Capacity configuration optimization method and device of energy storage equipment

Abstract

The embodiment of the invention provides a capacity configuration optimization method and device for energy storage equipment, and the method comprises the steps: taking the minimum resource consumption of the energy storage equipment as a target; combining the resource input amount, the power resource consumption amount and the demand resource consumption amount of the energy storage equipment in the target period to construct a corresponding target function; constructing a first linear constraint condition based on the charging and discharging states, the charging and discharging power and the upper and lower limit values of the charging and discharging power of the energy storage equipment in different time periods in the target period; constructing a second linear constraint condition based on the energy storage charge states of the energy storage equipment in different time periods in the target period and the upper and lower limit values of the electric quantity of the energy storage equipment; constructing a third linear constraint condition based on the upper and lower limit values of the power grid electricity purchasing and selling power and the electricity purchasing and selling state; and determining an energy storage capacity configuration result of the energy storage equipment in the target time period according to the target function, the first linear constraint condition, the second linear constraint condition and the third linear constraint condition.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of new energy technology, and in particular to a method for optimizing the capacity configuration of energy storage devices. Background Technology

[0002] In the current energy system transformation, the widespread application of distributed energy resources and the continuous increase in the proportion of renewable energy have brought unprecedented challenges and opportunities to the power grid. On the one hand, the instability of intermittent energy sources requires the power grid to have higher flexibility and regulation capabilities to maintain real-time balance between power supply and consumption; on the other hand, users have placed higher demands on the quality and reliability of energy services, prompting the power service system to adopt more advanced and efficient management measures to ensure the safe and stable operation of the power grid. Based on this, energy storage devices, due to their unique peak-shaving and valley-filling functions and rapid response characteristics, are widely used.

[0003] Energy storage devices can store excess electricity when there is a power surplus and release it during peak demand periods, thereby smoothing the power load curve and improving grid efficiency. However, selecting the capacity of energy storage devices involves a trade-off of several complex factors. While excessive capacity can enhance responsiveness and reserve margin, it significantly increases initial construction and subsequent operation and maintenance costs. Conversely, insufficient energy storage capacity may fail to adequately absorb excess energy or promptly replenish shortages, thus affecting the overall system performance. Therefore, an effective method is urgently needed to address these issues. Summary of the Invention

[0004] In view of this, embodiments of this specification provide a method for optimizing the capacity configuration of an energy storage device. One or more embodiments of this specification also relate to an energy storage device capacity configuration optimization apparatus, a computing device, a computer-readable storage medium, and a computer program, to address the technical deficiencies existing in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a method for optimizing the capacity configuration of an energy storage device is provided, comprising: With the goal of minimizing the resource consumption of energy storage devices, a corresponding objective function is constructed by combining the resource input, power consumption, and demand consumption of the energy storage devices within the target period. Based on the charging and discharging status, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period, a first linear constraint condition is constructed. Based on the energy storage state of charge of the energy storage device at different times within the target period and the upper and lower limits of the energy storage device's power, a second linear constraint condition is constructed. A third linear constraint condition is constructed based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status. Based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

[0006] Optionally, the capacity configuration optimization method for the energy storage device further includes: Based on the upper and lower limits of the installed capacity, the upper and lower limits of the installed power, and the energy conversion efficiency of the energy storage device, a fourth linear constraint condition is constructed. Based on the power purchased and sold by the energy storage device at different times during the target period, and the maximum demand in different intervals during the target period, a fifth linear constraint condition is constructed. Based on the objective function, the first linear constraint, the second linear constraint, the third linear constraint, the fourth linear constraint, and the fifth linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

[0007] Optionally, the first linear constraint condition is constructed based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period, including: Based on the product of the charging status and the upper and lower limits of the charging power of the energy storage device at different times within the target period, the first linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is constructed. Based on the product of the discharge state and the upper and lower limits of the discharge power of the energy storage device at different times within the target period, a second linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is constructed. Based on the planned maximum installed power of the energy storage device, construct the third linear sub-constraint conditions corresponding to the charging power of the energy storage device at different times within the target period; Based on the planned maximum installed power of the energy storage device, a fourth linear sub-constraint condition is constructed for the discharge power of the energy storage device at different times within the target period. The fifth linear sub-constraint is constructed based on the sum of the charging and discharging states of the energy storage device at different times within the target period. The first linear sub-constraint, the second linear sub-constraint, the third linear sub-constraint, the fourth linear sub-constraint, and the fifth linear sub-constraint together constitute the first linear constraint.

[0008] Optionally, the second linear constraint condition is constructed based on the energy storage device's state of charge at different times within the target period and the upper and lower limits of the energy storage device's power, including: Based on the upper and lower limits of the energy storage device's power, a second linear constraint condition is constructed for the energy storage device's state of charge at any time t within the target period. The energy storage state of charge during time period t is determined by the energy storage state of charge of the energy storage device during time period t-1, the charging and discharging power, charging and discharging efficiency, and rated capacity during time period t.

[0009] Optionally, the construction of the third linear constraint condition based on the upper and lower limits of power purchased and sold by the power grid and the power purchase and sale status includes: Based on the product of the power purchase status of the energy storage device at different times within the target period and the upper and lower limits of the power purchase by the grid, the sixth linear sub-constraint condition corresponding to the power purchase by the energy storage device at different times within the target period is constructed. Based on the product of the electricity sales status of the energy storage device at different times within the target period and the upper and lower limits of the grid electricity sales power, the seventh linear sub-constraint condition corresponding to the electricity sales power of the energy storage device at different times within the target period is constructed. The eighth linear sub-constraint is constructed based on the sum of the electricity purchase and sales status of the energy storage device at different times within the target period. The sixth, seventh, and eighth linear sub-constraints together constitute the third linear constraint.

[0010] Optionally, the capacity configuration optimization method for the energy storage device further includes: The first equation is established based on the grid exchange power and power purchased and sold by the energy storage device at different times during the target period; A second equation is established based on the grid exchange power, load power, charging and discharging power, photovoltaic power, and wind turbine power of the energy storage device at different times during the target period; Based on the first equation and the second equation, a ninth linear sub-constraint condition is constructed. The sixth, seventh, eighth, and ninth linear sub-constraint conditions together constitute the third linear constraint condition.

[0011] Optionally, the capacity configuration optimization method for the energy storage device further includes: The charging and discharging strategy of the energy storage device during the target period is optimized and adjusted based on the energy storage capacity configuration results.

[0012] According to a second aspect of the embodiments of this specification, a capacity configuration optimization device for an energy storage device is provided, comprising: The first construction module is configured to construct a corresponding objective function with the goal of minimizing the resource consumption of the energy storage device, in combination with the resource input, power consumption and demand consumption of the energy storage device in the target period. The second construction module is configured to construct a first linear constraint condition based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times during the target period. The third construction module is configured to construct a second linear constraint condition based on the energy storage state of charge of the energy storage device at different times within the target period and the upper and lower limits of the energy storage device's power. The fourth construction module is configured to construct the third linear constraint condition based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status; The determination module is configured to determine the energy storage capacity configuration result of the energy storage device in the target time period based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint.

[0013] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement any of the steps of the capacity configuration optimization method for the energy storage device.

[0014] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the capacity configuration optimization method for any of the energy storage devices described herein.

[0015] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, it causes the computer to perform the steps of the capacity configuration optimization method for the energy storage device described above.

[0016] One embodiment of this specification aims to minimize the resource consumption of energy storage devices. It constructs a corresponding objective function by combining the resource input, power consumption, and demand consumption of the energy storage devices within a target period. Based on the charging / discharging state, charging / discharging power, and upper and lower limits of the charging / discharging power of the energy storage devices at different times within the target period, a first linear constraint is constructed. Based on the state of charge of the energy storage devices at different times within the target period and the upper and lower limits of the energy storage devices' power capacity, a second linear constraint is constructed. Based on the upper and lower limits of the grid's power purchase and sale and the power purchase and sale state, a third linear constraint is constructed. Based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint, the energy storage capacity configuration result for the energy storage devices in the target period is determined. This approach helps ensure the accuracy of the energy storage capacity configuration result, thereby improving the stability of the energy dispatch process. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a capacity configuration optimization method for an energy storage device according to one embodiment of this specification; Figure 2 This is a schematic diagram of the structure of a capacity configuration optimization device for an energy storage device according to one embodiment of this specification; Figure 3 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0018] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0019] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0021] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0022] State of Charge (SOC): This reflects the remaining capacity of a battery. It is numerically defined as the ratio of the remaining capacity to the battery's total capacity, usually expressed as a percentage. Its value ranges from 0 to 1. When "SOC=0", it means the battery is fully discharged, and when "SOC=1", it means the battery is fully charged.

[0023] The purpose of the embodiments in this specification is to improve the solution efficiency of user-side energy storage capacity configuration optimization. It proposes a single-layer optimization model and adopts a hybrid linear integer programming method to fundamentally solve the multiple challenges faced in the design and operation of current energy storage systems, and achieve a harmonious balance between economic benefits and energy efficiency.

[0024] The mixed-integer linear programming model for energy storage systems aims not only to optimize the capacity planning and configuration of energy storage systems, but also to maximize cost-effectiveness by accurately determining the optimal size and charging / discharging strategy of energy storage devices.

[0025] Furthermore, this model accurately defines the ideal scale of energy storage facilities, avoiding cost waste caused by over-investment, ensuring proper resource allocation, and improving the efficiency and economic benefits of the entire system. It also comprehensively considers energy storage investment costs, grid interaction costs, and electricity supply and demand balance, providing power system operators with a powerful tool to facilitate reliable and economical data-driven decisions in dynamic electricity markets.

[0026] This specification provides a method for optimizing the capacity configuration of an energy storage device. It also relates to an apparatus for optimizing the capacity configuration of an energy storage device, a computing device, a computer-readable storage medium, and a computer program, which will be described in detail in the following embodiments.

[0027] Figure 1 A flowchart is shown of a capacity configuration optimization method for an energy storage device according to an embodiment of this specification, which specifically includes the following steps.

[0028] Step 102: With the goal of minimizing the resource consumption of the energy storage device, construct a corresponding objective function by combining the resource input, power consumption, and demand consumption of the energy storage device within the target period.

[0029] Specifically, the resource consumption of energy storage devices can be defined as the resources required for energy storage devices to store energy.

[0030] The embodiments in this specification aim to minimize the resource consumption of energy storage devices. At least two capacity configuration parameters of the energy storage devices are used as parameters to be optimized. By optimizing at least two configuration parameters, the minimum value of resource consumption is obtained.

[0031] Based on this, the embodiments of this specification take the resource consumption of the energy storage device as the first indicator, and construct an objective function based on the first indicator and at least two configuration parameters.

[0032] In practical applications, energy storage devices can be used to store power. The resource consumption of energy storage devices can be the capital consumption, that is, the total operating cost of energy storage devices.

[0033] Therefore, the objective function constructed based on the first index and at least two configuration parameters in the embodiments of this specification is as follows: (1) in, This refers to the resource input required for energy storage equipment during the target period. This represents the amount of electricity consumed by the energy storage device during the target period. This refers to the required resource consumption of energy storage devices within the target cycle.

[0034] In practical applications, resource input This could be the cost of energy storage investment; or the amount of electricity consumed. This can be the cost of purchasing electricity from the main grid; or the amount of resources consumed. This can be the demand-based electricity charge.

[0035] Resource investment in energy storage equipment The specific expression is as follows: (2) in, The rated power of the energy storage device; Rated capacity of energy storage equipment; The benchmark discount rate; The operating life of energy storage equipment; Cost per unit power of energy storage equipment; This refers to the unit capacity cost of energy storage equipment.

[0036] For the main grid electricity purchase cost of energy storage equipment Specifically, it can be calculated using the following expression: (3) in, This represents the power purchased by the energy storage device from the main grid during the t-th time period; It is the power sold by the energy storage device to the main grid in the t-th time period; It is the electricity purchase price for the t-th time period; Let T be the electricity price for the t-th time period. Each time period t is one hour long, and there are 24 × 365 hours in a year.

[0037] Electricity demand for energy storage devices Specifically, it can be calculated using the following expression: (4) in, This represents the maximum demand in month m. This is the demand electricity price for month m.

[0038] Step 104: Based on the charging and discharging status, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times during the target period, construct the first linear constraint condition.

[0039] Once the objective function is constructed, the corresponding constraints can be determined.

[0040] In one optional implementation, the construction of the first linear constraint condition based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period includes: Based on the product of the charging status and the upper and lower limits of the charging power of the energy storage device at different times within the target period, the first linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is constructed. Based on the product of the discharge state and the upper and lower limits of the discharge power of the energy storage device at different times within the target period, a second linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is constructed. Based on the planned maximum installed power of the energy storage device, construct the third linear sub-constraint conditions corresponding to the charging power of the energy storage device at different times within the target period; Based on the planned minimum installed power of the energy storage device, a fourth linear sub-constraint condition is constructed for the discharge power of the energy storage device at different times within the target period. The fifth linear sub-constraint is constructed based on the sum of the charging and discharging states of the energy storage device at different times within the target period. The first linear sub-constraint, the second linear sub-constraint, the third linear sub-constraint, the fourth linear sub-constraint, and the fifth linear sub-constraint together constitute the first linear constraint.

[0041] In the embodiments of this specification, based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period, the first linear constraint condition (energy storage charging and discharging power constraint condition) is constructed as follows: (5) in, This indicates the charging status of the energy storage device during time period t. A value of 1 indicates that the energy storage device is in a charging state. If the value is 0, then it is NOT, which means that the energy storage device is not in a charging state; This indicates the discharge state of the energy storage device during time period t. If the value is 1, then it is "yes", meaning the energy storage device is in a discharging state. If the value is 0, then it is NOT, which means that the energy storage device is not in a discharging state; This refers to the maximum allowable charging power for energy storage devices, also known as the upper limit of charging power. This refers to the minimum allowable charging power for energy storage devices, also known as the lower limit of charging power. The maximum allowable discharge power of an energy storage device, also known as the upper limit of discharge power; The minimum allowable discharge power of energy storage devices, also known as the lower limit of discharge power; The charging power of the energy storage device during time period t; Let t be the discharge power of the energy storage device during time period t; This represents the planned maximum installed capacity for energy storage equipment.

[0042] The first linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is (5.1), which is based on the product of the charging state and the upper and lower limits of the charging power of the energy storage device at different times within the target period. The second linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is (5.2), which is based on the product of the discharging state and the upper and lower limits of the discharging power of the energy storage device at different times within the target period. The third linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is (5.3), which is based on the planned maximum installed power of the energy storage device. The fourth linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is (5.4), which is based on the sum of the charging state and the discharging state of the energy storage device at different times within the target period. The fifth linear sub-constraint condition is (5.5), which together constitute the first linear constraint condition.

[0043] Step 106: Based on the energy storage state of charge of the energy storage device at different times during the target period and the upper and lower limits of the energy storage device, construct the second linear constraint condition.

[0044] In one optional implementation, the construction of the second linear constraint condition based on the energy storage device's state of charge at different times within the target period and the upper and lower limits of the energy storage device's power capacity includes: Based on the upper and lower limits of the energy storage device's power, a second linear constraint condition is constructed for the energy storage device's state of charge at any time t within the target period. The energy storage state of charge during time period t is determined by the energy storage state of charge of the energy storage device during time period t-1, the charging and discharging power, charging and discharging efficiency, and rated capacity during time period t.

[0045] In the embodiments of this specification, based on the energy storage state of charge of the energy storage device at different times within the target period and the upper and lower limits of the energy storage device's power, the second linear constraint condition (energy storage operation charge constraint condition) is constructed as follows: (6) in, The state of charge of the energy storage device during time period t is the remaining power of the energy storage device during time period t. This is the minimum allowable SOC value, which is also the lower limit of the energy capacity of the energy storage device; This is the maximum allowable SOC, which is also the upper limit of the energy storage device's capacity.

[0046] In the embodiments described in this specification, The energy storage device's state of charge during time period t-1, its charging and discharging power during time period t, its charging and discharging efficiency, and its rated capacity are determined by the following expression: (7) in, The energy storage state of charge for time period t-1; The charging efficiency of energy storage devices; This refers to the discharge efficiency of the energy storage device.

[0047] During charging, the amount of charge multiplied by the charging efficiency indicates that the input power cannot fully charge the battery, as some power is lost. During discharging, the amount of discharge divided by the discharging efficiency indicates that the actual energy loss of the battery is greater than the actual energy output.

[0048] Step 108: Construct a third linear constraint condition based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status.

[0049] In one optional implementation, the construction of the third linear constraint condition based on the upper and lower limits of power purchased and sold by the power grid and the power purchase and sale status includes: Based on the product of the power purchase status of the energy storage device at different times within the target period and the upper and lower limits of the power purchase by the grid, the sixth linear sub-constraint condition corresponding to the power purchase by the energy storage device at different times within the target period is constructed. Based on the product of the electricity sales status of the energy storage device at different times within the target period and the upper and lower limits of the grid electricity sales power, the seventh linear sub-constraint condition corresponding to the electricity sales power of the energy storage device at different times within the target period is constructed. The eighth linear sub-constraint is constructed based on the sum of the electricity purchase and sales status of the energy storage device at different times within the target period. The sixth, seventh, and eighth linear sub-constraints together constitute the third linear constraint.

[0050] Furthermore, the capacity configuration optimization method for the energy storage device also includes: The first equation is established based on the grid exchange power and power purchased and sold by the energy storage device at different times during the target period; A second equation is established based on the grid exchange power, load power, charging and discharging power, photovoltaic power, and wind turbine power of the energy storage device at different times during the target period; Based on the first equation and the second equation, a ninth linear sub-constraint condition is constructed. The sixth, seventh, eighth, and ninth linear sub-constraint conditions together constitute the third linear constraint condition.

[0051] In the embodiments of this specification, the third linear constraint (grid exchange power constraint) constructed based on the upper and lower limits of power purchased and sold by the power grid and the power purchase and sale status is as follows: (8) in, This is the minimum allowable power purchase capacity of the power grid, also known as the lower limit of the power purchase capacity of the power grid. This refers to the maximum allowable power purchase capacity of the power grid, also known as the upper limit of the power purchase capacity of the power grid. This is the minimum allowable power output of the power grid, also known as the lower limit of the power output of the power grid. This is the maximum allowable power output of the power grid, also known as the upper limit of the power output of the power grid. This indicates the electricity purchase status of the energy storage device during time period t, i.e., whether or not electricity is being purchased. If the value is 1, then it is yes, which means that the energy storage device purchases electricity during time period t; If the value is 0, then it is NOT, which means that the energy storage device does not purchase electricity during time period t. This indicates the electricity sales status of the energy storage device during time period t, i.e., whether it is selling electricity. If the value is 1, then it is yes, which means that the energy storage device sells electricity during time period t; If the value is 0, it is NOT, which means that the energy storage device does not sell electricity during time period t.

[0052] The sixth linear sub-constraint condition corresponding to the power purchase status of the energy storage device at different times within the target period and the upper and lower limits of the power purchase capacity of the grid is constructed based on the product of the power purchase status of the energy storage device at different times within the target period, which is (8.1); the seventh linear sub-constraint condition corresponding to the power sales capacity of the energy storage device at different times within the target period is constructed based on the product of the power sales status of the energy storage device at different times within the target period and the upper and lower limits of the power sales capacity of the grid, which is (8.2); and the eighth linear sub-constraint condition constructed based on the sum of the power purchase status and the power sales status of the energy storage device at different times within the target period is (8.3).

[0053] Furthermore, based on the first and second equations, the ninth linear sub-constraint condition is constructed as follows: (9) in, This represents the grid exchange power of the energy storage device during time period t. This represents the power consumption of the energy storage device during time period t. This represents the electricity sales power of the energy storage device during time period t. Let be the load power of the energy storage device during time period t; The photovoltaic power of the energy storage device during time period t; The fan power of the energy storage device during time period t.

[0054] The first equation based on the grid exchange power and power purchased and sold by the energy storage device at different times during the target period is (9.1); the second equation based on the grid exchange power, load power, charging and discharging power, photovoltaic power and wind turbine power of the energy storage device at different times during the target period is (9.2). The first and second equations together constitute the ninth linear sub-constraint condition, and the sixth, seventh, eighth and ninth linear sub-constraint conditions together constitute the third linear constraint condition.

[0055] Step 110: Determine the energy storage capacity configuration result of the energy storage device in the target time period based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint.

[0056] Specifically, after the objective function and all constraints are constructed, the objective function can be solved based on the constraints to obtain the energy storage capacity configuration result of the energy storage device in the target period. The target period can be a future day, month, or year, etc.

[0057] In practical applications, the energy storage capacity configuration of the energy storage device during the target period can be obtained by using gurobi (a new generation of large-scale mathematical programming optimizer) or cplex optimization solver.

[0058] In one optional implementation, the capacity configuration optimization method for the energy storage device further includes: Based on the upper and lower limits of the installed capacity, the upper and lower limits of the installed power, and the energy conversion efficiency of the energy storage device, a fourth linear constraint condition is constructed. Based on the power purchased and sold by the energy storage device at different times during the target period, and the maximum demand in different intervals during the target period, a fifth linear constraint condition is constructed. Based on the objective function, the first linear constraint, the second linear constraint, the third linear constraint, the fourth linear constraint, and the fifth linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

[0059] Specifically, based on the aforementioned first, second, and third linear constraints, to ensure the accuracy of the solution results, this embodiment of the specification can also construct a fourth linear constraint based on the upper and lower limits of the installed capacity and power of the energy storage device, as well as the energy conversion efficiency of the energy storage device. Furthermore, based on the grid power purchase and sale of the energy storage device at different times within the target period, and the maximum demand in different intervals within the target period, a fifth linear constraint can be constructed. The objective function is then solved by combining the first, second, third, fourth, and fifth linear constraints.

[0060] The fourth linear constraint (energy storage power and energy storage capacity constraint) is constructed as follows: (10) in, To plan the minimum installed capacity, that is, the lower limit of the installed capacity of energy storage equipment; To plan the maximum installed capacity, that is, the upper limit of the installed capacity of energy storage equipment; To plan the minimum installed capacity, that is, the lower limit of the installed capacity of energy storage equipment; To plan the maximum installed capacity, that is, the upper limit of the installed capacity of energy storage equipment; Energy storage energy conversion efficiency.

[0061] Furthermore, the fifth linear constraint condition is constructed as follows: (11) The embodiments in this specification aim to minimize the resource consumption of energy storage devices. At least two scheduling parameters of the energy storage devices are used as parameters to be optimized. By optimizing at least two scheduling parameters, the minimum value of resource consumption is obtained.

[0062] In practical applications, a mixed-integer linear programming model (a single-layer optimization model for user-side energy storage capacity configuration) can be established, using the aforementioned objective function and linear constraints as the objective function and constraints of this model. When solving for the objective function, the static parameter, demand price, can be used. ,life cycle Energy storage converter cost Energy storage battery costs Energy storage charging efficiency Energy storage and discharge efficiency Planned maximum installed capacity Planning minimum installed capacity Planned maximum installed capacity Planning minimum installed capacity Maximum allowable power of energy storage charging Minimum allowable power for energy storage charging Maximum allowable energy storage discharge power Minimum allowable energy storage discharge power Minimum allowable power purchase capacity of the power grid Maximum allowable power purchase capacity of the power grid Minimum allowable power sales capacity of the power grid Maximum allowable power output of the power grid SOC minimum allowable value SOC maximum allowable value And historical operating data (load power data for the past year). The parameters are input into the model for processing, and then the model outputs the solution results.

[0063] The model's output data may include: the charging power of each typical daily energy storage device. Discharge power of energy storage devices SOC variation curves of typical daily energy storage devices Power purchase and sale curve of the power grid and Maximum monthly demand over 12 months Optimal installed capacity of energy storage equipment and the optimal installed capacity of energy storage equipment This data can be used as the energy storage capacity configuration result for energy storage devices during the target period.

[0064] In the embodiments of this specification, the single-layer optimization model for energy storage capacity configuration adopts a mixed integer linear programming method, which aims to optimize the capacity planning and configuration of the energy storage system. By accurately determining the optimal scale and charging / discharging strategy of the energy storage device, the best economic benefits and operating efficiency of the energy storage system can be achieved.

[0065] In one optional implementation, the capacity configuration optimization method for the energy storage device further includes: The charging and discharging strategy of the energy storage device during the target period is optimized and adjusted based on the energy storage capacity configuration results.

[0066] Specifically, the aforementioned energy storage capacity configuration results can also be used to optimize and adjust the charging and discharging strategies of energy storage devices during the target period. Specifically, the capacity and power parameters of the energy storage devices during the target period can be configured based on the results, and the charging and discharging amounts at different times corresponding to the configuration results can be directly used as the charging and discharging strategies of the energy storage devices at different times. Alternatively, the determined charging and discharging amounts at different times can be adjusted according to the sudden situations that occur in real time during the charging and discharging process of the energy storage devices, and the adjustment results can be determined as the charging and discharging strategies of the energy storage devices at the corresponding times.

[0067] In the embodiments of this specification, the energy storage device configured according to the energy storage capacity configuration result can not only minimize its operating cost, but also maximize its operating time, while ensuring that the overall operating cost of the energy dispatch system is minimized.

[0068] This specification provides a single-layer optimization model for user-side energy storage capacity configuration. Considering factors such as cost and lifecycle, grid security, and equipment characteristics, a single-layer optimization planning model for energy storage is constructed. By optimizing the charging and discharging strategies of energy storage devices, the model effectively reduces demand charges and electricity purchase costs. Furthermore, by discharging during peak demand periods, energy storage devices help reduce grid load and improve grid stability and reliability. The ability of energy storage devices to respond to grid demand changes and reduce demand charges through demand response also improves algorithm performance. Experimental data shows that in this specification, the model can complete calculations within 9.66 seconds, meeting the performance requirement of no more than 30 seconds, making it suitable for real-time or near-real-time applications. In addition, it improves the accuracy of calculation results. Compared with the case of direct planning calculation using annual data without clustering, the error of the optimized objective function value is (969566-895654) / 969566. 100 = 7.6%, meaning that the model provided in the embodiments of this specification has a calculation accuracy of 92.4%.

[0069] One embodiment of this specification aims to minimize the resource consumption of energy storage devices. It constructs a corresponding objective function by combining the resource input, power consumption, and demand consumption of the energy storage devices within a target period. Based on the charging / discharging state, charging / discharging power, and upper and lower limits of the charging / discharging power of the energy storage devices at different times within the target period, a first linear constraint is constructed. Based on the state of charge of the energy storage devices at different times within the target period and the upper and lower limits of the energy storage devices' power capacity, a second linear constraint is constructed. Based on the upper and lower limits of the grid's power purchase and sale and the power purchase and sale state, a third linear constraint is constructed. Based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint, the energy storage capacity configuration result for the energy storage devices in the target period is determined. This approach helps ensure the accuracy of the energy storage capacity configuration result, thereby improving the stability of the energy dispatch process.

[0070] Corresponding to the above method embodiments, this specification also provides embodiments of a capacity configuration optimization device for energy storage devices. Figure 2 A schematic diagram of a capacity configuration optimization device for an energy storage device according to one embodiment of this specification is shown. Figure 2 As shown, the device includes: The first construction module 202 is configured to construct a corresponding objective function with the goal of minimizing the resource consumption of the energy storage device, in combination with the resource input, power consumption and demand consumption of the energy storage device in the target period. The second construction module 204 is configured to construct a first linear constraint condition based on the charging and discharging state, charging and discharging power and upper and lower limits of charging and discharging power of the energy storage device at different times during the target period. The third construction module 206 is configured to construct a second linear constraint condition based on the energy storage state of charge of the energy storage device at different times within the target period and the upper and lower limits of the energy storage device's power. The fourth construction module 208 is configured to construct the third linear constraint condition based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status; The determination module 210 is configured to determine the energy storage capacity configuration result of the energy storage device in the target time period based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint.

[0071] Optionally, the capacity configuration optimization device for the energy storage device further includes a processing module configured to: Based on the upper and lower limits of the installed capacity, the upper and lower limits of the installed power, and the energy conversion efficiency of the energy storage device, a fourth linear constraint condition is constructed. Based on the power purchased and sold by the energy storage device at different times during the target period, and the maximum demand in different intervals during the target period, a fifth linear constraint condition is constructed. Based on the objective function, the first linear constraint, the second linear constraint, the third linear constraint, the fourth linear constraint, and the fifth linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

[0072] Optionally, the second building module 204 is further configured to: Based on the product of the charging status and the upper and lower limits of the charging power of the energy storage device at different times within the target period, the first linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is constructed. Based on the product of the discharge state and the upper and lower limits of the discharge power of the energy storage device at different times within the target period, a second linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is constructed. Based on the planned maximum installed power of the energy storage device, construct the third linear sub-constraint conditions corresponding to the charging power of the energy storage device at different times within the target period; Based on the planned maximum installed power of the energy storage device, a fourth linear sub-constraint condition is constructed for the discharge power of the energy storage device at different times within the target period. The fifth linear sub-constraint is constructed based on the sum of the charging and discharging states of the energy storage device at different times within the target period. The first linear sub-constraint, the second linear sub-constraint, the third linear sub-constraint, the fourth linear sub-constraint, and the fifth linear sub-constraint together constitute the first linear constraint.

[0073] Optionally, the third building module 206 is further configured to: Based on the upper and lower limits of the energy storage device's power, a second linear constraint condition is constructed for the energy storage device's state of charge at any time t within the target period. The energy storage state of charge during time period t is determined by the energy storage state of charge of the energy storage device during time period t-1, the charging and discharging power, charging and discharging efficiency, and rated capacity during time period t.

[0074] Optionally, the fourth building module 208 is further configured to: Based on the product of the power purchase status of the energy storage device at different times within the target period and the upper and lower limits of the power purchase by the grid, the sixth linear sub-constraint condition corresponding to the power purchase by the energy storage device at different times within the target period is constructed. Based on the product of the electricity sales status of the energy storage device at different times within the target period and the upper and lower limits of the grid electricity sales power, the seventh linear sub-constraint condition corresponding to the electricity sales power of the energy storage device at different times within the target period is constructed. The eighth linear sub-constraint is constructed based on the sum of the electricity purchase and sales status of the energy storage device at different times within the target period. The sixth, seventh, and eighth linear sub-constraints together constitute the third linear constraint.

[0075] Optionally, the processing module is further configured to: The first equation is established based on the grid exchange power and power purchased and sold by the energy storage device at different times during the target period; A second equation is established based on the grid exchange power, load power, charging and discharging power, photovoltaic power, and wind turbine power of the energy storage device at different times during the target period; Based on the first equation and the second equation, a ninth linear sub-constraint condition is constructed. The sixth, seventh, eighth, and ninth linear sub-constraint conditions together constitute the third linear constraint condition.

[0076] Optionally, the processing module is further configured to: The charging and discharging strategy of the energy storage device during the target period is optimized and adjusted based on the energy storage capacity configuration results.

[0077] The above is a schematic scheme of a capacity configuration optimization device for an energy storage device according to this embodiment. It should be noted that the technical solution of this capacity configuration optimization device for an energy storage device belongs to the same concept as the technical solution of the capacity configuration optimization method for an energy storage device described above. For details not described in detail in the technical solution of the capacity configuration optimization device for an energy storage device, please refer to the description of the technical solution of the capacity configuration optimization method for an energy storage device described above.

[0078] Figure 3 A structural block diagram of a computing device 300 according to one embodiment of this specification is shown. The components of the computing device 300 include, but are not limited to, a memory 310 and a processor 320. The processor 320 is connected to the memory 310 via a bus 330, and a database 350 is used to store data.

[0079] The computing device 300 also includes an access device 340, which enables the computing device 300 to communicate via one or more networks 360. Examples of these networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 340 may include one or more of any type of wired or wireless network interface (e.g., a Network Interface Card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) interface, a Wi-MAX interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and so on.

[0080] In one embodiment of this specification, the aforementioned components of the computing device 300 and Figure 3 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 3 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0081] The computing device 300 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or PCs. The computing device 300 can also be a mobile or stationary server.

[0082] The processor 320 is used to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the capacity configuration optimization method for the energy storage device described above.

[0083] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the capacity configuration optimization method for energy storage devices described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the capacity configuration optimization method for energy storage devices described above.

[0084] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the capacity configuration optimization method for the energy storage device described above.

[0085] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium belongs to the same concept as the technical solution of the capacity configuration optimization method of the energy storage device described above. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the capacity configuration optimization method of the energy storage device described above.

[0086] An embodiment of this specification also provides a computer program, wherein when the computer program is executed in a computer, it causes the computer to perform the steps of the capacity configuration optimization method for the energy storage device described above.

[0087] The above is an illustrative example of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the above-described energy storage device capacity configuration optimization method belong to the same concept. Details not described in detail in the computer program's technical solution can be found in the description of the above-described energy storage device capacity configuration optimization method.

[0088] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0089] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0090] 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 the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0091] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0092] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A method for optimizing the capacity configuration of an energy storage device, comprising: With the goal of minimizing the resource consumption of energy storage devices, a corresponding objective function is constructed by combining the resource input, power consumption, and demand consumption of the energy storage devices within the target period. Based on the charging and discharging status, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period, a first linear constraint condition is constructed. Based on the upper and lower limits of the energy storage device's power, a second linear constraint condition is constructed for the energy storage device's state of charge at different times within the target period. The energy storage state of charge at different times t is determined by the energy storage state of charge of the energy storage device at time t-1, the charging and discharging power, charging and discharging efficiency, and rated capacity at time t. A third linear constraint condition is constructed based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status. Based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

2. The capacity configuration optimization method for energy storage devices according to claim 1 further includes: Based on the upper and lower limits of the installed capacity, the upper and lower limits of the installed power, and the energy conversion efficiency of the energy storage device, a fourth linear constraint condition is constructed. Based on the power purchased and sold by the energy storage device at different times during the target period, and the maximum demand in different intervals during the target period, a fifth linear constraint condition is constructed. Based on the objective function, the first linear constraint, the second linear constraint, the third linear constraint, the fourth linear constraint, and the fifth linear constraint, the energy storage capacity configuration result of the energy storage device during the target time period is determined.

3. The capacity configuration optimization method for energy storage devices according to claim 1 or 2, wherein constructing a first linear constraint condition based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times within the target period includes: Based on the product of the charging status and the upper and lower limits of the charging power of the energy storage device at different times within the target period, the first linear sub-constraint condition corresponding to the charging power of the energy storage device at different times within the target period is constructed. Based on the product of the discharge state and the upper and lower limits of the discharge power of the energy storage device at different times within the target period, a second linear sub-constraint condition corresponding to the discharge power of the energy storage device at different times within the target period is constructed. Based on the planned maximum installed power of the energy storage device, construct the third linear sub-constraint conditions corresponding to the charging power of the energy storage device at different times within the target period; Based on the planned maximum installed power of the energy storage device, a fourth linear sub-constraint condition is constructed for the discharge power of the energy storage device at different times within the target period. The fifth linear sub-constraint is constructed based on the sum of the charging and discharging states of the energy storage device at different times within the target period. The first linear sub-constraint, the second linear sub-constraint, the third linear sub-constraint, the fourth linear sub-constraint, and the fifth linear sub-constraint together constitute the first linear constraint.

4. The capacity configuration optimization method for energy storage devices according to claim 1 or 2, wherein the construction of the third linear constraint condition based on the upper and lower limits of power purchased and sold from the power grid and the power purchase and sale status includes: Based on the product of the power purchase status of the energy storage device at different times within the target period and the upper and lower limits of the power purchase by the grid, the sixth linear sub-constraint condition corresponding to the power purchase by the energy storage device at different times within the target period is constructed. Based on the product of the electricity sales status of the energy storage device at different times within the target period and the upper and lower limits of the grid electricity sales power, the seventh linear sub-constraint condition corresponding to the electricity sales power of the energy storage device at different times within the target period is constructed. The eighth linear sub-constraint is constructed based on the sum of the electricity purchase and sales status of the energy storage device at different times within the target period. The sixth, seventh, and eighth linear sub-constraints together constitute the third linear constraint.

5. The capacity configuration optimization method for energy storage devices according to claim 4 further includes: The first equation is established based on the grid exchange power and power purchased and sold by the energy storage device at different times during the target period; A second equation is established based on the grid exchange power, load power, charging and discharging power, photovoltaic power, and wind turbine power of the energy storage device at different times during the target period; Based on the first equation and the second equation, a ninth linear sub-constraint condition is constructed. The sixth, seventh, eighth, and ninth linear sub-constraint conditions together constitute the third linear constraint condition.

6. The capacity configuration optimization method for energy storage devices according to claim 1, wherein... The charging and discharging strategy of the energy storage device during the target period is optimized and adjusted based on the energy storage capacity configuration results.

7. A capacity configuration optimization device for an energy storage device, comprising: The first construction module is configured to construct a corresponding objective function with the goal of minimizing the resource consumption of the energy storage device, in combination with the resource input, power consumption and demand consumption of the energy storage device in the target period. The second construction module is configured to construct a first linear constraint condition based on the charging and discharging state, charging and discharging power, and upper and lower limits of charging and discharging power of the energy storage device at different times during the target period. The third construction module is configured to construct a second linear constraint condition corresponding to the energy storage state of charge of the energy storage device at different time periods within the target period, based on the upper and lower limits of the energy storage device's power. The energy storage state of charge at different time periods t is determined by the energy storage state of charge of the energy storage device at time period t-1, the charging and discharging power, charging and discharging efficiency, and rated capacity at time period t. The fourth construction module is configured to construct the third linear constraint condition based on the upper and lower limits of the power purchased and sold by the power grid and the power purchase and sale status; The determination module is configured to determine the energy storage capacity configuration result of the energy storage device in the target time period based on the objective function, the first linear constraint, the second linear constraint, and the third linear constraint.

8. A computing device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the capacity configuration optimization method of the energy storage device according to any one of claims 1 to 6.

9. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the capacity configuration optimization method for the energy storage device according to any one of claims 1 to 6.

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