New energy external sending and energy storage capacity cumulative configuration method, device, equipment and medium

Abstract

The application provides a new energy external sending energy storage capacity accumulation type configuration method, device, equipment and medium, comprising: obtaining an energy storage capacity initial value input energy storage optimization configuration model to obtain a new energy consumption amount; the energy storage optimization configuration model takes the maximum value of the new energy consumption amount as the target for calculation; inputting the new energy consumption amount into an intermediate variable transfer model to obtain a transfer variable and input the energy storage optimization configuration model and the intermediate variable transfer model for iterative calculation until the calculation requirement of a preset period is completed to determine the new energy utilization rate; the intermediate variable transfer model is used for constraining the energy storage capacity and the unit operation state; after determining that the new energy utilization rate does not meet the index requirement, an energy storage capacity calibration value is obtained, an accumulation value is calculated based on the energy storage capacity calibration value, and the accumulation value is used for iterative calculation again until the new energy utilization rate meets the index requirement, and a target energy storage capacity is output, so that a reasonable energy storage capacity can be optimized and calculated, and the configuration efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of new energy power technology, and in particular to a method, device, equipment and medium for accumulating new energy transmission and storage capacity. Background Technology

[0002] New energy sources are currently the main driving force of the power industry, possessing multiple advantages such as environmental friendliness and renewability. However, these advantages also bring many challenges, such as insufficient controllability, high volatility, and limited regulation capabilities. Effective planning of new energy storage capacity can enable unstable and highly volatile new energy sources to respond quickly and stably to fluctuations in electricity demand, thereby reducing unnecessary risks.

[0003] In existing technologies, a calculation method is constructed to improve the efficiency of energy storage capacity planning for large-scale new energy transmission, so as to ensure that the utilization efficiency of new energy is maximized and the cost of energy storage planning is reduced. This calculation method is usually based on the historical operation data of the power system to predict and plan the capacity.

[0004] However, due to the random fluctuations in new energy sources, in order to ensure that the calculation results are more consistent with the actual situation and obtain more reasonable and effective results, the above method requires data analysis and calculation over a long period of time, resulting in a long solution time and a significant reduction in the efficiency of energy storage planning. Summary of the Invention

[0005] This application provides a method, device, equipment, and medium for cumulative configuration of energy storage capacity for new energy transmission, which solves the problem that existing capacity prediction and planning based on historical power system operation data requires long-term data analysis and calculation, resulting in long solution times and a significant reduction in energy storage planning efficiency.

[0006] In a first aspect, this application provides a method for cumulatively configuring energy storage capacity for new energy transmission, the method comprising:

[0007] The system acquires the initial energy storage capacity, target renewable energy utilization rate, theoretical wind power output, theoretical photovoltaic output, and target power load. It then inputs the initial energy storage capacity and target power load into a pre-constructed energy storage optimization configuration model to obtain the renewable energy consumption for the first cycle. The target power load is the sum of the total unit power, renewable energy output, and charging / discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum renewable energy consumption. The model constrains renewable energy output and grid transmission requirements. The theoretical wind power output limits the upper limit of wind power output in the model, and the theoretical photovoltaic output limits the upper limit of photovoltaic output in the model.

[0008] The renewable energy consumption of the first cycle is input into a pre-constructed intermediate variable transfer model to obtain the transfer variables of the first cycle. The transfer variables of the first cycle are then input into a pre-constructed energy storage optimization configuration model and an intermediate variable transfer model for iterative calculation until the calculation requirements of the preset cycle are met, thereby obtaining multiple renewable energy consumption, actual wind power output, and actual photovoltaic output within the preset cycle. The intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status.

[0009] Based on the multiple new energy consumption, actual wind power output, and actual photovoltaic output, the new energy utilization rate is determined. After determining that the new energy utilization rate does not meet the target new energy utilization rate index, the energy storage capacity calibration value is obtained.

[0010] The sum of the energy storage capacity calibration value and the initial energy storage capacity value is calculated to obtain the cumulative value. Based on the cumulative value, the calculation is performed again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index. The target energy storage capacity is then output. The target energy storage capacity is the cumulative value.

[0011] Optionally, based on the multiple renewable energy consumption volumes, actual wind power output, and actual photovoltaic output, the renewable energy utilization rate is determined, including:

[0012] The sum of multiple renewable energy consumption amounts within the preset period is calculated to obtain the total renewable energy consumption. The sum of multiple actual wind power outputs and actual photovoltaic outputs within the preset period is calculated to obtain the total renewable energy output. The renewable energy utilization rate is calculated based on the total renewable energy consumption amount and the total renewable energy output.

[0013] Optionally, the new energy output includes actual wind power output and actual photovoltaic output; the construction process of the energy storage optimization configuration model includes:

[0014] The new energy power grid is divided into multiple zones, and a first constraint condition is set for the new energy output of each zone; the first constraint condition is that the actual wind power output of each zone is less than or equal to the theoretical wind power output, and the actual photovoltaic output of each zone is less than or equal to the theoretical photovoltaic output.

[0015] The following constraints are set: the second constraint on the output of thermal power units, the third constraint on the operating status of thermal power units, the fourth constraint on the operating status of pumped storage units, the fifth constraint on the power of pumped storage units, the sixth constraint on the storage capacity of pumped storage units, the seventh constraint on the charging and discharging power of lithium batteries, the eighth constraint on the depth of charging and discharging of lithium batteries, and the ninth constraint on the energy storage capacity of lithium batteries, thus forming the constraints for grid transmission requirements.

[0016] Based on the first constraint and the constraint of the power grid transmission requirements, an energy storage optimization configuration model is constructed.

[0017] The second constraint is used to constrain the optimized power of the thermal power unit; the third constraint is used to constrain the start-up and / or shutdown states of multiple units corresponding to the thermal power unit and the time of start-up and / or shutdown of multiple units; the fourth constraint is used to constrain the pumping or discharging state of the pumped storage unit; the fifth constraint is used to constrain the pumping power and discharging power of the pumped storage unit; the sixth constraint is used to constrain the capacity of the pumped storage unit reservoir; the seventh constraint is used to constrain the charging and discharging states of the lithium battery; the eighth constraint is used to constrain the remaining power of the lithium battery; and the ninth constraint is used to constrain the energy storage capacity of the lithium battery.

[0018] Optionally, the formula corresponding to the second constraint is:

[0019]

[0020]

[0021] in, This represents the upper limit of the output of the j-th unit in a thermal power unit; This represents the lower limit of the output of the j-th unit in a thermal power unit; This indicates the operating status of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the output of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the optimized power output of the j-th unit at time t in the s-th cycle of a thermal power unit.

[0022] The formula corresponding to the third constraint is:

[0023]

[0024] and,

[0025]

[0026]

[0027] in, This indicates the operating status of the j-th unit in the s-th cycle at time t, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. This indicates the startup status of the j-th unit in the s-th cycle at time t, where 0 indicates not in startup status and 1 indicates startup status. This indicates the shutdown status of the j-th unit in the s-th cycle at time t, where 0 indicates it is not in a shutdown state and 1 indicates it is in a shutdown state; t+k indicates time t+k, where k is the minimum time step for the unit to start or stop.

[0028] Optionally, the formula corresponding to the fourth constraint is:

[0029]

[0030] in, This indicates the pumping status of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates the water release status of the j-th unit at time t in the s-th cycle of the pumped storage unit.

[0031] The formula corresponding to the fifth constraint is:

[0032]

[0033]

[0034] in, This represents the optimized power of the j-th unit at time t in the s-th cycle of the pumped storage unit. This represents the maximum pumping power of the j-th unit in the pumped storage unit; This represents the minimum pumping power of the j-th unit in a pumped storage unit; This represents the maximum water discharge capacity of the j-th pumped storage unit. This represents the minimum water discharge capacity of the j-th pumped storage unit.

[0035] The formula corresponding to the sixth constraint is:

[0036]

[0037] in, This represents the upper limit of the capacity of the j-th unit in a pumped storage hydroelectric power unit; This indicates the lower limit of the capacity of the j-th unit in a pumped storage system. This represents the initial capacity of the j-th pumped storage unit at time t in the s-th cycle.

[0038] Optionally, the formula corresponding to the seventh constraint is:

[0039]

[0040]

[0041]

[0042] in, This indicates the charging state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not charging and 1 indicates that it is charging. This indicates the discharge state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not in the discharge state and 1 indicates that it is in the discharge state. This represents the maximum charging power of the battery pack at time t; This represents the maximum discharge power of the battery pack at time t; This represents the charging and discharging power of the battery pack at time t in the s-th cycle;

[0043] The formula corresponding to the eighth constraint is:

[0044]

[0045] in, This indicates the minimum remaining charge of the battery pack; This indicates the maximum remaining battery capacity of the battery pack; This represents the remaining charge of the battery pack at time t. and Determined based on the application scenario;

[0046] The formula corresponding to the ninth constraint is:

[0047]

[0048] in, Indicates the energy storage capacity of the battery pack; This indicates the minimum energy storage capacity corresponding to the battery pack; This indicates the maximum energy storage capacity of the battery pack.

[0049] Optionally, the transferred variables include the optimized power of the thermal power unit, the operating status of the thermal power unit, the optimized power of the pumped storage unit, the operating status of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charging and discharging power of the lithium battery, and the initial capacity of the lithium battery; the construction process of the intermediate variable transfer model includes:

[0050] The optimized power of the thermal power unit is set to meet a first preset condition, and the operating state of the thermal power unit is set to meet a second preset condition; the first preset condition is that the optimized power of the thermal power unit in the current cycle is consistent with the optimized power of the thermal power unit output to the next cycle; the second preset condition is that the operating state, shutdown state and start-up state of each unit in the thermal power unit in the current cycle are consistent with the operating state, shutdown state and start-up state output to the next cycle.

[0051] The optimal power of the pumped storage unit is set to meet a third preset condition, the operating state of the pumped storage unit is set to meet a fourth preset condition, and the initial reservoir capacity of the pumped storage unit is set to meet a fifth preset condition; the third preset condition is that the optimal power of the pumped storage unit in the current cycle is consistent with the optimal power output to the pumped storage unit in the next cycle; the fourth preset condition is that the pumping and discharging states of the pumped storage unit in the current cycle are consistent with the pumping and discharging states output to the pumped storage unit in the next cycle; the fifth preset condition is that the initial reservoir capacity of the pumped storage unit in the current cycle is consistent with the initial reservoir capacity output to the pumped storage unit in the next cycle.

[0052] The charging and discharging power of the lithium battery is set to meet a sixth preset condition, and the initial capacity of the lithium battery is set to meet a seventh preset condition; the sixth preset condition is that the charging and discharging power of the lithium battery in the current cycle is consistent with the charging and discharging power of the lithium battery output to the next cycle; the seventh preset condition is that the energy storage capacity of the lithium battery in the current cycle is consistent with the energy storage capacity of the lithium battery output to the next cycle.

[0053] An intermediate variable transfer model is constructed based on the first preset condition, the second preset condition, the third preset condition, the fourth preset condition, the fifth preset condition, the sixth preset condition, and the seventh preset condition.

[0054] Optionally, the method further includes:

[0055] When it is determined that the new energy utilization rate meets the target new energy utilization rate index, the initial value of the energy storage capacity is output.

[0056] Secondly, this application provides a new energy transmission and energy storage capacity accumulation configuration device, the device comprising:

[0057] The acquisition module is used to acquire the initial value of energy storage capacity, the target renewable energy utilization rate index, the theoretical output of wind power, the theoretical output of photovoltaic power, and the target power load. The initial value of energy storage capacity and the target power load are then input into a pre-constructed energy storage optimization configuration model to obtain the renewable energy consumption for the first cycle. The target power load is the sum of the total power of the generating units, the renewable energy output, and the charging and discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum value of renewable energy consumption. The energy storage optimization configuration model is used to constrain renewable energy output and grid transmission requirements. The theoretical output of wind power is used to limit the upper limit of wind power output in the energy storage optimization configuration model; the theoretical output of photovoltaic power is used to limit the upper limit of photovoltaic power output in the energy storage optimization configuration model.

[0058] The input module is used to input the renewable energy consumption of the first period into a pre-constructed intermediate variable transfer model to obtain the transfer variables of the first period. The transfer variables of the first period are then input into a pre-constructed energy storage optimization configuration model and the intermediate variable transfer model for iterative calculation until the calculation requirements of the preset period are met, thereby obtaining multiple renewable energy consumption, actual wind power output, and actual photovoltaic output within the preset period. The intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status.

[0059] The determination module is used to determine the new energy utilization rate based on the multiple new energy consumption, actual wind power output, and actual photovoltaic output. After determining that the new energy utilization rate does not meet the target new energy utilization rate index, the module obtains the energy storage capacity calibration value.

[0060] The accumulation module is used to calculate the sum of the energy storage capacity calibration value and the initial energy storage capacity value to obtain the accumulation value. Based on the accumulation value, it is iteratively calculated again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index, and the target energy storage capacity is output; the target energy storage capacity is the accumulation value.

[0061] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0062] The memory stores computer-executed instructions;

[0063] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0064] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method as described in any one of the first aspects.

[0065] In summary, this application provides a method, apparatus, equipment, and medium for cumulative configuration of energy storage capacity for new energy transmission. It utilizes a pre-constructed energy storage optimization configuration model that includes physical constraints on multiple generating units and an intermediate variable transfer model. Given an initial energy storage capacity, and with the maximum value of new energy consumption as the objective, it verifies hourly whether different energy storage capacities meet the new energy utilization rate requirements, and iteratively calculates the energy storage capacity that meets the given new energy utilization rate index. The intermediate variable transfer model ensures the continuity of operation of multiple generating units across cycles. Thus, this application's method for optimizing energy storage capacity through two model designs not only ensures that the model operation results are more consistent with actual conditions but also optimizes and calculates a more reasonable energy storage capacity, significantly improving the efficiency of planned capacity configuration. Attached Figure Description

[0066] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0067] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0068] Figure 2 A flowchart illustrating a method for cumulative configuration of energy storage capacity for new energy transmission provided in this application embodiment;

[0069] Figure 3 A flowchart illustrating a specific method for accumulating energy storage capacity for new energy transmission provided in this application embodiment;

[0070] Figure 4 A schematic diagram of a new energy transmission and energy storage capacity accumulation configuration device provided in this application embodiment;

[0071] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0072] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0073] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and purpose. For example, "first device" and "second device" are merely used to distinguish different devices and do not limit their order of execution. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0074] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0075] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0076] New energy sources are currently the main driving force of the power industry, possessing multiple advantages such as environmental protection and renewability. However, new energy also brings significant challenges, such as insufficient controllability, high volatility, and limited regulation capabilities. Effective planning of new energy storage capacity can enable unstable and highly volatile new energy sources to respond quickly and stably to fluctuations in electricity demand, reducing unnecessary risks. Therefore, more refined energy storage capacity configuration can reduce the cost of energy storage systems, improve resource utilization, fully realize the potential of renewable energy, and enhance the economic efficiency of the power system.

[0077] However, the configuration and planning of energy storage systems is a complex engineering problem, facing challenges such as numerous influencing factors and large amounts of data. This poses a significant challenge to the system's computing resources, planning efficiency, and effectiveness. Therefore, there is an urgent need to develop an efficient computing method to ensure that the utilization efficiency of new energy sources is maximized and the cost of energy storage planning is reduced.

[0078] One possible implementation involves configuring the energy storage system by constructing a calculation method to improve the efficiency of energy storage capacity planning for large-scale new energy transmission. This calculation method is typically based on historical power system operating data to predict and plan the capacity.

[0079] However, due to the random fluctuations in new energy sources, in order to ensure that the calculation results are more consistent with the actual situation and obtain more reasonable and effective results, the above method requires data analysis and calculation over a long period of time, resulting in a long solution time and a significant reduction in the efficiency of energy storage planning.

[0080] Understandably, long-term data analysis and computation can lead to a significant decrease in the efficiency of model planning.

[0081] To address the aforementioned issues, this application provides a cumulative configuration method for energy storage capacity in new energy transmission projects. This method utilizes a cumulative hourly iterative calculation approach based on energy storage capacity planning efficiency. Specifically, by pre-constructing an energy storage optimization configuration model that includes physical constraints on multiple generating units and an intermediate variable transfer model, given an initial energy storage capacity, and with the maximum value of new energy consumption as the objective, the method hourly verifies whether different energy storage capacities meet the new energy utilization rate requirements. Iterative verification is then performed to calculate the energy storage capacity that meets the given new energy utilization rate index. The intermediate variable transfer model ensures the continuity of operation across multiple generating units across cycles. Thus, this application's method for optimizing energy storage capacity through two model designs not only ensures that the model operation results are more consistent with actual conditions but also optimizes and calculates a more reasonable energy storage capacity, significantly improving the efficiency of planned capacity configuration.

[0082] For example, Figure 1 This is a schematic diagram of an application scenario provided in an embodiment of this application, such as... Figure 1 As shown, this application scenario can be applied to the planning of large-scale renewable energy transmission and energy storage capacity. The application scenario includes: user terminal equipment 101 and data processing system 102. The data processing system 102 is equipped with a pre-built energy storage optimization configuration model and an intermediate variable transfer model. The energy storage optimization configuration model is used to constrain renewable energy output and grid transmission requirements, with the goal of maximizing renewable energy consumption. The intermediate variable transfer model is used to constrain energy storage capacity and unit operating status.

[0083] Specifically, taking the construction of an energy storage optimization configuration model that includes hourly optimization of physical constraints such as thermal power units, pumped storage units, and lithium batteries as an example, the user's terminal device 101 can input the initial value of energy storage capacity and the new energy utilization rate index. Further, after receiving the initial energy storage capacity and the new energy utilization rate index, the data processing system 102 inputs the initial energy storage capacity into the energy storage optimization configuration model and the intermediate variable model to hourly verify whether different lithium battery energy storage capacities meet the new energy utilization rate index. Specifically, by inputting the initial energy storage capacity into the energy storage optimization configuration model, the new energy consumption amount for the first week is obtained, and then the new energy consumption amount for the first week is input into the intermediate variable transfer model. In the model, the transfer variables for the first week are obtained. Then, these transfer variables are input into the energy storage optimization configuration model and the intermediate variable transfer model to obtain the transfer variables for the second week. This process continues iteratively and repeatedly until the annual calculation is completed. Next, it is verified whether the calculated renewable energy utilization rate is less than the renewable energy utilization rate index. If so, a certain amount of energy storage capacity is added, and iterative calculations continue until the calculated renewable energy utilization rate meets the renewable energy utilization rate index, i.e., is greater than or equal to the renewable energy utilization rate index. Finally, the target energy storage capacity that meets the renewable energy utilization rate index is output. This target energy storage capacity is considered the most economical energy storage capacity.

[0084] Among them, the new energy utilization rate indicator is the utilization rate of new energy that meets the application scenarios and user needs, and is used to determine the target energy storage capacity to be output.

[0085] It should be noted that the embodiments of this application do not specifically limit the period for calculating the amount of new energy consumption and the transfer variables each time. It can be one week, two weeks or one month. Optionally, the preset period for iterative calculation can be one year, one quarter or two years, etc. The embodiments of this application do not specifically limit the preset period. The above is just an example.

[0086] Optionally, after the data processing system 102 outputs the target energy storage capacity, it can be sent to the user's terminal device 101 for visualization.

[0087] Optionally, the aforementioned terminal devices can be various electronic devices with a display screen and support web browsing. Terminal devices can also be referred to as terminals, user equipment (UE), mobile stations (MS), mobile terminals (MT), etc. Terminal devices can include mobile phones, smart TVs, wearable devices, smart speakers, smart security devices, smart gateways, tablets, computers with wireless transceiver capabilities, virtual reality (VR) terminal devices, augmented reality (AR) terminal devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, and wireless terminals in smart homes. These terminal devices include, but are not limited to, smartphones, tablets, laptops, and desktop computers.

[0088] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0089] Figure 2 This is a flowchart illustrating a method for cumulative configuration of new energy transmission and energy storage capacity provided in an embodiment of this application. Figure 2 As shown, the execution entity of the new energy transmission and energy storage capacity accumulation configuration method is a data processing system, and the new energy transmission and energy storage capacity accumulation configuration method includes the following steps:

[0090] S201. Obtain the initial value of energy storage capacity, target new energy utilization rate index, theoretical wind power output, theoretical photovoltaic output, and target power load. Input the initial value of energy storage capacity and target power load into the pre-constructed energy storage optimization configuration model to obtain the new energy consumption in the first cycle. The target power load is the sum of the total power of the unit, the new energy output, and the charging and discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum value of new energy consumption. The energy storage optimization configuration model is used to constrain the new energy output and grid transmission requirements. The theoretical wind power output is used to limit the upper limit of wind power output in the energy storage optimization configuration model. The theoretical photovoltaic output is used to limit the upper limit of photovoltaic output in the energy storage optimization configuration model.

[0091] In this embodiment of the application, the objective function aims to maximize the absorption of new energy sources, and the corresponding formula is:

[0092]

[0093]

[0094] in, Represent the objective function; This represents the total grid-connected power of new energy sources in each cycle, i.e., the total power of the power grid. This represents the new energy output of the nth partition at time t in the sth period; t takes values ​​from 1 to 168, which corresponds to one week; the period refers to one week, or it can refer to other predefined periods, and this application does not specifically limit it.

[0095] It should be noted that zoning refers to dividing the power grid into multiple regions according to predefined rules; the predefined rules may refer to different regional locations, different electricity demands, etc., and this application embodiment does not specifically limit this.

[0096] In this step, the data processing system can obtain the initial value of the energy storage capacity input manually. , And determine the new energy utilization rate targets that need to be achieved. This serves as a condition for determining whether the process should continue in a loop calculation; whereby the new energy utilization rate index is set using the following formula, we have:

[0097]

[0098] This represents the total renewable energy consumption of the base's energy storage system, which is the sum of renewable energy output. This represents the theoretical new energy output of the nth partition at time t in the s-th period; This indicates the set new energy utilization rate indicator.

[0099] Furthermore, the theoretical wind power output input by the user is obtained. This serves as the upper limit for wind power output per hour in the energy storage optimization configuration model; and it also provides the theoretical photovoltaic output input by the user.

[0100] ,

[0101] The theoretical output of photovoltaic power serves as the upper limit of the hourly photovoltaic output in the energy storage optimization configuration model; furthermore, the target power load also needs to be set. As the hourly load required in the energy storage optimization configuration model, the above data is further input into the energy storage optimization configuration model, and the data of the first cycle is simulated and calculated using a computer to ensure that the output of each unit is within the constraint range, and the renewable energy consumption of the first cycle is calculated; the formula corresponding to the target power load is:

[0102]

[0103] in, This represents the total power of the units in the nth partition at time t of the sth period, which is the sum of the total power of all conventional units; This represents the target power load of the nth partition at time t in the s-th period; This represents the charging and discharging power of the nth partition at time t in the s-th period.

[0104] It should be noted that all conventional units can refer to thermal power units, pumped storage units, and units using lithium batteries.

[0105] Optionally, considering the power transmission between zones, the power load balancing must be done on a zone-by-zone basis. The balancing equation is given by the following formula:

[0106]

[0107] in, Let represent the transmission capacity, i.e., the transmission power, of the i-th transmission line in the n-th partition and the s-th period; while the transmission capacity constraint between regions is expressed by the following formula:

[0108]

[0109] This represents the lower limit of the transmission power of the i-th transmission line; This represents the upper limit of the transmission power of the i-th transmission line; This represents the transmission power of the i-th transmission line. When transmitting power to the outside, it is considered a load, and when transmitting power inward, it is considered a generator.

[0110] Therefore, the energy storage optimization configuration model must satisfy the load curve constraint, that is, the power generated by the clean energy base + the grid-connected power = the channel load curve; where the grid-connected power is a positive number; the grid-connected power is the transmission power transmitted between multiple zones.

[0111] S202. Input the renewable energy consumption of the first cycle into the pre-constructed intermediate variable transfer model to obtain the transfer variables of the first cycle. Then, input the transfer variables of the first cycle into the pre-constructed energy storage optimization configuration model and the intermediate variable transfer model for iterative calculation until the calculation requirements of the preset cycle are completed, and obtain multiple renewable energy consumption, actual wind power output and actual photovoltaic output within the preset cycle. The intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status.

[0112] In this embodiment, the transmitted variables include the optimized power of the thermal power unit, the operating status of the thermal power unit, the optimized power of the pumped storage unit, the operating status of the pumped storage unit, the initial reservoir capacity of the pumped storage unit, the charging and discharging power of the lithium battery, and the initial capacity of the lithium battery; the optimized power can refer to the power that can be adjusted and optimized relative to the actual transmission power; the operating status can include the shutdown state, the running state, the non-starting state, the starting state, the shutdown state, and the shutdown state.

[0113] The preset period is a pre-set time period used to calculate the amount of new energy consumption to meet the needs of the scenario. This application embodiment does not limit the specific value corresponding to the preset period, such as one year; the first period can refer to a week, and the first week, or it can refer to the first period of a preset time period, such as the first month, etc. This application embodiment does not specifically limit this.

[0114] In this step, the amount of new energy consumption in the first cycle is input into the pre-constructed intermediate variable transfer model. The computer is used to extract data variables such as the operating status and energy storage capacity that need to be transferred. By transferring the variables, the continuity of the unit's operation throughout the year is ensured. Correspondingly, the transferred variables can also be stored for output.

[0115] Furthermore, the stored transfer variables are input into the energy storage optimization configuration model. Combined with the previously known parameter constraints, namely the theoretical output of wind power, the theoretical output of photovoltaic power, and the target power load, the computer is used to repeatedly perform S201-S202 iterative calculations until the calculation requirements of the preset cycle are completed, such as the data simulation calculation requirements for the whole year. In this way, data such as the amount of new energy consumption, the actual output of wind power, and the actual output of photovoltaic power for each cycle of the year are obtained.

[0116] S203. Based on the multiple new energy consumption, actual wind power output, and actual photovoltaic output, determine the new energy utilization rate. After determining that the new energy utilization rate does not meet the target new energy utilization rate index, obtain the energy storage capacity calibration value.

[0117] In this embodiment of the application, the energy storage capacity calibration value is a certain amount of energy storage capacity. The specific value corresponding to the energy storage capacity calibration value is preset in advance, and this embodiment of the application does not make specific limitations on it.

[0118] In this step, based on the renewable energy consumption for each cycle throughout the year, the annual renewable energy consumption is calculated. Simultaneously, based on the actual wind power output and actual photovoltaic power output for the year, the total theoretical renewable energy output for the year is calculated. Furthermore, based on the total annual renewable energy consumption and the total theoretical renewable energy output for the year, the annual renewable energy utilization rate, i.e., the renewable energy utilization rate, is calculated. , This is the utilization rate of new energy sources calculated iteratively hourly.

[0119] Furthermore, the utilization rate of new energy sources needs to be verified, that is, whether the utilization rate of new energy sources meets the set target utilization rate indicators. If the conditions are not met, that is Then obtain the energy storage capacity calibration value. .

[0120] S204. Calculate the sum of the energy storage capacity calibration value and the initial energy storage capacity value to obtain the cumulative value. Based on the cumulative value, perform iterative calculation again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index, and output the target energy storage capacity; the target energy storage capacity is the cumulative value.

[0121] In this step, the currently planned energy storage capacity will be... Add a certain amount of energy storage capacity calibration value to the existing value. The accumulated value is obtained, that is For example, when a certain amount of energy storage capacity calibration value is added for the first time, the cumulative value is the sum of the energy storage capacity calibration value and the initial energy storage capacity value, i.e. Furthermore, The newly set energy storage capacity is input again into S201, and the iterative verification process from S201 to S202 is repeated until the condition is met. This means that the obtained new energy utilization rate meets the target new energy utilization rate index, and then the target energy storage capacity, that is, the final planned energy storage capacity, is output and the cycle ends.

[0122] Therefore, this application embodiment aims to maximize the absorption of new energy sources and performs hourly simulation and iterative verification of the energy storage configuration capacity. This can yield the target energy storage capacity that meets the given utilization rate of new energy sources, greatly improving the efficiency of planning and making the energy storage capacity configuration plan more reasonable.

[0123] Optionally, based on the multiple renewable energy consumption volumes, actual wind power output, and actual photovoltaic output, the renewable energy utilization rate is determined, including:

[0124] The sum of multiple renewable energy consumption amounts within the preset period is calculated to obtain the total renewable energy consumption. The sum of multiple actual wind power outputs and actual photovoltaic outputs within the preset period is calculated to obtain the total renewable energy output. The renewable energy utilization rate is calculated based on the total renewable energy consumption amount and the total renewable energy output.

[0125] In this step, the sum of multiple renewable energy consumption amounts within a preset period is calculated, and the formula corresponding to the total renewable energy consumption amount is as follows:

[0126]

[0127] in, This represents the total amount of new energy consumption. Further, by calculating the sum of the actual output of wind power and photovoltaic power over a preset period, the formula corresponding to the total new energy output is obtained as follows:

[0128]

[0129]

[0130] in, This represents the total output of new energy sources. This represents the actual renewable energy output of the nth partition at time t in the s-th period. This represents the actual wind power output at time t in the nth partition of the s-th period; This represents the actual photovoltaic output at time t in the nth partition during the sth period.

[0131] Furthermore, based on the total amount of new energy consumption and the total output of new energy, the formula corresponding to the new energy utilization rate is calculated as follows:

[0132]

[0133] Therefore, the embodiments of this application can calculate the utilization rate of new energy sources iteratively on an hourly basis, making the calculation results more consistent with the actual situation and thus improving the accuracy of the calculation.

[0134] Optionally, the new energy output includes actual wind power output and actual photovoltaic output; the construction process of the energy storage optimization configuration model includes:

[0135] The new energy power grid is divided into multiple zones, and a first constraint condition is set for the new energy output of each zone; the first constraint condition is that the actual wind power output of each zone is less than or equal to the theoretical wind power output, and the actual photovoltaic output of each zone is less than or equal to the theoretical photovoltaic output.

[0136] The following constraints are set: the second constraint on the output of thermal power units, the third constraint on the operating status of thermal power units, the fourth constraint on the operating status of pumped storage units, the fifth constraint on the power of pumped storage units, the sixth constraint on the storage capacity of pumped storage units, the seventh constraint on the charging and discharging power of lithium batteries, the eighth constraint on the depth of charging and discharging of lithium batteries, and the ninth constraint on the energy storage capacity of lithium batteries, thus forming the constraints for grid transmission requirements.

[0137] Based on the first constraint and the constraint of the power grid transmission requirements, an energy storage optimization configuration model is constructed.

[0138] The second constraint is used to constrain the optimized power of the thermal power unit; the third constraint is used to constrain the start-up and / or shutdown states of multiple units corresponding to the thermal power unit and the time of start-up and / or shutdown of multiple units; the fourth constraint is used to constrain the pumping or discharging state of the pumped storage unit; the fifth constraint is used to constrain the pumping power and discharging power of the pumped storage unit; the sixth constraint is used to constrain the capacity of the pumped storage unit reservoir; the seventh constraint is used to constrain the charging and discharging states of the lithium battery; the eighth constraint is used to constrain the remaining power of the lithium battery; and the ninth constraint is used to constrain the energy storage capacity of the lithium battery.

[0139] In this embodiment of the application, based on the known premise that the actual output of new energy is less than or equal to the theoretical output curve, the output of new energy is constrained, i.e.

[0140]

[0141]

[0142] in, This represents the actual wind power output at time t in the nth partition of the s-th period; This represents the actual photovoltaic output of the nth partition at time t in the s-th period; This represents the theoretical wind power output of the nth partition at time t in the s-th period; This represents the theoretical photovoltaic output at time t in the nth partition of the s-th period. It should be noted that the theoretical output of wind power and the theoretical output of photovoltaic power are known values, and the specific values ​​corresponding to them are not limited in the embodiments of this application.

[0143] In this step, the output of thermal power units is constrained, that is, the optimized power of thermal power units is constrained; this is done using the specific expression for the total power of conventional units: The expression for optimizing power can be derived as follows: Furthermore, constraints are imposed on the upper and lower limits of the optimized power, which correspond to the second constraint condition.

[0144] Optionally, the formula corresponding to the second constraint is:

[0145]

[0146]

[0147] in, This represents the upper limit of the output of the j-th unit in a thermal power unit; This represents the lower limit of the output of the j-th unit in a thermal power unit; This indicates the operating status of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the output of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the optimized power of the j-th unit at time t in the s-th cycle of a thermal power unit.

[0148] The logic for the start-up and shutdown status of thermal power units and the minimum start-up and shutdown time of thermal power units are constrained, which corresponds to the third constraint condition; the formula for the third constraint condition is:

[0149]

[0150] and,

[0151]

[0152]

[0153] in, This indicates the operating status of the j-th unit in the s-th cycle at time t, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. This indicates the startup status of the j-th unit in the s-th cycle at time t, where 0 indicates not in startup status and 1 indicates startup status. This indicates the shutdown status of the j-th unit in the s-th cycle at time t, where 0 indicates not in shutdown status and 1 indicates in shutdown status; t+k indicates time t+k, where k is the minimum time step for unit startup or shutdown, and k is a preset value. In this application embodiment, the specific value corresponding to k is not limited.

[0154] Therefore, by constraining the optimized power of thermal power units, the start-up and / or stop states of multiple units corresponding to the thermal power units, and the time of multiple units in the start-up and / or stop states, the energy storage optimization configuration model can better optimize the energy storage capacity and make the planning more reasonable, so as to achieve the desired effect.

[0155] Furthermore, in order to meet the power grid transmission requirements, this application also needs to impose constraints on the pumped storage units, namely, on the pumping or releasing state of the pumped storage units, the pumping power and releasing power of the pumped storage units, and the capacity of the pumped storage unit reservoir.

[0156] Specifically, the pumping or releasing state of the pumped storage unit is constrained, that is, the logical state of pumping and releasing water is constrained, which corresponds to the fourth constraint condition.

[0157] Optionally, the formula corresponding to the fourth constraint is:

[0158]

[0159] in, This indicates the pumping status of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates the water release status of the j-th unit at time t in the s-th cycle of the pumped storage unit.

[0160] The pumping power and discharge power of the pumped storage unit are constrained, which corresponds to the fifth constraint condition.

[0161] Optionally, the formula corresponding to the fifth constraint is:

[0162]

[0163]

[0164] in, This represents the optimized power of the j-th unit at time t in the s-th cycle of the pumped storage unit. This represents the maximum pumping power of the j-th unit in the pumped storage unit; This represents the minimum pumping power of the j-th unit in a pumped storage unit; This represents the maximum water discharge capacity of the j-th pumped storage unit. This represents the minimum water discharge capacity of the j-th pumped storage unit.

[0165] It should be noted that the maximum pumping power, minimum pumping power, maximum discharge power, and minimum discharge power are preset values ​​that conform to the actual application scenario, and the specific values ​​corresponding to them are not limited in the embodiments of this application.

[0166] The capacity of the pumped storage unit reservoir is constrained, which corresponds to the sixth constraint condition.

[0167] Optionally, the formula corresponding to the sixth constraint is:

[0168]

[0169] in, This represents the upper limit of the capacity of the j-th unit in a pumped storage hydroelectric power unit; This represents the lower limit of the capacity of the j-th pumped storage unit. This represents the initial capacity of the j-th pumped storage unit at time t in the s-th cycle.

[0170] It should be noted that the upper and lower capacity limits are preset values ​​that conform to actual application scenarios, and the specific values ​​corresponding to them are not limited in this application embodiment.

[0171] Therefore, by constraining the pumping and releasing states, pumping power, releasing power, and reservoir capacity of the pumped storage unit, the embodiments of this application can enable the energy storage optimization configuration model to better optimize the energy storage capacity and make the planning more reasonable, so as to achieve the desired effect.

[0172] Furthermore, in order to meet the requirements of power grid transmission, the embodiments of this application also need to impose energy storage constraints on the lithium battery, that is, to constrain the charging state, discharging state, remaining power of the lithium battery, and energy storage capacity of the lithium battery.

[0173] Specifically, constraints are imposed on the charging and discharging states of the lithium battery, that is, on the charging and discharging power of the lithium battery, which corresponds to the seventh constraint condition.

[0174] Optionally, the formula corresponding to the seventh constraint is:

[0175]

[0176]

[0177]

[0178] in, This indicates the charging state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not charging and 1 indicates that it is charging. This indicates the discharge state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not in the discharge state and 1 indicates that it is in the discharge state. This represents the maximum charging power of the battery pack at time t; This represents the maximum discharge power of the battery pack at time t; This represents the charging and discharging power of the battery pack at time t in the s-th cycle.

[0179] It should be noted that the maximum charging power and maximum discharging power are preset values ​​that conform to the actual application scenario, and the specific values ​​corresponding to them are not limited in the embodiments of this application.

[0180] The constraint on the remaining capacity of the lithium battery, that is, the constraint on the depth of charge and discharge of the lithium battery, corresponds to the eighth constraint condition.

[0181] Optionally, the formula corresponding to the eighth constraint is:

[0182]

[0183] in, This indicates the minimum remaining charge of the battery pack; This indicates the maximum remaining battery capacity of the battery pack; This represents the remaining charge of the battery pack at time t. and Depending on the application scenario, the specific numerical values ​​in this application embodiment are not limited.

[0184] The energy storage capacity of lithium batteries is constrained, which corresponds to the ninth constraint condition.

[0185] Optionally, the formula corresponding to the ninth constraint is:

[0186]

[0187] in, Indicates the energy storage capacity of the battery pack; This indicates the minimum energy storage capacity corresponding to the battery pack; This indicates the maximum energy storage capacity of the battery pack.

[0188] It should be noted that the minimum and maximum energy storage capacities are preset values ​​that conform to actual application scenarios, and the specific values ​​corresponding to them are not limited in the embodiments of this application.

[0189] Therefore, by constraining the charging state, discharging state, remaining power, and energy storage capacity of the lithium battery, the embodiments of this application can enable the energy storage optimization configuration model to better optimize the energy storage capacity, calculate a more economical energy storage capacity, and make the planning more reasonable to achieve the desired effect.

[0190] In some embodiments, constraints also need to be placed on the timing of power curtailment, since the total curtailed power equals the theoretical renewable energy output minus the actual renewable energy output, i.e.:

[0191]

[0192] Therefore, the constraint condition for energy storage that is only constrained during the time of power abandonment is:

[0193]

[0194] in, This indicates the total power curtailment of the base's energy storage system.

[0195] In summary, by constructing an energy storage optimization configuration model through the first constraint and the grid transmission requirement constraint, the model's operation can be more consistent with the actual situation, improving the model's feasibility, and the optimized calculation yields a more reasonable energy storage capacity than other algorithms.

[0196] Optionally, the transferred variables include the optimized power of the thermal power unit, the operating status of the thermal power unit, the optimized power of the pumped storage unit, the operating status of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charging and discharging power of the lithium battery, and the initial capacity of the lithium battery; the construction process of the intermediate variable transfer model includes:

[0197] The optimized power of the thermal power unit is set to meet a first preset condition, and the operating state of the thermal power unit is set to meet a second preset condition; the first preset condition is that the optimized power of the thermal power unit in the current cycle is consistent with the optimized power of the thermal power unit output to the next cycle; the second preset condition is that the operating state, shutdown state and start-up state of each unit in the thermal power unit in the current cycle are consistent with the operating state, shutdown state and start-up state output to the next cycle.

[0198] The optimal power of the pumped storage unit is set to meet a third preset condition, the operating state of the pumped storage unit is set to meet a fourth preset condition, and the initial reservoir capacity of the pumped storage unit is set to meet a fifth preset condition; the third preset condition is that the optimal power of the pumped storage unit in the current cycle is consistent with the optimal power output to the pumped storage unit in the next cycle; the fourth preset condition is that the pumping and discharging states of the pumped storage unit in the current cycle are consistent with the pumping and discharging states output to the pumped storage unit in the next cycle; the fifth preset condition is that the initial reservoir capacity of the pumped storage unit in the current cycle is consistent with the initial reservoir capacity output to the pumped storage unit in the next cycle.

[0199] The charging and discharging power of the lithium battery is set to meet a sixth preset condition, and the initial capacity of the lithium battery is set to meet a seventh preset condition; the sixth preset condition is that the charging and discharging power of the lithium battery in the current cycle is consistent with the charging and discharging power of the lithium battery output to the next cycle; the seventh preset condition is that the energy storage capacity of the lithium battery in the current cycle is consistent with the energy storage capacity of the lithium battery output to the next cycle.

[0200] An intermediate variable transfer model is constructed based on the first preset condition, the second preset condition, the third preset condition, the fourth preset condition, the fifth preset condition, the sixth preset condition, and the seventh preset condition.

[0201] In this embodiment of the application, the construction process of the intermediate variable transfer model includes: setting the transfer process for the optimized power of thermal power units, setting the transfer process for the start-up and shutdown states of thermal power units, setting the transfer process for the optimized power of pumped storage units, setting the transfer process for the pumping and discharging logic states of pumped storage units, setting the transfer process for the pumped storage capacity of pumped storage units, setting the transfer process for the charging and discharging power of lithium batteries, and setting the transfer process for the energy storage capacity of lithium batteries.

[0202] Specifically, due to the limitations imposed by ramp-up constraints on thermal power units—meaning that the output of thermal power units cannot change drastically within a certain period—to ensure the continuity of unit operation, the optimized power output of the thermal power units in the current cycle can be stored and output to the next cycle for consideration and calculation in the next cycle.

[0203]

[0204] in, This represents the optimized power output of the thermal power unit from the previous cycle to the optimized power of the j-th unit at time t in the current cycle, and it is stored for later retrieval.

[0205] Due to the physical characteristics of the unit and the constraints of energy consumption and operating costs, thermal power units cannot be frequently started and stopped during operation. Therefore, a certain time interval is required between two start-up and shutdown operations of the same unit, so the constraint of the minimum start-up and shutdown time of thermal power units needs to be considered.

[0206] In some embodiments, the operating status of the thermal power unit in the previous cycle is output to the current cycle by passing variables, for consideration and calculation in the next cycle, that is:

[0207]

[0208] in, This indicates the operating status of the j-th unit at time t in the (s+1)-th cycle, which is the operating status of the j-th unit at time t in the next cycle. This indicates the startup status of the j-th unit at time t in the (s+1)-th cycle, which is the startup status of the j-th unit at time t in the next cycle. This indicates the shutdown status of the j-th unit at time t in the (s+1)-th cycle, which is the shutdown status of the j-th unit at time t in the next cycle.

[0209] Since the transfer function of pumped storage is related to the reservoir capacity, the reservoir capacity at the moment before the last moment of the previous cycle (e.g., if the last moment of cycle s is 168, then the moment before the last moment of cycle s is 165). Furthermore, the output at the moment before the last moment of cycle s minus the output at the last moment equals the remaining reservoir capacity at the last moment of cycle s. The remaining reservoir capacity at the last moment of cycle s equals the reservoir capacity at the beginning of cycle s+1. To ensure the continuity of unit operation, the optimized power generated by the pumped storage units in the previous cycle can be stored and output to the current cycle for retrieval and calculation.

[0210]

[0211] in, This represents the optimized power of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates that the optimized power output of the j-th pumped storage unit at time t in the previous cycle is transferred to the current cycle. Correspondingly, This represents the optimized power output of the j-th unit at time t in the next cycle, and it is stored for later retrieval.

[0212] Because pumped storage units are constrained by their physical characteristics, energy consumption, and operating costs during operation, they cannot be frequently started and stopped. Therefore, a certain time interval is required between two start-up and shutdown operations of the same unit, so the minimum start-up and shutdown time constraint of pumped storage units needs to be considered.

[0213] In some embodiments, the operating status of the pumped storage unit from the previous cycle is output to the current cycle by passing variables, for consideration and calculation in the next cycle, i.e.:

[0214]

[0215]

[0216] in, This indicates the pumping status of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates that the pumping status output of the j-th pumped storage unit at time t in the previous cycle is transmitted to the current cycle. Correspondingly, This indicates the pumping status of the j-th unit at time t in the next cycle, and stores it for later retrieval. This indicates the water release status of the j-th unit in the s-th cycle at time t. This indicates that the water discharge status of the j-th pumped storage unit at time t in the previous cycle is output to the current cycle. Correspondingly, This indicates the water discharge status of the j-th unit at time t in the next cycle, and stores it for later retrieval.

[0217] Furthermore, the process for transferring pumped storage capacity includes:

[0218]

[0219] in, Let represent the initial capacity of the j-th pumped storage unit at time t in the s-th cycle. This indicates that the initial reservoir capacity output from the pumped storage units in the previous cycle is transferred to the current cycle. This indicates the water discharge status of the j-th unit at time t in the next cycle, and stores it for later retrieval.

[0220] Furthermore, the process for transferring the charging and discharging power of the lithium battery is configured, including:

[0221]

[0222] in, This represents the charging and discharging power at time t in the s-th period, i.e., the energy storage output. This indicates that the charging and discharging power output from the previous cycle is transferred to the current cycle. This represents the charging and discharging power output at time t in the next cycle, and it is stored for later retrieval.

[0223] Furthermore, the process for transferring the energy storage capacity of lithium batteries includes:

[0224]

[0225] This represents the energy storage capacity of the lithium battery at time t in the s-th cycle; This indicates that the energy storage capacity from the previous cycle is output to the current cycle, and correspondingly, This indicates the energy storage capacity at time t in the next cycle, and it is stored for later retrieval.

[0226] Therefore, this application embodiment constructs an intermediate variable transfer model by setting the optimized power of thermal power units, the start-up and shutdown status of thermal power units, the optimized power of pumped storage units, the pumping and discharging logic status of pumped storage units, the pumped storage capacity of pumped storage units, the charging and discharging power of lithium batteries, and the energy storage capacity transfer process of lithium batteries. This ensures the continuity of cross-cycle operation of thermal power units, pumped storage units, and units in lithium batteries, and improves the stability of operation.

[0227] Optionally, the method further includes:

[0228] When it is determined that the new energy utilization rate meets the target new energy utilization rate index, the initial value of the energy storage capacity is output.

[0229] In this step, if the calculated annual renewable energy utilization rate is... The conditions are met, that is Then the currently planned energy storage capacity will be output as the final planned energy storage capacity, thus completing the optimization process.

[0230] Optionally, after obtaining the final planned energy storage capacity, the energy storage capacity can be visualized for users to view or apply.

[0231] Therefore, the embodiments of this application can be configured to obtain a reasonable energy storage capacity, thereby improving the efficiency of capacity planning and configuration.

[0232] In conjunction with the above embodiments, Figure 3 A flowchart illustrating a specific method for cumulative configuration of new energy transmission and energy storage capacity provided in this application embodiment is shown below. Figure 3 As shown, the method for cumulatively configuring new energy transmission and storage capacity includes the following steps:

[0233] Step 1: Build an energy storage optimization configuration model (Model 1) and an intermediate variable transfer model (Model 2) in advance, and set the initial values ​​of energy storage (initial values ​​of energy storage capacity), parameter constraints, and determine the new energy utilization rate index (target new energy utilization rate index).

[0234] Step 2: Input the above data into Model 1, and use a computer to simulate and calculate the data for the first cycle to ensure that the output of each unit is within the constraints and calculate the amount of new energy consumption for the first cycle.

[0235] Step 3: Input the data from Step 2 into Model 2, use a computer to extract the data variables such as the operating status and energy storage capacity that need to be transferred, and ensure the continuity of the unit's operation throughout the year by transferring the variables, and store the transferred variables for output.

[0236] Step 4: Input the data stored in Step 3 into Model 1, and combine it with the pre-set parameter constraints. Use a computer to repeat Step 2 and Step 3 iterative calculations until the data simulation calculation for the whole year is completed, and obtain the amount of new energy consumption for each cycle of the year.

[0237] Step 5: Based on the renewable energy consumption for each cycle throughout the year obtained in Step 4, calculate the total renewable energy consumption for the year and the total theoretical renewable energy output for the year. By calculating the ratio of the total renewable energy consumption for the year to the total theoretical renewable energy output for the year, the renewable energy utilization rate can be obtained.

[0238] Step 6: Determine whether the new energy utilization rate meets the conditions. If yes, output the final energy storage capacity and new energy utilization rate. If not, increase the energy storage capacity by a certain amount (energy storage capacity calibration value), obtain the accumulated value, and input the accumulated value back into Step 2. Repeat the above steps to continue the iterative verification until the conditions are met. The conditions can be set as the new energy utilization rate being greater than or equal to the target new energy utilization rate index.

[0239] Compared with traditional optimization calculation methods, the above-mentioned cumulative configuration method of new energy transmission and energy storage capacity can reduce running time and memory usage. As shown in Table 1, the calculation efficiency and calculation results of traditional optimization calculation methods and the method of this application are compared.

[0240] Table 1

[0241]

[0242] Among them, Example 1 is the traditional optimization calculation method, and Example 2 is the method of this application. As shown in Table 1, under the premise of ensuring optimization quality, the method of this application greatly reduces the running time and memory usage compared with the traditional optimization calculation method, thereby improving the running efficiency and also improving the optimization quality.

[0243] In the foregoing embodiments, the method for cumulative configuration of new energy transmission and energy storage capacity provided in this application has been described. To achieve the functions of the methods provided in the embodiments of this application, the electronic device serving as the execution entity may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0244] For example, Figure 4This application provides a schematic diagram of a new energy transmission and energy storage capacity accumulation configuration device. The device 400 includes: an acquisition module 401, an input module 402, a determination module 403, and an accumulation module 404. The acquisition module 401 acquires the initial value of the energy storage capacity, the target new energy utilization rate index, the theoretical output of wind power, the theoretical output of photovoltaic power, and the target power load. It then inputs the initial value of the energy storage capacity and the target power load into a pre-constructed energy storage optimization configuration model to obtain the new energy consumption amount for the first cycle. The target power load is the sum of the total power of the generating unit, the new energy output, and the charging and discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum value of the new energy consumption amount. The energy storage optimization configuration model is used to constrain the new energy output and grid transmission requirements. The theoretical output of wind power is used to limit the upper limit of wind power output in the energy storage optimization configuration model. The theoretical output of photovoltaic power is used to limit the upper limit of photovoltaic output in the energy storage optimization configuration model.

[0245] The input module 402 is used to input the renewable energy consumption of the first period into a pre-constructed intermediate variable transfer model to obtain the transfer variables of the first period, and input the transfer variables of the first period into a pre-constructed energy storage optimization configuration model and intermediate variable transfer model for iterative calculation until the calculation requirements of the preset period are completed, so as to obtain multiple renewable energy consumption, actual wind power output and actual photovoltaic output within the preset period; the intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status.

[0246] The determining module 403 is used to determine the new energy utilization rate based on the multiple new energy consumption, actual wind power output and actual photovoltaic output, and to obtain the energy storage capacity calibration value after determining that the new energy utilization rate does not meet the target new energy utilization rate index.

[0247] The accumulation module 404 is used to calculate the sum of the energy storage capacity calibration value and the initial energy storage capacity value to obtain the accumulated value, and then iteratively calculates the accumulated value again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index, and outputs the target energy storage capacity; the target energy storage capacity is the accumulated value.

[0248] Optionally, the determining module 403 is specifically used for:

[0249] The sum of multiple renewable energy consumption amounts within the preset period is calculated to obtain the total renewable energy consumption. The sum of multiple actual wind power outputs and actual photovoltaic outputs within the preset period is calculated to obtain the total renewable energy output. The renewable energy utilization rate is calculated based on the total renewable energy consumption amount and the total renewable energy output.

[0250] Optionally, the new energy output includes actual wind power output and actual photovoltaic output; the device 400 further includes a module for constructing an energy storage optimization configuration model; the module for constructing the energy storage optimization configuration model is used for:

[0251] The new energy power grid is divided into multiple zones, and a first constraint condition is set for the new energy output of each zone; the first constraint condition is that the actual wind power output of each zone is less than or equal to the theoretical wind power output, and the actual photovoltaic output of each zone is less than or equal to the theoretical photovoltaic output.

[0252] The following constraints are set: the second constraint on the output of thermal power units, the third constraint on the operating status of thermal power units, the fourth constraint on the operating status of pumped storage units, the fifth constraint on the power of pumped storage units, the sixth constraint on the storage capacity of pumped storage units, the seventh constraint on the charging and discharging power of lithium batteries, the eighth constraint on the depth of charging and discharging of lithium batteries, and the ninth constraint on the energy storage capacity of lithium batteries, thus forming the constraints for grid transmission requirements.

[0253] Based on the first constraint and the constraint of the power grid transmission requirements, an energy storage optimization configuration model is constructed.

[0254] The second constraint is used to constrain the optimized power of the thermal power unit; the third constraint is used to constrain the start-up and / or shutdown states of multiple units corresponding to the thermal power unit and the time of start-up and / or shutdown of multiple units; the fourth constraint is used to constrain the pumping or discharging state of the pumped storage unit; the fifth constraint is used to constrain the pumping power and discharging power of the pumped storage unit; the sixth constraint is used to constrain the capacity of the pumped storage unit reservoir; the seventh constraint is used to constrain the charging and discharging states of the lithium battery; the eighth constraint is used to constrain the remaining power of the lithium battery; and the ninth constraint is used to constrain the energy storage capacity of the lithium battery.

[0255] Optionally, the formula corresponding to the second constraint is:

[0256]

[0257]

[0258] in, This represents the upper limit of the output of the j-th unit in a thermal power unit; This represents the lower limit of the output of the j-th unit in a thermal power unit; This indicates the operating status of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the output of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the optimized power output of the j-th unit at time t in the s-th cycle of a thermal power unit.

[0259] The formula corresponding to the third constraint is:

[0260]

[0261] and,

[0262]

[0263]

[0264] in, This indicates the operating status of the j-th unit in the s-th cycle at time t, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. This indicates the startup status of the j-th unit in the s-th cycle at time t, where 0 indicates not in startup status and 1 indicates startup status. This indicates the shutdown status of the j-th unit in the s-th cycle at time t, where 0 indicates it is not in a shutdown state and 1 indicates it is in a shutdown state; t+k indicates time t+k, where k is the minimum time step for the unit to start or stop.

[0265] Optionally, the formula corresponding to the fourth constraint is:

[0266]

[0267] in, This indicates the pumping status of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates the water release status of the j-th unit at time t in the s-th cycle of the pumped storage unit.

[0268] The formula corresponding to the fifth constraint is:

[0269]

[0270]

[0271] in, This represents the optimized power of the j-th unit at time t in the s-th cycle of the pumped storage unit. This represents the maximum pumping power of the j-th unit in the pumped storage unit; This represents the minimum pumping power of the j-th unit in a pumped storage unit; This represents the maximum water discharge capacity of the j-th pumped storage unit. This represents the minimum water discharge capacity of the j-th pumped storage unit.

[0272] The formula corresponding to the sixth constraint is:

[0273]

[0274] in, This represents the upper limit of the capacity of the j-th unit in a pumped storage hydroelectric power unit; This indicates the lower limit of the capacity of the j-th unit in a pumped storage system. This represents the initial capacity of the j-th pumped storage unit at time t in the s-th cycle.

[0275] Optionally, the formula corresponding to the seventh constraint is:

[0276]

[0277]

[0278]

[0279] in, This indicates the charging state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not charging and 1 indicates that it is charging. This indicates the discharge state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not in the discharge state and 1 indicates that it is in the discharge state. This represents the maximum charging power of the battery pack at time t; This represents the maximum discharge power of the battery pack at time t; This represents the charging and discharging power of the battery pack at time t in the s-th cycle;

[0280] The formula corresponding to the eighth constraint is:

[0281]

[0282] in, This indicates the minimum remaining charge of the battery pack; This indicates the maximum remaining battery capacity of the battery pack; This represents the remaining charge of the battery pack at time t. and Determined based on the application scenario;

[0283] The formula corresponding to the ninth constraint is:

[0284]

[0285] in, Indicates the energy storage capacity of the battery pack; This indicates the minimum energy storage capacity corresponding to the battery pack; This indicates the maximum energy storage capacity of the battery pack.

[0286] Optionally, the transferred variables include the optimized power of the thermal power unit, the operating status of the thermal power unit, the optimized power of the pumped storage unit, the operating status of the pumped storage unit, the initial reservoir capacity of the pumped storage unit, the charging and discharging power of the lithium battery, and the initial capacity of the lithium battery; the device 400 further includes a module for constructing an intermediate variable transfer model; the module for constructing the intermediate variable transfer model is used for:

[0287] The optimized power of the thermal power unit is set to meet a first preset condition, and the operating state of the thermal power unit is set to meet a second preset condition; the first preset condition is that the optimized power of the thermal power unit in the current cycle is consistent with the optimized power of the thermal power unit output to the next cycle; the second preset condition is that the operating state, shutdown state and start-up state of each unit in the thermal power unit in the current cycle are consistent with the operating state, shutdown state and start-up state output to the next cycle.

[0288] The optimal power of the pumped storage unit is set to meet a third preset condition, the operating state of the pumped storage unit is set to meet a fourth preset condition, and the initial reservoir capacity of the pumped storage unit is set to meet a fifth preset condition; the third preset condition is that the optimal power of the pumped storage unit in the current cycle is consistent with the optimal power output to the pumped storage unit in the next cycle; the fourth preset condition is that the pumping and discharging states of the pumped storage unit in the current cycle are consistent with the pumping and discharging states output to the pumped storage unit in the next cycle; the fifth preset condition is that the initial reservoir capacity of the pumped storage unit in the current cycle is consistent with the initial reservoir capacity output to the pumped storage unit in the next cycle.

[0289] The charging and discharging power of the lithium battery is set to meet a sixth preset condition, and the initial capacity of the lithium battery is set to meet a seventh preset condition; the sixth preset condition is that the charging and discharging power of the lithium battery in the current cycle is consistent with the charging and discharging power of the lithium battery output to the next cycle; the seventh preset condition is that the energy storage capacity of the lithium battery in the current cycle is consistent with the energy storage capacity of the lithium battery output to the next cycle.

[0290] An intermediate variable transfer model is constructed based on the first preset condition, the second preset condition, the third preset condition, the fourth preset condition, the fifth preset condition, the sixth preset condition, and the seventh preset condition.

[0291] Optionally, the device 400 further includes an output module; the output module is used for:

[0292] When it is determined that the new energy utilization rate meets the target new energy utilization rate index, the initial value of the energy storage capacity is output.

[0293] The specific implementation principle and effects of the new energy transmission and energy storage capacity accumulation configuration device provided in this application embodiment can be found in the relevant descriptions and effects of the above embodiments, and will not be elaborated further here.

[0294] This application also provides a schematic diagram of the structure of an electronic device. Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 5 As shown, the electronic device may include: a processor 501 and a memory 502 communicatively connected to the processor; the memory 502 stores a computer program; the processor 501 executes the computer program stored in the memory 502, causing the processor 501 to perform the method described in any of the above embodiments.

[0295] The memory 502 and the processor 501 can be connected via bus 503.

[0296] This application also provides a computer-readable storage medium storing computer program execution instructions, which, when executed by a processor, are used to implement the methods described in any of the foregoing embodiments of this application.

[0297] This application also provides a chip for executing instructions, which is used to perform the methods described in any of the foregoing embodiments executed by an electronic device as described in any of the foregoing embodiments of this application.

[0298] This application also provides a computer program product, which includes a computer program that, when executed by a processor, can implement the methods described in any of the foregoing embodiments executed by an electronic device as described in any of the foregoing embodiments of this application.

[0299] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0300] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0301] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0302] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application.

[0303] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0304] The memory may include high-speed random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0305] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0306] The aforementioned storage media can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage media can be any available medium accessible to general-purpose or special-purpose computers.

[0307] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and storage medium can exist as discrete components in an electronic device or host device.

[0308] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0309] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0310] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0311] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0312] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the claims.

Claims

1. A method for cumulatively configuring energy storage capacity for new energy transmission, characterized in that, The method includes: The system acquires the initial energy storage capacity, target renewable energy utilization rate, theoretical wind power output, theoretical photovoltaic output, and target power load. It then inputs the initial energy storage capacity and target power load into a pre-constructed energy storage optimization configuration model to obtain the renewable energy consumption for the first cycle. The target power load is the sum of the total unit power, renewable energy output, and charging / discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum renewable energy consumption. The model constrains renewable energy output and grid transmission requirements. The theoretical wind power output limits the upper limit of wind power output in the model, and the theoretical photovoltaic output limits the upper limit of photovoltaic output in the model. The renewable energy consumption of the first cycle is input into a pre-constructed intermediate variable transfer model to obtain the transfer variables of the first cycle. The transfer variables of the first cycle are then input into a pre-constructed energy storage optimization configuration model and an intermediate variable transfer model for iterative calculation until the calculation requirements of the preset cycle are met, thereby obtaining multiple renewable energy consumption, actual wind power output, and actual photovoltaic output within the preset cycle. The intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status. Based on the multiple new energy consumption, actual wind power output, and actual photovoltaic output, the new energy utilization rate is determined. After determining that the new energy utilization rate does not meet the target new energy utilization rate index, the energy storage capacity calibration value is obtained. The sum of the energy storage capacity calibration value and the initial energy storage capacity value is calculated to obtain the cumulative value. Based on the cumulative value, the calculation is performed again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index. The target energy storage capacity is then output. The target energy storage capacity is the cumulative value.

2. The method according to claim 1, characterized in that, Based on the aforementioned renewable energy consumption, actual wind power output, and actual photovoltaic power output, the renewable energy utilization rate is determined, including: The sum of multiple renewable energy consumption amounts within the preset period is calculated to obtain the total renewable energy consumption. The sum of multiple actual wind power outputs and actual photovoltaic outputs within the preset period is calculated to obtain the total renewable energy output. The renewable energy utilization rate is calculated based on the total renewable energy consumption amount and the total renewable energy output.

3. The method according to claim 1, characterized in that, The new energy output includes the actual output of wind power and the actual output of photovoltaic power; The construction process of the energy storage optimization configuration model includes: The new energy power grid is divided into multiple zones, and a first constraint condition is set for the new energy output of each zone; the first constraint condition is that the actual wind power output of each zone is less than or equal to the theoretical wind power output, and the actual photovoltaic output of each zone is less than or equal to the theoretical photovoltaic output. The following constraints are set: the second constraint on the output of thermal power units, the third constraint on the operating status of thermal power units, the fourth constraint on the operating status of pumped storage units, the fifth constraint on the power of pumped storage units, the sixth constraint on the storage capacity of pumped storage units, the seventh constraint on the charging and discharging power of lithium batteries, the eighth constraint on the depth of charging and discharging of lithium batteries, and the ninth constraint on the energy storage capacity of lithium batteries, thus forming the constraints for grid transmission requirements. Based on the first constraint and the constraint of the power grid transmission requirements, an energy storage optimization configuration model is constructed. The second constraint is used to constrain the optimized power of the thermal power unit; the third constraint is used to constrain the start-up and / or shutdown states of multiple units corresponding to the thermal power unit and the time of start-up and / or shutdown of multiple units; the fourth constraint is used to constrain the pumping or discharging state of the pumped storage unit; the fifth constraint is used to constrain the pumping power and discharging power of the pumped storage unit; the sixth constraint is used to constrain the capacity of the pumped storage unit reservoir; the seventh constraint is used to constrain the charging and discharging states of the lithium battery; the eighth constraint is used to constrain the remaining power of the lithium battery; and the ninth constraint is used to constrain the energy storage capacity of the lithium battery.

4. The method according to claim 3, characterized in that, The formula corresponding to the second constraint is: in, This represents the upper limit of the output of the j-th unit in a thermal power unit; This represents the lower limit of the output of the j-th unit in a thermal power unit; This indicates the operating status of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the output of the j-th unit at time t in the s-th cycle of a thermal power unit; This represents the optimized power output of the j-th unit at time t in the s-th cycle of a thermal power unit. The formula corresponding to the third constraint is: and, in, This indicates the operating status of the j-th unit in the s-th cycle at time t, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. This indicates the startup status of the j-th unit in the s-th cycle at time t, where 0 indicates not in startup status and 1 indicates startup status. This indicates the shutdown status of the j-th unit in the s-th cycle at time t, where 0 indicates it is not in a shutdown state and 1 indicates it is in a shutdown state; t+k indicates time t+k, where k is the minimum time step for the unit to start or stop.

5. The method according to claim 3, characterized in that, The formula corresponding to the fourth constraint is: in, This indicates the pumping status of the j-th unit at time t in the s-th cycle of the pumped storage unit. This indicates the water release status of the j-th unit at time t in the s-th cycle of the pumped storage unit. The formula corresponding to the fifth constraint is: in, This represents the optimized power of the j-th unit at time t in the s-th cycle of the pumped storage unit. This represents the maximum pumping power of the j-th unit in the pumped storage unit; This represents the minimum pumping power of the j-th unit in a pumped storage unit; This represents the maximum water discharge capacity of the j-th pumped storage unit. This represents the minimum water discharge capacity of the j-th pumped storage unit. The formula corresponding to the sixth constraint is: in, This represents the upper limit of the capacity of the j-th unit in a pumped storage hydroelectric power unit; This indicates the lower limit of the capacity of the j-th unit in a pumped storage system. This represents the initial capacity of the j-th pumped storage unit at time t in the s-th cycle.

6. The method according to claim 3, characterized in that, The formula corresponding to the seventh constraint is: in, This indicates the charging state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not charging and 1 indicates that it is charging. This indicates the discharge state of the battery pack at time t in the s-th cycle, where 0 indicates that it is not in the discharge state and 1 indicates that it is in the discharge state. This represents the maximum charging power of the battery pack at time t; This represents the maximum discharge power of the battery pack at time t; This represents the charging and discharging power of the battery pack at time t in the s-th cycle; The formula corresponding to the eighth constraint is: in, This indicates the minimum remaining charge of the battery pack; This indicates the maximum remaining battery capacity of the battery pack; This represents the remaining charge of the battery pack at time t. and Determined based on the application scenario; The formula corresponding to the ninth constraint is: in, Indicates the energy storage capacity of the battery pack; This indicates the minimum energy storage capacity corresponding to the battery pack; This indicates the maximum energy storage capacity of the battery pack.

7. The method according to claim 1, characterized in that, The transmitted variables include the optimized power of the thermal power unit, the operating status of the thermal power unit, the optimized power of the pumped storage unit, the operating status of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charging and discharging power of the lithium battery, and the initial capacity of the lithium battery. The construction process of the intermediate variable transfer model includes: The optimized power of the thermal power unit is set to meet a first preset condition, and the operating state of the thermal power unit is set to meet a second preset condition; the first preset condition is that the optimized power of the thermal power unit in the current cycle is consistent with the optimized power of the thermal power unit output to the next cycle; the second preset condition is that the operating state, shutdown state and start-up state of each unit in the thermal power unit in the current cycle are consistent with the operating state, shutdown state and start-up state output to the next cycle. The optimal power of the pumped storage unit is set to meet a third preset condition, the operating state of the pumped storage unit is set to meet a fourth preset condition, and the initial reservoir capacity of the pumped storage unit is set to meet a fifth preset condition; the third preset condition is that the optimal power of the pumped storage unit in the current cycle is consistent with the optimal power output to the pumped storage unit in the next cycle; the fourth preset condition is that the pumping and discharging states of the pumped storage unit in the current cycle are consistent with the pumping and discharging states output to the pumped storage unit in the next cycle; the fifth preset condition is that the initial reservoir capacity of the pumped storage unit in the current cycle is consistent with the initial reservoir capacity output to the pumped storage unit in the next cycle. The charging and discharging power of the lithium battery is set to meet a sixth preset condition, and the initial capacity of the lithium battery is set to meet a seventh preset condition; the sixth preset condition is that the charging and discharging power of the lithium battery in the current cycle is consistent with the charging and discharging power of the lithium battery output to the next cycle; the seventh preset condition is that the energy storage capacity of the lithium battery in the current cycle is consistent with the energy storage capacity of the lithium battery output to the next cycle. An intermediate variable transfer model is constructed based on the first preset condition, the second preset condition, the third preset condition, the fourth preset condition, the fifth preset condition, the sixth preset condition, and the seventh preset condition.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: When it is determined that the new energy utilization rate meets the target new energy utilization rate index, the initial value of the energy storage capacity is output.

9. A new energy transmission and energy storage capacity accumulation configuration device, characterized in that, The device includes: The acquisition module is used to acquire the initial value of energy storage capacity, the target renewable energy utilization rate index, the theoretical output of wind power, the theoretical output of photovoltaic power, and the target power load. The initial value of energy storage capacity and the target power load are then input into a pre-constructed energy storage optimization configuration model to obtain the renewable energy consumption for the first cycle. The target power load is the sum of the total power of the generating units, the renewable energy output, and the charging and discharging power. The objective function of the energy storage optimization configuration model aims to calculate the maximum value of renewable energy consumption. The energy storage optimization configuration model is used to constrain renewable energy output and grid transmission requirements. The theoretical output of wind power is used to limit the upper limit of wind power output in the energy storage optimization configuration model; the theoretical output of photovoltaic power is used to limit the upper limit of photovoltaic power output in the energy storage optimization configuration model. The input module is used to input the renewable energy consumption of the first period into a pre-constructed intermediate variable transfer model to obtain the transfer variables of the first period. The transfer variables of the first period are then input into a pre-constructed energy storage optimization configuration model and the intermediate variable transfer model for iterative calculation until the calculation requirements of the preset period are met, thereby obtaining multiple renewable energy consumption, actual wind power output, and actual photovoltaic output within the preset period. The intermediate variable transfer model is used to constrain the energy storage capacity and the unit operating status. The determination module is used to determine the new energy utilization rate based on the multiple new energy consumption, actual wind power output, and actual photovoltaic output. After determining that the new energy utilization rate does not meet the target new energy utilization rate index, the module obtains the energy storage capacity calibration value. The accumulation module is used to calculate the sum of the energy storage capacity calibration value and the initial energy storage capacity value to obtain the accumulation value. Based on the accumulation value, it is iteratively calculated again through the pre-constructed energy storage optimization configuration model and intermediate variable transfer model until the obtained new energy utilization rate meets the target new energy utilization rate index, and the target energy storage capacity is output; the target energy storage capacity is the accumulation value.

10. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

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