A wind, solar, load and storage optimization configuration method and device in a comprehensive energy scenario

Abstract

An embodiment of the present invention relates to a method and device for optimizing the configuration of wind, solar, load and storage in an integrated energy scenario, the method comprising: obtaining a first objective function and a second objective function of a target integrated energy field; setting a first basic constraint condition, a second basic constraint condition and a load balance constraint condition of the target integrated energy field according to the first objective function and the second objective function; solving the first objective function and the second objective function based on the constraints to obtain the configuration parameters of each generator set in the target integrated energy field. The technical solution of the embodiment of the present invention, under the premise of meeting the different load demands of the integrated energy field, takes the lowest total operating cost and the lowest carbon emissions of the integrated energy field as the goal, and improves the absorption level of wind and solar energy and reduces the wind and solar abandonment rates in combination with the energy storage system by coordinating the demands between different load types, thereby enhancing the potential of the power system to absorb renewable energy power generation.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of system optimization and scheduling in the power industry, and in particular to a method and device for optimizing the configuration of wind, solar, load and storage in an integrated energy scenario. Background Art

[0002] Energy production and utilization are driving revolutions in energy consumption, energy supply, energy technology, and energy systems. The efficient utilization of renewable energy sources such as wind and solar power, along with the combined use of energy storage devices, has become a key research topic.

[0003] Wind and solar renewable energy sources are characterized by volatility, intermittency, and uncertainty. As their installed capacity and share of power generation increase annually, the demand for system peak regulation also increases. Currently, advantageous peak regulation resources (including pumped storage and gas-fired turbines) are severely insufficient. Even after accounting for appropriate wind and solar curtailment, they are still insufficient to support the integration of renewable energy generation into the grid. Energy storage systems can quickly mitigate the random intermittency and uncertainty of renewable energy generation, bringing new challenges and opportunities to the operation and dispatch of power systems. Summary of the Invention

[0004] Based on the above situation of the prior art, the purpose of the embodiments of the present invention is to provide a method and device for optimizing the configuration of wind, solar, load and storage in an integrated energy scenario. On the premise of meeting the different load requirements of the integrated energy field, with the goal of minimizing the total operating cost and carbon emissions of the integrated energy field, by coordinating the requirements between different load types and combining the energy storage system to improve the absorption level of wind and solar energy, reduce the wind and solar power abandonment rates, and enhance the potential of the power system to absorb renewable energy power generation.

[0005] To achieve the above object, according to one aspect of the present invention, a method for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario is provided, the method comprising:

[0006] Obtaining a first objective function and a second objective function of a target comprehensive energy field;

[0007] According to the first objective function and the second objective function, setting a first basic constraint condition, a second basic constraint condition and a load balance constraint condition of the target integrated energy field;

[0008] The first objective function and the second objective function are solved based on the constraint conditions to obtain the configuration parameters of each generator set in the target integrated energy field.

[0009] Furthermore, the first objective function includes a profit objective function, which is expressed according to the following formula:

[0010]

[0011] in, represents the cost of electricity, gas and heat purchases during time period t; represents the electricity, gas and heat sales costs in time period t; represents the startup cost of unit k in time period t; represents the downtime cost of unit k in time period t; represents the marginal cost of all units in time period t; represents the fixed cost of all units in period t; represents the revenue of all loads in period t; It represents the total revenue of peak and frequency regulation in time period t; F represents the compensation cost of reducing the electric load by demand response in time period t; PE represents the fixed cost of all production units; F SE represents the fixed cost of all energy storage units; k represents the collection of different units.

[0012] Furthermore, the second objective function includes a return on investment function:

[0013]

[0014] in, represents the cost of electricity, gas and heat purchases during time period t; represents the electricity, gas and heat sales costs in time period t; represents the startup cost of unit k in time period t; represents the downtime cost of unit k in time period t; represents the marginal cost of the unit in period t; represents the fixed cost of all units in period t; F represents the benefits of all different loads in time period t; SE represents the fixed cost of all energy storage units; k represents a collection of different units.

[0015] Furthermore, the first basic constraint condition includes a generator set output constraint condition, a generator set minimum start and stop time constraint condition, and a generator set ramp rate constraint condition.

[0016] Furthermore, the output constraints of the generator set include:

[0017]

[0018] Among them, P CU,min Indicates the minimum output of the generator set; P CU,max Indicates the maximum output of the generator set; The output of the generator set in time period t.

[0019] Furthermore, the minimum start and stop time constraints of the generator set include:

[0020]

[0021]

[0022] in, Indicates the start and stop status of the generator set in time period t, 0 means stop, 1 means start; Indicates the continuous start time of the generator set before it is shut down in time period t_1; T represents the continuous downtime of the generator set before the start time of time period t_1; CU,on Indicates the minimum continuous start time required by the generator set; T CU,off Indicates the minimum continuous downtime required for the generator set.

[0023] Furthermore, the generator set ramp rate constraints include:

[0024]

[0025] in, Indicates the descent rate of the generator set; Indicates the ramp rate of the generator set; Δt indicates the time interval; Indicates the output of the generator set at time t.

[0026] Furthermore, the second basic constraint condition includes a basic constraint condition of the energy storage device; the basic constraint condition of the energy storage device includes a capacity constraint condition of the energy storage device, a charge and discharge power constraint condition of the energy storage device, and an energy constraint condition of the energy storage device;

[0027] Energy storage device capacity constraints include:

[0028] E min ≤E t ≤E max

[0029] Among them, E min Indicates the minimum energy storage capacity of the energy storage device; E max Indicates the maximum energy storage capacity of the energy storage device; E t represents the total energy of the energy storage device during time period t;

[0030] The charging and discharging energy power constraints of the energy storage device include:

[0031]

[0032]

[0033]

[0034] Among them, P e,min 、P e,max Respectively represent the minimum and maximum charging power of the energy storage device; P d,min 、P d,max Respectively represent the minimum and maximum energy release power of the energy storage device; Respectively represent the charging state and discharging state of the energy storage device in time period t. A value of 1 indicates that it is charging or discharging, and a value of 0 indicates that it is not charging or discharging. Respectively represent the charging power and discharging power of the energy storage device in time period t;

[0035] The energy constraints of the energy storage device include:

[0036]

[0037] E0=E T-1

[0038] Among them, E t Represents the total energy of the energy storage device in time period t; η P Represents the self-damage rate of the energy storage device; η e,P ,η d,P Respectively represent the charging efficiency and discharging efficiency of the energy storage device; E0, E T-1 They respectively represent the initial state and the end state of the energy storage device within the scheduling period.

[0039] Furthermore, load balancing constraints include:

[0040]

[0041] in, Indicates the power purchased from the upper level during period t; Indicates the energy sold to the superior during time period t; Indicates the actual heating load power of the target integrated energy field during time period t; They represent the charging and discharging power of the energy storage device in time period t respectively.

[0042] According to another aspect of the present invention, a device for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario is provided, the device comprising:

[0043] An objective function acquisition module, used to obtain a first objective function and a second objective function of a target comprehensive energy field;

[0044] A constraint condition setting module, configured to set a first basic constraint condition, a second basic constraint condition, and a load balance constraint condition for the target integrated energy field according to the first objective function and the second objective function;

[0045] The configuration parameter calculation module is used to solve the first objective function and the second objective function based on the constraint conditions to obtain the configuration parameters of each generator set in the target integrated energy field.

[0046] In summary, embodiments of the present invention provide a method and apparatus for optimizing wind, solar, load, and storage configuration in an integrated energy scenario. The method comprises: obtaining a first objective function and a second objective function for a target integrated energy field; setting a first basic constraint, a second basic constraint, and a load balance constraint for the target integrated energy field based on the first and second objective functions; and solving the first and second objective functions based on the constraints to obtain configuration parameters for each generator set in the target integrated energy field. The technical solution of embodiments of the present invention, while meeting the diverse load demands of the integrated energy field and aiming to minimize the overall operating cost and carbon emissions of the integrated energy field, coordinates the demands of different load types and integrates an energy storage system to improve the absorption level of wind and solar power, reduce wind and solar curtailment rates, and enhance the power system's potential for absorbing renewable energy generation. This provides a reasonable generator set combination and specific configuration parameters for efficient and low-cost operation of the integrated energy field, while also providing the energy storage system with reasonable configuration parameters and real-time load charge and discharge signals and amounts. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a framework diagram of the integrated energy field;

[0048] Figure 2 This is a flow chart of a method for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario provided by an embodiment of the present invention;

[0049] Figure 3 This is a typical curve of the average daily wind power and photovoltaic output in February for the example park of the present invention;

[0050] Figure 4 This is the average daily forecast curve of electricity, heat, and gas loads in February for the example park of the present invention;

[0051] Figure 5 It is a diagram showing the recommended output of all energy supply devices at each time and the trading status of electrical load;

[0052] Figure 6 It is a schematic diagram of the remaining capacity information of the energy storage device. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present invention.

[0054] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in one or more embodiments of the present invention should have the usual meanings understood by people with ordinary skills in the field to which this disclosure belongs. The "first", "second" and similar words used in one or more embodiments of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0055] The technical solution of the present invention is described in detail below with reference to the accompanying drawings. The embodiment of the present invention provides a method for optimizing the configuration of wind, solar, load and storage in a comprehensive energy scenario. The electric load in the comprehensive energy field involved in the embodiment of the present invention is supplied by the main power grid, wind turbines, photovoltaic output, coal-fired power units and gas turbines. Figure 1 The framework diagram of the integrated energy field is shown in Figure 1 As shown, the gas load is jointly supplied by the upstream gas grid and the power-to-gas device; the heat load is provided by the upstream heat network, electric boilers, coal-fired power units, and gas turbines within the park; and the cooling load participates in park scheduling as a special heat load. The energy system within the park engages in two-way electricity purchase and sales, natural gas purchase and sales, and hydrogen purchase and sales with the upstream power grid and gas grid, enabling flexible energy conversion. The energy storage device coordinates energy storage and release, enabling different loads to participate in scheduling based on demand response. The technical solution of the embodiment of the present invention comprehensively considers multiple objectives in energy management scenarios, such as cost controllability, maximum revenue, and maximum return on investment. By solving historical typical wind and solar power generation curves, typical park demand curves for different load types, and typical free buying and selling price curves for loads, and by setting the physical performance parameter ranges of the generator set and energy storage device, the technical solution of the present invention can provide reasonable generator set parameter configuration and combination forms and reasonable energy storage device parameter configuration and combination forms for the normal operation of the park while meeting these multiple objectives.

[0056] Figure 2 FIG. 4 shows a flow chart of a method for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario provided by an embodiment of the present invention. The method comprises the following steps:

[0057] S202. Obtain the first objective function and the second objective function of the target integrated energy field. The efficient scheduling of wind, solar, load and storage optimization and the configuration of performance parameters of each device in the integrated energy scenario are aimed at increasing park revenue, reducing operating costs, improving investment return rate, and increasing park wind and solar penetration rate. Therefore, the present invention takes maximizing revenue and maximizing investment return rate as multi-objective functions, and provides reasonable generator set parameter configuration and combination form, and reasonable energy storage device parameter configuration and combination form for the normal operation of the park. Among them, the first objective function can include a revenue objective function, and the second objective function can include an investment return rate function.

[0058] The operating costs of a wind, solar, load, and energy storage system primarily include the cost of purchasing electricity from the upper-level power grid, the construction costs of wind and solar installations, and the construction costs of energy storage devices. The operating costs of the park primarily include the cost of purchasing electricity from the upper-level power grid and gas from the gas grid, as well as the marginal and fixed costs of the generator sets, plus the maintenance costs during actual operation and maintenance. The main revenue streams are load revenue and revenue from electricity and gas sales. For power plants, one of their goals is to maximize revenue. In this embodiment of the present invention, the following revenue objective function can be used:

[0059]

[0060] in, represents the cost of electricity, gas and heat purchases during time period t; represents the electricity, gas and heat sales costs in time period t; represents the startup cost of unit k in time period t; represents the downtime cost of unit k in time period t; represents the marginal cost of all units in time period t; represents the fixed cost of all units in period t; represents the revenue of all loads in period t; It represents the total revenue of peak and frequency regulation in time period t; F represents the compensation cost of reducing the electric load by demand response in time period t; PE represents the fixed cost of all production units; F SE represents the fixed cost of all energy storage units; k represents the collection of different units.

[0061] Another optimization goal of the wind-solar-load-storage system is to maximize the return on investment. The corresponding objective function is:

[0062]

[0063] in, represents the electricity purchase cost in period t; represents the electricity sales cost in time period t; represents the startup cost of unit k in time period t; represents the downtime cost of unit k in time period t; represents the marginal cost of the unit in period t; represents the fixed cost of all units in period t; F represents the benefits of all different loads in time period t; SE represents the fixed cost of all energy storage units; k represents a collection of different units.

[0064] S204. Based on the first and second objective functions, set a first basic constraint, a second basic constraint, and a load balance constraint for the target integrated energy field. Before determining the objective functions, consider the basic constraints and load balance constraints of the generator set. During actual operation, the physical performance constraints of the generator set itself must be considered. Therefore, consideration can be given to three aspects: the generator set output constraint, the generator set minimum start / stop time constraint, and the generator set ramp rate constraint.

[0065] The output constraints of the generator set include:

[0066] Among them, P CU,min Indicates the minimum output of the generator set; P CU,max Indicates the maximum output of the generator set; The output of the generator set in time period t.

[0067] The minimum start and stop time constraints of the generator set include:

[0068]

[0069]

[0070] in, Indicates the start and stop status of the generator set in time period t, 0 means stop, 1 means start; Indicates the continuous start time of the generator set before it is shut down in time period t_1; T represents the continuous downtime of the generator set before the start time of time period t_1; CU,on Indicates the minimum continuous start time required by the generator set (in hours); T CU,off Indicates the minimum continuous downtime required by the generator set (in hours).

[0071] The generator set ramp rate constraints include:

[0072]

[0073] in, Indicates the rate of decrease of the generator set (in MW / minute); Indicates the ramp rate of the generator set (in MW / minute); It indicates the output of the generator set at time t; Δt indicates the time interval, which can be set to 15 minutes. Usually for a generator set, 15 minutes is a unit of measurement.

[0074] The second basic constraint condition includes a basic constraint condition of the energy storage device; the basic constraint condition of the energy storage device includes a capacity constraint condition of the energy storage device, a charge and discharge energy power constraint condition of the energy storage device, and an energy constraint condition of the energy storage device;

[0075] Energy storage device capacity constraints include:

[0076] E min ≤E t ≤E max

[0077] Among them, E min Indicates the minimum energy storage capacity of the energy storage device; E max Indicates the maximum energy storage capacity of the energy storage device; E t represents the total energy of the energy storage device during time period t;

[0078] The charging and discharging energy power constraints of the energy storage device include:

[0079]

[0080]

[0081]

[0082] Among them, P e,min 、P e,max Respectively represent the minimum and maximum charging power of the energy storage device; P d,min 、P d,max Respectively represent the minimum and maximum energy release power of the energy storage device; Respectively represent the charging state and discharging state of the energy storage device in time period t. A value of 1 indicates that it is charging or discharging, and a value of 0 indicates that it is not charging or discharging. Respectively represent the charging power and discharging power of the energy storage device in time period t;

[0083] The energy constraints of the energy storage device include:

[0084]

[0085] E0=E T-1

[0086] Among them, E t Represents the total energy of the energy storage device in time period t; η P Represents the self-damage rate of the energy storage device; η e,P ,η d,P Respectively represent the charging efficiency and discharging efficiency of the energy storage device; E0, E T-1 They respectively represent the initial state and the end state of the energy storage device within the scheduling period.

[0087] Load balancing constraints include:

[0088]

[0089] in, Indicates the power purchased from the upper level during time period t (in MW); Indicates the power sold to the superior during time period t (in MW); represents the actual heating load power of the target integrated energy field during time period t (in MW); They represent the charging and discharging power of the energy storage device in time period t respectively.

[0090] S206. Solve the first objective function and the second objective function based on the constraints to obtain the configuration parameters of each generator set in the target integrated energy field. The generator sets involved in the embodiment of the present invention, in addition to wind power, photovoltaic, thermal power and other units, also include gas turbines and other power generation devices. In the optimization configuration method provided by the embodiment of the present invention, the parameters to be optimized are the specific installed capacity of each generator set, that is, all generator sets are optimized with unified parameters, and there is no need to distinguish the specific types of generator sets. Among them, all variables in the first objective function and the second objective function will change with the change of the installed capacity of the generator set, so all variables are intermediate variables, and the decision variable (that is, the variable finally optimized) is the installed capacity of each generator set.

[0091] An embodiment of the present invention further provides a device for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario, the device comprising:

[0092] An objective function acquisition module, used to obtain a first objective function and a second objective function of a target comprehensive energy field;

[0093] A constraint condition setting module, configured to set a first basic constraint condition, a second basic constraint condition, and a load balance constraint condition for the target integrated energy field according to the first objective function and the second objective function;

[0094] The configuration parameter calculation module is used to solve the first objective function and the second objective function based on the constraint conditions to obtain the configuration parameters of each generator set in the target integrated energy field.

[0095] The specific process of each module in the wind-solar-load-storage optimization configuration device under the integrated energy scenario provided by the above embodiment of the present invention to realize its function is the same as the steps of the wind-solar-load-storage optimization configuration method under the integrated energy scenario provided by the above embodiment of the present invention. Therefore, its repeated description will be omitted here.

[0096] The following is an illustration using a specific example.

[0097] The algorithm and rationality of the present invention are verified based on the typical electricity, heat and gas demand of a power plant in a certain park in Shanxi Province in February 2021. The park has built a certain scale of wind power and photovoltaic power generation equipment. Figure 3 The following is a typical curve of the average daily wind power and photovoltaic output of the park in February. The park can provide energy needs of three different loads: electricity, heat, and gas. Figure 4 This is the average daily forecast curve of the park's electricity, heat and gas loads in February.

[0098] This example primarily verifies the optimal installed capacity configuration parameters for each energy supply unit, as well as the optimal capacity and power configuration parameters for each energy storage device, while ensuring a dynamic balance of electricity, gas, and heat loads and clear boundaries for each device's configuration parameters. Table 1 shows the basic parameters and specific boundary constraints for each energy supply unit. Coal-fired unit 1 is the existing unit under construction with an installed capacity of 300 MW, while the remaining units are expansion units whose installed capacities need to be determined by an algorithm based on the target. Table 2 shows the basic parameters and specific boundary constraints for each energy storage device. Battery 1 is the existing energy storage device, while Battery 2 and the thermal storage tank are expansion units for which specific capacity and power information needs to be determined by an algorithm. Furthermore, considering actual market load purchasing conditions, the maximum power purchased and sold at each moment are set to 150 MW, the maximum gas purchased and sold are set to 10,000 cubic meters, and the maximum power purchased and sold are set to 150 MW.

[0099] Table 1 Operating parameters of each energy supply device

[0100]

[0101] Table 2 Energy storage device operating parameters

[0102]

[0103] Based on the characteristics of historical price transaction data, the whole day can be divided into three different time periods according to the level of electricity prices: valley price period, parity period, and peak price period. The valley price period is 23:00-7:00, the parity period is 7:00-8:00 and 11:00-18:00, and the peak price period is 8:00-11:00 and 18:00-23:00. The purchase price of heat load is set at 800 yuan / MWh, and the purchase price of natural gas is 2.5 yuan / m 3 The time-of-use electricity price of electric load is shown in Table 3.

[0104] Table 3 Time-of-use electricity prices

[0105]

[0106] For this example, using the method provided by the embodiments of the present invention, with the goal of maximizing revenue and return on investment, the CPLEX solver can be used to obtain the recommended optimal installed capacity for each energy supply unit, as shown in Table 3, and the optimal capacity and power configuration information for each energy storage device, as shown in Table 4. Table 5 shows that even if the coal-fired power unit is operating at full load, it is still necessary to expand the installed capacity of coal-fired power unit 2 with an installed capacity of 50MW. To meet the thermal and electrical load requirements, two gas turbines with installed capacities of 100MW and 80MW, respectively, and an electric boiler unit with an installed capacity of 100MW are also required. To improve revenue and return on investment, the algorithm also recommends a power-to-gas unit with an installed capacity of 200MW. Table 4 shows that to store load during periods of excess capacity and supplement capacity during periods of insufficient capacity, the algorithm recommends a battery 2 with a capacity of 57MWh and a power of 17MW and a thermal storage tank with a capacity of 76MWh and a power of 76MW.

[0107] Table 5 Recommended installed capacity of each energy supply device

[0108]

[0109] Table 5 Recommended capacity and power of each energy storage device

[0110]

[0111] The recommended output of all energy supply devices at each time and the electricity load trading situation are as follows Figure 5 Take the realization of dynamic balance of electric load as an example: Combined with the time-of-use electricity price and Figure 5The electricity purchase and sales data show that the algorithm recommends purchasing electricity in the valley price period and selling electricity in the peak price period. Because the peak price period may be a period with high demand for both electricity and heat loads, it is not possible to sell electricity loads completely in the high price period. Instead, the balance between different loads and the maximization of benefits should be considered. Figure 5 It can be seen that when all load demands increase from 17:00 to 19:00 in the afternoon, both gas turbines operate at maximum output, and electricity is purchased during this period, and the electric boilers also operate to meet the heat load demand.

[0112] The remaining capacity information of all energy storage devices is as follows: Figure 6 As shown by Figure 6 It is possible to store load during valley price periods and then release load during peak price periods or when load demand is excessive.

[0113] In summary, embodiments of the present invention relate to a method and apparatus for optimizing wind, solar, load, and storage configuration in an integrated energy scenario. The method comprises: obtaining a first objective function and a second objective function for a target integrated energy field; setting a first basic constraint, a second basic constraint, and a load balance constraint for the target integrated energy field based on the first and second objective functions; and solving the first and second objective functions based on the constraints to obtain configuration parameters for each generator set in the target integrated energy field. The technical solution of embodiments of the present invention, while meeting the diverse load demands of the integrated energy field and aiming to minimize the overall operating cost and carbon emissions of the integrated energy field, coordinates the demands of different load types and integrates an energy storage system to improve the absorption level of wind and solar power, reduce wind and solar curtailment rates, and enhance the power system's potential for absorbing renewable energy generation. This provides a reasonable generator set combination and specific configuration parameters for efficient and low-cost operation of the integrated energy field, while also providing the energy storage system with reasonable configuration parameters and real-time load charge and discharge signals and amounts.

[0114] It should be understood that the above-described specific embodiments of the present invention are merely illustrative or illustrative of the principles of the present invention and do not constitute limitations of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the scope of protection of the present invention. In addition, the appended claims are intended to cover all variations and modifications that fall within the scope and metes and bounds of the appended claims, or equivalents thereof.

Claims

1. A method for optimizing wind, solar, load and storage configuration in a comprehensive energy scenario, characterized by: The method comprises: Obtaining a first objective function and a second objective function of a target comprehensive energy field; According to the first objective function and the second objective function, setting a first basic constraint condition, a second basic constraint condition and a load balance constraint condition of the target integrated energy field; The second basic constraint condition includes a basic constraint condition of the energy storage device; the basic constraint condition of the energy storage device includes a capacity constraint condition of the energy storage device, a charge and discharge energy power constraint condition of the energy storage device, and an energy constraint condition of the energy storage device; Energy storage device capacity constraints include: in, Indicates the minimum energy storage capacity of the energy storage device; Indicates the maximum energy storage capacity of the energy storage device; Indicates time period The total energy of the internal energy storage device; The charging and discharging energy power constraints of the energy storage device include: in, 、 Respectively represent the minimum and maximum charging power of the energy storage device; 、 Respectively represent the minimum and maximum energy release power of the energy storage device; 、 Respectively indicate time periods The charging and discharging status of the internal energy storage device. A value of 1 indicates that the device is being charged or discharged, and a value of 0 indicates that the device is not being charged or discharged. 、 Respectively indicate time periods Charging power and discharging power of internal energy storage device; 、 ; The energy constraints of the energy storage device include: in, Indicates time period The total energy of the internal energy storage device; Indicates the self-damage rate of the energy storage device; 、 Respectively represent the charging efficiency and discharging efficiency of the energy storage device; 、 They represent the initial state and the final state of the energy storage device within the scheduling period respectively; Load balancing constraints include: in, Indicates time period Internal purchase of energy from superiors; Indicates time period Selling energy internally to superiors; Indicates time period Actual heating load power of the internal target integrated energy field; 、 Respectively indicate time periods The charging and discharging power of the internal energy storage device; The first objective function and the second objective function are solved based on the constraint conditions to obtain the configuration parameters of each generator set in the target integrated energy field.

2. The method according to claim 1, characterized in that The first objective function includes the profit objective function, which is expressed according to the following formula: in, Indicates time period The cost of purchasing electricity, gas and heat within the country; Indicates time period Electricity, gas and heat sales fees within the company; Indicates time period Internal unit device startup costs; Indicates time period Internal unit device downtime costs; Indicates time period The marginal cost of all units within the Indicates time period Fixed costs of all units within the facility; Indicates time period The benefits of all loads within; Indicates time period Total benefits of internal peak and frequency regulation; Indicates time period Internal demand response can reduce the compensation cost of electric load; represents the fixed cost of all production units; represents the fixed cost of all energy storage units; Represents a collection of different unit devices.

3. The method according to claim 1, characterized in that The second objective function includes the return on investment function: in, Indicates time period The cost of purchasing electricity, gas and heat within the country; Indicates time period Electricity, gas and heat sales fees within the company; Indicates time period Internal unit device startup costs; Indicates time period Internal unit device downtime costs; Indicates time period marginal cost of internal unit installations; Indicates time period Fixed costs of all units within the facility; Indicates time period The benefits of all loads within the different represents the fixed cost of all energy storage devices; Represents a collection of different unit devices.

4. The method according to claim 1, wherein The first basic constraint condition includes a generator set output constraint condition, a generator set minimum start and stop time constraint condition, and a generator set ramp rate constraint condition.

5. The method according to claim 4, characterized in that The output constraints of the generator set include: in, Indicates the minimum output of the generator set; Indicates the maximum output of the generator set; :The generator set is installed in the period of effort.

6. The method according to claim 4, characterized in that The minimum start and stop time constraints of the generator set include: in, Indicates the generator set is in the period Start and stop status, 0 means stop, 1 means start; Indicates the generator set is in the period Continuous power-on time before shutdown; Indicates the generator set is in the period Continuous downtime before the restart time; Indicates the minimum continuous start time required by the generator set; Indicates the minimum continuous downtime required for the generator set.

7. The method according to claim 4, characterized in that The generator set ramp rate constraints include: in, Indicates the descent rate of the generator set; Indicates the ramp rate of the generator set; Indicates a time interval; Indicates that the generator set is The output size at each moment.

8. A wind, solar, load and storage optimization configuration device in a comprehensive energy scenario, characterized by: The device comprises: An objective function acquisition module, used to obtain a first objective function and a second objective function of a target comprehensive energy field; a constraint setting module, configured to set a first basic constraint, a second basic constraint, and a load balance constraint for the target integrated energy field based on the first objective function and the second objective function; the second basic constraint includes a basic constraint for the energy storage device; the basic constraint for the energy storage device includes a capacity constraint for the energy storage device, a charge and discharge power constraint for the energy storage device, and an energy constraint for the energy storage device; Energy storage device capacity constraints include: in, Indicates the minimum energy storage capacity of the energy storage device; Indicates the maximum energy storage capacity of the energy storage device; Indicates time period The total energy of the internal energy storage device; The charging and discharging energy power constraints of the energy storage device include: in, 、 Respectively represent the minimum and maximum charging power of the energy storage device; 、 Respectively represent the minimum and maximum energy release power of the energy storage device; 、 Respectively indicate time periods The charging and discharging status of the internal energy storage device. A value of 1 indicates that the device is being charged or discharged, and a value of 0 indicates that the device is not being charged or discharged. 、 Respectively indicate time periods Charging power and discharging power of internal energy storage device; 、 ; The energy constraints of the energy storage device include: in, Indicates time period The total energy of the internal energy storage device; Indicates the self-damage rate of the energy storage device; 、 Respectively represent the charging efficiency and discharging efficiency of the energy storage device; 、 They represent the initial state and the final state of the energy storage device within the scheduling period respectively; Load balancing constraints include: in, Indicates time period Internal purchase of energy from superiors; Indicates time period Selling energy internally to superiors; Indicates time period Actual heating load power of the internal target integrated energy field; 、 Respectively indicate time periods The charging and discharging power of the internal energy storage device; The configuration parameter calculation module is used to solve the first objective function and the second objective function based on the constraint conditions to obtain the configuration parameters of each generator set in the target integrated energy field.

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