Power distribution method and device, computer readable storage medium and computer equipment

Abstract

The application discloses an electric energy distribution method and device, a computer readable storage medium and a computer device. The method comprises the following steps: determining a first electric energy distribution strategy of a second distribution area in a first distribution area based on a basic distribution limit condition corresponding to the first distribution area; determining a second electric energy distribution strategy of a third distribution area in the second distribution area based on the first electric energy distribution strategy and a current electricity price; and determining a third electric energy distribution strategy of a load terminal based on the second electric energy distribution strategy and an electricity consumption condition of the load terminal in the third distribution area. The application solves the technical problem of unreasonable electric power distribution.

Description

Technical Field

[0001] This invention relates to the field of power control technology, and more specifically, to a power distribution method, apparatus, computer-readable storage medium, and computer equipment. Background Technology

[0002] In related technologies, the power supply of the transmission network is usually allocated by using policy-regulated power consumption and demand information of various regions. However, this method has defects in practical applications, such as unreasonable power allocation, low overall power consumption efficiency, and insufficient optimization of the power grid supply and demand relationship.

[0003] Therefore, there is a technical problem of unreasonable power distribution in related technologies.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a power distribution method, apparatus, computer-readable storage medium, and computer device to at least solve the technical problem of unreasonable power distribution.

[0006] According to one aspect of the present invention, an energy allocation method is provided, comprising: determining a first energy allocation strategy for a second allocation area within the first allocation area based on basic allocation constraints corresponding to a first allocation area; determining a second energy allocation strategy for a third allocation area within the second allocation area based on the first energy allocation strategy and the current electricity price; and determining a third energy allocation strategy for load terminals based on the second energy allocation strategy and the electricity consumption of load terminals within the third allocation area.

[0007] Optionally, based on the basic allocation constraints corresponding to the first allocation area, a first power allocation strategy for the second allocation area within the first allocation area is determined, including: determining the power supply coefficient of the second allocation area based on the power demand data, historical power consumption data, and power supply importance of the second allocation area; and determining the first power allocation strategy based on the basic allocation constraints and the power supply coefficient.

[0008] Optionally, based on the first power allocation strategy and the current electricity price, a second power allocation strategy is determined for the third allocation area within the second allocation area, including: obtaining the electricity consumption forecast curve of the second allocation area within a predetermined time range based on the first power allocation strategy; determining, based on the electricity consumption forecast curve, the power gap value when the demand power of the third allocation area is greater than the maximum supply power of the second allocation area, and the power surplus value when the demand power of the third allocation area is less than the maximum supply power of the second allocation area; determining an adjustment coefficient based on the ratio between the power gap value and the power surplus value; and adjusting the current electricity price based on the adjustment coefficient to obtain the second power allocation strategy.

[0009] Optionally, based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, a third power allocation strategy is determined for the load terminals, including: determining the power consumption task of the load terminals based on the power consumption type and demand power of the load terminals; and determining the third power allocation strategy based on the second power allocation strategy and the power consumption task of the load terminals.

[0010] Optionally, after determining the first power allocation strategy for the second allocation area within the first allocation area based on the basic allocation constraints corresponding to the first allocation area, the method further includes: receiving the first load usage of the second allocation area under the first power allocation strategy; and adjusting the first power allocation strategy based on the first load usage and the basic allocation constraints.

[0011] Optionally, after determining the second power allocation strategy for the third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price, the method further includes: receiving the second load usage of the third allocation area under the second power allocation strategy; and adjusting the second power allocation strategy based on the second load usage, the first power allocation strategy, and the current electricity price.

[0012] Optionally, after determining the third power allocation strategy for the load terminals based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, the method further includes: receiving the third load usage of the load terminals under the third power allocation strategy; and adjusting the third power allocation strategy based on the third load usage, the second power allocation strategy, and the power consumption of the load terminals.

[0013] According to another aspect of the present invention, an energy distribution device is also provided, comprising: a first determining module, configured to determine a first energy distribution strategy for a second distribution area within the first distribution area based on basic distribution constraints corresponding to a first distribution area; a second determining module, configured to determine a second energy distribution strategy for a third distribution area within the second distribution area based on the first energy distribution strategy and a current electricity price; and a third determining module, configured to determine a third energy distribution strategy for load terminals based on the second energy distribution strategy and the electricity consumption status of load terminals within the third distribution area.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform any of the above-described power distribution methods.

[0015] According to another aspect of the present invention, a computer device is also provided, comprising: a memory and a processor, the memory storing a computer program; and a processor for executing the computer program stored in the memory, wherein the computer program, when running, causes the processor to execute any of the above-described power distribution methods.

[0016] In this embodiment of the invention, a multi-layered coordinated regulation approach is adopted. The power allocation area is divided into different levels, and different power allocation strategies are used for different levels of allocation areas. For example, the first allocation area determines a first power allocation strategy for the second allocation area within the first allocation area based on its basic allocation constraints. The second allocation area then determines a second power allocation strategy for the third allocation area within the second allocation area based on the power allocation results under the first power allocation strategy and the current electricity price within the second allocation area. Subsequently, the third allocation area determines a third power allocation strategy for the load terminals within the third allocation area based on the power allocation results under the second power allocation strategy and the electricity consumption of the load terminals within the third allocation area. This achieves the goal of using different power allocation strategies for different levels of allocation areas, thereby improving the utilization efficiency of the power grid, enhancing grid security, and improving the rationality of power allocation, thus solving the technical problem of unreasonable power allocation. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of an energy distribution method provided according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of an intelligent load management system for orderly power consumption provided according to an optional embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a four-layer node of an intelligent load management system for orderly power consumption provided according to an optional embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of determining the power supply coefficient based on a neural network according to an optional embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of regional electricity consumption curves provided according to an optional embodiment of the present invention;

[0023] Figure 6 This is a structural block diagram of an energy distribution device provided according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] Orderly electricity use refers to the management work of controlling some of the electricity demand of users on the demand side through administrative measures, economic means, and technical methods in the event of insufficient power supply or sudden accidents (events), so as to ensure the safety of the power supply of the large power grid and maintain the stable and orderly order of power supply and use.

[0027] The power load management system has been incorporated into the electricity consumption information collection system, becoming the main technical means for collecting electricity consumption information from customers of dedicated transformers.

[0028] The existing intelligent load management system for orderly electricity consumption still has the following problems:

[0029] 1) Existing orderly power consumption intelligent load management systems mostly adopt policy-regulated power consumption restriction methods. They typically use historical power consumption and demand information from various regions to allocate power supply to the transmission network. The rationality of power allocation is insufficient, resulting in some enterprises that urgently need power limiting their energy consumption and reducing production, and the overall efficiency of power consumption is low.

[0030] 2) While power supply-side regulation can ensure the safe operation of the power grid during orderly power consumption, its dynamic regulation capability on the power demand side is weak. It has not carried out system optimization at the levels of regional networks, buildings / parks, and smart electrical equipment, resulting in insufficient optimization of the power grid supply and demand relationship.

[0031] 3) When optimizing the orderly electricity load using electricity price regulation, the electricity price is mostly determined by the government, and the regulatory role of electricity price factors is not brought into play.

[0032] To address the aforementioned problems, this invention provides a method embodiment for power distribution. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] Figure 1 This is a flowchart of an energy distribution method provided according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0034] Step S102: Based on the basic allocation constraints corresponding to the first allocation area, determine the first power allocation strategy for the second allocation area within the first allocation area;

[0035] Step S104: Based on the first power allocation strategy and the current electricity price, determine the second power allocation strategy for the third allocation area within the second allocation area;

[0036] Step S106: Based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, determine the third power allocation strategy for the load terminals.

[0037] Through the above steps, a multi-layered coordinated regulation approach is adopted. This involves dividing the power distribution area into different levels, with each level employing a different power distribution strategy. For example, based on its basic distribution constraints, the first distribution area determines a first power distribution strategy for the second distribution area within the first distribution area. The second distribution area then determines a second power distribution strategy for the third distribution area based on the power distribution results under the first strategy and the current electricity price within the second distribution area. Finally, the third distribution area determines a third power distribution strategy for its load terminals based on the power distribution results under the second strategy and the electricity consumption of the load terminals within the third distribution area. This achieves the goal of using different power distribution strategies for different levels of distribution areas, thereby improving the utilization efficiency of the power grid, enhancing grid security, and increasing the rationality of power distribution. Ultimately, this solves the technical problem of unreasonable power distribution.

[0038] It should be noted that the first, second, and third allocation areas mentioned above can be specifically set according to the actual application scenario. For example, the first allocation area can be set as the power transmission network, the second allocation area can be set as a certain area in the power transmission network, and the third allocation area can be set as a certain building park in the second allocation area, and so on.

[0039] It should be noted that within the aforementioned first, second, and third distribution areas, a decision-making center and a load control center can be respectively established. The decision-making center performs calculations and analyses on the power allocation based on the information it receives, and sends decision commands to the load control center at the same level based on the results. The load control center then controls the power load within its current level according to the received decision commands. Furthermore, smart meters can be installed in the first, second, and third distribution areas, as well as at the load terminals. These smart meters can be used to monitor the power load in real time and provide power metering functionality.

[0040] As an optional embodiment, a first power allocation strategy for a second allocation area within the first allocation area is determined based on the basic allocation constraints corresponding to the first allocation area. This includes: determining the power supply coefficient of the second allocation area based on the power demand data, historical power consumption data, and power supply importance of the second allocation area; and determining the first power allocation strategy based on the basic allocation constraints and the power supply coefficient.

[0041] On the one hand, the electricity load in the first allocation area can be restricted as a whole through basic allocation constraints. For example, policy adjustments can be used to impose large-scale electricity restrictions on the first allocation area. On the other hand, the electricity load allocated to the second allocation area can be specifically adjusted by determining the power supply coefficient. The power supply coefficient can be determined based on the electricity demand data, historical electricity data, power supply importance, and the power supply capacity of the first allocation area when transmitting electricity to the second allocation area. Preferably, the determination of the power supply coefficient can be achieved using a neural network model. For example, first, obtain the electricity demand data, historical electricity data, industry power supply importance data, and the total power supply capacity of the power grid to transmit electricity to the N second allocation areas for N second allocation areas. Then, input the above data into the neural network, and the neural network outputs the power supply coefficient for each area. The calculation formula for the first power allocation strategy is as follows:

[0042]

[0043] Where P1, P2, ..., PN represent the load demand of N second distribution areas, P0 represents the total transmission capacity of the power supply network, and r1, r2, ..., rN represent the power supply coefficients. i ′ represents the power distribution load corresponding to each second allocation area.

[0044] This embodiment uses a neural network to allocate electricity demand in the second allocation area, fully considering electricity demand data, historical electricity data, and industry power supply importance data, thereby improving the rationality of electricity allocation.

[0045] As an optional embodiment, determining a second power allocation strategy for a third allocation area within a second allocation area based on a first power allocation strategy and the current electricity price includes: obtaining a power consumption forecast curve for the second allocation area within a predetermined time range based on the first power allocation strategy; determining a power gap value when the demand power of the third allocation area is greater than the maximum power supplied by the second allocation area, and a power surplus value when the demand power of the third allocation area is less than the maximum power supplied by the second allocation area, based on the power consumption forecast curve; determining an adjustment coefficient based on the ratio between the power gap value and the power surplus value; and adjusting the current electricity price based on the adjustment coefficient to obtain the second power allocation strategy.

[0046] Among them, the power gap value is the integral of the difference between the demand power and the maximum supply power over time when the demand power in the electricity consumption forecast curve is greater than the maximum supply power, and the power surplus value is the integral of the difference between the demand power and the maximum supply power over time when the demand power in the electricity consumption forecast curve is less than the maximum supply power.

[0047] After completing the power allocation from the first allocation area to the second allocation area based on the first power allocation strategy, the power allocation strategy from the second allocation area to the third allocation area can be determined. For example, the power consumption forecast curve of the second allocation area within a predetermined time range can be obtained first, so as to know the power consumption change of the second allocation area within the predetermined time range, and thus determine the power supply and demand situation of the second allocation area, that is, the power gap when the demand power is greater than the maximum supply power, and the power surplus when the demand power is less than the maximum supply power. When determining the adjustment coefficient, on the one hand, it can be determined by the time periods corresponding to the power gap and the power surplus and their power difference relative to the balance of power supply and demand. On the other hand, the adjustment coefficient can also be determined by the ratio between the power gap value and the power surplus value.

[0048] For example, when determining the adjustment coefficient based on the ratio between the power deficit value and the power surplus value, the larger the ratio, the larger the power load deficit in the second allocation area, which means that peak shaving and valley filling need to be strengthened. Therefore, a piecewise function can be used to set a threshold. When the ratio is less than or equal to the threshold, a smaller adjustment coefficient is used, and when the ratio is greater than the threshold, a larger adjustment coefficient is used, and so on.

[0049] It should be noted that the adjustment coefficients mentioned above are used to adjust the current electricity price to obtain the second electricity allocation strategy described above. The adjusted electricity price is calculated as follows:

[0050]

[0051] Where St is the adjusted electricity price, S0 is the current electricity price, Pt is the electricity consumption forecast curve for the second allocation area, and P i ′ represents the maximum transmission power of the second allocation area, u0 is the threshold mentioned above, h1 and h2 are adjustment coefficients, and h1 < h2.

[0052] This embodiment proposes a method for determining electricity prices by adopting a price adjustment approach, which promotes automatic load adjustment in the third allocation area based on the adjusted electricity price, thereby improving the overall electricity utilization efficiency.

[0053] In addition, when the load still exceeds the maximum power supply of the second allocation area under the adjusted electricity price, this embodiment can limit the power load by taking a mandatory restriction method to prevent grid collapse and improve the safety of grid operation.

[0054] As an optional embodiment, a third power allocation strategy for the load terminals is determined based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, including: determining the power consumption task of the load terminals based on the power consumption type and power demand of the load terminals; and determining the third power allocation strategy based on the second power allocation strategy and the power consumption task of the load terminals.

[0055] When determining the power allocation strategy for each load terminal in the third allocation area, a task adjustment approach can be adopted. For example, the power consumption task of the load terminal can be determined based on its power consumption type and required power. The power consumption type of the load terminal can be determined by its type, such as an energy storage device, a work equipment, etc. Different power consumption types may have different power consumption characteristics. The required power can be determined by the power required by the load terminal, such as a device that requires high power, etc., or it can be the trigger limit power of the load terminal, i.e., the minimum power required by the load terminal, etc.

[0056] Once the electricity consumption tasks are determined, a third electricity allocation strategy can be derived by combining a second electricity allocation strategy (e.g., adjusted electricity prices) to adjust the electricity consumption time and power consumption of each load terminal. For example, for energy storage devices (such as electric vehicles), charging operations can be carried out according to the lowest motor time; for operating equipment, high-power electrical devices can be adjusted to operate during off-peak hours, or their power can be appropriately reduced during peak hours; under power constraints, the power supply of necessary facilities (such as control systems, information and communication systems, etc.) can be prioritized according to the importance of the load terminal's operation, while the electricity load of non-essential facilities can be reduced.

[0057] Preferably, this embodiment can also use a multi-objective optimization approach to optimize the power load of each load terminal. For example, the following calculation method can be used:

[0058] J = Pareto{F1,F2,F3}

[0059] Where Pareto{} represents taking the Pareto optimal solution, F1 is the electricity price factor, F2 is the impact of power supply, and F3 is the potential loss due to power limitation.

[0060] Based on the third power allocation strategy, load terminals can optimize their own power load by adjusting their power consumption time and power. Load terminals such as lighting systems, air conditioning systems, and factory machinery are mainly optimized according to task necessity and policy requirements, making appropriate adjustments to working hours and power to meet the needs of orderly power consumption. For example, when the power load exceeds the maximum capacity of the power supply network, the lighting system automatically reduces brightness and power; the air conditioning system raises the cooling temperature or lowers the heating temperature; and factory machinery reduces its operating speed while ensuring basic functions are maintained.

[0061] As an optional embodiment, after determining the first power allocation strategy for the second allocation area within the first allocation area based on the basic allocation constraints corresponding to the first allocation area, the method further includes: receiving the first load usage of the second allocation area under the first power allocation strategy; and adjusting the first power allocation strategy based on the first load usage and the basic allocation constraints. The first allocation area, based on the communication network, can receive actual power load information from the second and third allocation areas. By analyzing and calculating the information reported by the second and third allocation areas, and controlling the power load provided by the first allocation area according to the analysis and calculation results, it can reduce or even cut off the output power as needed, and increase or decrease the output power of one or more second allocation areas, thereby achieving feedback adjustment of the first power allocation strategy.

[0062] As an optional embodiment, after determining the second power allocation strategy for the third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price, the method further includes: receiving the second load usage of the third allocation area under the second power allocation strategy; and adjusting the second power allocation strategy based on the second load usage, the first power allocation strategy, and the current electricity price. The second allocation area, based on the communication network, can receive actual power load information from the third allocation area. It analyzes and calculates the information reported by the third allocation area and controls the electricity price within the second allocation area based on the analysis and calculation results. Furthermore, based on the above analysis and calculation results, it can also control the power load supplied by the second allocation area to the third allocation area, etc. For example, similar to the first allocation area, the second allocation area can also reduce or even cut off its output power as needed, and increase or decrease the output power of one or more third allocation areas, thereby achieving feedback adjustment of the second power allocation strategy.

[0063] As an optional embodiment, after determining the third power allocation strategy for the load terminals based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, the method further includes: receiving the third load usage of the load terminals under the third power allocation strategy; and adjusting the third power allocation strategy based on the third load usage, the second power allocation strategy, and the power consumption of the load terminals. The third allocation area, based on the communication network, can receive the actual power load information of each load terminal within the third allocation area. By analyzing and calculating the information reported by the third allocation area, and controlling the power load provided by the third allocation area according to the analysis and calculation results, the output power can be reduced or even cut off as needed, and the output power of one or more load terminals can be increased or decreased, thereby achieving feedback adjustment of the third power allocation strategy.

[0064] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method, which will be described below.

[0065] An optional embodiment of the present invention proposes an intelligent load management system for orderly power consumption.

[0066] Figure 2 This is a schematic diagram of an intelligent load management system for orderly electricity consumption provided according to an optional embodiment of the present invention. Figure 3 This is a schematic diagram of a four-layer node of an intelligent load management system for orderly power consumption provided according to an optional embodiment of the present invention, as shown below. Figure 2 and Figure 3 As shown, the system adopts a four-layer collaborative management model to achieve optimal load management in the orderly use of electricity in the power grid.

[0067] The intelligent load management system mainly consists of smart meters, load control units, communication networks, and multi-level decision control centers.

[0068] 1) Smart meters are mainly used to monitor the power load at various nodes and provide power metering functions;

[0069] 2) Load control center, mainly located at nodes of the transmission network, controls the power distribution of the transmission network;

[0070] 3) The decision control center mainly uses data from the power transmission and distribution network, the demand for orderly power consumption tasks, and other tasks as inputs to make decisions on the load control mode of the power consumption nodes under this level, and manages the information data;

[0071] 4) Communication network, mainly used for information communication with smart meters, load control units, decision centers, etc., to complete functions such as information acquisition and decision information dissemination.

[0072] The intelligent load management system adopts a four-layer collaborative management model to configure power grid nodes, specifically including:

[0073] 1) Transmission network main node

[0074] This system is used for large-scale load regulation using policies. It mainly includes a central decision control center and a central load control center. The central decision control center, based on the communication network, can receive decision information from regional decision centers and building / park decision centers. It analyzes and calculates the information reported by the regional and building / park decision centers, issues load control decision instructions to the central load control center, and feeds back the total load status information and decision information to the regional and building / park node layers. The central load control center can control the power load provided by the total power transmission and distribution network, reduce or even cut off the output power as needed, and increase or decrease the total transmission power of a certain area.

[0075] 2) Regional nodes

[0076] Located one level below the transmission network summary point, it is used to adjust prices in conjunction with market prices. It mainly includes a regional decision control center and a load control center. The regional decision control center can receive decision information from the central decision center and building / park decision centers through the communication network. It analyzes and calculates the decision information issued by the central decision center and the information reported by the building / park decision centers, issues load control decision instructions to the regional load control center, and feeds back the load status information and decision information of the node to the central node level. The regional load control center can control the power load provided by the regional transmission and distribution network, reduce or even cut off the output power as needed, and increase or decrease the total transmission power of a certain building / park.

[0077] 3) Building / Park Nodes

[0078] Located one level below the regional node, it is used for power consumption adjustment in conjunction with power consumption tasks. It mainly includes a building / park decision control center and a load control center. The building / park decision control center can collect smart meter data at each terminal stage based on the communication network, receive decision information from the regional decision center and the overall decision center, analyze and calculate based on the decision information issued by the overall decision center and the regional decision center and the smart meter summary information, issue load control decision instructions to the building / park load control center, and feed back the load status information and decision information of the node to the upper level. The building / park load control center can control the power load provided by the building / park power distribution network according to the received decision instructions, reduce or even cut off the output power as needed, and increase or decrease the total transmission power of a certain terminal.

[0079] 4) Intelligent terminal node

[0080] Located one floor below the building / park node, it is used to adjust power consumption based on working hours and power usage. Smart meters are installed on the terminal electrical equipment to monitor power consumption data in real time and upload it to the building / park decision-making and control center via a communication network.

[0081] Based on the above system, an optional embodiment of the present invention also proposes an intelligent load management method for orderly power consumption.

[0082] 1) Transmission network general node layer

[0083] Regional electricity load is allocated and restricted through policy regulation. A comprehensive analysis is conducted based on historical electricity consumption data, electricity demand scale, and the characteristics of electricity-consuming industries. The power regulation coefficient is dynamically adjusted using a neural network.

[0084] 1. Obtain electricity demand data, historical electricity consumption data, industry power supply importance data, and the total power supply capacity of the power supply network to the N regional nodes for N regional nodes.

[0085] 2. Input the above data into the neural network, and the neural network outputs the power supply coefficient for each region. Figure 4 This is a schematic diagram of determining the power supply coefficient based on a neural network according to an optional embodiment of the present invention.

[0086] The load demands of N regional nodes are P1, P2, ..., PN, and the total transmission capacity of the power supply network is P0. After obtaining the power supply coefficients r1, r2, ..., rN, the distribution load P of each region is then calculated. i 'for:

[0087]

[0088] 2) Regional Node Layer

[0089] The main approach is to optimize and limit the electricity load at nodes such as parks and buildings by adjusting market prices.

[0090] First, price regulation methods, such as peak-valley electricity pricing, can be used to encourage electricity users to automatically adjust their loads. Second, maximum power limiting measures can be implemented to limit load.

[0091] Figure 5 This is a schematic diagram of regional electricity consumption curves provided according to an optional embodiment of the present invention, such as... Figure 5 As shown, taking the i-th region as an example, let the conventional electricity price be S0 yuan / kWh, the regional electricity consumption forecast curve be Pt, and the regional maximum transmission power be P. i ', optimize the price according to the following formula:

[0092]

[0093] The above formula first determines the ratio of power deficit to power surplus. Power deficit refers to the integral of the difference between demand power and maximum supply power over time; power surplus refers to the integral of the difference between maximum supply power and demand power over time. Then, the electricity price is adjusted according to the ratio. The larger the ratio, the larger the power load deficit, and the more necessary it is to strengthen peak shaving and valley filling. Therefore, a threshold u0 is set. When the ratio is less than or equal to u0, a smaller adjustment coefficient h1 is used, and when the ratio is greater than u0, a larger adjustment coefficient h2 is used for adjustment.

[0094] Furthermore, when electricity prices are used as a regulation tool, if the load still exceeds the maximum available power, a mandatory load limiting method is adopted to prevent grid collapse. In practice, the maximum power of each building / park node is pre-allocated according to the needs of each unit. If the total power does not exceed the limit, each building / park node can exceed the limit power; if the total power of the area reaches the maximum input power, load limiting is triggered, and each building / park node is limited according to the pre-allocated power.

[0095] 3) Building / Park Node Layer

[0096] The main approach is to optimize and limit the power load of smart terminal nodes by adjusting the task load.

[0097] Buildings / parks primarily optimize power consumption tasks based on electricity prices and trigger-limited power requirements. The following rules are adopted:

[0098] 1. All energy storage devices, such as electric vehicles, should be charged during the period with the lowest electricity price.

[0099] 2. Adjust the operating sequence of the equipment, shift high-power electrical devices to off-peak periods, or appropriately reduce power during peak electricity consumption periods.

[0100] 3. Under power constraints, priority should be given to ensuring power supply to essential facilities, such as control systems and information communication systems, while reducing the power load on non-essential facilities.

[0101] In addition, for some buildings / parks that consume a lot of electricity, multi-objective optimization can be used to optimize the electricity load.

[0102] J = Pareto{F1,F2,F3}

[0103] Where Pareto{} represents taking the Pareto optimal solution, F1 is the electricity price factor, F2 is the impact of power supply, and F3 is the potential loss due to power limitation.

[0104] 4) Intelligent terminal node layer

[0105] The main approach is to optimize its own electrical load by adjusting working time and power.

[0106] Intelligent terminals, such as lighting systems, air conditioning systems, and factory machinery, are optimized mainly based on task necessity and policy requirements, with appropriate adjustments to working hours and power consumption to meet the needs of orderly electricity use.

[0107] For example, when the electrical load exceeds the maximum capacity of the power supply network, the lighting system automatically reduces brightness and power; the air conditioning system raises the cooling temperature or lowers the heating temperature; and factory machines reduce their operating speed while ensuring basic functions are maintained.

[0108] In summary, the optional embodiments of the present invention have the following beneficial effects:

[0109] 1) An optimization approach is adopted at four levels, namely, overall nodes, regional nodes, building / park nodes, and smart power terminals. This improves the utilization efficiency of the power grid and is consistent with existing management methods, making it easy to implement.

[0110] 2) The use of neural networks to allocate electricity demand in various regions fully considers electricity demand data, historical electricity data, and industry power supply importance data, thereby improving the rationality of electricity allocation.

[0111] 3) By adopting a price adjustment approach, a method for determining electricity prices was proposed, which promotes automatic load adjustment by electricity users and improves the overall efficiency of electricity utilization.

[0112] 4) For buildings / parks, a task adjustment method was proposed to reasonably avoid peak electricity consumption while ensuring normal and orderly production and life, and to enhance the safety of the power grid.

[0113] According to an embodiment of the present invention, an electrical power distribution device is also provided. Figure 6 This is a structural block diagram of an energy distribution device provided according to an embodiment of the present invention, such as... Figure 6 As shown, the device includes a first determining module 61, a second determining module 62, and a third determining module 63. The device will be described below.

[0114] The first determining module 61 is used to determine a first power allocation strategy for a second allocation area within the first allocation area based on the basic allocation constraints corresponding to the first allocation area; the second determining module 62 is connected to the first determining module 61 and is used to determine a second power allocation strategy for a third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price; the third determining module 63 is connected to the second determining module 62 and is used to determine a third power allocation strategy for a load terminal based on the second power allocation strategy and the power consumption of the load terminal within the third allocation area.

[0115] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform any of the above-described power distribution methods.

[0116] According to an embodiment of the present invention, a computer device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program; and the processor is configured to execute the computer program stored in the memory, wherein the computer program, when running, causes the processor to execute any of the above-described power distribution methods.

[0117] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0118] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0119] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0120] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0121] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0122] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0123] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for distributing electrical energy, characterized in that, include: Based on the basic allocation constraints corresponding to the first allocation region, a first power allocation strategy for the second allocation region within the first allocation region is determined. Based on the first power allocation strategy and the current electricity price, determine the second power allocation strategy for the third allocation area within the second allocation area; Based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area, the third power allocation strategy for the load terminals is determined. The step of determining the first power allocation strategy for the second allocation area within the first allocation area based on the basic allocation constraints corresponding to the first allocation area includes: determining the power supply coefficient of the second allocation area based on the power demand data, historical power consumption data, and power supply importance of the second allocation area using a neural network model; and determining the first power allocation strategy based on the basic allocation constraints and the power supply coefficient, using the following calculation formula: ， Among them, P i Let P0 be the load demand of the i-th second distribution area, and r be the total transmission capacity of the power supply network. i The power supply coefficient for the i-th second allocation region. For the power distribution load corresponding to the i-th second allocation area; The step of determining a second power allocation strategy for a third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price includes: obtaining a power consumption forecast curve for the second allocation area within a predetermined time range based on the first power allocation strategy; determining a power gap value when the demand power of the third allocation area is greater than the maximum power supplied by the second allocation area, and a power surplus value when the demand power of the third allocation area is less than the maximum power supplied by the second allocation area, based on the power consumption forecast curve; determining an adjustment coefficient based on the ratio between the power gap value and the power surplus value; and adjusting the current electricity price based on the adjustment coefficient to obtain the second power allocation strategy.

2. The method according to claim 1, characterized in that, The step of determining the third power allocation strategy for the load terminals based on the second power allocation strategy and the power consumption of the load terminals in the third allocation area includes: Based on the power consumption type and power demand of the load terminal, the power consumption task of the load terminal is determined. The third power allocation strategy is determined based on the second power allocation strategy and the power consumption task of the load terminal.

3. The method according to claim 1, characterized in that, After determining the first power allocation strategy for the second allocation region within the first allocation region based on the basic allocation constraints corresponding to the first allocation region, the method further includes: Receive the first load usage information of the second allocation area under the first power allocation strategy; Based on the first load usage and the basic allocation constraints, the first power allocation strategy is adjusted.

4. The method according to claim 1, characterized in that, After determining the second power allocation strategy for the third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price, the method further includes: Receive the second load usage status of the third allocation area under the second power allocation strategy; Based on the second load usage, the first power allocation strategy and the current electricity price, the second power allocation strategy is adjusted.

5. The method according to claim 1, characterized in that, After determining the third power allocation strategy for the load terminals based on the second power allocation strategy and the power consumption of the load terminals within the third allocation area, the method further includes: Receive the third load usage information of the load terminal under the third power distribution strategy; Based on the third load usage, the second power allocation strategy, and the power consumption of the load terminal, the third power allocation strategy is adjusted.

6. An electrical energy distribution device, characterized in that, include: The first determining module is used to determine the first power allocation strategy of the second allocation area within the first allocation area based on the basic allocation constraints corresponding to the first allocation area; The second determining module is used to determine the second power allocation strategy of the third allocation area within the second allocation area based on the first power allocation strategy and the current electricity price. The third determining module is used to determine the third power allocation strategy for the load terminal based on the second power allocation strategy and the power consumption of the load terminal in the third allocation area. The first determining module is further configured to determine the power supply coefficient of the second allocation area based on the electricity demand data, historical electricity data, and power supply importance of the second allocation area, using a neural network model; and to determine the first power allocation strategy based on the basic allocation constraints and the power supply coefficient, using the following calculation formula: ， Among them, P i Let P0 be the load demand of the i-th second distribution area, and r be the total transmission capacity of the power supply network. i The power supply coefficient for the i-th second allocation region. For the power distribution load corresponding to the i-th second allocation area; The second determining module is further configured to: obtain the electricity consumption forecast curve of the second allocation area within a predetermined time range based on the first electricity allocation strategy; determine the power gap value when the demand power of the third allocation area is greater than the maximum supply power of the second allocation area, and the power surplus value when the demand power of the third allocation area is less than the maximum supply power of the second allocation area, based on the electricity consumption forecast curve; determine an adjustment coefficient based on the ratio between the power gap value and the power surplus value; and adjust the current electricity price based on the adjustment coefficient to obtain the second electricity allocation strategy.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the power distribution method according to any one of claims 1 to 5.

8. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the power distribution method according to any one of claims 1 to 5.

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