Data processing method, system and storage medium for control system

Abstract

The present application provides a data processing method, system and storage medium for a control system, wherein the data processing method for a control system comprises: determining the ideal energy supply parameters of each energy supply system according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period. The present application can uniformly allocate energy storage devices and uniformly dispatch electricity according to the load of each energy supply system, thereby improving the phenomenon of energy waste and uneven distribution of energy storage devices, thereby ensuring the smooth operation of the power system.

Description

Technical Field

[0001] The present application relates to the technical field of data processing systems and methods, and in particular to a data processing method, system and storage medium for a control system. Background Art

[0002] The emergence of energy storage technology can meet the variable load of the power system, reduce the cost of power generation, stabilize electricity prices, etc. At present, the application of energy storage technology is basically that some energy supply systems in the power system (for example, some power plants) have energy storage devices and then perform storage control, and then use real-time prices to arbitrage to gain profits. In this case, it will lead to defects such as uneven distribution of energy storage devices and energy waste, which is not conducive to the development and smooth operation of the entire power system.

[0003] Therefore, how to uniformly allocate energy storage devices and uniformly dispatch electricity according to the load of each energy supply system in the power system has become a technical problem that needs to be urgently solved in the industry. Summary of the invention

[0004] In view of the shortcomings of the related technologies mentioned above, the purpose of the present application is to provide a data processing method, system and storage medium for a control system, which are used to solve the technical problems of how to uniformly allocate energy storage devices and uniformly dispatch electricity according to the load of each energy supply system.

[0005] To achieve the above-mentioned purpose and other related purposes, the first aspect of the present application provides a data processing method for a control system, wherein the control system is communicatively connected to multiple energy supply systems; wherein at least some of the energy supply systems are coupled to each other for energy transmission, and each of the energy supply systems supplies energy to its energy-consuming objects; within each time interval, the energy supply parameters of each of the energy supply systems satisfy the following constraints: the difference between the energy production of each of the energy supply systems and the storage / release energy of each of the energy supply systems, and the estimated energy demand of the energy-consuming objects of each of the energy supply systems is equivalent to the sum of the directional power flows transmitted between each of the energy supply systems and other energy supply systems coupled to each of the energy supply systems; the sum of the configuration capacities of the energy storage devices in each of the energy supply systems satisfies the total configuration capacity; the data processing method for a control system comprises: determining the ideal energy supply parameters of each of the energy supply systems based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each of the energy supply systems in each time interval in a unit energy supply period.

[0006] In certain embodiments of the first aspect of the present application, the energy supply parameters include: the energy production of each energy supply system in each time interval in a unit energy supply period, the storage / release energy of the energy storage device in each energy supply system in each time interval in the unit energy supply period, and one or more of the configuration capacity of the energy storage device in each energy supply system.

[0007] In certain embodiments of the first aspect of the present application, the ideal energy supply parameter is an energy supply parameter that optimizes the optimization target within a unit energy supply period.

[0008] In certain embodiments of the first aspect of the present application, the optimization target includes the total production capacity cost of multiple energy supply systems; the ideal energy supply parameters of each energy supply system are determined based on the preset total configuration capacity and the estimated energy demand of the energy-using objects of each energy supply system in each time interval in the unit energy supply period, including: based on the preset total configuration capacity and the estimated energy demand of the energy-using objects of each energy supply system in each time interval in the unit energy supply period, the energy supply parameters that minimize the total production capacity cost of the multiple energy supply systems in the unit energy supply period are taken as the ideal energy supply parameters; wherein the production capacity cost of each energy supply system in each time interval satisfies a preset functional relationship with the production capacity of each energy supply system.

[0009] In certain embodiments of the first aspect of the present application, the preset functional relationship is a quadratic functional relationship.

[0010] In certain embodiments of the first aspect of the present application, the data processing method for controlling the system further includes: determining the marginal price of energy supplied by each energy supply system in each time interval in a unit energy supply period based on the coefficients in the preset functional relationship and the ideal output of each energy supply system in each time interval.

[0011] In certain embodiments of the first aspect of the present application, the data processing method for controlling the system further includes: determining the impact of each energy-consuming object on the production capacity cost of its energy supply system within a unit period based on the estimated energy demand of each energy-consuming object in each time interval in a unit energy supply period and the marginal price of energy supplied by the energy supply system.

[0012] In certain embodiments of the first aspect of the present application, each energy supply system sets the capacity of the energy storage device in accordance with an ideal configuration capacity of the energy storage device in each energy supply system determined by the control system.

[0013] In certain embodiments of the first aspect of the present application, each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production capacity of each energy supply system and the ideal energy storage / release energy of each energy supply system determined by the control system.

[0014] In certain embodiments of the first aspect of the present application, the estimated energy demand is obtained based on historical data of the energy demand.

[0015] In certain embodiments of the first aspect of the present application, the data processing method for controlling the system further includes: determining whether the ideal energy supply parameters meet the actual energy demand based on the actual energy demand of the energy-consuming objects in each energy supply system within each time interval in the unit energy supply period; if met, each energy supply system continues to produce energy, store energy, release energy, and supply energy based on the ideal energy production capacity of each energy supply system and the ideal storage / release energy of each energy supply system.

[0016] To achieve the above-mentioned purpose and other related purposes, the second aspect of the present application provides a data processing system for a control system, wherein the control system is communicatively connected to multiple energy supply systems; wherein at least some of the energy supply systems are coupled to each other for energy transmission, and each of the energy supply systems supplies energy to its energy-consuming objects; within each time interval, the energy supply parameters of each of the energy supply systems are configured to satisfy the following constraints: the difference between the energy production of each of the energy supply systems and the storage / release energy of each of the energy supply systems, and the estimated energy demand of the energy-consuming objects of each of the energy supply systems is equivalent to the sum of the directional power flows transmitted between each of the energy supply systems and other energy supply systems coupled to each of the energy supply systems; the sum of the configuration capacities of the energy storage devices in each of the energy supply systems satisfies the total configuration capacity; the data processing system for the control system comprises: an ideal energy supply parameter determination module, which is used to determine the ideal energy supply parameters of each of the energy supply systems based on a preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each of the energy supply systems in each time interval in a unit energy supply period.

[0017] In certain embodiments of the second aspect of the present application, the energy supply parameters include: the energy production of each energy supply system in each time interval in a unit energy supply period, the storage / release energy of the energy storage device in each energy supply system in each time interval in the unit energy supply period, and one or more of the configuration capacity of the energy storage device in each energy supply system.

[0018] In certain embodiments of the second aspect of the present application, the ideal energy supply parameter is an energy supply parameter that optimizes the optimization target within a unit energy supply period.

[0019] In certain embodiments of the second aspect of the present application, the optimization target includes the total production capacity cost of multiple energy supply systems; the ideal energy supply parameters of each energy supply system are determined based on the preset total configuration capacity and the estimated energy demand of the energy users of each energy supply system in each time interval in the unit energy supply period, including: the ideal energy supply parameter determination module takes the energy supply parameters that minimize the total production capacity cost of the multiple energy supply systems in a unit energy supply period as the ideal energy supply parameters based on the preset total configuration capacity and the estimated energy demand of the energy users of each energy supply system in each time interval in the unit energy supply period; wherein the production capacity cost of each energy supply system in each time interval satisfies a preset functional relationship with the production capacity of each energy supply system.

[0020] In certain embodiments of the second aspect of the present application, the preset functional relationship is a quadratic functional relationship.

[0021] In certain embodiments of the second aspect of the present application, the data processing system for controlling the system also includes: a marginal price determination module, which is used to determine the marginal price of energy supplied by each energy supply system in each time interval in a unit energy supply period based on the coefficients in the preset functional relationship and the ideal output of each energy supply system in each time interval.

[0022] In certain embodiments of the second aspect of the present application, the data processing system for controlling the system further includes: an impact determination module for determining the impact of each of the energy-consuming objects on the production capacity cost of its energy supply system within a unit period based on the estimated energy demand of each of the energy-consuming objects in each time interval in a unit energy supply period and the marginal price of energy supplied by the energy supply system.

[0023] In certain embodiments of the second aspect of the present application, each energy supply system sets the capacity of the energy storage device in accordance with the ideal configuration capacity of the energy storage device in each energy supply system determined by the control system.

[0024] In certain embodiments of the second aspect of the present application, each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production capacity of each energy supply system and the ideal energy storage / release energy of each energy supply system determined by the control system.

[0025] In certain embodiments of the second aspect of the present application, the predicted energy demand is obtained based on historical data of the energy demand.

[0026] In certain embodiments of the second aspect of the present application, the data processing system for controlling the system further includes: a verification module for determining whether the ideal energy supply parameters meet the actual energy demand based on the actual energy demand of the energy-consuming objects in each energy supply system within each time interval in the unit energy supply period; if met, each energy supply system continues to produce energy, store energy, release energy, and supply energy based on the ideal energy production capacity of each energy supply system and the ideal storage / release energy of each energy supply system.

[0027] To achieve the above-mentioned purpose and other related purposes, the third aspect of the present application provides a control system, including: a communication device for communicating with multiple energy supply systems; a storage device for storing at least one program; and a processing device for calling the at least one program to execute a data processing method for a control system as described in any one of the first aspects of the present application.

[0028] To achieve the above-mentioned purpose and other related purposes, the fourth aspect of the present application provides an energy system, including: multiple energy supply systems; a control system as described in the third aspect of the present application, used to communicate with the multiple energy supply systems, and to determine the ideal energy supply parameters of each of the energy supply systems; wherein each of the energy supply systems is used to perform production capacity, energy storage, energy release, energy supply, and capacity setting of the energy storage device according to the ideal energy supply parameters determined by the control system.

[0029] To achieve the above-mentioned purpose and other related purposes, the fifth aspect of the present application provides a computer-readable storage medium storing at least one program, which, when called, executes and implements the data processing method for a control system as described in any one of the first aspects of the present application.

[0030] In summary, the data processing method, system and storage medium for controlling the system disclosed in the present application determine the ideal energy supply parameters of each energy supply system according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period. The present application can realize the unified allocation of energy storage devices and the unified dispatch of electricity according to the load of each energy supply system, which improves the utilization rate of energy and improves the phenomenon of energy waste on the one hand, and improves the phenomenon of uneven distribution of energy storage devices on the other hand, thereby ensuring the smooth operation of the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The specific features of the invention involved in this application are shown in the attached claims. The features and advantages of the invention involved in this application can be better understood by referring to the exemplary embodiments and drawings described in detail below. A brief description of the drawings is as follows:

[0032] Figure 1 Shown is a schematic structural diagram of an energy system of the present application in one embodiment.

[0033] Figure 2 Shown is a schematic structural diagram of an energy supply system of the present application in one embodiment.

[0034] Figure 3 Shown is a schematic diagram of the structure of a control system of the present application in one embodiment.

[0035] Figure 4 Shown is a schematic diagram of a data processing system for controlling a system according to an embodiment of the present application.

[0036] Figure 5 Shown is a schematic diagram of a data processing system for controlling a system according to another embodiment of the present application.

[0037] Figure 6Shown is a schematic diagram of a data processing system for a control system according to another embodiment of the present application.

[0038] Figure 7 Shown is a schematic diagram of a data processing system for a control system according to yet another embodiment of the present application. DETAILED DESCRIPTION

[0039] The following is an explanation of the implementation of the present application by means of specific embodiments. People familiar with the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification.

[0040] In the following description, reference is made to the accompanying drawings, which describe several embodiments of the present application. It should be understood that other embodiments may also be used, and that changes in module or unit composition, electrical and operational aspects may be made without departing from the spirit and scope of the present disclosure. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present application is limited only by the claims of the published patents. The terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0041] As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless there is an indication to the contrary in the context. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, steps, operations, elements, components, projects, kinds, and / or groups, but do not exclude the presence, occurrence or addition of one or more other features, steps, operations, elements, components, projects, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B or C" or "A, B and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C". Exceptions to this definition will only occur when the combination of elements, functions, steps or operations is inherently mutually exclusive in some way.

[0042] The main structure of the power system includes power plants, substations, transmission / distribution lines, and load centers. The power plants include but are not limited to hydropower plants, thermal power plants, and nuclear power plants. Depending on the type of energy, the types of power systems include but are not limited to: power grids based on traditional fuel power generation, microgrids based on new energy power generation, etc. The new energy includes but is not limited to: one or more of coal, natural gas, wind energy, hydropower, photovoltaics, biomass energy, ocean energy, and other forms. The power system also needs to include a control system to measure, regulate, control, protect, communicate, and dispatch the production process of electric energy.

[0043] In the power system, the production and supply of electric energy should be balanced. Existing technologies usually obtain load forecasts for a period of time in the future based on the user's load, and then dispatch electricity according to the forecast results. The emergence of energy storage technology can enhance the flexibility of power dispatch. However, at present, it is basically that some energy supply systems in the power system (such as some power plants) have energy storage devices and only consider their own costs to control storage, and then use real-time prices for arbitrage to make profits for themselves. In this case, it will lead to defects such as uneven distribution of energy storage devices and energy waste, which is not conducive to the development and smooth operation of the country's entire power system.

[0044] Therefore, how to uniformly allocate energy storage devices and uniformly dispatch electricity according to the load of each energy supply system has become a technical problem that needs to be urgently solved in the industry.

[0045] Based on this, the solution of this application realizes the unified allocation of energy storage devices and the unified dispatch of electricity to prevent some energy supply systems from using energy storage devices for arbitrage to gain benefits. On the one hand, it improves the utilization rate of energy and improves the phenomenon of energy waste. On the other hand, it improves the phenomenon of uneven distribution of energy storage devices, thereby ensuring the smooth operation of the entire power system.

[0046] See also Figure 1 , Figure 1 The schematic diagram of the structure of the energy system of the present application in one embodiment is shown as follows: Figure 1 As shown, the energy system includes multiple energy supply systems 200 and a control system 100. The energy system is exemplified by the power system mentioned above.

[0047] The control system 100 is used to communicate with multiple energy supply systems 200 and to determine the ideal energy supply parameters of each of the energy supply systems. In one embodiment, the control system 100 determines the ideal energy supply parameters of each of the energy supply systems based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each of the energy supply systems in each time interval in the unit energy supply period. In one embodiment, the control system 100 sends the ideal energy supply parameters to each of the energy supply systems 200 through its communication device so that each of the energy supply systems 200 can determine its corresponding ideal energy supply parameters. Among them, the specific description of the ideal energy supply parameters and the determination method thereof will be described in detail later.

[0048] The control system 100 aims to improve the social welfare of the entire energy system and is independent of each energy supply system 200. In this way, the control system 100 does not favor any energy supply system 200 in the energy system, thereby improving the uneven distribution of energy storage devices, energy waste, etc. For example, the control system 100 takes the total production capacity cost of the entire energy system as the optimization target, and uniformly dispatches energy for each energy supply system 200 and uniformly allocates energy storage devices to minimize the total production capacity cost of the entire energy system.

[0049] At least some of the multiple energy supply systems 200 are coupled to each other for energy transmission. The energy supply systems transmit energy through a transmission medium. In one embodiment, each energy supply system is coupled to other energy supply systems in the energy system. In another embodiment, each energy supply system is coupled to some energy supply systems in the energy system. The energy system includes M=||N||0 energy supply systems, wherein the N set is a set of energy supply systems in the energy system, and the elements in the N set represent energy supply systems in the energy system.

[0050] Each energy supply system supplies energy to its energy users. Each energy supply system can provide energy supply to one or more energy users, and each energy user pays the energy supply system at a price that varies over time. The energy supply system can supply energy such as electrical energy, thermal energy, etc.

[0051] The energy-consuming object refers to one or more devices that require energy, such as industrial equipment, such as manufacturing / processing equipment, assembly line equipment, etc.; and household appliances, such as televisions, refrigerators, air conditioners, etc., and lamps of lighting systems, etc. In some examples, the energy-consuming object may be a general term for at least one energy-consuming device connected to the same metering device.

[0052] The type of the energy supply system and the transmission medium for supplying energy to the energy-consuming object can be determined according to the type of energy. The type of energy includes but is not limited to electrical energy, thermal energy, etc. For example, when the energy is electrical energy, the energy system includes but is not limited to the power system described above, and the power system includes: a traditional thermal power generation grid, and / or a microgrid based on distributed energy. The energy supply system includes but is not limited to a power supply system such as a power generation system or a distribution system for providing electricity to the energy-consuming object, and the transmission medium includes but is not limited to electric wires.

[0053] See also Figure 2 , Figure 2Shown is a schematic diagram of the structure of the energy supply system of the present application in one embodiment. As shown in the figure, the energy supply system 200 includes a power generation device and an energy storage device, and the energy supply system 200 is used to supply energy to an energy-consuming object. The energy storage device of the energy supply system 200 is coupled to the power generation device of the energy supply system 200 to obtain energy. The energy storage device is used to store a certain capacity of energy. The energy storage device includes but is not limited to a battery, a supercapacitor, etc. Among them, the battery can be a lead-acid battery, a nickel-cadmium battery, a nickel-hydrogen battery, a sodium-sulfur battery, a lithium battery or a fuel cell, etc.

[0054] The energy supply system 200 may also not include a power generation device, and supply energy to its corresponding energy-consuming objects by obtaining surplus energy from other energy supply systems.

[0055] It should be noted that the energy supply system is only a general expression and does not limit it to an independent physical device. The coupling relationship between the energy supply system and the energy-consuming object refers to a direct or indirect connection relationship, as long as the energy-consuming object can obtain energy from the energy supply system, and does not limit its specific implementation form.

[0056] It is understandable that since the transaction object is not restricted to electricity, the expression of its price is not limited to electricity price. In this article, it is expressed by "price", "marginal price" and "average energy price"; accordingly, power supply system, heating system, etc. are also expressed alternatively by "energy supply system".

[0057] In an embodiment of the present application, in order to meet the estimated energy demand of the energy-consuming object, when the control system 100 performs energy scheduling on multiple energy supply systems 200, the energy supply parameters of each energy supply system 200 must satisfy the constraints corresponding to formulas (1) to (3).

[0058] The energy supply parameters include the energy output g of each energy supply system in each time interval of the unit energy supply period. n,t , the storage / release energy u of the energy storage device in each energy supply system in each time interval during the unit energy supply period n,t 、Configuration capacity of energy storage devices in each energy supply system n One or more of .

[0059] Wherein, t represents a time interval. The time interval includes, but is not limited to: one or more hours, one or more days, one or more weeks, or one or more months, etc. Wherein, multiple time intervals t constitute a unit energy supply period T. For example, suppose the unit energy supply period T is one day, and the time interval t is each hour of the day. Alternatively, in a unit energy supply period T, it can be divided into multiple time intervals t according to different prices, namely: 0AM~7AM time interval, 7AM~11PM time interval, 11PM~5PM time interval, 5PM~7PM time interval, 7PM~12PM time interval.

[0060] The energy output g of each energy supply system in each time interval in the unit energy supply period n,t and the storage / release energy u of the energy storage device in each energy supply system in each time interval during the unit energy supply period n,t Need to meet:

[0061]

[0062] Wherein, formula (1) represents: the energy output g of each energy supply system n,t The storage / release energy u of each energy supply system n,t , and the estimated energy demand d of each energy-consuming object of the energy supply system n,t The difference between the two is the same as the directional power flow f transmitted between each energy supply system and other energy supply systems coupled with each energy supply system nm,t The sum is equivalent.

[0063] Among them, f nm,t =Y nm (θ n,t -θ m,t ), m, n∈N and m≠n, nm∈V, V is the set of transmission lines between each energy supply system and other energy supply systems coupled with each energy supply system. θ n,t is the voltage phase angle at energy supply system n, θ m,t Y is the voltage phase angle at other energy supply system m coupled with energy supply system n. nm is the admittance in the transmission line nm.

[0064] in, It is the maximum capacity allowed to be transmitted in the transmission line nm in any time interval.

[0065] Among them, u n,t A positive value indicates that energy is stored in the energy storage device, u n,t A negative value indicates that the energy storage device releases energy. Based on the storage / release energy u of the energy storage device in each energy supply system in each time interval in the unit energy supply period n,t, the total energy x stored in each energy supply system in each time interval t during the unit energy supply period n,t The constraints of formula (2) need to be met:

[0066] x n,t =x n,t-1 +u n,t (2)

[0067] Where n∈N, 0≤x n,t ≤e n , x n,0 It is expressed as the total energy stored in each energy supply system during the initial time interval in the unit energy supply period, x n,T It is expressed as the total energy stored in each energy supply system in the last time interval of the unit energy supply period, e n is the configuration capacity of the energy storage device in each energy supply system, and the configuration capacity of each energy supply system is e n The sum satisfies the total configuration capacity:

[0068]

[0069] Where E is the total configuration capacity.

[0070] Under the above constraints, the present application provides a data processing method for a control system, the data processing method for a control system comprising: determining the ideal energy supply parameters of each energy supply system according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period. The data processing method is applied to Figure 1 The control system shown.

[0071] See also Figure 3 , Figure 3 The structure diagram of the control system in one embodiment of the present application is shown as follows: Figure 3 As shown, the control system 100 includes a communication device 101 , a storage device 102 , and a processing device 103 .

[0072] The storage device 102 is used to store at least one program. In some embodiments, the storage device 102 includes one or more memories, which are used to execute the data processing method for the control system exemplified based on the technical idea of ​​the present application when executed. In an embodiment, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more disk storage devices, flash memory devices or other non-volatile solid-state storage devices. In some embodiments, the memory may also include a memory away from one or more processors, such as a network attached memory accessed via an RF circuit or an external port and a communication network, wherein the communication network may be the Internet, one or more intranets, local area networks, wide area networks, storage area networks, etc., or a suitable combination thereof. The memory controller may control access to the memory by other components of the device such as the CPU and peripheral interfaces.

[0073] The processing device 103 is connected to the storage device 102. In some embodiments, the processing device 103 includes one or more processors, and the processing device 103 is used to call the at least one program to execute the data processing method for the control system described in the present application. In an embodiment, the processor is operably coupled to a memory and / or a non-volatile storage device. More specifically, the processor can execute instructions stored in the memory and / or the non-volatile storage device to perform operations in the control system, such as generating ideal energy supply parameter data and / or transmitting the ideal energy supply parameter data to each energy supply system through the communication device. In this way, the processor may include one or more general-purpose microprocessors, one or more special-purpose processors, one or more field programmable logic arrays, or any combination thereof.

[0074] The communication device 101 is used to communicate with multiple energy supply systems. Through the communication device 101, the control system 100 can perform data interaction or communication transmission with multiple energy supply systems 200. For example, the control system sends the ideal energy production of each energy supply system in each time interval within a unit cycle to each energy supply system 200 through the communication device, so that each energy supply system 200 can produce energy according to the ideal energy production allocated by the control system. Among them, the communication device 101 may include: wired communication circuits and / or wireless communication circuits, wired communication circuits such as wired network cards, wireless communication circuits such as 2G-5G, WiFi, 314 / 433 radio frequency circuits, etc., so as to access a communication network, and the communication network may include the Internet, a mobile network, a local area network (LAN), a wide area network (WAN), a storage area network (SAN), or one or more intranets, etc., or one or more of any other appropriate communication networks.

[0075] The control system 100 can interact with various other electronic devices and enable users to interact with the control system through the communication device 101. For example, the user sends a preset total configuration capacity to the control system 100 through the communication network.

[0076] In one embodiment, the control system 100 is, for example, an electronic device loaded with an APP application or having webpage / website access capabilities, such as a desktop computer, a smart TV, a server, a mobile terminal (such as a mobile phone, a tablet computer, a laptop computer, etc.), and these electronic devices may also include input and output units such as a display unit / audio unit. The display unit may include a touch component that facilitates user input by detecting the occurrence and / or position of an object touching its screen (for example, the surface of an electronic display); for example, an operator on the control system side touches the screen of the electronic device to input the preset total configuration capacity, etc.

[0077] In one embodiment, the energy supply parameters of each of the energy supply systems satisfy the above constraints, and the data processing method for the control system includes: determining the ideal energy supply parameters of each of the energy supply systems based on a preset total configuration capacity and an estimated energy demand of energy-consuming objects of each of the energy supply systems in each time interval in a unit energy supply period T.

[0078] The ideal energy supply parameter is an energy supply parameter that optimizes the optimization target within the unit energy supply period T.

[0079] The optimization target is the overall target of multiple energy supply systems corresponding to the entire energy system, for example, the total energy production of multiple energy supply systems, the total production capacity cost of multiple energy supply systems, or the total energy storage of multiple energy supply systems in each time interval.

[0080] Specifically, in order to make the entire energy system run with high quality and stability, and to make the optimization target reach the optimum in the unit energy supply period T, the control system is based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period, by making the functional relationship corresponding to the optimization target obtain the optimal solution in the unit energy supply period. Among them, the values ​​of each energy supply parameter corresponding to the optimal solution of the objective function corresponding to the optimization target are the ideal energy supply parameters of each energy supply system. In the actual operation process, each energy supply system can achieve the optimization target when producing energy, storing energy, releasing energy, and supplying energy according to the ideal energy supply parameters.

[0081] In a specific embodiment, the optimization target includes the total capacity cost of multiple energy supply systems, and the data processing method for the control system includes taking the energy supply parameters that minimize the total capacity cost of the multiple energy supply systems in a unit energy supply period as ideal energy supply parameters based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period. Among them, the capacity cost of each energy supply system in each time interval and the capacity of each energy supply system satisfy a preset functional relationship. The preset functional relationship is determined based on the technical level of the actual capacity and the prices of various factors required for the capacity. The factors are related to the capacity mode. For example, the energy is electrical energy, the capacity mode is thermal power generation, the factors include coal, and the corresponding factor price is the price of coal.

[0082] Taking the quadratic function relationship as an example, the capacity cost C of each energy supply system in each time interval is n (g n,t ) and the energy output g of each energy supply system n,t Satisfies the following functional relationship:

[0083]

[0084] in, is the quadratic term coefficient of the quadratic function, b n is the coefficient of the first term of the quadratic function, c n is the constant term of the quadratic function. Of course, although the energy output g of each energy supply system is represented by a quadratic function in this application n,t and the capacity cost C of each energy supply system n (g n,t ), but is not limited to this, and may be replaced by other polynomial forms in other embodiments.

[0085] It should be noted that, for the energy supply system that does not include a power generation device in the energy system, the corresponding cost function is set to be sufficiently large. Taking the functional relationship as a quadratic functional relationship as an example, one or more of the quadratic term coefficient, the linear term coefficient, and the constant term can be set to a sufficiently large constant. The value range of the sufficiently large constant can be: 10 million to 100 million, 1 million to 10 million, etc.

[0086] Based on the functional relationship corresponding to formula (4), when the energy supply parameters of each energy supply system meet the above constraints, the data processing method for the control system needs to solve the optimization problem shown in formula (5):

[0087]

[0088] Specifically, the optimization problem to be solved is: according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period, determine the ideal energy supply parameters corresponding to the minimum total capacity cost of multiple energy supply systems in the unit energy supply period T. The estimated energy demand is obtained based on the historical data of the energy demand of each energy supply system.

[0089] For example, the estimated energy demand can be obtained based on the historical data of energy demand of each energy supply system and the energy demand prediction method. The energy demand prediction method includes but is not limited to: neural network prediction method, fuzzy prediction method, time series method, regression analysis method, grey mathematical theory prediction method, etc.

[0090] For another example, the estimated energy demand may be obtained by processing historical data of the energy demand in multiple unit energy supply periods.

[0091] The preset total configuration capacity is determined based on the preset cost of purchasing the energy storage device. For example, the control system is exemplified as a control system on the independent system operator (ISO) side. The independent system operator purchases energy storage devices according to its preset cost, and it is expected that the energy storage devices with the preset total configuration capacity will be allocated to each of the energy supply systems according to the obtained ideal energy supply parameters. The independent system operator refers to a power dispatching center that is not for profit and is independent of all other market entities such as power generation companies, power trading centers, power distribution companies, and power users. The independent system operator is responsible for the safe, stable, high-quality and economical operation of the power system, and is an institution that provides non-discriminatory dispatching services for the power system.

[0092] The data processing method for the control system solves the optimization problem corresponding to formula (5) by constructing a Lagrangian function and applying the KKT (Karush-Kuhn-Tucker) condition.

[0093] The Lagrangian function L can be expressed by the following formula:

[0094]

[0095] Among them, ρ is the corresponding constraint The Lagrange multiplier, ν n,t is the corresponding constraint The Lagrange multiplier, π nm,t is the corresponding constraint The Lagrange multiplier, ξ n,t is the corresponding constraint x n,t =x n,t-1 +u n,tThe Lagrange multiplier, λ n,t is the corresponding constraint x n,t ≤e n The Lagrange multiplier, μ n,t is the corresponding constraint 0≤x n,t The Lagrange multiplier, φ n,t is the corresponding constraint The Lagrange multiplier, φ n,0 is the corresponding constraint The Lagrange multiplier of .

[0096] The KKT condition corresponding to formula (6) can be expressed by the following equations:

[0097]

[0098] In the KKT condition, * represents the optimal solution when the optimization problem corresponding to formula (5) is minimized. The optimal solution includes the ideal energy supply parameters and the ideal Lagrange multipliers corresponding to each constraint condition.

[0099] By solving the above KKT conditions, the energy supply parameters that minimize the total production capacity cost of the multiple energy supply systems in the unit energy supply period T can be obtained, and the values ​​of the energy supply parameters are taken as ideal energy supply parameters.

[0100] It should be noted that the applicant has proved that the estimated energy demand d of the energy-consuming objects in each energy supply system is n,t And when the constraints mentioned above remain unchanged, by increasing the preset total configuration capacity, the minimum value of the total production capacity cost of the multiple energy supply systems in a unit energy supply period can be reduced.

[0101] In one embodiment, after obtaining the ideal energy supply parameters in the above manner, the control system sends the ideal energy supply parameters to each energy supply system through the communication device. The ideal energy supply parameters include: the ideal energy production of each energy supply system in each time interval in a unit energy supply period, the ideal storage / release energy of the energy storage device in each energy supply system in each time interval in a unit energy supply period, and / or the ideal configuration capacity of the energy storage device in each energy supply system. Each energy supply system sets the capacity of the energy storage device in accordance with the ideal configuration capacity of the energy storage device in each energy supply system determined by the control system. For example, the energy system includes energy supply system 1, energy supply system 2, and energy supply system 3, and the control system estimates that a total configuration capacity of 1000MW will be allocated to each energy supply system, and the ideal configuration capacities obtained by solving the above method are respectively Then energy supply system 1 is equipped with an energy storage device with a capacity of 300MW, energy supply system 2 is equipped with an energy storage device with a capacity of 300MW, and energy supply system 3 is equipped with an energy storage device with a capacity of 400MW.

[0102] Wherein, after each energy supply system sets the energy storage device according to the ideal configuration capacity, each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production of each energy supply system and the ideal storage / release energy of each energy supply system determined by the control system. Specifically, each energy supply system generates energy according to the ideal energy production of each time interval in the unit cycle, stores energy or releases energy according to the ideal storage / release energy of each time interval in the unit cycle, and supplies energy according to the actual energy demand of each time interval in the unit cycle.

[0103] Since the estimated energy requirement d n,t It is to estimate the demand for future periods based on the historical data of demand. It is affected by various complex factors, and various influencing factors are also developing and changing. When forecasting demand, some of these developments and changes can be estimated in advance, while others are difficult to foresee in advance. In addition, the impact of some temporary changes determines the expected demand. n,t inaccuracy or incomplete accuracy.

[0104] Since the estimated energy requirement d n,t In the case of inaccuracy or incomplete accuracy, the data processing method for the control system further includes determining whether the ideal energy supply parameters meet the actual energy demand according to the actual energy demand of the energy-consuming object in each energy supply system in each time interval in the unit energy supply period. If satisfied, each energy supply system continues to produce energy, store energy, release energy, and supply energy according to the ideal energy production of each energy supply system and the ideal storage / release energy of each energy supply system.

[0105] For example, the energy supply cycle includes three time intervals, and the energy system includes energy supply system 1 and energy supply system 2. When solving the optimization problem corresponding to formula (5), the control system takes the estimated energy requirements of energy supply system 1 and energy supply system 2 as d 1,1 =d 2,1 =500MW, d 1,2 =d 2,2 =600MW, d 1,3 =d 2,3 = 800MW, and then the ideal energy production and ideal storage / release energy of each energy supply system in each time interval can be obtained. The control system can receive the actual energy demand of each energy supply system in each time interval through its communication device. If the actual energy demand of the energy-consuming objects in the energy supply system 1 and the energy supply system 2 is still d 1,1 =d2,1 =500MW, d 1,2 =d 2,2 =600MW, d 1,3 =d 2,3 =800MW, the energy supply system 1 and the energy supply system 2 continue to produce energy, store energy, release energy, and supply energy according to the ideal energy production and ideal storage / release energy previously solved. If the actual energy demand of the energy-consuming objects in the energy supply system 1 and / or the energy supply system 2 does not match the estimated energy demand, the control system may issue an alarm through its display unit or audio unit to indicate that the ideal energy supply parameters cannot meet the actual energy demand of the energy-consuming objects in each energy supply system. The control system may also display the specific energy supply system that has changed and the actual energy demand corresponding to the energy supply system through its display unit for subsequent processing by the control system.

[0106] The data processing method for a control system further includes: determining the marginal price of energy supplied by each energy supply system in each time interval in a unit energy supply period according to the coefficients in the preset functional relationship and the ideal energy production of each energy supply system in each time interval. Each energy supply system can determine the price of energy supplied to its energy-consuming object in each time interval according to the marginal price.

[0107] Specifically, due to ν n,t is the corresponding constraint The Lagrange multiplier of , the opposite of the Lagrange multiplier - ν n,t It represents the total capacity cost of the multiple energy supply systems when the estimated energy demand of the energy-consuming objects in each energy supply system increases by one unit value in each time interval. Therefore, when each energy supply system performs production, energy storage, energy release, and energy supply according to the ideal energy supply parameters, the marginal price p of each energy supply system is n,t The opposite of the ideal value of the Lagrange multiplier can be obtained by express:

[0108]

[0109] in, is the ideal energy production of each energy supply system in each time interval, is the quadratic coefficient of the capacity cost of each energy supply system, b n It is the first-order coefficient of the capacity cost of each energy supply system.

[0110] It should be noted that the marginal price p of each energy supply system is n,t Includes the part that does not change with the total configuration capacity E (e.g. a n d n,t +b n), and the part that varies with the total configuration capacity E (e.g. ). It can be understood that for different capacity cost functions, the marginal price is expressed in different forms and is not limited to the expression shown in formula (8).

[0111] In actual scenarios, energy consumption patterns (Energy Consumption Patterns) are different between energy-consuming objects, and the energy demand of each energy-consuming object will change over time. Although deploying energy storage devices with ideal configuration capacity in each energy supply system can reduce the production capacity cost of the entire energy system, it is impossible to benefit all energy-consuming objects with different energy usage habits by deploying energy storage devices to supply power at the marginal price obtained based on the ideal energy supply parameters. Therefore, this application uses the impact of each energy-consuming object on the production capacity cost of its energy supply system to evaluate the average energy price of energy-consuming objects with different energy consumption patterns within a unit energy supply period, and then it can be determined whether the deployment of energy storage devices is beneficial to energy-consuming objects with different energy usage habits.

[0112] The energy demand may be the estimated energy demand as described above or directly the historical data of actual energy demand.

[0113] In a unit energy supply period T, the impact of each energy-consuming object on the capacity cost of its energy supply system is measured by the change in the capacity cost of the energy supply system caused by the change in the energy demand obtained by the energy-consuming object from its energy supply system. In an example, formula (9) gives the impact MCI of each energy-consuming object i on the capacity cost of its energy supply system in each energy supply system: i,n Definition:

[0114]

[0115] In formula (9), ||L i,n ||1 is the total energy demand of energy-consuming object i in the unit energy supply period T; where ||L i,n ||1 is the energy demand of a single energy-consuming object i in an energy supply system at each time interval t within a unit energy supply period T. Obtained by calculation.

[0116] It should be noted that in other embodiments, the calculation method of the total energy demand may also be changed. For example, the total energy demand in the unit energy supply period T may be the average or weighted sum of the energy demand in each time interval t, but it is not limited to this.

[0117] In one embodiment, the relationship between the capacity cost and the capacity is defined by the functional relationship represented by formula (4), then the capacity cost impact MCI of each energy-consuming object i in each energy supply system on its energy supply system is:i,n It can be expressed by the following formula:

[0118]

[0119] Of course, although the mathematical relationship between the production capacity cost and the production capacity is represented by a quadratic function in this embodiment, it is not limited to this, and in other embodiments, it can be replaced by other polynomial forms.

[0120] In one embodiment, based on formula (10), the data processing method for controlling the system further includes: determining the impact of each energy-consuming object on the production capacity cost of its energy supply system within a unit period based on the estimated energy demand of each energy-consuming object within each time interval in a unit energy supply period and the marginal price of energy supplied by the energy supply system.

[0121] Specifically, the node marginal price of energy supplied by each energy supply system in each time interval can be obtained through the ideal energy supply parameters and the coefficients in the quadratic function. Determine the impact MCI of each energy-consuming object on the production cost of its energy supply system i,n In a unit energy supply period, the impact of each energy-consuming object on the production capacity cost of its energy supply system MCI i,n It can be used to evaluate the average energy price of each energy-consuming object.

[0122] It can be understood that if the energy consumption object's capacity cost impact MCI on its energy supply system is obtained based on the ideal energy supply parameters i,n If it is greater than the average energy price before the deployment of energy storage devices, then the deployment of energy storage devices will be harmful to the energy users with the energy consumption habits.

[0123] In one embodiment, based on the above method, the impact of deploying energy storage devices on different energy-consuming objects can be determined, and energy-using strategy prompts can be provided to different energy-consuming objects.

[0124] In another embodiment, the capacity cost impact MCI can also be used. i,n The relevant impact distance condition classifies each of the energy-consuming objects, and divides the energy-consuming objects into one or more energy-consuming object groups with energy supply cost impact as a measurement indicator, so as to provide different energy-using strategy prompts for energy-using object groups with different impact amounts. It can be understood that in the same energy-using object group, the energy-using habits of each energy-using object are roughly the same.

[0125] Each of the energy-consuming objects may be classified by clustering (e.g., K-means clustering), manual classification, or other methods to obtain one or more energy-consuming object groups. The impact distance condition includes: the maximum difference between the energy supply cost impact amounts of each energy-consuming object belonging to the same energy-consuming object group is within a preset distance value range.

[0126] The energy usage strategy prompt includes: maintaining energy usage habits, changing energy usage habits, or providing energy usage habits with a small impact on production capacity cost based on energy usage.

[0127] It should be noted that by increasing the preset total configuration capacity, the energy users with different energy usage habits can have an impact on the production capacity cost of their energy supply system MCI. i,n In one embodiment, if the relationship between production capacity cost and production capacity is defined by the functional relationship represented by formula (4), the stable value is in, It is the ideal energy production of each energy supply system in each time interval.

[0128] The present application also provides a data processing system for a control system, which is used to determine the ideal energy supply parameters of each of the energy supply systems. The ideal energy supply parameters are energy supply parameters that optimize the optimization target within a unit energy supply period T. The control system is communicatively connected to a plurality of energy supply systems, wherein at least some of the energy supply systems are coupled to each other for energy transmission, and each of the energy supply systems supplies energy to its energy-consuming objects.

[0129] The data processing system can be applied in Figure 1 In the control system 100 shown in FIG. Figure 1 The control system 100 shown is used to implement corresponding functions.

[0130] See also Figure 4 , Figure 4 The diagram is a schematic diagram of a data processing system for a control system of the present application in one embodiment, as shown in the figure, the data processing system 300 includes an ideal energy supply parameter determination module 301. In one embodiment, the energy supply parameters of each energy supply system meet the above constraints, and the ideal energy supply parameter determination module 301 determines the ideal energy supply parameters of each energy supply system according to the preset total configuration capacity and the estimated energy demand of the energy-consuming object of each energy supply system in each time interval in the unit energy supply period T.

[0131] The ideal energy supply parameter is an energy supply parameter that optimizes the optimization target within the unit energy supply period T.

[0132] The optimization target is the overall target of multiple energy supply systems corresponding to the entire energy system, for example, the total energy production of multiple energy supply systems, the total production capacity cost of multiple energy supply systems, or the total energy storage of multiple energy supply systems in each time interval.

[0133] Specifically, in order to make the entire energy system run with high quality and stability, and to make the optimization target reach the optimum in the unit energy supply period T, the control system is based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period, by making the functional relationship corresponding to the optimization target obtain the optimal solution in the unit energy supply period. Among them, the values ​​of each energy supply parameter corresponding to the optimal solution of the objective function corresponding to the optimization target are the ideal energy supply parameters of each energy supply system. In the actual operation process, each energy supply system can achieve the optimization target when producing energy, storing energy, releasing energy, and supplying energy according to the ideal energy supply parameters.

[0134] In a specific embodiment, the optimization target includes the total capacity cost of multiple energy supply systems, and the data processing system for controlling the system includes, based on the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each of the energy supply systems in each time interval in the unit energy supply period, taking the energy supply parameters that minimize the total capacity cost of the multiple energy supply systems in the unit energy supply period as ideal energy supply parameters. Among them, the capacity cost of each of the energy supply systems in each time interval and the capacity of each of the energy supply systems satisfy a preset functional relationship. The preset functional relationship is determined based on the technical level of the actual capacity and the prices of various factors required for the capacity. The factors are related to the capacity mode. For example, the energy is electrical energy, the capacity mode is thermal power generation, the factors include coal, and the corresponding factor price is the price of coal.

[0135] Taking the quadratic function relationship as an example, the capacity cost C of each energy supply system in each time interval is n (g n,t ) and the energy output g of each energy supply system n,t Satisfies the following functional relationship:

[0136]

[0137] in, is the quadratic term coefficient of the quadratic function, b n is the coefficient of the first term of the quadratic function, c n is the constant term of the quadratic function. Of course, although the energy output g of each energy supply system is represented by a quadratic function in this application n,t and the capacity cost C of each energy supply system n (gn,t ), but is not limited to this, and may be replaced by other polynomial forms in other embodiments.

[0138] It should be noted that, for the energy supply system that does not include a power generation device in the energy system, the corresponding cost function is set to be sufficiently large. Taking the functional relationship as a quadratic functional relationship as an example, one or more of the quadratic term coefficient, the linear term coefficient, and the constant term can be set to a sufficiently large constant. The value range of the sufficiently large constant can be: 10 million to 100 million, 1 million to 10 million, etc.

[0139] After determining the functional relationship, when the energy supply parameters of each energy supply system meet the above constraints, the data system method for controlling the system needs to solve the optimization problem shown in formula (5):

[0140]

[0141] Specifically, the optimization problem to be solved is: according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period, determine the ideal energy supply parameters corresponding to the minimum total capacity cost of multiple energy supply systems in the unit energy supply period T. The estimated energy demand is obtained based on the historical data of the energy demand of each energy supply system.

[0142] For example, the estimated energy demand can be obtained based on the historical data of energy demand of each energy supply system and the energy demand prediction method. The energy demand prediction method includes but is not limited to: neural network prediction method, fuzzy prediction method, time series method, regression analysis method, grey mathematical theory prediction method, etc.

[0143] For another example, the estimated energy demand may be obtained by processing historical data of the energy demand in multiple unit energy supply periods.

[0144] The preset total configuration capacity is determined based on the preset cost of purchasing the energy storage device. For example, the control system is exemplified by the control system of an independent system operator (ISO). The independent system operator purchases energy storage devices according to its preset cost, and it is expected that the energy storage devices with the preset total configuration capacity will be allocated to each of the energy supply systems according to the obtained ideal energy supply parameters. The independent system operator refers to a power dispatching center that is not for profit and is independent of all other market entities such as power generation companies, power trading centers, power distribution companies, and power users. The independent system operator is responsible for the safe, stable, high-quality and economical operation of the power system, and is an institution that provides non-discriminatory dispatching services for the power system.

[0145] The ideal energy supply parameter determination module 301 constructs a Lagrangian function and applies the KKT (Karush-Kuhn-Tucker) condition to solve the optimization problem corresponding to formula (5).

[0146] The Lagrangian function L can be expressed by the following formula:

[0147]

[0148] Among them, ρ is the corresponding constraint The Lagrange multiplier, ν n,t is the corresponding constraint The Lagrange multiplier, π nm,t is the corresponding constraint The Lagrange multiplier, ξ n,t is the corresponding constraint x n,t =x n,t-1 +u n,t The Lagrange multiplier, λ n,t is the corresponding constraint x n,t ≤e n The Lagrange multiplier, μ n,t is the corresponding constraint 0≤x n,t The Lagrange multiplier, φ n,t is the corresponding constraint The Lagrange multiplier, φ n,0 is the corresponding constraint The Lagrange multiplier of .

[0149] The KKT condition corresponding to formula (6) can be expressed by the following equations:

[0150]

[0151] In the KKT condition, * represents the optimal solution when the optimization problem corresponding to formula (5) is minimized. The optimal solution includes the ideal energy supply parameters and the ideal Lagrange multipliers corresponding to each constraint condition.

[0152] By solving the above KKT conditions, the energy supply parameters that minimize the total production capacity cost of the multiple energy supply systems in the unit energy supply period T can be obtained, and the values ​​of the energy supply parameters are taken as ideal energy supply parameters.

[0153] It should be noted that the applicant has proved that the estimated energy demand d of the energy-consuming objects in each energy supply system is n,t And when the constraints mentioned above remain unchanged, by increasing the preset total configuration capacity, the minimum value of the total production capacity cost of the multiple energy supply systems in a unit energy supply period can be reduced.

[0154] In one embodiment, after obtaining the ideal energy supply parameters in the above manner, the control system sends the ideal energy supply parameters to each energy supply system through the communication device. The ideal energy supply parameters include: the ideal energy production of each energy supply system in each time interval in a unit energy supply period, the ideal storage / release energy of the energy storage device in each energy supply system in each time interval in a unit energy supply period, and / or the ideal configuration capacity of the energy storage device in each energy supply system. Each energy supply system sets the capacity of the energy storage device in accordance with the ideal configuration capacity of the energy storage device in each energy supply system determined by the control system. For example, the energy system includes energy supply system 1, energy supply system 2, and energy supply system 3, and the control system estimates that a total configuration capacity of 1000MW will be allocated to each energy supply system, and the ideal configuration capacities obtained by solving the above method are respectively Then energy supply system 1 is equipped with an energy storage device with a capacity of 300MW, energy supply system 2 is equipped with an energy storage device with a capacity of 300MW, and energy supply system 3 is equipped with an energy storage device with a capacity of 400MW.

[0155] Wherein, after each energy supply system sets the energy storage device according to the ideal configuration capacity, each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production of each energy supply system and the ideal storage / release energy of each energy supply system determined by the control system. Specifically, each energy supply system generates energy according to the ideal energy production of each time interval in the unit cycle, stores energy or releases energy according to the ideal storage / release energy of each time interval in the unit cycle, and supplies energy according to the actual energy demand of each time interval in the unit cycle.

[0156] Since the estimated energy requirement d n,t It is to estimate the demand for future periods based on the historical data of demand. It is affected by various complex factors, and various influencing factors are also developing and changing. When forecasting demand, some of these developments and changes can be estimated in advance, while others are difficult to foresee in advance. In addition, the impact of some temporary changes determines the expected demand. n,t inaccuracy or incomplete accuracy.

[0157] Since the estimated energy requirement d n,t inaccuracy or incomplete accuracy, so please refer to Figure 5 , Figure 5 The diagram shows a data processing system for a control system of the present application in another embodiment. As shown in the diagram, the data processing system 400 for a control system includes: an ideal energy supply parameter determination module 401 and a verification module 402 .

[0158] The ideal energy supply parameter determination module 401 and Figure 4The ideal energy supply parameter determination module 301 described in the specification is the same or similar and will not be described in detail here.

[0159] The verification module 402 determines whether the ideal energy supply parameters meet the actual energy demand according to the actual energy demand of the energy-consuming objects in each energy supply system in each time interval in the unit energy supply period. If satisfied, each energy supply system continues to produce energy, store energy, release energy, and supply energy according to the ideal energy production capacity of each energy supply system and the ideal storage / release energy of each energy supply system.

[0160] For example, the energy supply cycle includes three time intervals, and the energy system includes energy supply system 1 and energy supply system 2. When solving the optimization problem corresponding to formula (5), the control system takes the estimated energy requirements of energy supply system 1 and energy supply system 2 as d 1,1 =d 2,1 =500MW, d 1,2 =d 2,2 =600MW, d 1,3 =d 2,3 = 800MW, and then the ideal energy production and ideal storage / release energy of each energy supply system in each time interval can be obtained. The control system can receive the actual energy demand of each energy supply system in each time interval through its communication device. If the actual energy demand of the energy-consuming objects in the energy supply system 1 and the energy supply system 2 is still d 1,1 =d 2,1 =500MW, d 1,2 =d 2,2 =600MW, d 1,3 =d 2,3 =800MW, the energy supply system 1 and the energy supply system 2 continue to produce energy, store energy, release energy, and supply energy according to the ideal energy production and ideal storage / release energy previously solved. If the actual energy demand of the energy-consuming objects in the energy supply system 1 and / or the energy supply system 2 does not match the estimated energy demand, the control system may issue an alarm through its display unit or audio unit to indicate that the ideal energy supply parameters cannot meet the actual energy demand of the energy-consuming objects in each energy supply system. The control system may also display the specific energy supply system that has changed and the actual energy demand corresponding to the energy supply system through its display unit for subsequent processing by the control system.

[0161] See also Figure 6 , Figure 6 Shown is a schematic diagram of a data processing system for a control system of the present application in another embodiment. As shown in the figure, the data processing system 500 for a control system includes: an ideal energy supply parameter determination module 501 and a marginal price determination module 502.

[0162] The ideal energy supply parameter determination module 501 and Figure 4 The ideal energy supply parameter determination module 301 described in the specification is the same or similar and will not be described in detail here.

[0163] The marginal price determination module 502 determines the marginal price of energy supplied by each energy supply system in each time interval in the unit energy supply period according to the coefficients in the preset functional relationship and the ideal output of each energy supply system in each time interval. Each energy supply system can determine the price of energy supplied to its energy user in each time interval according to the marginal price.

[0164] Specifically, due to ν n,t is the corresponding constraint The Lagrange multiplier of , the opposite of the Lagrange multiplier - ν n,t It represents the total capacity cost of the multiple energy supply systems when the estimated energy demand of the energy-consuming objects in each energy supply system increases by one unit value in each time interval. Therefore, when each energy supply system performs production, energy storage, energy release, and energy supply according to the ideal energy supply parameters, the marginal price p of each energy supply system is n,t The opposite of the ideal value of the Lagrange multiplier can be obtained by express:

[0165]

[0166] in, is the ideal energy production of each energy supply system in each time interval, is the quadratic coefficient of the capacity cost of each energy supply system, b n It is the first-order coefficient of the capacity cost of each energy supply system.

[0167] It should be noted that the marginal price p of each energy supply system is n,t Includes the part that does not change with the total configuration capacity E (e.g. a n d n,t +b n ), and the part that varies with the total configuration capacity E (e.g. ). It can be understood that for different capacity cost functions, the marginal price is expressed in different forms and is not limited to the expression shown in formula (8).

[0168] In actual scenarios, energy consumption patterns (Energy Consumption Patterns) are different between energy-consuming objects, and the energy demand of each energy-consuming object will change over time. Although deploying energy storage devices with ideal configuration capacity in each energy supply system can reduce the production capacity cost of the entire energy system, it is impossible to benefit all energy-consuming objects with different energy usage habits by deploying energy storage devices to supply power at the marginal price obtained based on the ideal energy supply parameters. Therefore, this application uses the impact of each energy-consuming object on the production capacity cost of its energy supply system to evaluate the average energy price of energy-consuming objects with different energy consumption patterns within a unit energy supply period, and then it can be determined whether the deployment of energy storage devices is beneficial to energy-consuming objects with different energy usage habits.

[0169] The energy demand may be the estimated energy demand as described above or directly the historical data of actual energy demand.

[0170] In a unit energy supply period T, the impact of each energy-consuming object on the capacity cost of its energy supply system is measured by the change in the capacity cost of the energy supply system caused by the change in the energy demand obtained by the energy-consuming object from its energy supply system. In an example, formula (9) gives the impact MCI of each energy-consuming object i on the capacity cost of its energy supply system in each energy supply system: i,n Definition:

[0171]

[0172] In formula (9), ||L i,n ||1 is the total energy demand of energy-consuming object i in the unit energy supply period T; where ||L i,n ||1 is the energy demand of a single energy-consuming object i in an energy supply system at each time interval t within a unit energy supply period T. Obtained by calculation.

[0173] It should be noted that in other embodiments, the calculation method of the total energy demand may also be changed. For example, the total energy demand in the unit energy supply period T may be the average or weighted sum of the energy demand in each time interval t, but it is not limited to this.

[0174] In one embodiment, the relationship between the capacity cost and the capacity is defined by the functional relationship represented by formula (4), then the capacity cost impact MCI of each energy-consuming object i in each energy supply system on its energy supply system is: i,n It can be expressed by the following formula:

[0175]

[0176] Of course, although the mathematical relationship between the production capacity cost and the production capacity is represented by a quadratic function in this embodiment, it is not limited to this, and in other embodiments, it can be replaced by other polynomial forms.

[0177] In one embodiment, based on formula (10), see Figure 7 , Figure 7 Shown is a schematic diagram of a data processing system for a control system of the present application in yet another embodiment. As shown in the figure, the data processing system 600 for a control system includes: an ideal energy supply parameter determination module 601, a marginal price determination module 602, and an influence quantity determination module 603.

[0178] The ideal energy supply parameter determination module 601 and the marginal price determination module 602 are Figure 6 The ideal energy supply parameter determination module 501 and the marginal price determination module 502 described in are the same or similar and will not be described in detail here.

[0179] The impact determination module 603 determines the impact of each energy-consuming object on the capacity cost of its energy supply system in a unit period according to the estimated energy demand of each energy-consuming object in each time interval in the unit energy supply period and the marginal price of energy supplied by the energy supply system.

[0180] Specifically, the marginal price determination module 602 can obtain the node marginal price of each energy supply system in each time interval through the ideal energy supply parameters and the coefficients in the quadratic function. The impact quantity determination module 603 determines the estimated energy demand of each energy-consuming object in each time interval of the unit energy supply period according to the node marginal price of the energy supply system and the estimated energy demand of each energy-consuming object in each time interval of the unit energy supply period. Determine the impact MCI of each energy-consuming object on the production cost of its energy supply system i,n In a unit energy supply period, the impact of each energy-consuming object on the production capacity cost of its energy supply system MCI i,n It can be used to evaluate the average energy price of each energy-consuming object.

[0181] It can be understood that if the energy consumption object's capacity cost impact MCI on its energy supply system is obtained based on the ideal energy supply parameters i,n If it is greater than the average energy price before the deployment of energy storage devices, then the deployment of energy storage devices will be harmful to the energy users with the energy consumption habits.

[0182] In one embodiment, based on the above method, the impact of deploying energy storage devices on different energy-consuming objects can be determined, and energy-using strategy prompts can be provided to different energy-consuming objects.

[0183] In another embodiment, the influence determination module 603 can also use the capacity cost influence MCI i,n The relevant impact distance condition classifies each of the energy-consuming objects, and divides the energy-consuming objects into one or more energy-consuming object groups with energy supply cost impact as a measurement indicator, so as to provide different energy-using strategy prompts for energy-using object groups with different impact amounts. It can be understood that in the same energy-using object group, the energy-using habits of each energy-using object are roughly the same.

[0184] Each of the energy-consuming objects may be classified by clustering (e.g., K-means clustering), manual classification, or other methods to obtain one or more energy-consuming object groups. The impact distance condition includes: the maximum difference between the energy supply cost impact amounts of each energy-consuming object belonging to the same energy-consuming object group is within a preset distance value range.

[0185] The energy usage strategy prompt includes: maintaining energy usage habits, changing energy usage habits, or providing energy usage habits with a small impact on production capacity cost based on energy usage.

[0186] It should be noted that by increasing the preset total configuration capacity, the energy users with different energy usage habits can have an impact on the production capacity cost of their energy supply system MCI. i,n In one embodiment, if the relationship between production capacity cost and production capacity is defined by the functional relationship represented by formula (4), the stable value is in, It is the ideal energy production of each energy supply system in each time interval.

[0187] In addition, the present application also discloses a computer-readable storage medium storing at least one computer program, which, when executed, implements at least one embodiment of the data processing method for a control system described above.

[0188] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application.

[0189] In the embodiments provided in the present application, the computer readable and writable storage medium may include a read-only memory, a random access memory, an EEPROM, a CD-ROM or other optical disk storage device, a disk storage device or other magnetic storage device, a flash memory, a USB flash drive, a mobile hard disk, or any other medium that can be used to store a desired program code in the form of an instruction or data structure and can be accessed by a computer. In addition, any connection can be appropriately referred to as a computer-readable medium. For example, if the instruction is sent from a website, a server or other remote source using a coaxial cable, an optical fiber cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, optical fiber cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. However, it should be understood that computer readable and writable storage media and data storage media do not include connections, carriers, signals, or other temporary media, but are intended to be non-temporary, tangible storage media. Disk and disc, as used in this application, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.

[0190] In one or more exemplary aspects, the functions described by the computer program of the method described in the present application can be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored or transmitted as one or more instructions or codes on a computer-readable medium. The steps of the method or algorithm disclosed in the present application can be embodied in a processor-executable software module, wherein the processor-executable software module can be located on a tangible, non-temporary computer-readable and writable storage medium. A tangible, non-temporary computer-readable and writable storage medium can be any available medium that a computer can access.

[0191] The block diagram in the accompanying drawings above of the present application illustrates the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. Based on this, each box in the block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be realized by a dedicated hardware-based system that performs a specified function or operation, or can be realized by a combination of dedicated hardware and computer instructions.

[0192] In summary, the data processing system, method, and storage medium for controlling the system of the present application determine the ideal energy supply parameters of each of the energy supply systems. The control system is communicatively connected with a plurality of energy supply systems; wherein at least some of the energy supply systems are coupled to each other for energy transmission, and each of the energy supply systems supplies energy to its energy users; within each time interval, the energy supply parameters of each of the energy supply systems satisfy the following constraints: the difference between the energy production of each of the energy supply systems and the storage / release energy of each of the energy supply systems, and the estimated energy demand of the energy users of each of the energy supply systems is equivalent to the sum of the directional power flows transmitted between each of the energy supply systems and other energy supply systems coupled to each of the energy supply systems; the sum of the configuration capacities of the energy storage devices in each of the energy supply systems satisfies the total configuration capacity. In the scheme of the present application, the ideal energy supply parameters of each of the energy supply systems are determined based on the preset total configuration capacity and the estimated energy demand of the energy users of each of the energy supply systems in each time interval in the unit energy supply period. The solution of the present application can uniformly allocate energy storage devices and uniformly dispatch electricity according to the estimated energy demand of energy-consuming objects in each energy supply system, thereby improving energy waste and uneven distribution of energy storage devices, thereby ensuring the smooth operation of the power system.

[0193] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A data processing method for a control system, characterized in that: The control system is in communication with a plurality of energy supply systems; wherein the energy supply system is a power supply system, at least some of which are coupled to each other for energy transmission, and each energy supply system supplies energy to its energy-consuming object; within each time interval, the energy supply parameters of each energy supply system satisfy the following constraints: the difference between the energy production of each energy supply system and the storage / release energy of each energy supply system and the estimated energy demand of the energy-consuming object of each energy supply system is equivalent to the sum of the directed power flows transmitted between each energy supply system and other energy supply systems coupled to each energy supply system; the sum of the configuration capacity of the energy storage device in each energy supply system satisfies the total configuration capacity; the data processing method for the control system comprises: According to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each of the energy supply systems in each time interval in the unit energy supply period, the energy supply parameters that minimize the total capacity cost of the multiple energy supply systems in the unit energy supply period are used as ideal energy supply parameters; wherein the capacity cost of each of the energy supply systems in each time interval and the capacity of each of the energy supply systems satisfy a preset functional relationship; Determine the marginal price of energy supplied by each energy supply system in each time interval in a unit energy supply period according to the coefficients in the preset functional relationship and the ideal energy production of each energy supply system in each time interval; Based on the estimated energy demand of each energy-consuming object in each time interval in the unit energy supply period and the marginal price of energy supplied by the energy supply system, the impact of each energy-consuming object on the capacity cost of its energy supply system in the unit period is determined, so that the control system can provide energy usage strategy prompts to different energy-consuming objects according to the capacity cost impact, wherein the energy usage strategy prompts include: maintaining energy usage habits, changing energy usage habits, or providing energy usage habits with a small corresponding capacity cost impact based on energy usage.

2. The data processing method for a control system according to claim 1, characterized in that: The energy supply parameters include: the energy production of each energy supply system in each time interval in a unit energy supply period, the storage / release energy of the energy storage device in each energy supply system in each time interval in a unit energy supply period, and the configuration capacity of the energy storage device in each energy supply system. One or more.

3. The data processing method for a control system according to claim 1, characterized in that: The preset functional relationship is a quadratic functional relationship.

4. The data processing method for a control system according to claim 1, characterized in that: include: Each energy supply system sets the capacity of the energy storage device in accordance with the ideal configuration capacity of the energy storage device in each energy supply system determined by the control system.

5. The data processing method for a control system according to claim 1, characterized in that: include: Each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production capacity and the ideal storage / release energy of each energy supply system determined by the control system.

6. The data processing method for a control system according to claim 1, characterized in that: The estimated energy demand is obtained based on historical energy demand data.

7. The data processing method for a control system according to claim 1, characterized in that: The data processing method for the control system also includes: Determining whether the ideal energy supply parameters meet the actual energy demand according to the actual energy demand of the energy-consuming objects in each energy supply system in each time interval in the unit energy supply period; When the conditions are met, each energy supply system continues to generate energy, store energy, release energy, and supply energy according to the ideal energy production capacity and the ideal energy storage / release capacity of each energy supply system.

8. A data processing system for a control system, characterized in that: The control system is in communication connection with a plurality of energy supply systems; wherein the energy supply system is a power supply system, at least some of which are coupled to each other for energy transmission, and each energy supply system supplies energy to its energy-consuming object; within each time interval, the energy supply parameters of each energy supply system are configured to satisfy the following constraints: the difference between the energy production of each energy supply system and the storage / release energy of each energy supply system and the estimated energy demand of the energy-consuming object of each energy supply system is equivalent to the sum of the directed power flows transmitted between each energy supply system and other energy supply systems coupled to each energy supply system; the sum of the configured capacities of the energy storage devices in each energy supply system satisfies the total configured capacity; The data processing system for controlling the system comprises: An ideal energy supply parameter determination module is used to determine the energy supply parameters that minimize the total production capacity cost of the multiple energy supply systems in a unit energy supply period according to the preset total configuration capacity and the estimated energy demand of the energy-consuming objects of each energy supply system in each time interval in the unit energy supply period as the ideal energy supply parameters; wherein the production capacity cost of each energy supply system in each time interval and the production capacity of each energy supply system satisfy a preset functional relationship; A marginal price determination module, used to determine the marginal price of energy supplied by each energy supply system in each time interval in a unit energy supply period according to the coefficients in the preset functional relationship and the ideal energy production of each energy supply system in each time interval; An impact determination module is used to determine the impact of each energy-consuming object on the capacity cost of its energy supply system within a unit period based on the estimated energy demand of each energy-consuming object in each time interval in a unit energy supply period and the marginal price of energy supplied by the energy supply system, so that the control system can provide energy usage strategy prompts to different energy-consuming objects based on the capacity cost impact, wherein the energy usage strategy prompts include: maintaining energy usage habits, changing energy usage habits, or providing energy usage habits with a small corresponding capacity cost impact based on energy usage.

9. The data processing system for controlling a system according to claim 8, characterized in that: The energy supply parameters include: the energy production of each energy supply system in each time interval in a unit energy supply period, the storage / release energy of the energy storage device in each energy supply system in each time interval in a unit energy supply period, and the configuration capacity of the energy storage device in each energy supply system. One or more.

10. The data processing system for controlling a system according to claim 8, characterized in that: The preset functional relationship is a quadratic functional relationship.

11. The data processing system for controlling a system according to claim 8, characterized in that: include: Each energy supply system sets the capacity of the energy storage device in accordance with the ideal configuration capacity of the energy storage device in each energy supply system determined by the control system.

12. The data processing system for controlling a system according to claim 8, characterized in that: include: Each energy supply system generates energy, stores energy, releases energy, and supplies energy according to the ideal energy production capacity and the ideal storage / release energy of each energy supply system determined by the control system.

13. The data processing system for controlling a system according to claim 8, characterized in that: The estimated energy demand is obtained based on historical energy demand data.

14. The data processing system for controlling a system according to claim 8, characterized in that: The data processing system for controlling the system also includes: A verification module, used to determine whether the ideal energy supply parameters meet the actual energy demand according to the actual energy demand of the energy-consuming objects in each energy supply system in each time interval in the unit energy supply period; When the conditions are met, each energy supply system continues to generate energy, store energy, release energy, and supply energy according to the ideal energy production capacity and the ideal energy storage / release capacity of each energy supply system.

15. A control system, characterized in that: include: A communication device, used for communicating with a plurality of energy supply systems; A storage device, used to store at least one program; A processing device, used for calling the at least one program to execute the data processing method for a control system as claimed in any one of claims 1 to 7.

16. An energy system, characterized in that: include: Multiple energy supply systems; The control system according to claim 15, used for communicating with the plurality of energy supply systems and for determining the ideal energy supply parameters of each of the energy supply systems; Among them, each of the energy supply systems is used to perform production capacity, energy storage, energy release, energy supply, and capacity setting of the energy storage device according to the ideal energy supply parameters determined by the control system.

17. A computer-readable storage medium, characterized in that: At least one program is stored, and when the at least one program is called, it is executed and implements the data processing method for a control system according to any one of claims 1 to 7.

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