical constraint of renewable energy is only the output limit, and renewable energy does not have backup and fm capacity constraints corresponding thereto because renewable energy does not have backup and fm capabilities.
2) Based onSolving the model established in the step 1) by the IBM CPLEX optimization platform to respectively obtain the output, reserve capacity and peak regulation capacity of the energy storage system, the thermal power generating unit, the hydroelectric generating unit and the renewable energy power generation, namely solving the output, reserve capacity and peak regulation capacity
Figure GDA0002584001100000095
When the generating set changes the bidding strategy, the change of the resource configuration of the power system can be reflected by the objective function. And comparing resource allocation results at different moments to obtain the power output of each type of generator set, wherein the standby capacity and the peak shaving capacity are used as optimization results, and the resource allocation of the power generation side of the power system is optimized.

Claims (1)

1. A power system power generation side resource allocation optimization method is characterized by comprising the following steps:
1) constructing a power system power generation side resource allocation optimization model, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
1-1) determining an objective function of the model, wherein an expression is shown as a formula (1):
Figure FDA0002584001090000011
in the formula,
Figure FDA0002584001090000012
the method is characterized by comprising the following steps of (1) performing an optimization objective function of an overall power generation system, namely the output of the ith power generation unit in an energy storage system, a thermal power generation unit, a hydroelectric power generation unit and a renewable energy power generation unit at the moment t, and the corresponding benefits brought by the reserve capacity and the peak regulation capacity of the corresponding power generation unit;
Figure FDA0002584001090000013
the output of the type generating set is determined at the ith station at the moment t,
Figure FDA0002584001090000014
is at t timeAt the moment, the ith station determines the spare capacity of the type generator set,
Figure FDA0002584001090000015
determining the peak shaving capacity of the type generator set at the ith station at the moment T, wherein E represents the output of the generator set, R represents the standby capacity of the generator set, F represents the peak shaving capacity of the generator set, T represents 24 hours a day, and N represents the total number of market participants; α (t) and β (t) are coefficients corresponding to the slope and intercept, respectively, of the anti-demand function at time t, λR(t) represents the price of the alternate market at time t,
Figure FDA0002584001090000016
representing the peak shaver capacity price at time t,
Figure FDA0002584001090000017
representing peak shaving use price at time t, thetaXiIndicating the peak shaving ratio, C, of the ith generator setTiRepresenting the power generation cost coefficient of the ith thermal generator set;
1-2) determining the constraint conditions of the model, specifically as follows:
1-2-1) market clearing constraints, the expression is as follows:
Figure FDA0002584001090000018
in the formula, ES represents the number of energy storage systems, TP represents the number of thermal power generating units, HP represents the number of hydroelectric generating units, and RE represents the number of renewable energy generating units; si represents i units of the energy storage system for power generation, Ti represents i units of the thermal power generation, Hi represents i units of the hydraulic power generation, and Ri represents i units of the renewable energy power generation; q. q.sD(t) is the total power demand at time t, λE(t) is market price of electrical energy at time t;
1-2-2) energy storage system technical constraint, the expression is as follows:
Figure FDA0002584001090000021
Figure FDA0002584001090000022
Figure FDA0002584001090000023
in the formula (3), the reaction mixture is,
Figure FDA0002584001090000024
is the power generation output of the ith unit of the energy storage system at the moment t,
Figure FDA0002584001090000025
and
Figure FDA0002584001090000026
the discharge output and the charge input of the ith unit of the energy storage system at the moment t are respectively,
Figure FDA0002584001090000027
and
Figure FDA0002584001090000028
all are binary variables which respectively represent the discharge state and the charge state of the ith unit of the energy storage system at the moment t, and q isSimaxThe maximum output of the ith unit of the energy storage system;
in the formula (4), the reaction mixture is,
Figure FDA0002584001090000029
is the reserve capacity of the ith unit of the energy storage system at the moment t,
Figure FDA00025840010900000210
the frequency modulation capacity of the ith unit of the energy storage system at the moment t;
in the formula (5), h is the number of hours of the energy storage system, ESi(t) the energy stored by the ith unit of the energy storage system at the moment t;
1-2-3) thermal power generating unit constraint, wherein the expression is as follows:
Figure FDA00025840010900000211
Figure FDA0002584001090000031
in the formula (6), the reaction mixture is,
Figure FDA0002584001090000032
is the power generation output of the ith thermal power generating unit at the moment t,
Figure FDA0002584001090000033
is the spare capacity of the ith thermal power generating unit at the moment t,
Figure FDA0002584001090000034
is the frequency modulation capacity q of the ith thermal power generating unit at the moment tTimaxIs the maximum limit value of the power generation of the ith thermal power generating unit, qTiminThe minimum limit value of the power generation of the ith thermal power generating unit;
in the formula (7), the reaction mixture is,
Figure FDA0002584001090000035
is the upper limit of the ramp rate of the ith thermal power generating unit,
Figure FDA0002584001090000036
is the lower limit of the ramp rate of the ith thermal power generating unit; t is tRIs a standby response time limit, tFIs the peak shaver response time limit;
1-2-4) hydroelectric generating set constraints, the expression is as follows:
Figure FDA0002584001090000037
Figure FDA0002584001090000038
in the formula (8), the reaction mixture is,
Figure FDA0002584001090000039
is the power generation output of the ith hydroelectric generating set at the moment t,
Figure FDA00025840010900000310
is the reserve capacity of the ith hydroelectric generating set at the moment t,
Figure FDA00025840010900000311
is the frequency modulation capacity of the ith hydroelectric generating set at the moment t, qHimaxAnd q isHiminThe maximum limit value and the minimum limit value of the power generation of the ith hydroelectric generating set are respectively set;
in the formula (9), EHimaxThe maximum hydropower output which can be provided by the ith hydroelectric generating set in one day;
1-2-5) renewable energy power generation constraints, the expression is as follows:
Figure FDA00025840010900000312
in the formula (10), qRimax(t) is the output upper limit of the ith renewable energy power generator set at the moment t, qRimin(t) the lower limit of the output of the ith renewable energy power generator set at the moment t;
2) solving the model established in the step 1) to respectively obtain the output, reserve capacity and peak regulation capacity of the energy storage system, the thermal power generating unit, the hydroelectric generating unit and the renewable energy power generation, namely solving
Figure FDA00025840010900000313
And finishing the optimization of the resource allocation of the power generation side of the power system.
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