Power distribution network dispatching method and device and computer equipment

Abstract

The invention relates to a power distribution network dispatching method and device and computer equipment. The method comprises the following steps: determining a load equipment cluster accessed to a power distribution network, wherein the load equipment cluster comprises at least one piece of load equipment; constructing a cluster state change model of the load equipment cluster based on the access state parameter and the access quantity parameter in the process of accessing the load equipment cluster to the power distribution network; determining respective device state distribution information of the at least one load device through a cluster state change model; based on the equipment state distribution information, the day-ahead operation data of the power distribution network and the carbon emission information of the power distribution network, determining power distribution cost information of the power distribution network for a load equipment cluster; and power distribution scheduling information of the power distribution network is obtained according to the power distribution cost information, and power distribution scheduling is performed on the at least one load device according to the power distribution scheduling information, so that the scheduling cost and the carbon emission are effectively balanced, and efficient and economical power low-carbon scheduling is realized.

Description

Technical Field

[0001] The present application relates to the technical field of low-carbon dispatching of power grids, and in particular to a distribution network dispatching method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] In order to achieve the control of carbon emissions in the power industry and power system, low-carbon dispatch is a means of regulation covering all aspects of the power system, including source, grid, and load. By calling low-carbon generators, carrying out load demand response, and applying energy storage and other resources, low-carbon dispatch of the power system can be achieved, which is conducive to the construction of a new clean and low-carbon power system. For the research on low-carbon dispatch, the focus has gradually shifted from calling low-carbon generators to demand response on the load side. Establishing low-carbon optimized dispatch of flexible loads such as electric vehicles (EVs) participating in the power system has gradually become an important means to reduce carbon emissions.

[0003] As a mobile storage resource, EV is different from other conventional loads in the power system. It can not only charge at any node in the power system, but also feed back to the nodes in the system through vehicle-to-grid (V2G) technology. Through low-carbon scheduling, EV users can change the charging period of EV while maintaining the charging demand unchanged, encouraging users to use electricity during low-carbon periods and reduce carbon emissions.

[0004] However, most of the existing low-carbon dispatching technologies achieve low-carbon dispatching by optimizing power supply or load demand response. For EVs participating in distribution networks to achieve low-carbon dispatching, it is difficult to balance the reduction of carbon emissions and the control of dispatching costs, which may lead to sacrificing cost-effectiveness in the pursuit of low-carbon goals, or ignoring the effective management of carbon emissions when reducing costs. Summary of the invention

[0005] Based on this, it is necessary to provide a distribution network dispatching method, device, computer equipment, computer-readable storage medium and computer program product that can effectively balance the dispatching cost and carbon emissions in response to the above-mentioned technical problems.

[0006] In a first aspect, the present application provides a distribution network scheduling method, the method comprising:

[0007] Determine a load device cluster connected to the power distribution network, wherein the load device cluster includes at least one load device;

[0008] Based on the access state parameters and access quantity parameters of the load device cluster in the process of accessing the load device cluster to the distribution network, construct a cluster state change model of the load device cluster;

[0009] Determining device state distribution information of each of the at least one load devices through the cluster state change model;

[0010] Determine the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network;

[0011] Power distribution scheduling information of the distribution network is obtained according to the power distribution cost information, and power distribution scheduling is performed for the at least one load device according to the power distribution scheduling information.

[0012] In one embodiment, determining the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network includes:

[0013] According to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network, a distribution scheduling cost function is constructed with the goal of minimizing the distribution cost of the distribution network for the load equipment cluster;

[0014] Determining constraints of the power distribution scheduling cost function;

[0015] According to the power distribution scheduling cost function and the constraint condition, power distribution cost information of the power distribution network for the load device cluster is determined.

[0016] In one embodiment, the power distribution scheduling cost function is constructed based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network, with the goal of minimizing the power distribution cost of the distribution network for the load device cluster, including:

[0017] Determine the load dispatching cost of the distribution network within a preset time period according to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network;

[0018] Determine the total carbon emissions of the distribution network within the preset period according to the device status distribution information and the carbon emission information of the distribution network, and determine the carbon emission cost of the distribution network within the preset period according to the total carbon emissions and the carbon emission cost conversion coefficient of the distribution network;

[0019] A distribution scheduling cost function is constructed based on the goal of minimizing the sum of the load scheduling cost and the carbon emission cost.

[0020] In one embodiment, determining the load dispatching cost of the distribution network within a preset period of time according to the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network includes:

[0021] Determine the charging cost of the load device cluster within a preset time period according to the device status distribution information, the charging power of the at least one load device and the charging electricity price of at least one load device in the day-ahead operation data of the distribution network;

[0022] Determine the electricity cost of the user side in the distribution network within the preset time period according to the carbon emission information of the distribution network and the load electricity price in the day-ahead operation data of the distribution network;

[0023] Based on the charging cost and the electricity cost, a load dispatching cost of the distribution network within a preset time period is determined.

[0024] In one embodiment, determining the total carbon emissions of the distribution network within the preset period according to the device status distribution information and the carbon emission information of the distribution network includes:

[0025] Determining the charging power of the load device cluster within a preset time period according to the device state distribution information and the charging power of the at least one load device;

[0026] Determining the active power of the user side in the distribution network within the preset time period according to the carbon emission information of the distribution network;

[0027] Based on the active power, the charging power of the load device cluster and the dynamic carbon emission factor in the carbon emission information, the total carbon emissions of the distribution network within the preset time period are determined.

[0028] In one embodiment, the method further comprises:

[0029] Determine access status parameters of load devices accessing and leaving the distribution network according to the access status of the load device cluster accessing the distribution network; the access status includes charging state, idle state and discharging state;

[0030] The access quantity parameters of the load devices of the load device cluster in the charging state, the idle state and the discharging state are determined respectively.

[0031] In one embodiment, respectively determining the access quantity parameters of the load devices of the load device cluster in the charging state, the idle state, and the discharging state includes:

[0032] respectively determining a state of charge parameter of the load device in the charging state, the idle state, and the discharging state;

[0033] According to the access state of the load device and the charge state parameter, the state sub-interval of the load device is determined, and the number of the load devices in each state sub-interval is obtained; the state sub-interval is formed by discretizing the charge state of the load device according to the charge variation range of the load device;

[0034] For each of the state sub-intervals, an access quantity parameter of the number of the load devices in the state sub-interval is determined according to the number of the load devices and the state of charge parameter.

[0035] In a second aspect, the present application further provides a distribution network dispatching device, the device comprising:

[0036] A cluster determination module, used to determine a load device cluster connected to the power distribution network, wherein the load device cluster includes at least one load device;

[0037] A model building module, used to build a cluster state change model of the load device cluster based on the access state parameter and access quantity parameter of the load device cluster in the process of accessing the load device cluster to the distribution network;

[0038] A state determination module, used to determine the device state distribution information of each of the at least one load devices through the cluster state change model;

[0039] A cost determination module, configured to determine the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network;

[0040] A dispatching control module is used to obtain power distribution dispatching information of the distribution network according to the power distribution cost information, and perform power distribution dispatching for the at least one load device according to the power distribution dispatching information.

[0041] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0043] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0044] The above-mentioned distribution network dispatching method, apparatus, computer equipment, computer-readable storage medium and computer program product determine a load device cluster connected to the distribution network, wherein the load device cluster includes at least one load device; construct a cluster state change model of the load device cluster based on the access state parameter and access quantity parameter of the load device cluster in the process of accessing the distribution network; determine the device state distribution information of at least one load device through the cluster state change model; determine the distribution cost information of the distribution network for the load device cluster based on the device state distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network; obtain the distribution dispatching information of the distribution network according to the distribution cost information, and dispatch the distribution device according to the distribution dispatching information; The power distribution scheduling is performed for at least one load device based on the degree information; by comprehensively considering the access status, quantity and equipment status distribution information of the load equipment cluster, the power distribution cost of the distribution network can be evaluated more accurately. Combined with the carbon emission information of the distribution network, the carbon emissions can be effectively reduced under the premise of ensuring the reasonable power distribution cost, and an effective balance between scheduling costs and carbon emissions can be achieved; at the same time, by constructing a cluster state change model of the load equipment cluster, the state change of the load equipment cluster can be tracked and predicted in real time, so as to more accurately determine the equipment status distribution information of each load device, which is conducive to more accurate execution of power distribution scheduling, reducing scheduling errors caused by uncertain equipment status, and improving the overall accuracy and reliability of scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 An application environment diagram of a distribution network dispatching method in an embodiment;

[0047] Figure 2 A schematic diagram of a flow chart of a distribution network dispatching method in one embodiment;

[0048] Figure 3 A schematic diagram of a process for constructing a power distribution scheduling cost function in one embodiment;

[0049] Figure 4 is a structural block diagram of a distribution network dispatching device in one embodiment;

[0050] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] The distribution network dispatching method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 determines the load device cluster connected to the distribution network, and the load device cluster includes at least one load device. It can obtain the access state parameters and access quantity parameters of the load device cluster in the process of accessing the distribution network, and construct a cluster state change model of the load device cluster, and then determine the device state distribution information of at least one load device in the load device cluster; then, based on the device state distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network, determine the distribution cost information of the distribution network for the load device cluster, obtain the distribution scheduling information of the distribution network according to the distribution cost information, and perform distribution scheduling for at least one load device according to the distribution scheduling information.

[0053] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices may be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server 104 may be an independent physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0054] In an exemplary embodiment, Figure 2 As shown, a distribution network scheduling method is provided, which is applied to Figure 1 The server 104 in FIG. 1 is used as an example to illustrate. It is understandable that the method can also be applied to Figure 1 The terminal 102 in the embodiment may also be applied to a system including the terminal 102 and the server 104, and implemented through interaction between the terminal 102 and the server 104. The method of this embodiment includes:

[0055] Step 201: Determine a load device cluster connected to a power distribution network, wherein the load device cluster includes at least one load device.

[0056] Among them, the distribution network refers to the power network that receives electrical energy from the transmission network or large power plants and distributes it to users or electrical equipment. The distribution network usually includes substations, distribution lines, switchgear, etc. to safely and reliably transmit electrical energy to the user end.

[0057] Among them, the load device cluster refers to a collection of a series of load devices that are interrelated or work in coordination. The load devices can be various types of electrical appliances, motors, lighting equipment, etc., to form a group that can be connected to the distribution network for power consumption. In this embodiment, the load device mainly refers to a device with a bidirectional charging and discharging function, that is, a V2G device. The V2G device is a key device that can realize bidirectional energy transmission between the load device and the power grid through V2G technology. Taking electric vehicles as an example, electric vehicles can obtain electric energy from the power grid at rated power, and can also feed back electric energy to the power grid at rated power to achieve optimal configuration and efficient utilization of energy. In the charging mode, the power grid provides electric energy to the electric vehicle, the power electronic device converts AC power into DC power, and manages the battery charging process through the electric vehicle's BMS (Battery Management System); in the discharge mode, the battery of the electric vehicle converts DC power into AC power through the power electronic device and feeds it back to the power grid.

[0058] Exemplarily, taking electric vehicles as load devices, the server determines an electric vehicle cluster connected to the distribution network, in which there is at least one electric vehicle, so as to achieve optimal configuration and efficient use of energy through the access of the electric vehicle cluster.

[0059] It is understandable that in some other embodiments, the load device may also be other devices with bidirectional charging and discharging functions, such as other electric vehicles, energy storage devices, emergency power supplies, etc.

[0060] Step 202: construct a cluster state change model of the load device cluster based on the access state parameters and access quantity parameters in the process of the load device cluster being connected to the distribution network.

[0061] Among them, the access state parameter refers to the state distribution parameter that describes the state of each load device when the load device cluster is connected to the distribution network. It is used to reflect the state distribution of the load device when it is connected to and leaving the distribution network during distribution scheduling, that is, how many load devices are connected to the distribution network and participate in distribution scheduling at a certain moment, and how many load devices leave the distribution network and do not participate in distribution scheduling.

[0062] Among them, the access quantity parameter refers to the quantity change parameter of the load devices connected to the distribution network in the load device cluster, which is used to reflect the quantity change of the load devices when participating in the distribution scheduling, that is, the change rate of the number of load devices connected to the distribution network at a certain moment.

[0063] The cluster state change model refers to a mathematical model of how the state of a load device cluster changes over time. The cluster state change model can determine the real-time state of the load device based on information such as access state parameters and access quantity parameters, so as to facilitate power distribution scheduling based on this.

[0064] Exemplarily, the server constructs a cluster state change model of the electric vehicle cluster based on the state distribution parameters of each electric vehicle in the process of the electric vehicle cluster being connected to the distribution network and the number change parameters of the electric vehicles connected to the distribution network.

[0065] Step 203: Determine the device state distribution information of at least one load device through the cluster state change model.

[0066] Among them, the device status distribution information refers to the information on the status distribution of each device in the load device cluster, which is used to reflect the access status of each load device in the cluster at a certain moment and the number, number change and status distribution of load devices in the corresponding access state.

[0067] Exemplarily, the server determines the device status distribution information corresponding to each electric vehicle respectively by calling the constructed cluster status change model for each electric vehicle.

[0068] Step 204 : determining the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network.

[0069] Among them, the day-ahead operation data refers to the day-ahead clearing result data obtained from the electricity spot market, including but not limited to the interconnection line plan arrangement, the unit types and output arrangements of all generator sets in the power system and other data. The start-up, shutdown and output arrangements of the generator sets are based on the interconnection line plan, maintenance plan, etc., with the goal of minimizing the power generation cost, and are the results obtained through operations optimization. The generator set types and output arrangements include different types of unit types and output conditions such as coal-fired, gas-fired, hydropower, wind power, photovoltaic, biomass, etc. that have won bids in the electricity spot market.

[0070] Among them, carbon emission information refers to information describing the emission of greenhouse gases such as carbon dioxide generated by the distribution network during the power generation and distribution process, including but not limited to the power flow data of each branch in the distribution network and the carbon emission flow index data, which is used to evaluate the carbon emission responsibility of the distribution network. Among them, power flow data refers to data describing the voltage, active power, reactive power and steady-state distribution status of each node in the power system. Carbon emission flow index data refers to parameters for evaluating the carbon emission intensity and environmental impact of the power system, including but not limited to the carbon potential of each load node in the distribution network, dynamic carbon emission factors, active load of load nodes, etc.

[0071] Among them, the distribution cost information refers to the cost of describing the distribution network when using load equipment clusters to participate in distribution scheduling, which is used to formulate distribution scheduling plans and evaluate distribution efficiency.

[0072] Exemplarily, the server determines the distribution cost information of the distribution network for electric vehicle clusters participating in distribution scheduling based on the access status parameters and access quantity parameters in the equipment status distribution information, the unit type and output arrangement of the generator sets in the day-ahead operation data of the distribution network, and the flow data and carbon emission flow indicator data in the carbon emission information of the distribution network.

[0073] Step 205: Obtain power distribution scheduling information of the distribution network according to the power distribution cost information, and perform power distribution scheduling for at least one load device according to the power distribution scheduling information.

[0074] Among them, distribution dispatching information refers to the distribution network dispatching plan for load devices based on the participation in dispatching, which is determined based on the distribution cost information, including but not limited to the power supply sequence, power supply time, power supply amount and other information of each load device. The distribution dispatching information is used to guide the actual operation and dispatching operation of the distribution network.

[0075] Among them, distribution dispatching refers to the process of distributing and dispatching electric energy to load equipment according to distribution dispatching information to ensure the safe, reliable and economical operation of the power grid.

[0076] Exemplarily, the server determines the distribution scheduling information of the distribution network for the electric vehicle cluster based on the distribution cost information, the distribution scheduling information includes the power supply sequence, power supply time, power supply amount and other information of each electric vehicle, and performs distribution scheduling for each electric vehicle according to the power supply sequence, power supply time, power supply amount and other information.

[0077] In the above-mentioned distribution network dispatching method, a load device cluster connected to the distribution network is determined, and the load device cluster includes at least one load device; a cluster state change model of the load device cluster is constructed based on the access state parameters and access quantity parameters of the load device cluster in the process of accessing the distribution network; the device state distribution information of at least one load device is determined through the cluster state change model; the distribution cost information of the distribution network for the load device cluster is determined based on the device state distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network; the distribution dispatching information of the distribution network is obtained according to the distribution cost information, and the distribution dispatching information is dispatched for at least one load device according to the distribution dispatching information. Conduct power distribution scheduling; by comprehensively considering the access status, quantity and equipment status distribution information of the load equipment cluster, the distribution cost of the distribution network can be evaluated more accurately. Combined with the carbon emission information of the distribution network, it can effectively reduce carbon emissions while ensuring that the distribution cost is reasonable, and achieve an effective balance between scheduling costs and carbon emissions; at the same time, by constructing a cluster state change model of the load equipment cluster, it can track and predict the state changes of the load equipment cluster in real time, so as to more accurately determine the equipment status distribution information of each load equipment, which is conducive to more accurate execution of distribution scheduling, reducing scheduling errors caused by uncertain equipment status, and improving the overall accuracy and reliability of scheduling.

[0078] In one embodiment, determining power distribution cost information of a power distribution network for a load device cluster includes:

[0079] According to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network, a distribution scheduling cost function is constructed with the goal of minimizing the distribution cost of the distribution network for the load equipment cluster; the constraints of the distribution scheduling cost function are determined; and according to the distribution scheduling cost function and the constraints, the distribution cost information of the distribution network for the load equipment cluster is determined.

[0080] Among them, the distribution dispatch cost function refers to the function that describes the relationship between the distribution cost of the distribution network for the load equipment cluster and the information or data such as the equipment status distribution information, the day-ahead operation data and the carbon emission information. Through the distribution dispatch cost function, the optimal solution that minimizes the distribution cost can be found. Constraints refer to the restrictions considered when constructing the distribution dispatch cost function to ensure the rationality of the distribution dispatch plan in terms of feasibility and economy.

[0081] Among them, the distribution cost information refers to the distribution cost data of the distribution network for the load equipment cluster calculated based on the distribution scheduling cost function and constraints, which provides important data support for the scheduling decision of the distribution network.

[0082] Exemplarily, first, the server constructs a distribution scheduling cost function based on the relationship between the equipment status distribution information, the day-ahead operation data of the distribution network, the carbon emission information of the distribution network, and the distribution cost of the distribution network for the load equipment cluster, with the goal of minimizing the distribution cost. Then, the server determines the constraints of the distribution scheduling cost function based on the equipment status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network. Finally, the server iteratively solves the distribution scheduling cost function based on the distribution scheduling cost function and the constraints until the optimal solution that minimizes the distribution cost is obtained, so as to determine the distribution cost information of the distribution network for the load equipment cluster.

[0083] In this embodiment, by comprehensively considering the equipment status distribution information, the day-ahead operation data and the carbon emission information, a distribution scheduling cost function is constructed with the goal of minimizing the distribution cost, and its constraints are clarified. This can accurately determine the distribution cost information of the distribution network for the load equipment cluster, which is beneficial to improving the economy and environmental protection of the distribution network and achieving efficient and low-carbon configuration of power resources.

[0084] In one embodiment, Figure 3 As shown in the figure, with the goal of minimizing the distribution cost of the distribution network for the load equipment cluster, a distribution scheduling cost function is constructed, including:

[0085] Step 301, determining the load dispatching cost of the distribution network within a preset time period according to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network.

[0086] Among them, load dispatching cost refers to the total cost incurred by the distribution network for power dispatching to meet load demand within a preset period of time. It is used to reflect the relationship between equipment status distribution information, day-ahead operation data of the distribution network, and carbon emission information of the distribution network and load dispatching.

[0087] Exemplarily, the server determines the cost incurred by the distribution network for power dispatching to meet load demand within a preset time period based on the equipment status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network.

[0088] Step 302, determining the total carbon emissions of the distribution network within a preset period of time based on the equipment status distribution information and the carbon emission information of the distribution network, and determining the carbon emission cost of the distribution network within the preset period of time based on the total carbon emissions and the carbon emission cost conversion coefficient of the distribution network.

[0089] Among them, total carbon emissions refer to the total amount of greenhouse gases such as carbon dioxide generated by the distribution network due to power generation, transmission, distribution and other activities within a preset period of time.

[0090] Among them, the carbon emission cost conversion coefficient refers to the proportional coefficient of converting carbon emissions into economic costs, which is used to reflect the economic cost brought by each unit of carbon emissions. The carbon emission cost conversion coefficient is usually determined based on factors such as the carbon emission rights trading price and carbon tax.

[0091] Among them, carbon emission cost refers to the total economic cost incurred by the distribution network due to carbon emissions within a preset period, calculated based on the total carbon emissions and the carbon emission cost conversion coefficient.

[0092] Exemplarily, the server determines the total carbon emissions generated by the distribution network's power generation, transmission, distribution and other activities within a preset time period based on the determined equipment status distribution information and the carbon emission information of the distribution network, and determines the carbon emission cost generated by the distribution network's carbon emissions within the preset time period based on the total carbon emissions and the carbon emission cost conversion coefficient of the distribution network.

[0093] Step 303, constructing a distribution scheduling cost function based on the goal of minimizing the sum of load scheduling cost and carbon emission cost.

[0094] Among them, the goal of minimizing the sum of load dispatching cost and carbon emission cost means configuring and optimizing the operating parameters of the distribution network so that the sum of load dispatching cost and carbon emission cost is minimized while meeting basic needs and constraints.

[0095] Exemplarily, the server constructs a power distribution scheduling cost function based on the goal of minimizing the sum of load scheduling cost and carbon emission cost. The power distribution scheduling cost function is expressed as:

[0096] (1)

[0097] in, is the distribution dispatch cost function; is the load dispatch cost of the distribution network; is the total carbon emissions of the distribution network; is the carbon emission cost conversion coefficient of the distribution network; the product of the total carbon emissions and the carbon emission cost conversion coefficient This is the carbon emission cost of the distribution network.

[0098] Based on this, the goal is to minimize the distribution cost of the distribution network for the load device cluster, which is:

[0099] (2)

[0100] The above formula (2) represents minimizing the load dispatching cost and carbon emission cost.

[0101] In this embodiment, by comprehensively considering the equipment status, distribution network operation data and its carbon emission information, the total load dispatching cost and total carbon emission cost of the distribution network within the preset time period can be accurately calculated, and the distribution dispatching cost function is constructed on this basis, which is conducive to minimizing the sum of the total dispatching cost and the total carbon emission cost, which can not only optimize the economic operation of the distribution network, but also promote environmentally friendly energy management, and contribute to the reasonable and low-carbon dispatch of load equipment; at the same time, by putting the total load dispatching cost and the total carbon emissions on the same level for optimization, while ensuring the accuracy of the model solution, the difficulty of the model solution is reduced and the speed of the model solution is improved.

[0102] In one embodiment, determining the load dispatching cost of the distribution network within a preset period includes:

[0103] Determine the charging cost of the load device cluster within a preset time period based on the device status distribution information, the charging power of at least one load device and the charging electricity price of at least one load device in the day-ahead operation data of the distribution network; determine the electricity usage cost on the user side of the distribution network within the preset time period based on the carbon emission information of the distribution network and the load electricity price in the day-ahead operation data of the distribution network; determine the load dispatching cost of the distribution network within the preset time period based on the charging cost and the electricity usage cost.

[0104] Among them, charging power refers to the power received by the load device from the power grid during the charging process. The size of the charging power depends on factors such as the type of load device, battery capacity and charging rate. Charging electricity price refers to the unit price of electricity when the load device is charging, which usually varies according to the charging period, electricity consumption and price fluctuations in the electricity market. Charging cost refers to the cost incurred when using electricity to charge the load device.

[0105] The load price refers to the unit price paid by users for using electricity on the user side of the power system, which usually varies according to the time of use, the amount of electricity used, and the price fluctuations in the power market. The user side refers to the electricity consumer or end user in the power system. The electricity cost refers to the fee paid by users in the process of using electricity.

[0106] In specific implementation, the device status distribution information includes the charging and discharging status of the load devices connected to the distribution network area and the number of load devices connected to the distribution network area; the carbon emission information includes the active load of the load node, etc.

[0107] Exemplarily, first, the server determines the charging cost of charging the load device cluster according to the charging power and the charging electricity price within a preset time period based on the charging and discharging status of the load devices connected to the distribution network area, the number of load devices connected to the distribution network area, the charging power of at least one load device, and the charging electricity price of at least one load device in the day-ahead operation data of the distribution network; then, the server determines the electricity cost of using electric energy according to the active power load electricity price of the corresponding time period on the user side of the distribution network within the preset time period based on the active load of the load node and the load electricity price in the day-ahead operation data of the distribution network; finally, the server determines the load dispatching cost of the distribution network within the preset time period based on the charging cost and the electricity cost.

[0108] Among them, the load dispatching cost of the distribution network within the preset period is expressed as:

[0109] (3)

[0110] in, For preset time period Load dispatching cost of internal distribution network; for Active load (or active power) of the load node at any moment; for The load electricity price at the moment; the product of the active load (or active power) of the load node and the load electricity price Indicates the preset time period The electricity cost on the user side of the internal distribution network; for The first area connected to the distribution network at any time The charge and discharge status of each load device. , is the number of load devices in the load device cluster. When the load device is in charging state, On the contrary, when the load device is not in charging state, ; for The first area connected to the distribution network at any time Charging power of each load device; for Charging electricity price of load equipment in the distribution network area at any moment; The first area connected to the distribution network at any time The product of the charge and discharge status of each load device, the charging power and the charging electricity price Indicates the preset time period Charging cost of internal load device cluster.

[0111] In an exemplary embodiment, the active load (or active power) of the load node is determined based on the active power flow matrix in the power flow data. The active power flow matrix is ​​expressed as:

[0112] (4)

[0113] in, is the active power flow matrix; It is an element in the active power flow matrix, representing the active power of each load node.

[0114] In the active power flow matrix In the definition, under ideal conditions, there is no loss in active power transmission between load nodes, and the non-diagonal elements are set to 0. Based on this, the diagonal elements It is expressed as:

[0115] (5)

[0116] in, Load node Active power of It is the active power flow entering the load node; For the load node A collection of branches of adjacent and productive generator sets; is the branch index of the generator set, For the Output data of the generator sets in the branch; when a load node When it is not adjacent to any generator set, When the load node Active power Load node The active trend , when a load node When it is adjacent to the branch of the generator set, that is, When the load node Active power Load node The active trend With Output data of the generator sets in the branch sum.

[0117] Thus, the determined diagonal elements are integrated to form the active load matrix , Respectively indicate the preset time period Active load at each moment.

[0118] In an embodiment, by comprehensively considering the equipment status, the charging power and electricity price of the load equipment, and the carbon emissions and load electricity price information of the distribution network, the charging cost of the load equipment cluster and the electricity cost on the user side within a preset time period can be accurately calculated, and then the load scheduling cost of the distribution network can be obtained.

[0119] In one embodiment, determining the total carbon emissions of the power distribution network within a preset period includes:

[0120] According to the device status distribution information and the charging power of at least one load device, the charging power of the load device cluster within the preset time period is determined; according to the carbon emission information of the distribution network, the active power on the user side in the distribution network within the preset time period is determined; based on the active power, the charging power of the load device cluster and the dynamic carbon emission factor in the carbon emission information, the total carbon emissions of the distribution network within the preset time period are determined.

[0121] Among them, charging power refers to the power received by the load device from the power grid during the charging process. The size of the charging power depends on factors such as the type of load device, battery capacity and charging rate.

[0122] Among them, the dynamic carbon emission factor refers to the carbon emissions generated per unit of electricity in the power production process. The dynamic carbon emission factor is used to calculate the specific carbon emissions generated by grid operation or electricity consumption.

[0123] In specific implementation, the device status distribution information includes the charging and discharging status of the load devices connected to the distribution network area and the number of load devices connected to the distribution network area; the carbon emission information includes the active load of the load node, etc.

[0124] Exemplarily, the server determines the charging power of the load device cluster within a preset time period based on the charging and discharging status of the load devices connected to the distribution network area, the number of load devices connected to the distribution network area, and the charging power of at least one load device; determines the active power on the user side in the distribution network within the preset time period based on the active load of the load node in the carbon emission information of the distribution network; and determines the total carbon emissions of the distribution network within the preset time period based on the active power, the charging power of the load device cluster and the dynamic carbon emission factor in the carbon emission information.

[0125] Among them, the total carbon emissions of the distribution network within the preset period are expressed as:

[0126] (6)

[0127] in, For preset time period Total carbon emissions of the internal distribution network; for Active load (or active power) of the load node at any moment; for The first area connected to the distribution network at any time The charge and discharge status of each load device. , is the number of load devices in the load device cluster. When the load device is in charging state, On the contrary, when the load device is not in charging state, ; for The first area connected to the distribution network at any time Charging power of each load device; The product of the charging and discharging status and charging power of all load devices connected to the distribution network area at all times The sum represents the preset period Charging power of the internal load device cluster; for Dynamic carbon emission factor of the distribution network area at every moment.

[0128] In an exemplary embodiment, the active load (or active power) of the load node is determined based on the active power flow matrix in the power flow data. The specific determination process can be found in the description of the above embodiment and will not be elaborated in this embodiment.

[0129] In an exemplary embodiment, the dynamic carbon emission factor is determined based on the node carbon potential of the load node and the power injected into the load node. In this embodiment, the dynamic carbon emission factor is expressed as:

[0130] (7)

[0131] in, for Dynamic carbon emission factors of distribution network areas at all times; for Inject the first Power of load nodes (power flow) , is the number of load nodes; for Moment The nodal carbon potential of each load node.

[0132] Among them, the node carbon potential refers to the ratio of the carbon flow into the load node to the active power of the load node for a certain load node. Its physical meaning is the carbon emissions on the power generation side corresponding to the unit of electricity consumed by the load node. The numerical value is the weighted average of the carbon flow density of the generator set of the load node and the carbon flow density of the adjacent nodes with respect to the injected power of the generator set and the adjacent load nodes, and the unit is kgCO2 / kWh. In this embodiment, the node carbon potential of the load node in the distribution network is expressed as:

[0133] (8)

[0134] in, is the node carbon potential of the load node (i.e. ); To inject The power of each load node; For the The carbon flow density of each load node; For the The injected power of the generator sets connected to each load node; For the The node carbon potential of the generator connected to the load node.

[0135] Therefore, the dynamic carbon emission factors of the distribution network area at each time are integrated to form a dynamic carbon emission factor matrix , Respectively indicate the preset time period Dynamic carbon emission factors at each moment.

[0136] In this embodiment, by integrating the equipment status, the charging power of the load equipment and the carbon emission information of the distribution network, the charging power of the load equipment cluster and the active power on the user side within the preset time period can be accurately calculated, and then combined with the dynamic carbon emission factor, the total carbon emissions of the distribution network can be accurately evaluated.

[0137] In an exemplary embodiment, the constraints for the distribution dispatch cost function include but are not limited to the system load balance constraints of the distribution network, the distribution flow constraints of the distribution network, the dispatchable load constraints of the load device cluster, the battery capacity constraints of the load device cluster and the total load constraints on the user side.

[0138] The system load balance constraint of the distribution network refers to the need to satisfy the balance relationship between external and internal power supply and load for the distribution network at any time. That is, the power supply output of all external nodes in the distribution network and the predicted output of all distributed power sources in the distribution network are balanced with the charging power received by the load equipment from the power grid during the charging process and the active power on the user side.

[0139] The system load balance constraint of the distribution network is expressed as:

[0140] (9)

[0141] in, for The first The power output of external nodes, , is the number of external nodes; for The distribution network at the moment The predicted output of each distributed generation unit, , is the number of distributed generation in the distribution network.

[0142] The distribution flow constraint of the distribution network refers to the flow constraint relationship that needs to be satisfied for the distribution network at any time.

[0143] The power flow constraint for active power is expressed as:

[0144] (10)

[0145] in, for From the load node Flow to load node Active power of Load node With load node The resistance of the branch between them; for From the load node Flow to load node The current; Load Node The branch starting node set of the terminal; Load Node is the set of branch terminal nodes at the starting end; for At any time, Distributed power flows to load nodes Active power of for Time load node Active power of the load at for Time load node The active power of distributed generation at the location.

[0146] The power flow constraint for reactive power is expressed as:

[0147] (11)

[0148] in, for From the load node Flow to load node Reactive power; Load node With load node The reactance of the branch between them; for From the load node Flow to load node The current; Load Node The branch starting node set of the terminal; Load Node is the set of branch terminal nodes at the starting end; for At any time, Distributed power flows to load nodes Reactive power; for Time load node The reactive power of the load at for Time load node The reactive power of distributed generation at the location.

[0149] The dispatchable load constraint of the load device cluster means that, for the load device cluster, the load of the load device in each time period needs to be less than the load of the dispatchable load device in the time period.

[0150] The dispatchable load constraint of the load device cluster is expressed as:

[0151] (12)

[0152] in, for The number of load devices being charged at any given time, The maximum charging power of each load device.

[0153] The battery capacity constraint of the load device cluster means that for the load device cluster, in order to maintain battery life and prevent deep charging, the charging amount of each electric vehicle in the cluster in each period should be less than the upper limit of its battery capacity.

[0154] The battery capacity constraint of the load device cluster is expressed as:

[0155] (13)

[0156] in, for Always check the remaining battery power of the load device; The maximum capacity of the battery of the load device; is the charging protection factor. In this embodiment, .

[0157] Among them, the total load constraint on the user side means that low-carbon scheduling must first ensure that the total power supply in this mode remains unchanged. Under the low-carbon scheduling mode, the total load of the user needs to be maintained unchanged throughout the day, and only the time period of the user's electricity consumption is shifted.

[0158] The total load constraint on the user side is expressed as:

[0159] (14)

[0160] in, Before scheduling optimization Active power of load nodes at all times; After scheduling optimization Active power of load nodes at all times; Before scheduling optimization Charging power of load equipment at all times; After scheduling optimization The charging power of the load device at all times.

[0161] In one embodiment, the method further includes:

[0162] According to the access status of the load device cluster connected to the distribution network, the access status parameters of the load devices connected to and leaving the distribution network are determined; the access status includes charging state, idle state and discharging state; the access quantity parameters of the load devices of the load device cluster in the charging state, idle state and discharging state are determined respectively.

[0163] Among them, the access state refers to the connection state of the load device relative to the distribution network. The access state includes charging state, idle state and discharge state, which are used to reflect the energy exchange between the load device and the distribution network. The charging state refers to the state in which the load device obtains electric energy from the distribution network at rated active power for charging; the idle state refers to the state in which there is no active power exchange between the load device and the distribution network; the discharge state refers to the state in which the load device feeds back electric energy to the distribution network or other devices at rated active power.

[0164] Exemplarily, the server determines access status parameters of load devices connecting to and leaving the distribution network based on the access status of the load device cluster connected to the distribution network; the access status includes charging state, idle state and discharging state; and the access quantity parameters of the load devices in the load device cluster in the charging state, idle state and discharging state are determined respectively.

[0165] In this embodiment, the access status parameters and access quantity parameters of the load devices in different states are determined by the access status of the load devices, which is beneficial to optimizing the configuration of power resources according to the actual conditions of each load device during the power dispatching process and promoting the rational use of energy.

[0166] In one embodiment, respectively determining the access quantity parameters of the load devices of the load device cluster in the charging state, the idle state, and the discharging state includes:

[0167] Determine the state of charge parameters of the load device in the charging state, idle state and discharge state respectively; determine the state sub-interval in which the load device is located according to the access state and the state of charge parameters of the load device, and obtain the number of load devices in each state sub-interval; for each state sub-interval, determine the access number parameter of the number of load devices in the state sub-interval according to the number of load devices and the state of charge parameters.

[0168] The state of charge parameter refers to an indicator that measures the amount of electrical energy stored inside the load device, and is used to reflect the proportional relationship between the current power of the load device and its maximum storage capacity.

[0169] The state sub-interval refers to a more detailed range or interval formed by discretizing the charge state of the load device according to the charge variation range of the load device. The state sub-interval is used to describe and analyze the state of the load device and its quantity distribution.

[0170] Exemplarily, the server determines the charge state parameters of the load device in the charging state, idle state and discharging state respectively; determines the corresponding state sub-interval according to the access state and charge state parameters of the load device, and aggregates each load device according to the determined state sub-interval to obtain the number of load devices in each state sub-interval; then, for each state sub-interval, the server determines the access number parameter of the number of load devices in the state sub-interval according to the number of load devices and the charge state parameters.

[0171] In this embodiment, by distinguishing the state of charge parameters of the load device in the charging, idle and discharging states, and subdividing the load device into different state sub-intervals according to the access state and these parameters, the quantity distribution of the load devices in each state sub-interval can be fully grasped, and then for each state sub-interval, combined with the number of load devices and the specific state of charge parameters, the access quantity parameter is determined, which helps to achieve more refined equipment management and energy scheduling.

[0172] In an exemplary embodiment, in order to facilitate the analysis of each load device, a state model is performed for each load device according to the access state of the load device to obtain a single state model of each load device, which is expressed as:

[0173] (15)

[0174] in, for Moment The rate of change of the charge state of each load device; Respectively Rated charging power and discharging power of each load device; Respectively Charging efficiency and discharging efficiency of each load device; For the The CS state, IS state and DS state represent the charging state, idle state and discharging state respectively.

[0175] According to the above single state model of each load device, for the charging state, define The charge state of the load devices in the load device cluster at the moment is And the number of load devices in charging state is , the charge variation range of the load equipment is , are the upper and lower limits of the state of charge of the load device, respectively. , That is The state of charge at the moment is The number of load devices. As time goes by, the state of charge exist Internal changes, the speed of change is Definition From the state of charge to Changes to The total number of load devices is , then we have the following relationship:

[0176] (16)

[0177] in, for From the state of charge to Changes to The total number of load devices; for The state of charge at the moment is The number of load devices; for The average change rate of the charge state of the load devices in the load device cluster that are in the outgoing state at the moment.

[0178] After the load equipment is connected to the distribution network, The average change rate of the charge state of the load devices in the load device cluster that are in the outgoing state at the moment Determined by the following formula:

[0179] (17)

[0180] in, are the average rated charging power, charging efficiency and battery capacity of the load device cluster respectively; is the number of load devices in the load device cluster; For the Rated charging power of each load device; For the Charging efficiency of each load device; For the The battery capacity of each load device.

[0181] Combining formula (16) and formula (17), From the state of charge to Changes to The total number of load devices Further expressed as:

[0182] (18)

[0183] Divide the load device flow in an infinitely small interval. The number of load devices in , About the moment The partial derivative of is the rate of change of the flow rate of the load device in the interval. Combined with formula (16), the ratio of the flow difference of the load device entering and leaving the interval to the interval length is obtained: for:

[0184] (19)

[0185] in, Infinitely small intervals upper and lower limits.

[0186] For the idle state, define The charge state of the load devices in the load device cluster at the moment is And the number of load devices in idle state is Since the state of charge of the load device in the idle state does not change over time, the number of load devices in the idle state is Rate of change over time It is expressed as:

[0187] (20)

[0188] For the discharge state, the definition The charge state of the load devices in the load device cluster at the moment is And the number of load devices in the discharge state is According to the above analysis under charging state, the number of load devices in the discharge state Rate of change over time It is expressed as:

[0189] (twenty one)

[0190] Then the average rated charging power and charging efficiency of the load device cluster are expressed as:

[0191] (twenty two)

[0192] (twenty three)

[0193] in, are the average rated discharge power and discharge efficiency of the load device cluster respectively; is the number of load devices in the load device cluster; For the Rated discharge power of each load device; For the The discharge efficiency of a load device.

[0194] The charge range of the above load equipment is Discretization state subintervals, and the length of each state subinterval is , considering the three access states of load devices, namely charging, idle and discharging, each load device in the load device cluster can determine the corresponding state sub-interval according to the access state and charge state parameters at the current moment, and finally Each state sub-interval describes the state distribution of each load device in the load device cluster and the flow change of the load device between adjacent state sub-intervals.

[0195] definition , , are the number of load devices in the charging, idle, and discharging states in the corresponding state subintervals. , then the load device cluster is in the state sub-interval Number of load devices It can be expressed as:

[0196] (twenty four)

[0197] in, for The access status and charge status parameters of the load device cluster at this moment indicate that the load device is in the state sub-interval The number of load devices in the

[0198] According to formula (19) to formula (21), define:

[0199] (25)

[0200] (26)

[0201] Thus, the flow change of the load devices in the load device cluster between each state sub-interval is expressed as:

[0202] (27)

[0203] in, In the state subinterval The number of load devices within The rate of change, , .

[0204] The above formula (27) is transformed using a 3J×3J sparse matrix to obtain the state subinterval The number of load devices within Rate of change The matrix representation of is:

[0205] (28)

[0206] in, , is a 3J×3J sparse matrix.

[0207] Based on the above, the access quantity parameter of the number of load devices in each state sub-interval is obtained.

[0208] In an exemplary embodiment, the dynamic access and departure of load devices to the power grid will affect the number of load devices in the load device cluster, thereby affecting the number of load devices in each state sub-interval at each moment. for The access status parameters of the load devices that are connected to and leave the power grid at all times are expressed as:

[0209] (29)

[0210] in, They are The probability density function of the load equipment dynamically connecting to and leaving the power grid at each moment; are the number of load devices connected to and leaving the power grid in a day; are the proportions of load devices connected to and leaving the grid in each state sub-interval, They are all vectors of order 3J×1.

[0211] Based on the above, the cluster state change model of the electric vehicle cluster can be obtained:

[0212] (30)

[0213] In this embodiment, the load device cluster in the distribution network area is taken as the research object. Within the same distribution network area, the load device cluster is mobilized to participate in low-carbon scheduling, which can effectively avoid the problem of poor effect of single load device participating in low-carbon scheduling.

[0214] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0215] Based on the same inventive concept, the embodiment of the present application also provides a distribution network dispatching device for implementing the distribution network dispatching method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more distribution network dispatching device embodiments provided below can refer to the limitations of the distribution network dispatching method above, and will not be repeated here.

[0216] In an exemplary embodiment, Figure 4 As shown, a distribution network dispatching device is provided, including: a cluster determination module 401, a model construction module 402, a state determination module 403, a cost determination module 404 and a dispatching control module 405, wherein:

[0217] The cluster determination module 401 is used to determine a load device cluster connected to the power distribution network, and the load device cluster includes at least one load device.

[0218] The model building module 402 is used to build a cluster state change model of the load device cluster based on the access state parameters and access quantity parameters in the process of the load device cluster being connected to the distribution network.

[0219] The state determination module 403 is used to determine the device state distribution information of each of at least one load device through a cluster state change model.

[0220] The cost determination module 404 is used to determine the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network.

[0221] The dispatch control module 405 is used to obtain power distribution dispatch information of the distribution network according to the power distribution cost information, and perform power distribution dispatch for at least one load device according to the power distribution dispatch information.

[0222] In an optional embodiment, the model building module 402 is also used to determine the access state parameters of the load devices connecting to and leaving the distribution network according to the access state of the load device cluster connected to the distribution network; the access state includes a charging state, an idle state and a discharging state; and respectively determine the access quantity parameters of the load devices of the load device cluster in the charging state, the idle state and the discharging state.

[0223] In an optional embodiment, the model building module 402 is also used to determine the charge state parameters of the load device in the charging state, idle state and discharge state respectively; determine the state sub-interval in which the load device is located according to the access state and charge state parameters of the load device, and obtain the number of load devices in each state sub-interval; the state sub-interval is formed by discretizing the charge state of the load device according to the charge variation range of the load device; for each state sub-interval, determine the access number parameter of the number of load devices in the state sub-interval according to the number of load devices and the charge state parameters.

[0224] In an optional embodiment, the cost determination module 404 is also used to construct a distribution scheduling cost function based on the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network, with the goal of minimizing the distribution cost of the distribution network for the load device cluster; determine the constraints of the distribution scheduling cost function; and determine the distribution cost information of the distribution network for the load device cluster based on the distribution scheduling cost function and the constraints.

[0225] In an optional embodiment, the cost determination module 404 is also used to determine the load dispatching cost of the distribution network within a preset time period based on the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network; determine the total carbon emissions of the distribution network within the preset time period based on the equipment status distribution information and the carbon emission information of the distribution network, and determine the carbon emission cost of the distribution network within the preset time period based on the total carbon emissions and the carbon emission cost conversion coefficient of the distribution network; and construct a distribution dispatching cost function based on the goal of minimizing the sum of the load dispatching cost and the carbon emission cost.

[0226] In an optional embodiment, the cost determination module 404 is also used to determine the charging cost of the load device cluster within a preset time period based on the device status distribution information, the charging power of at least one load device and the charging electricity price of at least one load device in the day-ahead operation data of the distribution network; determine the electricity usage cost on the user side of the distribution network within the preset time period based on the carbon emission information of the distribution network and the load electricity price in the day-ahead operation data of the distribution network; and determine the load scheduling cost of the distribution network within the preset time period based on the charging cost and the electricity usage cost.

[0227] In an optional embodiment, the dispatching control module 405 is also used to determine the charging power of the load device cluster within a preset time period based on the device status distribution information and the charging power of at least one load device; determine the active power on the user side of the distribution network within the preset time period based on the carbon emission information of the distribution network; and determine the total carbon emissions of the distribution network within the preset time period based on the active power, the charging power of the load device cluster and the dynamic carbon emission factor in the carbon emission information.

[0228] Each module in the above-mentioned distribution network dispatching device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0229] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store access status parameters, access quantity parameters, cluster state change models, device state distribution information, day-ahead operation data of the distribution network, carbon emission information of the distribution network and other data. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a distribution network scheduling method is implemented.

[0230] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0231] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the distribution network scheduling method of the above embodiment is implemented.

[0232] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the distribution network scheduling method of the above embodiment is implemented.

[0233] In one embodiment, a computer program product is provided, including a computer program, which implements the distribution network scheduling method of the above embodiment when executed by a processor.

[0234] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0235] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0236] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0237] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A distribution network dispatching method, characterized in that: The method comprises: Determine a load device cluster connected to the power distribution network, wherein the load device cluster includes at least one load device; Based on the access state parameters and access quantity parameters of the load device cluster in the process of accessing the load device cluster to the distribution network, construct a cluster state change model of the load device cluster; Determining device state distribution information of each of the at least one load devices through the cluster state change model; Determine the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network; Power distribution scheduling information of the distribution network is obtained according to the power distribution cost information, and power distribution scheduling is performed for the at least one load device according to the power distribution scheduling information.

2. The method according to claim 1, characterized in that The determining, based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network, the power distribution cost information of the distribution network for the load device cluster includes: According to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network, a distribution scheduling cost function is constructed with the goal of minimizing the distribution cost of the distribution network for the load equipment cluster; Determining constraints of the power distribution scheduling cost function; According to the power distribution scheduling cost function and the constraint condition, power distribution cost information of the power distribution network for the load device cluster is determined.

3. The method according to claim 2, characterized in that The constructing of a distribution scheduling cost function based on the device status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network with the goal of minimizing the distribution cost of the distribution network for the load device cluster includes: Determine the load dispatching cost of the distribution network within a preset time period according to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network; Determine the total carbon emissions of the distribution network within the preset period according to the device status distribution information and the carbon emission information of the distribution network, and determine the carbon emission cost of the distribution network within the preset period according to the total carbon emissions and the carbon emission cost conversion coefficient of the distribution network; A distribution scheduling cost function is constructed based on the goal of minimizing the sum of the load scheduling cost and the carbon emission cost.

4. The method according to claim 3, characterized in that The determining, according to the equipment status distribution information, the day-ahead operation data of the distribution network and the carbon emission information of the distribution network, the load dispatching cost of the distribution network within a preset period of time comprises: Determine the charging cost of the load device cluster within a preset time period according to the device status distribution information, the charging power of the at least one load device and the charging electricity price of at least one load device in the day-ahead operation data of the distribution network; Determine the electricity cost of the user side in the distribution network within the preset time period according to the carbon emission information of the distribution network and the load electricity price in the day-ahead operation data of the distribution network; Based on the charging cost and the electricity cost, a load dispatching cost of the distribution network within a preset time period is determined.

5. The method according to claim 3, characterized in that: The determining, according to the device status distribution information and the carbon emission information of the distribution network, the total carbon emissions of the distribution network within the preset period of time comprises: Determining the charging power of the load device cluster within a preset time period according to the device state distribution information and the charging power of the at least one load device; Determining the active power of the user side in the distribution network within the preset time period according to the carbon emission information of the distribution network; Based on the active power, the charging power of the load device cluster and the dynamic carbon emission factor in the carbon emission information, the total carbon emissions of the distribution network within the preset time period are determined.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Determine access status parameters of load devices accessing and leaving the distribution network according to the access status of the load device cluster accessing the distribution network; the access status includes charging state, idle state and discharging state; The access quantity parameters of the load devices of the load device cluster in the charging state, the idle state and the discharging state are determined respectively.

7. The method according to claim 6, characterized in that The step of respectively determining the access quantity parameters of the load devices of the load device cluster in the charging state, the idle state, and the discharging state includes: respectively determining a state of charge parameter of the load device in the charging state, the idle state, and the discharging state; According to the access state of the load device and the charge state parameter, the state sub-interval of the load device is determined, and the number of the load devices in each state sub-interval is obtained; the state sub-interval is formed by discretizing the charge state of the load device according to the charge variation range of the load device; For each of the state sub-intervals, an access quantity parameter of the number of the load devices in the state sub-interval is determined according to the number of the load devices and the state of charge parameter.

8. A distribution network dispatching device, characterized in that: The device comprises: A cluster determination module, used to determine a load device cluster connected to the power distribution network, wherein the load device cluster includes at least one load device; A model building module, used to build a cluster state change model of the load device cluster based on the access state parameter and access quantity parameter of the load device cluster in the process of accessing the load device cluster to the distribution network; A state determination module, used to determine the device state distribution information of each of the at least one load devices through the cluster state change model; A cost determination module, configured to determine the power distribution cost information of the distribution network for the load device cluster based on the device status distribution information, the day-ahead operation data of the distribution network, and the carbon emission information of the distribution network; A dispatching control module is used to obtain power distribution dispatching information of the distribution network according to the power distribution cost information, and perform power distribution dispatching for the at least one load device according to the power distribution dispatching information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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