CN115511180A - Optimal configuration method and system for flexible resources of power system - Google Patents

Optimal configuration method and system for flexible resources of power system Download PDF

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CN115511180A
CN115511180A CN202211183445.9A CN202211183445A CN115511180A CN 115511180 A CN115511180 A CN 115511180A CN 202211183445 A CN202211183445 A CN 202211183445A CN 115511180 A CN115511180 A CN 115511180A
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power system
capacity
generating unit
power
flexibility
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文明
涂钊颖
文云峰
刘晓丹
谭玉东
巴文岚
吴思嘉
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State Grid Corp of China SGCC
State Grid Hunan Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Hunan Electric Power Co Ltd
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State Grid Corp of China SGCC
State Grid Hunan Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Hunan Electric Power Co Ltd
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Abstract

The invention discloses an optimal configuration method of flexible resources of an electric power system, which comprises the steps of obtaining data information of a target electric power system; constructing a flexible resource capacity demand evaluation model and solving to obtain a flexible resource capacity demand; constructing a flexible resource planning model and solving to obtain a preliminary configuration scheme; and constructing a running simulation model and checking a preliminary configuration scheme of the flexible resources to obtain a final optimized configuration scheme of the flexible resources of the power system. The invention also discloses a system for realizing the optimal configuration method of the flexible resources of the power system. The method can effectively improve the flexibility of the new energy high-occupancy-ratio power grid, is beneficial to the safe and stable operation of a power grid system, and has high reliability, good accuracy and objective science.

Description

Optimal configuration method and system for flexible resources of power system
Technical Field
The invention belongs to the field of electrical automation, and particularly relates to an optimal configuration method and system for flexible resources of an electric power system.
Background
With the development of economic technology and the improvement of living standard of people, electric energy becomes essential secondary energy in production and life of people, and brings endless convenience to production and life of people. Therefore, ensuring stable and reliable supply of electric energy is one of the most important tasks of the power system.
At present, as more and more new energy power generation systems are incorporated into a power grid, the randomness and uncertainty of the new energy power generation systems make the power system face greater and greater operating pressure. At present, the overall power supply regulation performance of a power system in China mainly depends on the thermal power peak regulation depth. However, the access of a high-proportion new energy power generation system increases the burden of power system regulation; the conventional power supply not only needs to follow the load change, but also needs to balance the output fluctuation of new energy. When the output of the new energy exceeds the adjustable range of the system, wind or light abandoning of the new energy power generation system can be induced, and resource waste is caused.
The flexibility resource of the power system is an important adjusting resource of the power system, can ensure the consumption of new energy and the flexibility and stability of power supply of a power grid, and has extremely important significance. However, the current technical solutions for flexible resource allocation of power systems still use methods that depend on empirical values or simulation models for configuration. However, the existing configuration mode has low reliability and accuracy and low scientificity, and is no longer suitable for the requirements of the current power system.
Disclosure of Invention
The invention aims to provide an objective and scientific optimal configuration method for flexible resources of a power system, which has high reliability and good accuracy.
The invention also aims to provide a system for realizing the optimal configuration method of the flexible resources of the power system.
The invention provides an optimal configuration method of flexible resources of an electric power system, which comprises the following steps:
s1, acquiring data information of a target power system;
s2, according to the data information obtained in the step S1, constructing a flexible resource capacity requirement evaluation model of the target power system and solving to obtain the flexible resource capacity requirement of the target power system;
s3, based on the flexibility resource capacity requirement of the target power system obtained in the step S2, considering the fluctuation characteristics of source-to-load terminals and the flexibility supply-demand balance characteristics, constructing a flexibility resource planning model of the target power system and solving the flexibility resource planning model to obtain a preliminary configuration scheme of the flexibility resources of the target power system;
s4, constructing an operation simulation model according to a set typical scene;
and S5, verifying the preliminary configuration scheme of the target electric power system flexible resources obtained in the step S3 by adopting the operation simulation model constructed in the step S4, so as to obtain a final optimized configuration scheme of the electric power system flexible resources.
Step S2, constructing a flexible resource capacity demand evaluation model of the target power system, specifically including the following steps:
in order to guarantee the power supply, the following formula is adopted as a constraint condition that the flexible resource capacity of the power system must meet the maximum demand generated in a day:
Figure BDA0003866229500000021
in the formula
Figure BDA0003866229500000022
An upward force output value of the power system flexibility resource is obtained; l is a radical of an alcohol max (ii) a predicted maximum load level for the day ahead; r is n Is a spare capacity factor; p j The output of the j-th power supply; m total number of power source classes;
in order to improve the utilization rate of new energy, the following formula is adopted as a constraint condition that the minimum output level of the flexibility resources of the power system is lower than the demand generated by loads and other power sources:
Figure BDA0003866229500000031
in the formula
Figure BDA0003866229500000032
Downward force values of the flexibility resources of the power system are obtained; l is min A predicted minimum load level for the day ahead; delta j Lower limit of output for class j power supplyCounting; p j,max The maximum output level of the j-th power supply; p RES Output for new energy;
in order to meet the regulation capacity of the system, the following formula is adopted as a constraint condition that the climbing rate of the flexible resource is greater than the climbing demand of the target power system:
Figure BDA0003866229500000033
in the formula
Figure BDA0003866229500000034
The grade j power supply ascending ramp rate; r up An uphill demand for the target power system;
the following formula is adopted as a constraint condition that the downward climbing rate of the flexible resource is greater than the climbing demand of the target power system:
Figure BDA0003866229500000035
in the formula
Figure BDA0003866229500000036
The down-hill climbing speed of the j-th power supply; r dn A down grade demand for the target power system;
the following equation is adopted as a constraint condition that the overall inertia level of the target power system is higher than the minimum inertia requirement:
Figure BDA0003866229500000037
in the formula
Figure BDA0003866229500000038
The lowest inertia requirement of the target power system in the time period t; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure BDA0003866229500000039
wherein
Figure BDA00038662295000000310
The maximum output of the thermal power generating unit H g Is the inertia time constant of the g-th thermal power generating unit, u g,t For the start-up and shut-down states of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s The output of the s-th energy storage power station, H s Is the inertia time constant of the s-th energy storage power station, N s For the total number of energy-storing power stations, P i The starting capacity of the ith other power supply; omega res As a collection of other power sources.
Step S3, constructing a flexible resource planning model of the target power system specifically includes the following steps:
the following equation is used as the objective function of the model:
min C 1 ＝C IN -C SV
in the formula C 1 Cost of the resource investment decision stage; c IN Investment cost for newly increased resources; c SV The residual value of the existing resources;
the following formula is adopted as a constraint condition:
electric power and electric quantity balance constraint:
Figure BDA0003866229500000041
Figure BDA0003866229500000042
in the formula
Figure BDA0003866229500000043
Newly-increased capacity of a power supply i in the t year is built; g kt The existing power supply capacity in the t year;
Figure BDA0003866229500000044
is a newly added power supply set;Ω E is an existing power supply set; l is t,max A maximum demand for a year t load for the target power system;
Figure BDA0003866229500000045
a load reserve capacity factor for the target power system; e it Generating capacity for the newly added power supply; e kt The generated energy of the existing power supply is generated; epsilon loss A power supply loss rate for a power supply of the target power system;
Figure BDA0003866229500000046
predicting an electric quantity demand for the t year of the target power system;
the following formula is adopted as the capacity constraint for flexibility modification of the power supply installation machine and the thermal power generating unit:
Figure BDA0003866229500000051
in the formula
Figure BDA0003866229500000052
The installed capacity of the energy storage power station is newly increased; g s,max The maximum installed capacity of the energy storage power station;
Figure BDA0003866229500000053
the maximum installed capacity for newly increasing water pumping and energy storage is obtained; g hps,max The maximum installed capacity for pumped storage;
Figure BDA0003866229500000054
installing capacity for a new gas-electric device; g gas,max The maximum installed capacity of the gas-electric device;
Figure BDA0003866229500000055
capacity is flexibly improved for the thermal power generating unit; g g,max The maximum capacity is flexibly reconstructed for the thermal power generating unit;
the following equation is used as a flexibility margin constraint:
Figure BDA0003866229500000056
Figure BDA0003866229500000057
in the formula of gamma i The peak shaving capacity coefficient of the power supply i; x is the number of it A variable 0-1 for whether power i is put into operation; g it The installed capacity of a power supply i in the t year; omega S A set comprising all newly added and existing power supplies; omega R A new energy power supply set; gamma ray j The peak shaving capacity coefficient of the flexible resource j; x is the number of jt A variable 0-1 is set up for the flexible power supply j;
Figure BDA0003866229500000058
newly adding a capacity for the flexible resource j in the t year; gamma ray r The peak regulation demand coefficient of the new energy r; x is the number of rt A variable of 0-1 is set for the new energy r in the t year; g rt Newly adding and building capacity for new energy r in the t year; gamma ray d Peak shaving coefficient which is the annual maximum load; l is a radical of an alcohol t,max The maximum demand for the year t load of the target power system; r i Is the ramp rate of power supply i; r j The climbing rate of the flexible resource j; r r The climbing demand coefficient of the new energy r; r d The coefficient of the climbing demand of the annual maximum load.
Step S4, constructing an operation simulation model according to the set typical scene, specifically including the following steps:
the following equation is used as the objective function for running the simulation model:
min C 2 ＝C OP +C FE +C CURT
in the formula C 2 Cost to run the simulation phase for production; c OP The production operation and maintenance cost in the production operation simulation stage; c FE Fuel and environmental costs for the production run simulation phase; c CURT Penalty cost and carbon trade income for new energy electricity abandonment in a production operation simulation stage;
the following equation is used as a power balance constraint:
Figure BDA0003866229500000061
in the formula P g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p f,t The output of the thermal power generating unit is improved for the flexibility of the f-th station in the simulated operation time period t; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained; p r,t The output of a new energy machine set in the simulated operation time period t is obtained; l is a radical of an alcohol t Load in the simulation operation time period t;
the following formula is adopted as the operation constraint of the thermal power generating unit:
P g,min ≤δ g,t P g,t ≤P g,max
Figure BDA0003866229500000062
Figure BDA0003866229500000063
Figure BDA0003866229500000064
in the formula P g,min The minimum output of the g-th thermal power generating unit is obtained; delta g,t The operating state of the g-th thermal power generating unit in the simulated operating period t is shown; p g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p g,max The maximum output of the g thermal power generating unit is obtained;
Figure BDA0003866229500000065
the minimum climbing limit of the g thermal power generating unit is set;
Figure BDA0003866229500000066
is the g stageThe maximum climbing limit of the thermal power generating unit;
Figure BDA0003866229500000067
the starting time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure BDA0003866229500000068
the minimum starting time of the g-th thermal power generating unit is set;
Figure BDA0003866229500000069
the shutdown time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure BDA00038662295000000610
the minimum shutdown time of the g-th thermal power generating unit is obtained;
Figure BDA00038662295000000611
the climbing capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA0003866229500000071
the uphill speed of the g-th thermal power generating unit; Δ t is the time interval;
Figure BDA0003866229500000072
the maximum output of the g-th thermal power generating unit is obtained;
Figure BDA0003866229500000073
the output of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA0003866229500000074
the creep-down capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA0003866229500000075
the lower climbing speed of the g-th thermal power generating unit is obtained;
Figure BDA0003866229500000076
the minimum output of the g thermal power generating unit is obtained;
the following formula is adopted as the operation constraint of the energy storage power station:
Figure BDA0003866229500000077
E s,min ≤E s,t ≤E s,max
0≤P C,s,t ≤c s,t P C,s,max
0≤P D,s,t ≤d s,t P D,s,max
P s,t ＝P D,s,t -P C,s,t
c s,t +d s,t ≤1
Figure BDA0003866229500000078
in the formula E s,t The method comprises the steps of providing stored electric quantity of an energy storage power station s in a simulation operation time period t; eta C The charging efficiency of the energy storage power station is obtained; p C,s,t Charging power of an energy storage power station s in a simulation operation time period t; Δ t is the time interval; p D,s,t The discharge power of the energy storage power station s in the simulation operation time period t is obtained; eta D The discharge efficiency of the energy storage power station; e s,min The lower limit of the stored electricity quantity of the energy storage power station s; e s,max The upper limit of the stored electricity quantity of the energy storage power station s is set; c. C s,t Indicating variables for the charging state of the energy storage power station s in the simulation operation time period t; p C,s,max The maximum charging power of the energy storage power station s; d s,t Indicating variables for the discharge state of the energy storage power station s in the simulation operation time period t; p D,s,max The maximum discharge power of the energy storage power station s; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure BDA0003866229500000079
the climbing capacity of the energy storage power station s in the simulation operation time period t is obtained; p D,s,max For the operation of energy-storing power stations s in simulationMaximum discharge power over time period t; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure BDA0003866229500000081
the climbing capacity of the energy storage power station s in the simulated operation time period t is obtained;
the following equation is adopted as a flexibility supply and demand balance constraint:
Figure BDA0003866229500000082
in the formula
Figure BDA0003866229500000083
Providing a capability for upward flexibility of the target power system during the simulated operation period t;
Figure BDA0003866229500000084
the method comprises the steps of (1) adjusting up flexibility of a g th thermal power generating unit before flexibility modification in a simulated operation time period t;
Figure BDA0003866229500000085
the flexibility of the up-regulation of the f-th thermal power generating unit after the flexibility modification within the simulated operation time period t is achieved;
Figure BDA0003866229500000086
flexibility in up-regulation of supply for the energy storage power station s during the simulated operation period t;
Figure BDA0003866229500000087
providing a downward flexibility capability for the target power system during the simulated operation period t;
Figure BDA0003866229500000088
the method comprises the steps of regulating flexibility of a g th thermal power generating unit before flexibility modification in a simulation operation time period t;
Figure BDA0003866229500000089
to run in simulationThe down regulation flexibility of the f-th thermal power generating unit is improved within the time period t;
Figure BDA00038662295000000810
the method comprises the following steps of (1) providing down-regulation flexibility for the supply of an energy storage power station s in a simulation operation time period t; n is a radical of f The total number of the transformed thermal power generating units is calculated;
the following equation is used as the minimum inertia requirement constraint:
Figure BDA00038662295000000811
in the formula
Figure BDA00038662295000000812
The minimum inertia requirement of a target power system in a simulation operation period t is set; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure BDA00038662295000000813
wherein
Figure BDA00038662295000000814
The maximum output of the thermal power generating unit H g Is the inertia time constant, u, of the g-th thermal power generating unit g,t For the start-up or shut-down state of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s Output of the s-th energy storage station, H s Is the inertia time constant of the s-th energy storage power station, N s For the total number of energy-storing power stations, P i The starting capacity of the ith other power supply; omega res As a collection of other power sources.
Step S5, verifying the preliminary configuration scheme of the target power system flexible resource obtained in step S3 by using the operation simulation model constructed in step S4, so as to obtain a final optimized configuration scheme of the power system flexible resource, specifically including the following steps:
checking the preliminary configuration scheme of the target power system flexibility resources by operating a simulation model:
if the verification is passed, taking the preliminary configuration scheme passed by the verification as the final optimized configuration scheme of the flexible resources of the power system;
and if the verification fails, adjusting the parameters, and repeating the steps S2-S5 until the verification passes to obtain the final optimal configuration scheme of the flexible resources of the power system.
The invention also discloses a system for realizing the optimal configuration method of the electric power system flexible resources, which specifically comprises a data acquisition module, a capacity demand calculation module, a preliminary configuration calculation module, an operation simulation structure modeling module and a verification module; the data acquisition module, the capacity demand calculation module, the preliminary configuration calculation module, the operation simulation structure modeling module and the check module are sequentially connected in series; the data acquisition module is used for acquiring data information of the target power system and uploading the data to the capacity demand calculation module; the capacity demand calculation module is used for constructing a flexible resource capacity demand evaluation model of the target power system according to the received data and solving the flexible resource capacity demand evaluation model to obtain the flexible resource capacity demand of the target power system, and uploading the data to the preliminary configuration calculation module; the preliminary configuration calculation module is used for constructing a flexible resource planning model of the target power system and solving the flexible resource planning model according to the received data by considering the volatility characteristics of the source, the load and the end and the flexibility supply and demand balance characteristics, so as to obtain a preliminary configuration scheme of the flexible resources of the target power system and upload the data to the operation simulation construction module; the operation simulation construction module is used for constructing an operation simulation model according to the received data and the set typical scene and uploading the data to the verification module; and the checking module is used for checking the preliminary configuration scheme of the target electric power system flexible resources by adopting the constructed operation simulation model according to the received data to obtain the final optimized configuration scheme of the electric power system flexible resources.
According to the optimal configuration method and system for the flexibility resources of the power system, a flexibility resource capacity demand evaluation model is established for evaluating the flexibility resource capacity demand of a power grid under the condition of high-proportion new energy access, then a flexibility resource planning model of a target power system is established according to the obtained capacity demand for solving a decision scheme of flexibility resource construction and thermal power unit flexibility modification, and an operation simulation model is established according to a typical scene to check the decision scheme and obtain a final scheme; therefore, the flexibility of the new energy high-occupancy-ratio power grid can be effectively improved, the safe and stable operation of a power grid system is facilitated, and the method is high in reliability, good in accuracy and objective and scientific.
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FIG. 1 is a schematic flow chart of the method of the present invention.
FIG. 2 is a schematic diagram of a power system regulated power supply and flexible resource capacity demand timing curve according to an embodiment of the method of the present invention.
Fig. 3 is a schematic diagram of a timing curve of the equivalent inertia and the minimum inertia demand of the power system according to the embodiment of the method of the present invention.
Fig. 4 is a schematic diagram of results of flexible resource deployment and flexible thermal power unit modification according to the embodiment of the method of the present invention.
FIG. 5 is a functional block diagram of the system of the present invention.
Detailed Description
FIG. 1 is a schematic flow chart of the method of the present invention: the optimal configuration method for the flexible resources of the power system, provided by the invention, comprises the following steps:
s1, acquiring data information of a target power system;
s2, according to the data information obtained in the step S1, constructing a flexible resource capacity demand evaluation model of the target power system and solving to obtain the flexible resource capacity demand of the target power system;
in specific implementation, the method for constructing the flexible resource capacity requirement evaluation model of the target power system comprises the following steps:
in order to guarantee the power supply, the following formula is adopted as a constraint condition that the flexible resource capacity of the power system must meet the maximum demand generated in a day:
Figure BDA0003866229500000111
in the formula
Figure BDA0003866229500000112
An upward force output value of the power system flexibility resource is obtained; l is max (ii) a predicted maximum load level for the day ahead; r n Is the spare capacity factor; p j The output of the j-th power supply; m total number of power source classes;
in order to improve the utilization rate of new energy, the following formula is adopted as a constraint condition that the minimum output level of the flexibility resources of the power system is lower than the demand generated by loads and other power sources:
Figure BDA0003866229500000113
in the formula
Figure BDA0003866229500000114
Downward force values of the flexibility resources of the power system are obtained; l is min A predicted minimum load level for the day ahead; delta. For the preparation of a coating j The output lower limit coefficient of the j-th power supply is obtained; p j,max The maximum output level of the j-th power supply; p RES Exerting power for new energy;
in order to meet the regulation capacity of the system, the following formula is adopted as a constraint condition that the climbing rate of the flexible resource is greater than the climbing demand of the target power system:
Figure BDA0003866229500000115
in the formula
Figure BDA0003866229500000116
The grade j power supply ascending ramp rate; r is up An uphill demand for the target power system;
the following formula is adopted as a constraint condition that the downward climbing rate of the flexible resource is greater than the climbing demand of the target power system:
Figure BDA0003866229500000121
in the formula
Figure BDA0003866229500000122
The down-hill climbing speed of the j-th power supply; r dn A down hill demand for the target power system;
the following equation is adopted as a constraint condition that the overall inertia level of the target power system is higher than the minimum inertia requirement:
Figure BDA0003866229500000123
in the formula
Figure BDA0003866229500000124
The lowest inertia requirement of the target power system in the time period t; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure BDA0003866229500000125
wherein
Figure BDA0003866229500000126
The maximum output of the thermal power generating unit H g Is the inertia time constant of the g-th thermal power generating unit, u g,t For the start-up and shut-down states of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s The output of the s-th energy storage power station, H s Is the inertia time constant of the s-th energy storage power station, N s Is the total number of energy storage power stations, P i The starting capacity of the ith other power supply; omega res Is a collection of other power sources;
s3, based on the flexibility resource capacity requirement of the target power system obtained in the step S2, considering the fluctuation characteristics of source-to-load terminals and the flexibility supply-demand balance characteristics, constructing a flexibility resource planning model of the target power system and solving the flexibility resource planning model to obtain a preliminary configuration scheme of the flexibility resources of the target power system;
in specific implementation, the method for constructing the flexible resource planning model of the target power system comprises the following steps:
the following equation is used as the objective function of the model:
min C 1 ＝C IN -C SV
in the formula C 1 Cost of the resource investment decision stage; c IN Investing the cost for newly added resources; c SV The residual value of the existing resources;
the following formula is adopted as a constraint condition:
electric power and electric quantity balance constraint:
Figure BDA0003866229500000131
Figure BDA0003866229500000132
in the formula
Figure BDA0003866229500000133
Newly adding and putting into operation capacity for the power supply i in the t year; g kt The existing power supply capacity in the t year;
Figure BDA0003866229500000134
is a newly added power supply set; omega E Is an existing power supply set; l is t,max The maximum demand for the year t load of the target power system;
Figure BDA0003866229500000135
a load reserve capacity factor for the target power system; e it Generating capacity for the newly added power supply; e kt The generated energy of the existing power supply is generated; epsilon loss A power supply loss rate for a power supply of the target power system;
Figure BDA0003866229500000136
predicting power for the t year of the target power systemA demand;
the following formula is adopted as the capacity constraint for flexibility modification of the power supply installation machine and the thermal power generating unit:
Figure BDA0003866229500000137
in the formula
Figure BDA0003866229500000138
Installing capacity for a newly-increased energy storage power station; g s,max The maximum installed capacity of the energy storage power station;
Figure BDA0003866229500000139
the maximum installed capacity for newly increasing water pumping and energy storage is obtained; g hps,max The maximum installed capacity for pumped storage;
Figure BDA00038662295000001310
installing capacity for a new gas-electric device; g gas,max The maximum installed capacity of the gas-electric device;
Figure BDA00038662295000001311
capacity is flexibly improved for the thermal power generating unit; g g,max The maximum capacity is flexibly reconstructed for the thermal power generating unit;
the following equation is used as a flexibility margin constraint:
Figure BDA00038662295000001312
Figure BDA0003866229500000141
in the formula of gamma i The peak shaving capacity coefficient of the power supply i; x is the number of it A variable 0-1 for whether power i is put into operation; g it The installed capacity of a power supply i in the t year; omega S A set comprising all newly added and existing power supplies; omega R A new energy power supply set is provided; gamma ray j The peak shaving capacity coefficient of the flexible resource j; x is the number of jt A variable 0-1 is set up for the flexible power supply j;
Figure BDA0003866229500000142
newly adding a capacity for the flexible resource j in the t year; gamma ray r The peak regulation demand coefficient of the new energy r; x is the number of rt A variable of 0-1 is set for the new energy r in the t year; g rt Newly adding and building capacity for new energy r in the t year; gamma ray d Peak shaving coefficient which is the annual maximum load; l is t,max The maximum demand for the year t load of the target power system; r i Is the ramp rate of power supply i; r j The climbing rate of the flexible resource j; r r The climbing demand coefficient of the new energy r; r d A climbing demand coefficient for annual maximum load;
s4, constructing an operation simulation model according to a set typical scene; the method specifically comprises the following steps:
the following equation is used as the objective function for running the simulation model:
min C 2 ＝C OP +C FE +C CURT
in the formula C 2 Cost for the production run simulation phase; c OP The production operation and maintenance cost of the production operation simulation stage; c FE Fuel and environmental costs for the production run simulation stage; c CURT Penalty cost and carbon trade income for new energy electricity abandonment in a production operation simulation stage;
the following equation is used as the power balance constraint:
Figure BDA0003866229500000143
in the formula P g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p is f,t The output of the thermal power generating unit is improved for the flexibility of the f-th station in the simulated operation time period t; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained; p r,t The output of a new energy machine set in the simulated operation time period t is obtained; l is t To simulateLoad during the operating time period t;
the following formula is adopted as the operation constraint of the thermal power generating unit:
P g,min ≤δ g,t P g,t ≤P g,max
Figure BDA0003866229500000151
Figure BDA0003866229500000152
Figure BDA0003866229500000153
in the formula P g,min The minimum output of the g-th thermal power generating unit is obtained; delta g,t The operating state of the g-th thermal power generating unit in the simulated operating period t is shown; p g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p g,max The maximum output of the g-th thermal power generating unit is obtained;
Figure BDA0003866229500000154
the minimum climbing limit of the g-th thermal power generating unit is set;
Figure BDA0003866229500000155
the maximum climbing limit of the g-th thermal power generating unit is set;
Figure BDA0003866229500000156
the starting time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure BDA0003866229500000157
the minimum starting time of the g-th thermal power generating unit is set;
Figure BDA0003866229500000158
the shutdown time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure BDA0003866229500000159
the shortest shutdown time of the g thermal power generating unit is obtained;
Figure BDA00038662295000001510
the climbing capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA00038662295000001511
the uphill speed of the g-th thermal power generating unit; Δ t is the time interval;
Figure BDA00038662295000001512
the maximum output of the g-th thermal power generating unit is obtained;
Figure BDA00038662295000001513
the output of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA00038662295000001514
the creep-down capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure BDA00038662295000001515
the lower climbing speed of the g-th thermal power generating unit is obtained;
Figure BDA00038662295000001516
the minimum output of the g thermal power generating unit is obtained;
the following formula is adopted as the operation constraint of the energy storage power station:
Figure BDA00038662295000001517
E s,min ≤E s,t ≤E s,max
0≤P C,s,t ≤c s,t P C,s,max
0≤P D,s,t ≤d s,t P D,s,max
P s,t ＝P D,s,t -P C,s,t
c s,t +d s,t ≤1
Figure BDA0003866229500000161
in the formula E s,t The method comprises the steps of providing stored electric quantity of an energy storage power station s in a simulation operation time period t; eta C The charging efficiency of the energy storage power station is obtained; p C,s,t Charging power of an energy storage power station s in a simulation operation time period t; Δ t is the time interval; p D,s,t The discharge power of the energy storage power station s in the simulation operation time period t is obtained; eta D The discharge efficiency of the energy storage power station; e s,min The lower limit of the stored electricity quantity of the energy storage power station s; e s,max The upper limit of the stored electricity quantity of the energy storage power station s is set; c. C s,t Indicating variables for the charging state of the energy storage power station s in the simulated operation time period t; p C,s,max The maximum charging power of the energy storage power station s; d s,t Indicating variables for the discharge state of the energy storage power station s in the simulation operation time period t; p D,s,max The maximum discharge power of the energy storage power station s; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure BDA0003866229500000162
the climbing capacity of the energy storage power station s in the simulation operation time period t is obtained; p D,s,max The maximum discharge power of the energy storage power station s in the simulation operation time period t is obtained; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure BDA0003866229500000163
the climbing capacity of the energy storage power station s in the simulated operation time period t is obtained;
the following equation is adopted as a flexibility supply and demand balance constraint:
Figure BDA0003866229500000164
in the formula
Figure BDA0003866229500000165
Providing a capability for upward flexibility of the target power system during the simulated operation period t;
Figure BDA0003866229500000166
the method comprises the steps of (1) adjusting up flexibility of a g th thermal power generating unit before flexibility modification in a simulated operation time period t;
Figure BDA0003866229500000167
the flexibility of the up-regulation of the f-th thermal power generating unit after the flexibility modification within the simulated operation time period t is achieved;
Figure BDA0003866229500000168
flexibility of up-regulation of supply for the energy storage plant s during the simulated operation time period t;
Figure BDA0003866229500000171
providing a downward flexibility capability for the target power system during the simulated operation period t;
Figure BDA0003866229500000172
the method comprises the steps of regulating flexibility of a g th thermal power generating unit before flexibility modification in a simulation operation time period t;
Figure BDA0003866229500000173
the down-regulation flexibility of the f-th thermal power generating unit is achieved after the flexibility is improved in the simulated operation time period t;
Figure BDA0003866229500000174
the method comprises the following steps of (1) providing down-regulation flexibility for the supply of an energy storage power station s in a simulation operation time period t; n is a radical of f The total number of the transformed thermal power generating units is set;
the following equation is used as the minimum inertia requirement constraint:
Figure BDA0003866229500000175
in the formula
Figure BDA0003866229500000176
The minimum inertia requirement of a target power system in a simulation operation period t is set; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure BDA0003866229500000177
wherein
Figure BDA0003866229500000178
The maximum output of the thermal power generating unit H g Is the inertia time constant of the g-th thermal power generating unit, u g,t For the start-up and shut-down states of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s The output of the s-th energy storage power station, H s Is the inertia time constant of the s-th energy storage power station, N s For the total number of energy-storing power stations, P i The starting capacity of the ith other power supply; omega res A set of other power sources;
s5, verifying the preliminary configuration scheme of the target electric power system flexible resources obtained in the step S3 by adopting the operation simulation model constructed in the step S4, so as to obtain a final optimized configuration scheme of the electric power system flexible resources; the method specifically comprises the following steps:
checking the preliminary configuration scheme of the target power system flexibility resources by operating a simulation model:
if the verification is passed, taking the preliminary configuration scheme passed by the verification as the final optimized configuration scheme of the flexible resources of the power system;
and if the verification fails, adjusting the parameters, and repeating the steps S2-S5 until the verification passes to obtain the final optimal configuration scheme of the flexible resources of the power system.
FIG. 2 is a schematic diagram of a regulated power supply and flexible resource capacity demand timing curve for a typical day; the equivalent inertia and the lowest inertia requirement time sequence curve of the system are shown in FIG. 3; the calculation results of the flexible resource capacity requirement index are shown in the following table 1:
TABLE 1 Flexible resource Capacity requirement schematic
Figure BDA0003866229500000181
Finally, the results of flexible resource deployment and thermal power unit flexibility modification based on various typical scene operation checks are shown in fig. 4.
FIG. 5 is a schematic diagram of functional modules of the system of the present invention: the system for realizing the optimal configuration method of the electric power system flexible resources, disclosed by the invention, specifically comprises a data acquisition module, a capacity demand calculation module, a preliminary configuration calculation module, an operation simulation structure modeling module and a verification module; the data acquisition module, the capacity demand calculation module, the preliminary configuration calculation module, the operation simulation structure modeling module and the check module are sequentially connected in series; the data acquisition module is used for acquiring data information of the target power system and uploading the data to the capacity demand calculation module; the capacity demand calculation module is used for constructing a flexible resource capacity demand evaluation model of the target power system according to the received data and solving the flexible resource capacity demand evaluation model to obtain the flexible resource capacity demand of the target power system, and uploading the data to the preliminary configuration calculation module; the preliminary configuration calculation module is used for constructing a flexible resource planning model of the target power system and solving the flexible resource planning model according to the received data by considering the volatility characteristics of the source, the load and the end and the flexibility supply and demand balance characteristics, so as to obtain a preliminary configuration scheme of the flexible resources of the target power system and upload the data to the operation simulation construction module; the operation simulation construction module is used for constructing an operation simulation model according to the received data and the set typical scene and uploading the data to the verification module; and the verification module is used for verifying the preliminary configuration scheme of the flexible resources of the target power system by adopting the constructed operation simulation model according to the received data to obtain the final optimized configuration scheme of the flexible resources of the power system.

Claims (6)

1. An optimal configuration method for flexible resources of an electric power system comprises the following steps:
s1, acquiring data information of a target power system;
s2, according to the data information obtained in the step S1, constructing a flexible resource capacity requirement evaluation model of the target power system and solving to obtain the flexible resource capacity requirement of the target power system;
s3, based on the flexibility resource capacity requirement of the target power system obtained in the step S2, considering the fluctuation characteristics of source-to-load terminals and the flexibility supply-demand balance characteristics, constructing a flexibility resource planning model of the target power system and solving the flexibility resource planning model to obtain a preliminary configuration scheme of the flexibility resources of the target power system;
s4, constructing an operation simulation model according to a set typical scene;
and S5, verifying the preliminary configuration scheme of the target electric power system flexible resources obtained in the step S3 by adopting the operation simulation model constructed in the step S4, so as to obtain a final optimized configuration scheme of the electric power system flexible resources.
2. The method according to claim 1, wherein the step S2 of constructing a flexible resource capacity requirement evaluation model of the target power system specifically includes the following steps:
in order to guarantee the power supply, the following formula is adopted as a constraint condition that the flexible resource capacity of the power system must meet the maximum demand generated in a day:
Figure FDA0003866229490000011
in the formula
Figure FDA0003866229490000012
An upward force output value of the power system flexibility resource is obtained; l is max (ii) a predicted maximum load level for the day ahead; r is n Is a spare capacity factor; p is j The output of the j-th power supply; m total number of power source classes;
in order to improve the utilization rate of new energy, the following formula is adopted as a constraint condition that the minimum output level of the flexibility resources of the power system is lower than the demand generated by loads and other power sources:
Figure FDA0003866229490000021
in the formula
Figure FDA0003866229490000022
Downward force values of the flexibility resources of the power system are obtained; l is min A predicted minimum load level for the day ahead; delta j The output lower limit coefficient of the j-th power supply is obtained; p j,max The maximum output level of the j-th power supply; p RES Output for new energy;
in order to meet the regulation capacity of the system, the following formula is adopted as a constraint condition that the climbing rate of the flexible resource is greater than the climbing requirement of the target power system:
Figure FDA0003866229490000023
in the formula
Figure FDA0003866229490000024
The grade j power supply ascending ramp rate; r up An uphill demand for the target power system;
the following formula is adopted as a constraint condition that the downward climbing rate of the flexible resource is greater than the climbing demand of the target power system:
Figure FDA0003866229490000025
in the formula
Figure FDA0003866229490000026
The down-ramp rate for the j-th power supply; r is dn Is a target powerThe down-hill climbing requirement of the system;
the following equation is adopted as a constraint condition that the overall inertia level of the target power system is higher than the minimum inertia requirement:
Figure FDA0003866229490000027
in the formula
Figure FDA0003866229490000028
The lowest inertia requirement of the target power system in the time period t; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure FDA0003866229490000029
wherein
Figure FDA00038662294900000210
The maximum output of the thermal power generating unit H g Is the inertia time constant of the g-th thermal power generating unit, u g,t For the start-up and shut-down states of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s The output of the s-th energy storage power station, H s Is the inertia time constant of the s-th energy storage power station, N s For the total number of energy-storing power stations, P i The starting capacity of the ith other power supply; omega res As a collection of other power sources.
3. The method for optimal configuration of flexible resources of an electric power system according to claim 2, wherein the step S3 of constructing a flexible resource planning model of the target electric power system specifically includes the following steps:
the following equation is used as the objective function of the model:
min C 1 ＝C IN -C SV
in the formula C 1 Cost of the resource investment decision stage; c IN Investing the cost for newly added resources; c SV The residual value of the existing resources;
the following formula is adopted as a constraint condition:
electric power and electric quantity balance constraint:
Figure FDA0003866229490000031
Figure FDA0003866229490000032
in the formula
Figure FDA0003866229490000033
Newly-increased capacity of a power supply i in the t year is built; g kt The existing power supply capacity in the t year;
Figure FDA0003866229490000034
a newly added power supply set is obtained; omega E Is an existing power supply set; l is t,max The maximum demand for the year t load of the target power system;
Figure FDA0003866229490000035
a load reserve capacity factor for the target power system; e it Generating capacity for the newly added power supply; e kt The generated energy of the existing power supply is generated; epsilon loss A power supply loss rate for a power supply of the target power system;
Figure FDA0003866229490000036
predicting an electric quantity demand for the t year of the target power system;
the following formula is adopted as the capacity constraint for flexibility modification of the power supply installation machine and the thermal power generating unit:
Figure FDA0003866229490000037
in the formula
Figure FDA0003866229490000041
The installed capacity of the energy storage power station is newly increased; g s,max The maximum installed capacity of the energy storage power station;
Figure FDA0003866229490000042
the maximum installed capacity for newly increasing water pumping and energy storage is obtained; g hps,max The maximum installed capacity for pumped storage;
Figure FDA0003866229490000043
installing capacity for a new gas-electric device; g gas,max Is the maximum installed capacity of the gas-electric device;
Figure FDA0003866229490000044
capacity is flexibly improved for the thermal power generating unit; g g,max The maximum capacity is flexibly reconstructed for the thermal power generating unit;
the following equation is used as a flexibility margin constraint:
Figure FDA0003866229490000045
Figure FDA0003866229490000046
in the formula of gamma i The peak shaving capacity coefficient of the power supply i; x is a radical of a fluorine atom it A variable 0-1 for whether power i is put into operation; g it The installed capacity of a power supply i in the t year; omega S A set comprising all newly added and existing power supplies; omega R A new energy power supply set; gamma ray j The peak shaving capacity coefficient of the flexible resource j; x is the number of jt A variable 0-1 is set up for the flexible power supply j;
Figure FDA0003866229490000047
newly adding a capacity for the flexible resource j in the t year; gamma ray r For the regulation of new energy rA peak demand coefficient; x is the number of rt A variable of 0-1 is set for the new energy r in the t year; g rt Newly adding and building capacity for new energy r in the t year; gamma ray d Peak shaving coefficient which is the annual maximum load; l is t,max The maximum demand for the year t load of the target power system; r i Is the ramp rate of power supply i; r j A ramp rate for flexible resource j; r r The climbing demand coefficient of the new energy r; r d The climbing demand coefficient of annual maximum load.
4. The optimal configuration method for the flexibility resources of the power system according to claim 3, wherein the step S4 of constructing the operation simulation model according to the set typical scenario specifically comprises the following steps:
the following equation is used as the objective function for running the simulation model:
min C 2 ＝C OP +C FE +C CURT
in the formula C 2 Cost for the production run simulation phase; c OP The production operation and maintenance cost of the production operation simulation stage; c FE Fuel and environmental costs for the production run simulation stage; c CURT Penalty cost and carbon trade income for new energy electricity abandonment in a production operation simulation stage;
the following equation is used as a power balance constraint:
Figure FDA0003866229490000051
in the formula P g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p f,t The output of the thermal power generating unit is improved for the flexibility of the f-th station in the simulated operation time period t; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained; p r,t The output of the new energy unit in the simulated operation time period t is obtained; l is t Load in the simulation operation time period t;
the following formula is adopted as the operation constraint of the thermal power generating unit:
P g,min ≤δ g,t P g,t ≤P g,max
Figure FDA0003866229490000052
Figure FDA0003866229490000053
Figure FDA0003866229490000054
in the formula P g,min The minimum output of the g-th thermal power generating unit is obtained; delta. For the preparation of a coating g,t The operating state of the g-th thermal power generating unit in the simulated operating period t is shown; p g,t The output of the g-th thermal power generating unit in the simulated operation time period t is obtained; p g,max The maximum output of the g-th thermal power generating unit is obtained;
Figure FDA0003866229490000055
the minimum climbing limit of the g-th thermal power generating unit is set;
Figure FDA0003866229490000056
the maximum climbing limit of the g-th thermal power generating unit is set;
Figure FDA0003866229490000057
the starting time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure FDA0003866229490000058
the minimum starting time of the g-th thermal power generating unit is set;
Figure FDA0003866229490000059
the shutdown time of the g-th thermal power generating unit in the simulated operation time period t-1 is set;
Figure FDA00038662294900000510
the minimum shutdown time of the g-th thermal power generating unit is obtained;
Figure FDA00038662294900000511
the climbing capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure FDA00038662294900000512
the uphill speed of the g-th thermal power generating unit; Δ t is the time interval;
Figure FDA00038662294900000513
the maximum output of the g-th thermal power generating unit is obtained;
Figure FDA00038662294900000514
the output of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure FDA0003866229490000061
the creep-down capacity of the g-th thermal power generating unit in the simulated operation time period t is obtained;
Figure FDA0003866229490000062
the lower climbing speed of the g-th thermal power generating unit is obtained;
Figure FDA0003866229490000063
the minimum output of the g-th thermal power generating unit is obtained;
the following formula is adopted as the operation constraint of the energy storage power station:
Figure FDA0003866229490000064
E s,min ≤E s,t ≤E s,max
0≤P C,s,t ≤c s,t P C,s,max
0≤P D,s,t ≤d s,t P D,s,max
P s,t ＝P D,s,t -P C,s,t
c s,t +d s,t ≤1
Figure FDA0003866229490000065
in the formula E s,t The method comprises the steps of providing stored electric quantity of an energy storage power station s in a simulation operation time period t; eta C The charging efficiency of the energy storage power station is obtained; p is C,s,t Charging power of the energy storage power station s in the simulated operation time period t; Δ t is the time interval; p is D,s,t The discharge power of the energy storage power station s in the simulation operation time period t is obtained; eta D The discharge efficiency of the energy storage power station; e s,min The lower limit of the stored electricity quantity of the energy storage power station s; e s,max The upper limit of the stored electricity quantity of the energy storage power station s is set; c. C s,t Indicating variables for the charging state of the energy storage power station s in the simulated operation time period t; p C,s,max The maximum charging power of the energy storage power station s; d s,t Indicating variables for the discharge state of the energy storage power station s in the simulation operation time period t; p D,s,max The maximum discharge power of the energy storage power station s; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure FDA0003866229490000066
the climbing capacity of the energy storage power station s in the simulation operation time period t is obtained; p D,s,max The maximum discharge power of the energy storage power station s in the simulation operation time period t is obtained; p s,t The output of the s-th energy storage power station in the simulated operation time period t is obtained;
Figure FDA0003866229490000067
the climbing capacity of the energy storage power station s in the simulated operation time period t is obtained;
the following equation is adopted as a flexibility supply and demand balance constraint:
Figure FDA0003866229490000071
in the formula
Figure FDA0003866229490000072
Providing a capability for upward flexibility of the target power system during the simulated operation period t;
Figure FDA0003866229490000073
the method comprises the steps of (1) adjusting up flexibility of a g th thermal power generating unit before flexibility modification in a simulated operation time period t;
Figure FDA0003866229490000074
the flexibility of the up-regulation of the f-th thermal power generating unit after the flexibility modification within the simulated operation time period t is achieved;
Figure FDA0003866229490000075
flexibility in up-regulation of supply for the energy storage power station s during the simulated operation period t;
Figure FDA0003866229490000076
providing a downward flexibility capability for the target power system during the simulated operation period t;
Figure FDA0003866229490000077
the flexibility of the down regulation of the g th thermal power generating unit before the flexibility modification in the simulated operation time period t is realized;
Figure FDA0003866229490000078
the down-regulation flexibility of the f-th thermal power generating unit is achieved after the flexibility is improved in the simulated operation time period t;
Figure FDA0003866229490000079
the method comprises the following steps of (1) providing down-regulation flexibility for the supply of an energy storage power station s in a simulation operation time period t; n is a radical of f The total number of the transformed thermal power generating units is calculated;
the following equation is used as the minimum inertia requirement constraint:
Figure FDA00038662294900000710
in the formula
Figure FDA00038662294900000711
The minimum inertia requirement of a target power system in a simulation operation period t is set; h eq,t Is an equivalent inertia time constant of the target power system, and
Figure FDA00038662294900000712
wherein
Figure FDA00038662294900000713
The maximum output of the thermal power generating unit H g Is the inertia time constant, u, of the g-th thermal power generating unit g,t For the start-up and shut-down states of the g-th thermal power generating unit, N g Is the total number of thermal power generating units, P s The output of the s-th energy storage power station, H s Is the inertia time constant of the s-th energy storage power station, N s For the total number of energy-storing power stations, P i The starting capacity of the ith other power supply; omega res As a collection of other power sources.
5. The optimal configuration method for the flexibility resources of the power system according to claim 4, wherein the step S5 of verifying the preliminary configuration scheme of the flexibility resources of the target power system obtained in the step S3 by using the operation simulation model constructed in the step S4 to obtain a final optimal configuration scheme of the flexibility resources of the power system specifically comprises the following steps:
and (3) checking the preliminary configuration scheme of the target power system flexibility resources by operating a simulation model:
if the verification is passed, taking the preliminary configuration scheme passed by the verification as the final optimized configuration scheme of the flexible resources of the power system;
and if the verification fails, adjusting the parameters, and repeating the steps S2-S5 until the verification passes to obtain the final optimal configuration scheme of the flexible resources of the power system.
6. A system for realizing the optimal configuration method of the electric power system flexible resources, which is described in one of claims 1 to 5, is characterized by specifically comprising a data acquisition module, a capacity demand calculation module, a preliminary configuration calculation module, an operation simulation structure modeling module and a verification module; the data acquisition module, the capacity demand calculation module, the preliminary configuration calculation module, the operation simulation structure modeling module and the check module are sequentially connected in series; the data acquisition module is used for acquiring data information of the target power system and uploading the data to the capacity demand calculation module; the capacity demand calculation module is used for constructing a flexible resource capacity demand evaluation model of the target power system according to the received data and solving the flexible resource capacity demand evaluation model to obtain the flexible resource capacity demand of the target power system, and uploading the data to the preliminary configuration calculation module; the preliminary configuration calculation module is used for constructing a flexible resource planning model of the target power system and solving the flexible resource planning model according to the received data by considering the volatility characteristics of the source, the load and the end and the flexibility supply and demand balance characteristics, so as to obtain a preliminary configuration scheme of the flexible resources of the target power system and upload the data to the operation simulation construction module; the operation simulation construction module is used for constructing an operation simulation model according to the received data and the set typical scene and uploading the data to the verification module; and the checking module is used for checking the preliminary configuration scheme of the target electric power system flexible resources by adopting the constructed operation simulation model according to the received data to obtain the final optimized configuration scheme of the electric power system flexible resources.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116523279A (en) * 2023-07-05 2023-08-01 国网湖北省电力有限公司经济技术研究院 Determination method of flexible resource allocation scheme considering frequency modulation requirement
CN116805792A (en) * 2023-06-21 2023-09-26 国网湖南省电力有限公司 Thermal power-energy storage regulation demand judging method and system in high-proportion new energy system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116805792A (en) * 2023-06-21 2023-09-26 国网湖南省电力有限公司 Thermal power-energy storage regulation demand judging method and system in high-proportion new energy system
CN116523279A (en) * 2023-07-05 2023-08-01 国网湖北省电力有限公司经济技术研究院 Determination method of flexible resource allocation scheme considering frequency modulation requirement
CN116523279B (en) * 2023-07-05 2023-09-22 国网湖北省电力有限公司经济技术研究院 Determination method of flexible resource allocation scheme considering frequency modulation requirement

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