CN117318182B - Fire, wind and light storage integrated base capacity optimization configuration method - Google Patents
Fire, wind and light storage integrated base capacity optimization configuration method Download PDFInfo
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Abstract
The invention relates to the field of optimal configuration of fire and wind energy storage planning capacity, in particular to a method for optimal configuration of fire and wind energy storage integrated base capacity, which comprises the following steps: 1. obtaining a base annual wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence; 2. presetting base related constraint conditions to obtain real-time output magnitude sequences and load real-time magnitude sequences of power supplies and energy storage; 3. confirming the configuration capacity of the base thermal power, the starting mode of the thermal power and the energy storage operation strategy, and constructing a fire, wind and solar energy storage integrated base capacity optimization configuration model; 4. forming a plurality of power capacity configuration schemes; 5. and calculating the total power generation amount of new annual energy sources under various configuration schemes, and selecting a power supply capacity configuration scheme with the maximum total power generation amount as an objective function as a final scheme. The invention considers the economic benefit rate of the base and the electricity discarding rate of new energy, can exert the maximum comprehensive benefit of the base, and has great guiding significance for the early planning of the fire and wind energy storage integrated base.
Description
Technical Field
The invention relates to the technical field of optimal configuration of fire and wind energy storage planning capacity, in particular to a method for optimal configuration of fire and wind energy storage integrated base capacity.
Background
Wind power and photovoltaic power generation output have the characteristics of randomness, intermittence and volatility, the wind power and photovoltaic power generation output has no self-adjusting capability, and the phenomena of unstable output, off-grid and the like directly influence the safe, stable and economic operation of a power system.
The integrated fire and wind energy storage base provides a new path for improving the level of renewable energy consumption, increasing the consumption proportion of non-fossil energy and promoting the large-scale development of new energy, and provides reasonable development scale of the new energy of the integrated multi-energy complementary base under the new path for exploring new situations. In view of the above, the research of a fire, wind and solar energy storage integrated base capacity optimization configuration method which simultaneously considers the economic benefit rate and the new energy power-losing rate is a technical problem to be solved urgently in the technical field, and the invention fills the blank in the technical field.
Disclosure of Invention
The invention provides a capacity optimization configuration method of a fire wind and light storage integrated base, which aims to solve the technical problems that the existing new energy scale configuration methods all adopt production simulation or safe and stable check, take single targets such as maximum wind and light total development regulation or renewable energy proportion as research objects, and have little significance in early planning guidance of the fire wind and light storage integrated base.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
the invention provides a fire, wind and solar energy storage integrated base capacity optimization configuration method, which specifically comprises the following steps:
s1, acquiring wind power historical output data, photovoltaic historical output data and load historical characteristic curves of all-year-round preset time periods of a base region, and respectively calculating to obtain a base all-year-round wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence by adopting arithmetic average values;
s2, presetting relevant constraint conditions of a fire, wind and light storage integrated base by using output data of the S1, wherein the relevant constraint conditions comprise output constraint, load characteristic constraint and energy storage charge and discharge constraint of each power supply, so as to obtain real-time output size sequences and load real-time size sequences of each power supply and energy storage;
s3, confirming a base thermal power configuration capacity, a thermal power starting mode and an energy storage operation strategy according to a preset real-time output and load real-time size sequence of each power supply, and constructing a fire, wind and solar energy storage integrated base capacity optimization configuration model based on electric power and electric quantity balance constraint;
s4, constructing two objective functions of internal yield and new energy power-off rate in consideration of base economy, namely, meeting the related constraint conditions of the base integrated with fire and wind power storage in S2, and forming various power capacity configuration schemes by fully listing all required power capacity combinations of the two objective functions of the internal yield and the new energy power-off rate in a traversing mode, wherein the power capacity configuration capacity and the power starting mode of the base integrated with fire and wind power storage in S3, the energy storage operation strategy and the power capacity optimization configuration model of the base integrated with fire and wind power storage based on electric power and electric quantity balance constraint;
and S5, calculating the total power generation amount of new annual energy sources under various configuration schemes, and selecting a power supply capacity configuration scheme with the maximum total power generation amount as an objective function as a final optimization scheme.
Further, the step S1 of calculating to obtain a base annual wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence specifically comprises the following steps:
s11, utilizing output historical data of a wind power plant established in a base region before a specified year, and calculating by adopting an arithmetic average value to obtain a power output coefficient time sequence of a jth day and an ith hour of the wind power plant of 8760 hours of the whole year of the fire, wind and solar energy storage integrated base；
S12, calculating to obtain a power output coefficient time sequence of a j-th day and i-th hour of the photovoltaic power station of the fire, wind and solar energy storage integrated base all year 8760 hours by utilizing the power output historical data of the photovoltaic power station established by the specified year of the base region and adopting an arithmetic average value；
S13, calculating a load coefficient time sequence of the j th day and i th hour of the fire, wind and solar energy storage integrated base all year 8760 hours by means of arithmetic average value by utilizing actual condition of user load before the base region is designated year and year load prediction data of the development level。
Further, each power supply output constraint in the S2 comprises a wind power output constraint, a photovoltaic output constraint and a thermal power output constraint;
the wind power output constraint is expressed by a formula, and specifically comprises the following steps:
（1）
wherein:for the real-time output magnitude sequence of wind power, +.>Configuring capacity for the base wind power planning;
the photovoltaic output constraint is expressed by a formula, specifically:
（2）
wherein:real-time output magnitude sequence for photovoltaic power generation, < >>Planning and configuring capacity for the base photovoltaic power generation;
the thermal power output constraint is expressed by a formula, and is specifically as follows:
（3）
（4）
wherein:capacity allocation for base thermal power, +.>Setting ∈0 for thermal power>Starting capacity of time period, < >>Setting ∈0 for thermal power>Real-time output magnitude sequence under the starting capacity of time period, +.>The maximum peak regulating depth of the thermal power is obtained.
Further, the load characteristic constraint in S2 is expressed by a formula, specifically:
（5）
wherein:for the load real-time size sequence,/o>Maximum load for planning horizontal annual base;
the energy storage charging and discharging constraint in the S2 is expressed by adopting a formula, and is specifically as follows:
（6）
（7）
wherein:for energy storage real-time output magnitude sequence, +.>Configuring capacity for a base energy storage plan +.>Is the maximum charge and discharge multiple of energy storage +.>Day of presentation,/->，/>Time of presentation->。
Further, each power supply and energy storage real-time output size sequence in the S2 comprises a wind power real-time output size sequenceReal-time output magnitude sequence of photovoltaic power generation>Thermal power is set at->Real-time output size sequence under time period starting capacity +.>Energy storage real-time output magnitude sequence>。
Further, the step S3 of confirming the base thermal power configuration capacity, the thermal power starting mode and the energy storage operation strategy is specifically as follows:
determining the configuration capacity of the base thermal power: in order to ensure that the load in the base area has power guarantee at any time point, the thermal power planning capacity is determined according to the condition that the maximum load is met and the capacity of a single thermal power unit is considered to form multiple, and the thermal power planning capacity is expressed by adopting a formula, specifically:
（8）
wherein:is the capacity of a single thermal power generating unit in a base +.>Is rounded upwards;
determining a thermal power starting mode: in order to reduce the low-load operation time of the unit and the operation cost of thermal power, each setting of the base thermal power unitThe time period can be set to be that the starting-up mode is readjusted according to different modes such as week, month, specific time and the like, and the thermal power starting-up capacity is set according to the requirement +.>The maximum load in the time period is determined by considering the capacity of a single thermal power generating unit to form multiple, and the maximum load is expressed by adopting a formula, specifically:
（9）
wherein:setting +.>A real-time output magnitude sequence within a time period;
determining an energy storage operation strategy: the energy storage charging and discharging strategy can select a charging and discharging mode with one charging and one discharging mode and two charging and two discharging modes according to the day.
Further, the power and electricity balance constraint-based fire and wind energy storage integrated base capacity optimization configuration model in the step S3 is specifically as follows:
（10）
（11）
wherein:the power is discarded in real time.
Further, the step S4 specifically includes the following steps:
s41, constructing two objective functions of internal yield and new energy power rejection rate in consideration of base economy, wherein the two objective functions comprise a yield objective function and a power rejection rate objective function;
s42, all power supply capacity combinations meeting all requirements of the power supply output constraint, the load characteristic constraint and the energy storage charging and discharging constraint in S2, the configuration capacity and the starting mode of the thermal power in the base thermal power in S3, the energy storage operation strategy, the fire, wind and solar energy storage integrated base capacity optimization configuration model based on the electric power and electric quantity balance constraint, and the yield objective function and the power rejection objective function in S41 are all listed in a traversing mode, and granularity is determined by self according to the measuring and calculating precision requirement, so that various power supply capacity configuration schemes are formed.
Further, the yield objective function in S41 is:
（12）
wherein:comprehensive internal yield of fire, wind and light storage integrated base>Engineering life is designed for fire wind and light storage projects>To design the +.>Annual (I)>Is->Annual cash inflow, includingReserve the residual value and the electricity selling income,is->Annual cash flows, including investment costs, operational maintenance costs, equipment update costs, raw material cost,minimum revenue requirements set for the in-base revenue rate objective function;
the rejection rate objective function in S41 is:
（13）
wherein:comprehensive electricity discarding rate for new energy of fire, wind and light storage integrated base>The highest power rejection requirement set for the base power rejection rate objective function.
Further, the step S5 specifically includes the following steps:
s51, calculating total annual new energy generating capacity under various configuration schemes, wherein the annual new energy generating capacity is expressed by adopting a formula as follows:
（14）
wherein:is->Total new energy generating capacity under the configuration scheme of seed fire wind and light storage>Is the first/>Wind power total generating capacity under wind power generation and wind power storage configuration scheme>Is->The total power generation amount of the photovoltaic power generation under the wind-solar energy storage configuration scheme,is->The new energy total abandoned electric quantity under the configuration scheme of the seed fire wind and light storage;
s52, selecting a power supply capacity configuration scheme with the maximum total power generation amount, namely takingThe corresponding wind and light is stored as the final optimal configuration scale.
The invention has the beneficial effects that:
in the specific operation, the power combination scheme meeting the requirements of a plurality of targets of the base is formed by combining a wind-light real-time output size sequence and a real-time load size sequence which are obtained based on wind power, photovoltaic and load history data in the base region and integrating a thermal power starting mode, an energy storage operation strategy, a yield target and a power rejection target comprehensive algorithm (namely a yield target function and a power rejection target function), and the power combination scheme with the maximum total power generation capacity of new energy sources of the annual base is selected for capacity optimization configuration. Compared with the traditional planning mode of only considering single-target wind, light and fire storage integrated base capacity proportioning, the method disclosed by the invention not only considers the economic benefit rate of the base, but also considers the electricity discarding rate of new energy, can exert the maximum comprehensive benefit of the base, and has great guiding significance for the early planning of the wind, light and fire storage integrated base.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graph showing the coefficient of wind power output curve according to an embodiment of the present invention;
FIG. 3 is a graph showing the coefficients of a photovoltaic output curve according to an embodiment of the present invention;
FIG. 4 is a graph showing load characteristic coefficients in an embodiment of the present invention;
FIG. 5 shows a thermal power configuration scheme and a unit start-up mode for meeting the base load requirements in an embodiment of the invention;
FIG. 6 is a graph showing power output data for a typical day based on power balance constraints in an embodiment of the present invention;
fig. 7 shows the calculated wind-solar power generation total amount of each scheme in the embodiment of the invention.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many other different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Referring to fig. 1, an embodiment of the present application provides a method for optimizing and configuring a capacity of a fire, wind and solar energy storage integrated base, which specifically includes the following steps:
s1, acquiring wind power historical output data, photovoltaic historical output data and load historical characteristic curves of all-year-round preset time periods of a base region, and respectively calculating to obtain a base all-year-round wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence by adopting arithmetic average values;
s2, presetting relevant constraint conditions of a fire, wind and light storage integrated base by using output data of the S1, wherein the relevant constraint conditions comprise output constraint, load characteristic constraint, energy storage charge and discharge constraint and the like of each power supply, so as to obtain real-time output size sequences and load real-time size sequences of each power supply and energy storage;
s3, confirming a base thermal power configuration capacity, a thermal power starting mode and an energy storage operation strategy according to a preset real-time output and load real-time size sequence of each power supply, and constructing a fire, wind and solar energy storage integrated base capacity optimization configuration model based on electric power and electric quantity balance constraint;
s4, constructing two objective functions of internal yield and new energy power-off rate in consideration of base economy, namely, meeting the related constraint conditions of the base integrated with fire and wind power storage in S2, and forming various power capacity configuration schemes by fully listing all required power capacity combinations of the two objective functions of the internal yield and the new energy power-off rate in a traversing mode, wherein the power capacity configuration capacity and the power starting mode of the base integrated with fire and wind power storage in S3, the energy storage operation strategy and the power capacity optimization configuration model of the base integrated with fire and wind power storage based on electric power and electric quantity balance constraint;
and S5, calculating the total power generation amount of new annual energy sources under various configuration schemes, and selecting a power supply capacity configuration scheme with the maximum total power generation amount as an objective function as a final optimization scheme.
In some embodiments, the application environment is thermal power, wind power, photovoltaic and energy storage to be configured are optimized according to a load prediction result and a load characteristic curve, and the calculation in the step S1 obtains a base annual wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence, which specifically comprises the following steps:
s11, utilizing output historical data of a wind power plant established in the past five years of a base region, and calculating by adopting an arithmetic average value to obtain a power output coefficient time sequence of the jth and ith hours of the wind power plant of 8760 hours of the whole year of the fire, wind and solar energy storage integrated base，；
Specifically, the total capacity of the wind power plant is established in the base area in the past five yearsAnnual average real-time output sequence is +.>Then->As in fig. 2.
S12, utilizing output historical data of a photovoltaic power station established in the past five years of a base region, and calculating by adopting an arithmetic average value to obtain a power output coefficient time sequence of a j-th day and i-th hour of a photovoltaic power station of 8760-hour all-year of a fire, wind and solar energy storage integrated base，/>；
Specifically, the past five years of setting the base region has established the total capacity of the photovoltaic power station asAnnual average real-time output sequence is +.>Then->As shown in fig. 3.
S13, calculating a load coefficient time sequence of the j th day and i th hour of the fire, wind and solar energy storage integrated base all year 8760 hours by using actual condition of the user load in the past five years and load prediction data of the state of the development year in the base region and adopting arithmetic average value，/>。
Specifically, the average actual maximum load of the base area in the past five years is set asThe annual average real-time load size sequence is +.>Then->As shown in fig. 4.
In some embodiments, each power supply output constraint in S2 includes a wind power output constraint, a photovoltaic output constraint, and a thermal power output constraint;
the wind power output constraint is expressed by a formula, and specifically comprises the following steps:
（1）
wherein:for the real-time output magnitude sequence of wind power, +.>Configuring capacity for the base wind power planning;
the photovoltaic output constraint is expressed by a formula, specifically:
（2）
wherein:real-time output magnitude sequence for photovoltaic power generation, < >>Planning and configuring capacity for the base photovoltaic power generation;
the thermal power output constraint is expressed by a formula, and is specifically as follows:
（3）
（4）
wherein:the capacity is configured for the base thermal power,/>setting ∈0 for thermal power>Starting capacity of time period, < >>Setting ∈0 for thermal power>Real-time output magnitude sequence under the starting capacity of time period, +.>The maximum peak regulating depth of the thermal power is obtained.
In some embodiments, the load characteristic constraint in S2 is expressed by a formula, specifically:
（5）
wherein:for the load real-time size sequence,/o>Maximum load for planning horizontal annual base;
the energy storage charging and discharging constraint in the S2 is expressed by adopting a formula, and is specifically as follows:
（6）
（7）
wherein:for energy storage real-time output magnitude sequence, +.>Configuring capacity for a base energy storage plan +.>Is the maximum charge and discharge multiple of energy storage +.>Day of presentation,/->，/>Time of presentation->。
In some embodiments, each power supply and energy storage real-time output magnitude sequence in S2 includes a wind power real-time output magnitude sequenceReal-time output magnitude sequence of photovoltaic power generation>Thermal power is set at->Real-time output size sequence under time period starting capacity +.>Energy storage real-time output magnitude sequence>。
In some embodiments, the determining the base thermal power configuration capacity, the thermal power starting mode and the energy storage operation strategy in S3 specifically includes:
determining the configuration capacity of the base thermal power: to ensure that the load in the base area has power guarantee at any time point, the thermal power planning capacity meets the maximum loadAnd consider the determination of the double number of the capacities of the single thermal power generating units, in the embodiment, the 1800MW according to the load prediction result comprises 4 thermal power generating units, and the rated capacities are respectivelyThe method adopts a formula to express, and is specifically as follows:
（8）
wherein:is the capacity of a single thermal power generating unit in a base +.>Is rounded upwards;
determining a thermal power starting mode: in order to reduce the low-load operation time of the unit and the operation cost of thermal power, each setting of the base thermal power unitThe time period can be set to be that the starting-up mode is readjusted according to different modes such as week, month, specific time and the like, and the thermal power starting-up capacity is set according to the requirement +.>The maximum load in the time period is determined by considering the capacity multiple of a single thermal power generating unit, in this embodiment, the monthly startup is selected as shown in fig. 5, and the maximum load is expressed by adopting a formula, specifically:
（9）
wherein:setting +.>A real-time output magnitude sequence within a time period;
determining an energy storage operation strategy: the energy storage charging and discharging strategy can select modes of charging and discharging at random, charging and discharging one by one, charging and discharging two by two and the like according to days, and the charging and discharging mode with highest control requirement and highest energy storage utilization rate is selected in the embodiment.
In some embodiments, the power and electricity balance constraint-based fire and wind energy storage integrated base capacity optimization configuration model in S3 is shown in fig. 6, and specifically includes the following steps:
（10）
（11）
wherein:the power is discarded in real time.
Specifically, the capacity optimization configuration model of the fire, wind and solar energy storage integrated base based on the electric power and electric quantity balance constraint is integrated with algorithms of different starting modes of the thermal power generating unit, the power optimal capacities of wind power, photovoltaic power, energy storage and the like in the integrated base are calculated in each starting mode by traversing the different starting modes such as weekly, monthly and specific time on the basis of the traditional optimization configuration algorithm, and the configuration precision of the wind and solar energy storage capacity is improved after preferred selection.
In some embodiments, the step S4 specifically includes the following steps:
s41, constructing two objective functions of internal yield and new energy power rejection rate in consideration of base economy, wherein the two objective functions comprise a yield objective function and a power rejection rate objective function;
s42, all power supply capacity combinations meeting all requirements of the power supply output constraint, the load characteristic constraint and the energy storage charging and discharging constraint in S2, the base thermal power configuration capacity and the thermal power starting mode in S3, the energy storage operation strategy, the fire, wind and solar energy storage integrated base capacity optimization configuration model based on the electric power and electric quantity balance constraint, and the yield rate objective function and the power rejection rate objective function in S41 are listed in a traversing mode, and granularity is determined by self according to the measuring and calculating precision requirement as shown in a table I, so that various power supply capacity configuration schemes are formed.
Table one: calculated wind-solar energy storage configuration scheme meeting requirements of power rejection rate and yield rate
In some embodiments, the yield objective function in S41 is:
（12）
wherein:comprehensive internal yield of fire, wind and light storage integrated base>Engineering life is designed for fire wind and light storage projects>To design the +.>Annual (I)>Is->Annual cash flows including device residues, electricity returns, +.>Is->Annual cash flows including investment costs, operating maintenance costs, equipment update costs, raw material cost, etc., are->Minimum revenue requirements set for the in-base revenue rate objective function;
the rejection rate objective function in S41 is:
（13）
wherein:comprehensive electricity discarding rate for new energy of fire, wind and light storage integrated base>The highest power rejection requirement set for the base power rejection rate objective function is taken as 5% in this example.
Specifically, the fire wind-solar energy storage capacity configuration scheme simultaneously considers two indexes of new energy construction economy (namely a yield objective function) and new energy consumption electricity rejection rate (namely an electricity rejection rate objective function) into an algorithm, so that a configuration result is more reasonable.
In some embodiments, the step S5 specifically includes the following steps:
s51, calculating total annual new energy generating capacity under various configuration schemes, wherein the annual new energy generating capacity is expressed by adopting a formula as follows:
（14）
wherein:is->Total new energy generating capacity under the configuration scheme of seed fire wind and light storage>Is->Wind power total generating capacity under wind power generation and wind power storage configuration scheme>Is->The total power generation amount of the photovoltaic power generation under the wind-solar energy storage configuration scheme,is->The new energy total abandoned electric quantity under the configuration scheme of the seed fire wind and light storage;
s52, selecting a power supply capacity configuration scheme with the maximum total power generation amount, as shown in FIG. 7, and selecting the power supply capacity configuration scheme with the maximum total power generation amount corresponding to scheme 39, namely takingThe corresponding wind and light is stored as the final optimal configuration scale.
According to the invention, the wind power and photovoltaic power generation capacity data and the load characteristic curves of the local near five years are fully utilized, the thermal power starting mode and different energy storage operation strategies are further considered outside the framework of the traditional production simulation method, the investment yield and wind power rejection rate of the wind-light-fire storage integrated base are calculated in detail, and the capacity ratio of each power supply of the wind-light-fire storage integrated base is optimized from multiple angles. The multi-element optimization algorithm is integrated, so that the configuration result is more accurate, and the technical blank of multi-objective unified consideration of a power-on mode, economy, power rejection rate, power generation capacity and the like in capacity ratio optimization is filled.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Moreover, the technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can implement the embodiments, and when the technical solutions are contradictory or cannot be implemented, it should be considered that the combination of the technical solutions does not exist, and is not within the scope of protection claimed by the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. The fire, wind and light storage integrated base capacity optimization configuration method is characterized by comprising the following steps of:
s1, acquiring wind power historical output data, photovoltaic historical output data and load historical characteristic curves of all-year-round preset time periods of a base region, and respectively calculating to obtain a base all-year-round wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence by adopting arithmetic average values;
the calculation in the step S1 obtains a base annual wind power plant output coefficient time sequence, a photovoltaic power station output coefficient time sequence and a load coefficient time sequence, and specifically comprises the following steps:
s11, utilizing output historical data of a wind power plant established in the past five years of a base region, and calculating by adopting an arithmetic average value to obtain a power output coefficient time sequence of the jth and ith hours of the wind power plant of 8760 hours of the whole year of the fire, wind and solar energy storage integrated base，；
Specifically, the total capacity of the wind power plant is established in the base area in the past five yearsAnnual average real-time output sequence isThen->；
S12, utilizing output historical data of a photovoltaic power station established in the past five years of a base region, and calculating by adopting an arithmetic average value to obtain a power output coefficient time sequence of a j-th day and i-th hour of a photovoltaic power station of 8760-hour all-year of a fire, wind and solar energy storage integrated base，；
Specifically, the past five years of setting the base region has established the total capacity of the photovoltaic power station asAnnual average real-time output sequence is +.>Then->；
S13, calculating a load coefficient time sequence of the j th day and i th hour of the fire, wind and solar energy storage integrated base all year 8760 hours by using actual condition of the user load in the past five years and load prediction data of the state of the development year in the base region and adopting arithmetic average value，/>；
Specifically, the average actual maximum load of the base area in the past five years is set asThe annual average real-time load size sequence isThen->；
S2, presetting relevant constraint conditions of a fire, wind and light storage integrated base by using output data of the S1, wherein the relevant constraint conditions comprise output constraint, load characteristic constraint and energy storage charge and discharge constraint of each power supply, so as to obtain real-time output size sequences and load real-time size sequences of each power supply and energy storage;
s3, confirming a base thermal power configuration capacity, a thermal power starting mode and an energy storage operation strategy according to a preset real-time output and load real-time size sequence of each power supply, and constructing a fire, wind and solar energy storage integrated base capacity optimization configuration model based on electric power and electric quantity balance constraint;
s4, constructing two objective functions of internal yield and new energy power-off rate in consideration of base economy, namely, meeting the related constraint conditions of the base integrated with fire and wind power storage in S2, and forming various power capacity configuration schemes by fully listing all required power capacity combinations of the two objective functions of the internal yield and the new energy power-off rate in a traversing mode, wherein the power capacity configuration capacity and the power starting mode of the base integrated with fire and wind power storage in S3, the energy storage operation strategy and the power capacity optimization configuration model of the base integrated with fire and wind power storage based on electric power and electric quantity balance constraint;
and S5, calculating the total power generation amount of new annual energy sources under various configuration schemes, and selecting a power supply capacity configuration scheme with the maximum total power generation amount as an objective function as a final optimization scheme.
2. The method for optimizing and configuring the capacity of the fire, wind and solar energy storage integrated base according to claim 1, wherein the power output constraints in the step S2 comprise wind power output constraints, photovoltaic output constraints and thermal power output constraints;
the wind power output constraint is expressed by a formula, and specifically comprises the following steps:
（1）
wherein:for the real-time output magnitude sequence of wind power, +.>Configuring capacity for the base wind power planning;
the photovoltaic output constraint is expressed by a formula, specifically:
（2）
wherein:real-time output magnitude sequence for photovoltaic power generation, < >>Planning and configuring capacity for the base photovoltaic power generation;
the thermal power output constraint is expressed by a formula, and is specifically as follows:
（3）
（4）
wherein:capacity allocation for base thermal power, +.>Setting ∈0 for thermal power>Starting capacity of time period, < >>Setting ∈0 for thermal power>Real-time output magnitude sequence under the starting capacity of time period, +.>The maximum peak regulating depth of the thermal power is obtained.
3. The method for optimizing and configuring the capacity of the fire, wind and solar energy storage integrated base according to claim 2, wherein the load characteristic constraint in the S2 is expressed by adopting a formula, specifically:
（5）
wherein:for the load real-time size sequence,/o>Maximum load for planning horizontal annual base;
the energy storage charging and discharging constraint in the S2 is expressed by adopting a formula, and is specifically as follows:
（6）
（7）
wherein:for energy storage real-time output magnitude sequence, +.>Configuring capacity for a base energy storage plan +.>Is the maximum charge and discharge multiple of energy storage +.>Day of presentation,/->，/>Time of presentation->。
4. The method for optimizing and configuring the capacity of a fire, wind and solar energy storage integrated base according to claim 3, wherein the power supply and energy storage real-time output size sequence in the step S2 comprises a wind power real-time output size sequenceReal-time output magnitude sequence of photovoltaic power generation>Thermal power is set at->Real-time output size sequence under time period starting capacity +.>Energy storage real-time output magnitude sequence>。
5. The method for optimizing and configuring the capacity of the fire, wind and solar energy storage integrated base according to claim 4, wherein the method for confirming the configuration capacity of the base thermal power, the starting mode of the thermal power and the energy storage operation strategy in the step S3 is specifically as follows:
determining the configuration capacity of the base thermal power: in order to ensure that the load in the base area has power guarantee at any time point, the thermal power planning capacity is determined according to the condition that the maximum load is met and the capacity of a single thermal power unit is considered to form multiple, and the thermal power planning capacity is expressed by adopting a formula, specifically:
（8）
wherein:is the capacity of a single thermal power generating unit in a base +.>Is rounded upwards;
determining a thermal power starting mode: in order to reduce the low-load operation time of the unit and the operation cost of thermal power, each setting of the base thermal power unitReadjusting the starting mode in a time period, wherein the thermal power starting capacity meets the setting>The maximum load in the time period is determined by considering the capacity of a single thermal power generating unit to form multiple, and the maximum load is expressed by adopting a formula, specifically:
（9）
wherein:setting +.>A real-time output magnitude sequence within a time period;
determining an energy storage operation strategy: the energy storage charging and discharging strategy can select a charging and discharging mode with one charging and one discharging mode and two charging and two discharging modes according to the day.
6. The method for optimizing and configuring the capacity of the integrated fire, wind and solar energy storage base according to claim 5, wherein the power and electricity balance constraint-based capacity optimizing and configuring model of the integrated fire, wind and solar energy storage base in the step S3 is specifically as follows:
（10）
（11）
wherein:the power is discarded in real time.
7. The method for optimizing and configuring the capacity of the fire, wind and solar energy storage integrated base according to claim 6, wherein the step S4 specifically comprises the following steps:
s41, constructing two objective functions of internal yield and new energy power rejection rate in consideration of base economy, wherein the two objective functions comprise a yield objective function and a power rejection rate objective function;
s42, all power supply capacity combinations meeting all requirements of the power supply output constraint, the load characteristic constraint and the energy storage charging and discharging constraint in S2, the configuration capacity and the starting mode of the thermal power in the base thermal power in S3, the energy storage operation strategy, the fire, wind and solar energy storage integrated base capacity optimization configuration model based on the electric power and electric quantity balance constraint, and the yield objective function and the power rejection objective function in S41 are all listed in a traversing mode, and granularity is determined by self according to the measuring and calculating precision requirement, so that various power supply capacity configuration schemes are formed.
8. The method for optimizing and configuring the capacity of the integrated fire, wind and solar energy storage base according to claim 7, wherein the yield objective function in S41 is as follows:
（12）
wherein:comprehensive internal yield of fire, wind and light storage integrated base>Engineering life is designed for fire wind and light storage projects>To design the +.>Annual (I)>Is->Annual cash flows including device residues, electricity returns, +.>Is->Annual cash flows including investment costs, operating maintenance costs, equipment update costs, raw material cost, and->Minimum revenue requirements set for the in-base revenue rate objective function;
the rejection rate objective function in S41 is:
（13）
wherein:comprehensive electricity discarding rate for new energy of fire, wind and light storage integrated base>The highest power rejection requirement set for the base power rejection rate objective function.
9. The method for optimizing and configuring the capacity of the fire, wind and solar energy storage integrated base according to claim 8, wherein the step S5 specifically comprises the following steps:
s51, calculating total annual new energy generating capacity under various configuration schemes, wherein the annual new energy generating capacity is expressed by adopting a formula as follows:
（14）
wherein:is->Total new energy generating capacity under the configuration scheme of seed fire wind and light storage>Is->Wind power total generating capacity under wind power generation and wind power storage configuration scheme>Is->Fire-planting wind-light storage configuration methodTotal power generation of photovoltaic power generation under the scheme +.>Is->The new energy total abandoned electric quantity under the configuration scheme of the seed fire wind and light storage;
s52, selecting a power supply capacity configuration scheme with the maximum total power generation amount, namely takingThe corresponding wind and light is stored as the final optimal configuration scale.
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