Power supply configuration method and device, terminal equipment and computer readable storage medium

Abstract

The invention discloses a power supply configuration method and device, terminal equipment and a computer readable storage medium, and the method comprises the steps: determining the fitting state information of a plurality of power supply ends, load ends and energy storage ends in a power distribution network at the current moment according to the values of a plurality of variables which affect the source-load storage state in the power distribution network at the current moment, each variable corresponds to one uncertainty factor, and the plurality of power supply ends comprise a host power supply end and at least one standby power supply end; determining line state information of each power supply line in the power distribution network at the current moment, wherein each power supply line comprises a first power supply line respectively connected with a host power supply end and a load end at the current moment, and at least one second power supply line respectively connected with at least one standby power supply end; and determining a power supply configuration strategy at the current moment according to the fitting state information and the line state information, and executing a control flow corresponding to the power supply configuration strategy. The scheme can improve the power supply recovery capability and efficiency of the important load node power supply line in the power distribution network.

Description

Technical Field

[0001] The present application belongs to the technical field of power supply configuration, and in particular, relates to a power supply configuration method, apparatus, terminal equipment and computer-readable storage medium. Background Art

[0002] In recent years, the new power system has evolved from the traditional source-load dynamic to a flexible management of dynamic coordination of source, load and storage. Especially driven by the dual carbon goals and supply-side policies, a large number of power equipment mainly based on new energy have begun to be connected to the distribution network, which has greatly increased the flexibility of the distribution network and the user side has an increasingly strong demand for stable line power supply. Especially with the increase in the proportion of new energy installed capacity, the source, load and storage subnet of the power grid has entered a stage of rapid development. The local absorption capacity of the low-voltage side of the distribution network is insufficient, and the operating voltage on the low-voltage side will continue to rise, which is prone to cause power outages or fire incidents. If the load on the low-voltage side cannot locally absorb the power generation of distributed power sources, the circuit breaker disconnection moment is likely to cause short-term overvoltage, which has a greater impact on the recovery of distribution network line faults. If a severe situation occurs again, the output of distributed power sources will drop sharply, and the low voltage situation at the end of the line will be even worse, which will have a greater impact on the correctness, accuracy and reliability of the distribution network fault recovery.

[0003] Therefore, how to quickly restore power supply when a line failure occurs in the distribution network is an important issue that needs to be urgently solved in the current new power system. Summary of the invention

[0004] In order to at least partially solve the above technical problems, the embodiments of the present application provide a power supply configuration method, apparatus, terminal device and computer-readable storage medium, which can accurately identify power supply line faults in the distribution network in real time and quickly restore power supply when the power supply line fails.

[0005] A first aspect of an embodiment of the present application provides a power supply configuration method, including:

[0006] According to the values ​​of multiple variables that affect the source-load-storage state in the distribution network at the current moment, determine the fitting state information of multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal;

[0007] Determine the line status information of each power supply line in the distribution network at the current moment, wherein each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to at least one backup power supply end;

[0008] According to the fitting state information and the line state information, the power supply configuration strategy at the current moment is determined, and the control process corresponding to the power supply configuration strategy is executed.

[0009] A second aspect of an embodiment of the present application provides a power supply configuration device, including:

[0010] A fitting module, used to determine the fitting state information of multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment according to the values ​​of multiple variables affecting the source-load-storage state in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal;

[0011] A first determination module is used to determine the line status information of each power supply line in the distribution network at the current moment, wherein each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to at least one standby power supply end;

[0012] The configuration module is used to determine the power supply configuration strategy at the current moment according to the fitting state information and the line state information, and execute the control process corresponding to the power supply configuration strategy.

[0013] A third aspect of an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the steps of the above-mentioned power supply configuration method are performed when the processor executes the computer program.

[0014] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned power supply configuration method are implemented.

[0015] The power supply configuration method provided by the first aspect of the embodiment of the present application first fully considers the influence of the uncertainty factors of source, load and storage, and determines the fitting state information of multiple power supply ends, load ends and energy storage ends in the distribution network at the current moment in real time and accurately. Then, the line state information of each power supply line in the distribution network at the current moment is accurately determined. And based on the fitting state information and line state information, the power supply configuration strategy at the current moment is quickly and accurately determined, and then the control process corresponding to the power supply configuration strategy can be executed in time, so as to realize the rapid restoration of power supply for multiple lines in the distribution network, and can also significantly reduce the operating cost of the distribution network.

[0016] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art 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 drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 It is a schematic diagram of the components of a new power system in the prior art;

[0019] Figure 2 It is a flowchart of a power supply configuration method provided by an embodiment of the present application;

[0020] Figure 3 It is a partial schematic diagram of a distribution network line topology diagram provided by an embodiment of the present application;

[0021] Figure 4a It is a curve diagram of the change of power generation with wind speed described by a wind power generation output model provided by an embodiment of the present application;

[0022] Figure 4b It is a schematic diagram of a curve showing the variation of power generation with light intensity described by a photovoltaic power generation output model provided in an embodiment of the present application;

[0023] Figure 5a is a schematic diagram of an automatic line switching process provided by an embodiment of the present application;

[0024] Figure 5b is a flowchart of a power supply configuration method provided by another embodiment of the present application;

[0025] Figure 6 is a schematic diagram of a power supply configuration calculation model provided by an embodiment of the present application;

[0026] Figure 7a It is a schematic diagram of a dynamic simulation verification result of a power supply configuration provided by an embodiment of the present application;

[0027] Figure 7b is a schematic diagram of a fast communication model provided by an embodiment of the present application;

[0028] Figure 8 is a structural schematic diagram of a power supply configuration device provided by an embodiment of the present application;

[0029] Fig. 9 It is a structural diagram of a terminal device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0030] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0031] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0032] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0033] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0034] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0035] As mentioned above, in recent years, the new power system has evolved from the traditional source-load dynamic to a flexible management of source-load-storage dynamic coordination. Figure 1 As shown in Figure 1, the components of the new power system include: renewable energy and generators, load side, energy storage side, public power grid, power supply / heat supply. With the increase in the installed capacity of distributed power sources with high penetration of new energy, the complexity of the power system is increasing, and the problem of power supply restoration in the power system is also receiving more and more attention. How to quickly restore power supply when a line failure occurs in the distribution network is an important issue that needs to be solved urgently in the current new power system.

[0036] Through research, it is found that many uncertain factors affecting the source, load and storage are the main factors leading to power supply line failures in the distribution network. However, most of the power supply recovery technologies for terminal line failures in the distribution network in the existing technology do not consider the uncertainty of the source, load and storage, and do not accurately analyze their models. First, the traditional power supply recovery technology requires unified analysis and decision-making by the master station for its automatic conversion algorithm control strategy and self-healing model, which takes a long time to schedule and often cannot adapt to the rapid changes of the source, load and storage and the rapid response of the demand side, which may lead to problems such as slow power supply recovery, power outages, and unclear fault characteristics in the distribution network. Secondly, the existing source-side modeling methods are often oversimplified, require historical state data evaluation, have scene combinations that cannot be traversed, ignore some minor uncertain factors, and thus cannot accurately reflect the actual situation of the model, which may lead to incomplete control strategies for the operation of the distribution network self-healing model. Finally, on the basis of dealing with the uncertainty of the source, load and storage, the existing technology requires a large number of examples and communication resources for the self-healing model, which may increase the actual operating cost of the distribution network.

[0037] In order to at least partially solve the above-mentioned technical problems, the embodiments of the present application provide a power supply configuration method, apparatus, terminal equipment and computer-readable storage medium applied to a distribution network. This solution can be widely used in technical fields such as power system power supply restoration, source-load-storage uncertainty analysis, and power supply operation of important load nodes in distribution networks. It can also be applied to other fields that need to deal with source-load-storage uncertainty, such as electricity market transactions, power system planning and design, virtual electric field transactions, etc. The distribution network power supply rapid recovery technology based on source-load-storage uncertainty proposed in the present invention can improve the power supply recovery capability and efficiency of the power supply lines of important load nodes in the distribution network, ensure the stable operation of the power system, and reduce the operating costs of the distribution network.

[0038] like Figure 2 As shown, the power supply configuration method provided in the embodiment of the present application includes the following steps:

[0039] Step S210, according to the values ​​of multiple variables that affect the source-load-storage state in the distribution network at the current moment, determine the fitting state information of multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal. The fitting state information can be the state information of the source-load-storage fitted by various suitable fitting methods. It can be understood that the fitting state information may be consistent with the actual state information, or may be inconsistent with the actual state information.

[0040] The power supply end in the distribution network is used to provide electrical energy to the power grid. Exemplarily, the power supply end may be a power station, and different power supply ends may correspond to different power stations. Alternatively, different power supply ends may also correspond to different power generation devices in a power station. These power generation devices may be various energy power generation devices, including but not limited to thermal power, hydropower, wind power, solar power or nuclear power, etc. According to an embodiment of the present application, the fitting state information of the power supply end may at least include information that can represent the power generation capacity of the power generation device at the current moment, such as the power generation output power. In some examples, the fitting state information of the power supply end may also include: operating state information of the power generation device (such as whether it is in normal operation, maintenance or fault state), environmental conditions (such as wind speed, wind direction, light intensity, etc.), fuel state, etc.

[0041] The load end in the distribution network may be various electrical equipment. The fitting state information of the load end may at least include the current power demand information of the electrical equipment, for example, the power consumed by the electrical equipment at the current moment, that is, the fitting operating power. In some examples, the fitting state information of the load end may also include: the power type information of the electrical equipment (for example, interruptible load, non-interruptible load; industrial electrical equipment, commercial electrical equipment or residential electrical equipment, etc.), the power efficiency information of the electrical equipment (such as the energy efficiency level of the equipment), etc.

[0042] The energy storage end in the distribution network may be various energy storage devices in the power grid, such as a battery energy storage system. The fitting state information of the energy storage end may at least include the energy storage capacity information of the energy storage device, such as the state of charge (SOC) of the energy storage device at the current moment. In some examples, the fitting state information of the energy storage end may also include: charging and discharging state information, health state information, etc. of the energy storage device.

[0043] According to an embodiment of the present application, the variables affecting the source-load-storage state in the distribution network may include a first variable affecting the state of the power supply end, a second variable affecting the state of the load end, and a third variable affecting the state of the energy storage end. Each variable may correspond to an uncertainty factor. The first variable may correspond to an uncertainty factor affecting the state of the power supply end during the charging process. It can be understood that different power supply ends may correspond to different first variables. The number of first variables corresponding to each power supply end may be one or more. These uncertainty factors may be factors found in the research process that have a dependency relationship with the fitting state information of the power supply end. For example, for a wind power generation device, the uncertainty factors may include various factors affecting the output power of wind power generation (such as wind speed and wind direction at the current moment). Thus, the first variable affecting the wind power generation device may include the wind speed at the current moment, or may also include the wind direction at the current moment. For a hydropower generation device, the uncertainty factors may include: rainfall at the current moment, river flow, water level height, water flow velocity, etc. Similarly, for the load end, different electrical equipment corresponds to different uncertainty factors, so different influencing variables can be set accordingly. For example, for air conditioning, uncertainty factors may include: outdoor temperature, indoor heat load, air conditioning setting temperature, etc. For example, for public street lamps, uncertainty factors may include sunlight intensity, etc. Uncertainty factors affecting the state information of the energy storage device may include: efficiency, charge and discharge cycles, charge and discharge rate, etc. of the energy storage device.

[0044] In this step, according to the values ​​of multiple variables that affect the source-load-storage state in the distribution network at the current moment, a variety of suitable fitting methods can be used to determine the fitting state information of each of the multiple power supply terminals, load terminals, and energy storage terminals in the distribution network at the current moment. In one example, the power generation output model of each power supply terminal, the power consumption model of the load terminal, and the energy storage model of the energy storage terminal can be pre-fitted. Then, in this step, the values ​​of each variable collected or calculated in real time can be matched with the corresponding model, and the fitting state information of each power supply terminal, load terminal, and energy storage terminal can be obtained according to the matching results.

[0045] According to an embodiment of the present application, the multiple power supply terminals include a host power supply terminal and a backup power supply terminal. The host power supply terminal can be a power supply connected to an electrical device in a power grid to supply power to the electrical device. The number of backup power supply terminals can be one or more. The energy types corresponding to the host power supply terminals can be the same or different, and this application does not limit them.

[0046] Step S220, determine the line status information of each power supply line in the distribution network at the current moment, wherein each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to at least one backup power supply end.

[0047] The number of power supply lines in the distribution network can be the same as the number of power supply terminals (e.g. one power supply terminal corresponds to one power supply line), or different (e.g. multiple power supply terminals correspond to one power supply line, etc.). The number of power supply lines can be any number greater than 2. Figure 3 As shown, the distribution network may include three power supply lines: line 1, line 2 and line 3 in the figure, and different lines may connect different switch rooms and different power supply terminals. In this example, the distribution network may include one first power supply line (i.e., the main power supply line) and two second power supply lines (i.e., the backup power supply lines).

[0048] According to an embodiment of the present application, the line status information of the power supply line may include current information (phase current and line current), voltage information (phase voltage and line voltage), power information, load information (such as the power load on the line, including real-time load and historical load data), line temperature, line health information, power quality, line load rate, etc. In this step, various suitable methods can be used to monitor the line status information of each power supply line in the distribution network in real time, and this application does not limit it. For example, an intelligent distribution network line status monitoring system can be used, which is composed of a sensor acquisition unit, a collection unit, a data analysis platform and an AI algorithm module to realize real-time monitoring of distribution lines, detect line faults, record fault waveforms, locate fault sections, warn of risks and hidden dangers, and analyze power quality.

[0049] Step S230, determining the power supply configuration strategy at the current moment according to the fitting state information and the line state information, and executing the control flow corresponding to the power supply configuration strategy.

[0050] In one example, a power supply configuration strategy model can be pre-trained, and the power supply configuration strategy model has the ability to output the optimal power supply configuration strategy. In this step, the fitting state information of the source load storage and the line state information of each power supply line can be input into the trained power supply configuration model, and the model outputs the optimal power supply configuration strategy. Afterwards, the corresponding control process can be executed according to the optimal power supply configuration strategy.

[0051] The power supply configuration strategy can be set arbitrarily according to actual needs. Exemplarily, the power supply configuration strategy may include at least a power conversion strategy. The power conversion strategy may be a strategy for quickly switching to a backup power supply and / or a backup power supply line when a fault or unpredictable event occurs in the power grid, thereby ensuring continuous power supply to critical loads. In some examples, the power supply configuration strategy may also include one or more of a priority strategy, an economic dispatch strategy, a reliability dispatch strategy, an energy storage optimization strategy, a regional coordination strategy, and a predictive maintenance strategy. The priority strategy may be a strategy for dividing loads into different priorities according to the importance of the loads, and giving priority to power supply to high-priority loads. The economic dispatch strategy may be a dispatch strategy for giving priority to using lower-cost power supplies based on the cost-effectiveness of each power supply to reduce the overall power supply cost. The reliability dispatch strategy may be a strategy for increasing backup power supplies or adjusting power supply lines according to the power supply needs of critical loads and critical areas. The energy storage optimization strategy may be a strategy for using energy storage devices to store energy when there is an oversupply of electricity and release energy when there is an undersupply to balance supply and demand. The regional coordination strategy may be a strategy for dispatching electricity between multiple power supply areas to achieve optimal allocation of resources. A predictive maintenance strategy can be a strategy that performs maintenance in advance on equipment or lines that may fail based on predictive analysis results.

[0052] In another example, an optimization algorithm may be used to determine the current power supply configuration strategy. For example, a linear programming or nonlinear programming method may be used to predefine an objective function (such as minimizing cost, maximizing reliability, etc.) and constraints (such as power supply demand, line capacity limitation, voltage stability, etc.) to solve the optimal power supply configuration strategy.

[0053] In another example, a rule-based method can be used to determine the power supply configuration strategy at the current moment. Optionally, preset rules can be used to guide power supply configuration decisions. In other words, a suitable power supply configuration strategy can be inferred based on the fitting state information of the source-load-storage and the line state information of the power supply line, combined with a predefined set of rules. Alternatively, a fuzzy logic method can be used to divide the source-load-storage state and the line state into different fuzzy sets, and define fuzzy rules, thereby realizing fuzzy reasoning and decision-making of the power supply configuration. Specifically, first, based on actual operation data and experience, multiple fuzzy sets can be defined to describe the state of the source-load-storage and the line state of each power supply line respectively. For example: power supply state: {low power, medium power, high power}; load state: {light load, medium load, heavy load}; energy storage state: {low power, medium power, high power}; line state: {good, general, dangerous}. Then, a corresponding membership function can be defined for each fuzzy set. The shape of the membership function can be set according to the actual situation, which can be a triangle, trapezoid, Gaussian, etc. After that, a series of fuzzy rules can be defined according to the logic of system operation and expert knowledge. These rules describe the corresponding power supply configuration strategies that should be adopted under different source-load-storage states and line states. That is, the corresponding relationship rules between different power supply configuration strategies and different combinations of source-load-storage states and line states are defined. Afterwards, the fuzzy reasoning engine can be used to perform fuzzy reasoning based on the currently fitted source-load-storage state and the line state of each power supply line, the defined fuzzy rules, and the membership function to obtain the final power supply configuration strategy.

[0054] Of course, the above-mentioned different power supply configuration strategy determination methods can also be combined together. In some examples, one or more of the above-mentioned combination methods can be used to determine the preliminary one or more power supply configuration strategies, and then one or more power supply configuration schemes can be simulated using power system simulation software to evaluate the system performance (such as voltage stability, power balance, loss, etc.) under each scheme. For the case of simulating multiple configuration schemes, the optimal power supply configuration strategy can be selected by comparing and analyzing the simulation results of different schemes. For the case of simulating a configuration scheme, the power supply configuration strategy can be verified and corrected through the simulation results. In this way, the rationality and accuracy of the power supply configuration strategy can be improved.

[0055] In some preferred schemes, the source-load-storage state can also be tracked in real time in combination with real-time monitoring technology. The actual state information of the source-load-storage can be fused with the fitted state information in real time or at a preset frequency to obtain fused state information. In this step, any of the above-mentioned power supply configuration strategy determination methods can be used to accurately determine the power supply configuration strategy at the current moment based on the fused state information of each power source end, load end, and energy storage end and the line state information of each power supply line. This scheme can further improve the rationality and accuracy of the power supply configuration strategy.

[0056] After determining the power storage configuration strategy, the control process corresponding to the corresponding power supply configuration strategy can be executed. Different power supply configuration strategies correspond to different control processes. For example, for the power conversion strategy, the host power supply line can be controlled to be disconnected, and the backup power supply line can be connected to the load end. For other power supply configuration strategies, the control process can also include: controlling the power supply end to adjust the power output power, switching load priority, controlling the charging and discharging of the energy storage system, etc.

[0057] According to the power supply configuration method of the embodiment of the present application, the influence of the uncertainty factors of source, load and storage is first fully considered, and the fitting state information of multiple power supply ends, load ends and energy storage ends in the distribution network at the current moment is determined in real time and accurately. Then, the line state information of each power supply line in the distribution network at the current moment is accurately determined. And based on the fitting state information and line state information, the power supply configuration strategy at the current moment is quickly and accurately determined, and then the control process corresponding to the power supply configuration strategy can be executed in time, so as to realize the rapid restoration of power supply for multiple lines in the distribution network, and can also significantly reduce the operating cost of the distribution network.

[0058] In one implementation, the plurality of variables include a first variable, a second variable, and a third variable. The method further includes:

[0059] Step S201, respectively fitting at least one power output model of the power supply end, the load model of the load end, and the energy storage model of the energy storage end. The power output model is used to describe the dependency between the first variable and the fitted power generation power of the power supply end, the load model is used to describe the dependency between the second variable and the fitted operating power of each electrical device at the load end, and the energy storage model is used to describe the dependency between the third variable and the fitted state of charge of the energy storage end.

[0060] The first variable can be any uncertainty factor that affects the power generation at the power supply end. For example, for a wind power generation device, the first variable can include the wind speed and wind direction at the current moment. For the load end, different electrical equipment corresponds to different uncertainty factors, so different electrical equipment corresponds to different second variables. For example, for air conditioning, the corresponding second variable may include: outdoor temperature, indoor heat load, air conditioning setting temperature, etc. For the corresponding energy storage end, the third variable may include: the efficiency of the energy storage device, the number of charge and discharge cycles, the charge and discharge rate, etc.

[0061] According to the embodiments of the present application, the power generation output model, the load model, and the energy storage model can be a theoretical model, a statistical model, or a simulation model. A variety of suitable methods can be used to fit each model. Taking a photovoltaic power generation device as an example, a mathematical model can be established based on the principle of photovoltaic power generation technology, and a mathematical formula can be used to describe the influence of factors such as light intensity and temperature on the power generation output. Alternatively, a model established based on historical data and statistical methods, such as a multivariate linear regression model and a support vector machine model, can be used to predict future power generation output power through regression analysis.

[0062] Step S210 determines the fitting state information of each of the multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment, including:

[0063] Step S211, matching the value of the first variable at the current moment with the power generation output model, and determining the fitted power generation of each power supply terminal in the distribution network at the current moment. The value of the first variable determined in real time can be input into the power generation output model fitted for each power supply terminal to obtain the fitted power generation of the power supply terminal.

[0064] Step S212, the value of the second variable at the current moment is matched with the load model to determine the fitted operating power of the load end at the current moment. The value of the second variable determined in real time can be input into the load model fitted for each electrical device at the load end to obtain the fitted operating power of the electrical device. The fitted power generation power of the entire load end can also be obtained.

[0065] Step S213, matching the value of the third variable at the current moment with the energy storage model to determine the fitted state of charge of the energy storage terminal at the current moment. The value of the third variable determined in real time can be input into the energy storage model fitted for each energy storage device to obtain the fitted state of charge of the energy storage device.

[0066] The above scheme takes into account multiple variables that affect the source-load-storage state in the distribution network, and these variables correspond to different uncertain factors. By obtaining the values ​​of these variables in real time, the state of the power supply end, the load end and the energy storage end in the distribution network can be dynamically determined, so that the power supply configuration strategy can adapt to various real-time changes. By fitting the power generation output model of the power supply end, the load model of the load end and the energy storage model of the energy storage end, the method can achieve refined management of each component in the distribution network. This refined management not only improves the accuracy of the power supply configuration strategy, but also helps to optimize resource utilization and reduce energy waste. In addition, the real-time performance of the scheme is good, ensuring that the power supply configuration strategy can respond to changes in the distribution network in a timely manner, thereby improving the stability and reliability of the power supply system. In addition, when determining the power supply configuration strategy, the state information of the power supply end, the load end and the energy storage end, as well as the state of each power supply line are comprehensively considered. This comprehensive consideration method helps to formulate a more comprehensive and reasonable power supply configuration strategy to meet the various needs of the distribution network. In addition, the method can accommodate multiple power supply ends, load ends and energy storage ends, as well as multiple uncertain factors, so it has strong scalability. This makes the method adaptable to distribution networks of different sizes and complexities, providing flexibility and adaptability for future grid development and upgrades.

[0067] In one implementation, the power generation output model includes a wind power generation output model and a photovoltaic power generation output model. Step S201 fits the power generation output model of at least one power supply end, the load model of the load end, and the energy storage model of the energy storage end, respectively, including the following steps:

[0068] Step S201a, using a non-parametric kernel density estimation method to fit a wind power output model.

[0069] like Figure 4a As shown, the power generation of a wind power generation device increases with the increase of wind speed under certain conditions. The wind power generation output model can be expressed by the following formula:

[0070]

[0071] Where f(v) represents the fitted power generation of the wind power generation device, K h represents the selected kernel density function, for example, a Gaussian kernel, v i Indicates rated wind speed, v t represents the actual wind speed at time t.

[0072] Step S201b, using the Beta distribution function to fit the photovoltaic power generation output model.

[0073] like Figure 4bAs shown in Figure 1, the power generation of photovoltaic power generation devices increases with the increase of light intensity under certain conditions. The photovoltaic power generation output model can be expressed by the following formula:

[0074]

[0075] p PV (t) = P r，pv ,h t >h r

[0076] Among them, p PV (t) is the fitted power generation of the photovoltaic power generation device, P r，pv is the rated power of the photovoltaic power generation device, h t is the actual light intensity at time t, h r is the rated light intensity.

[0077] It can be understood that the non-parametric method does not depend on the specific distribution form of the data and can capture the complex structure and nonlinear relationship in the data. As the amount of data increases, the non-parametric kernel density estimation method can automatically adjust the model complexity and improve the fitting accuracy. Therefore, through the kernel density parameter estimation method, the scene data can be accurately simulated without historical data evaluation, and various scene combinations can be quickly and accurately traversed, which can fully reflect the authenticity and integrity of the wind power output model. The value range of the beta distribution function is between (0, 1), which is consistent with the normalized value of the photovoltaic power output power (that is, the ratio of the actual output power to the maximum output power). Therefore, the beta distribution function can more accurately describe the output characteristics of photovoltaic power generation. And the parameter estimation method of the beta distribution is simpler and faster. When the conditions such as light intensity and temperature are relatively stable, the output power distribution of photovoltaic power generation often shows a certain regularity. The beta distribution function can better capture this regularity and accurately predict the output power distribution and probability characteristics of photovoltaic power generation. Therefore, the operating status and change trend of the power system can be predicted more accurately, providing a scientific basis for the dispatch and planning of the power system.

[0078] In one implementation, respectively fitting a power generation output model of at least one power supply end, a load model of a load end, and an energy storage model of an energy storage end includes fitting the load model of the load end using the following formula:

[0079]

[0080] Where a represents each electrical equipment at the interruptible load end, It indicates that the interruptible load end is equivalent to the maximum charging power of the energy storage device at time t, It represents the maximum discharge power of the energy storage device equivalent to the interruptible load end at time t, P a，trepresents the operating power of device a at time t, P a，e It represents the average power of device a in normal operation, P a.max Indicates the maximum active power that can be withdrawn by device a in the interruptible load, X a，t represents the value of the second variable corresponding to device a at time t, X a，min The minimum value of the second variable corresponding to device a.

[0081] For example, the electrical equipment at the load end may include multiple air conditioners. These air conditioners may be interruptible loads. The second variable may include the air conditioner setting temperature X at each moment. According to the interruptible loads, the load node can shut down, increase or reduce the operating power during operation, and participate in the peak shaving control of the new power system. The sum of the interruptible loads is represented by A, and each air conditioner can be represented by a. Therefore, P a，t represents the operating power of air conditioner a at time t, P a，e represents the average power of air conditioner a in normal operation, X a，t represents the set temperature of air conditioner a at time t, X a，min Indicates the minimum setting temperature of air conditioner a.

[0082] In one implementation, the power generation output model of at least one power supply end, the load model of the load end, and the energy storage model of the energy storage end are fitted respectively, including fitting the energy storage model of the energy storage end using the following formula:

[0083]

[0084] Where S(t) represents the state of charge of the energy storage device at the energy storage end at time t, δ represents the discharge rate of the energy storage device, and η in and η out They represent the charging efficiency and discharging efficiency of the energy storage device, E r Indicates the rated power of the energy storage device, P in and P out They represent the charging power and discharging power of the energy storage device respectively.

[0085] In one implementation, the power supply configuration strategy includes a power conversion strategy. Step S230 determines the power supply configuration strategy at the current moment according to the fitting state information and the line state information, and executes the control flow corresponding to the power supply configuration strategy, including:

[0086] Step S231, based on the fitting state information and the line state information, determine whether the line switching condition is currently met. In this step, a variety of suitable methods can be used to determine whether the line switching condition is currently met. For example, the aforementioned rule-based method, fuzzy logic-based method, etc. can be used to determine whether the line switching condition is currently met. Alternatively, the fitting state information and line state information obtained in real time can be input into a trained model, and a classification result of whether the line switching condition is met can be output through a binary classification method.

[0087] Step S232: If yes, determine that the current power supply configuration strategy is a power conversion strategy.

[0088] Step S233 , executing a power conversion process to control one of the at least one second power supply lines to be connected to the load end.

[0089] In the above scheme, by determining the fitting state information of the source-load-storage and the line state information of the power supply line at each moment, potential problems in the distribution network, such as line faults and insufficient power generation at the power supply end, can be discovered in time. When the line switching conditions are met, the power conversion strategy is quickly executed to ensure continuous power supply to the load end, thereby improving the reliability of the entire power supply system. The power conversion strategy allows the backup power supply end to be connected to the power supply line when necessary to replace or assist the main power supply end. This flexibility helps to optimize the use of power resources and ensure that the available power generation capacity can be fully utilized at critical moments. In the traditional power supply configuration, if there is a problem with the main power supply end, the load end may face the risk of power outage. After adopting the power conversion strategy, when there is a problem with the main power supply end, it can be quickly switched to the backup power supply end, thereby greatly reducing the risk of power outage. Through the power conversion process, it is possible to respond quickly and perform power conversion operations when the line switching conditions are met. This rapid response capability helps to reduce the power supply interruption time caused by power problems. The power conversion strategy enables the power supply system to better adapt to various changes and challenges, such as load fluctuations, power failures, etc. By flexibly adjusting the power supply configuration, it can be ensured that the system can maintain stable operation under various circumstances. The above-mentioned power supply configuration scheme including the power conversion strategy has the advantages of improving power supply reliability, optimizing resource allocation, reducing power outage risks, improving response speed and enhancing system adaptability, which can significantly improve the overall performance and stability of the power supply system.

[0090] In one implementation, step S231 determines whether the line switching condition is currently met based on the fitting state information and the line state information, including: step S231.1, at least based on the fitting state information, respectively determining whether each power supply end, load end and energy storage end is in a normal state at the current moment; step S231.2, for each power supply line, determining whether the power supply line is in a normal state based on the line state information of the power supply line; step S231.3, when the power supply end connected to the first power supply line is in an abnormal state, the power supply end connected to the second reference power supply line is in a normal state, the load end and the energy storage end are both in a normal state, and the first power supply line is in an abnormal state and the second reference power supply line is in a normal state, determining that the line switching condition is currently met, wherein the second reference power supply line is any one of at least one second power supply line.

[0091] In one example, a fuzzy logic method can be used to define multiple fuzzy sets to describe the state of the source, load and storage and the line state of each power supply line in advance based on actual operation data and experience. For example: power supply state: {normal, abnormal}; load state: {normal, abnormal}; energy storage state: {normal, abnormal}; line state: {normal, abnormal}. And a corresponding membership function can be defined for each fuzzy set. In step S231.1, the membership function corresponding to each end can be matched at least according to the fitting state information of each end of each power supply end, load end, and energy storage end, and the set state corresponding to each end can be determined. Similarly, in step S231.2, the line state information of each power supply line can be matched with the membership function corresponding to the power supply line to determine the set state corresponding to each power supply line. In step S231.3, the combination state can be determined according to the set state corresponding to each end in the source, load and storage and the set state corresponding to each power supply line, and it can be judged whether the combination state is consistent with the preset line switching combination state. If so, it is determined that the line switching condition is currently met.

[0092] In another example, multiple logical judgments may be performed successively to quickly determine whether the line switching condition is currently met. A specific example of this solution will be described later and will not be repeated here.

[0093] Step S233 executes the power conversion process, including: disconnecting the first power supply line from the load end, and controlling the second reference power supply line to be connected to the load end.

[0094] like Figure 5aAs shown, the automatic switching of the power supply line can be realized by remote control of the automatic transfer switch (Automatic Transfer Switch), thereby realizing power conversion. Specifically, the automatic conversion state transition includes: start, disabled, enabled, started, converting, single-side conversion successful, conversion completed, and end of the process. When the line switching conditions are met, the ATS can be controlled to switch from the disabled state to the enabled state. When the start condition is met, the state of the ATS is controlled to be started. The ATS is used to perform the opening and closing operations on the first power supply line and the selected second power supply line, and the actual conversion result (conversion success or failure or single-side conversion success) is fed back. After the remote control ATS is in the enabled state, first determine whether the state of the bus voltage, incoming current, and load switch opening and closing position on this side is normal. After determining that it is normal, control the ATS to the started state. If the device is powered off and restarted, or the communication is abnormal, the ATS will enter the disabled mode to ensure the reliability of power supply recovery. When there is bus voltage imbalance or low voltage residual pressure on this side, and the current setting judgment condition is performed, the ATS continues to enter the started state. After the ATS started state takes effect, the master / standby roles can be automatically assigned through the communication model file. The master power supply line (first power supply line) performs split action through fast communication, and shares the switch signal through the fast communication service. Then the ATS in the selected standby power supply line (second power supply line) enters the started state, quickly performs the closing action, and informs the normal state. After the host receives the normal state, the host and the standby send the conversion success status at the same time, ending the conversion process.

[0095] The above scheme sets the line switching conditions including the power supply end, the load end, the energy storage end and the status of the power supply line, so that the decision-making process is clear and predictable, reducing the subjectivity and uncertainty of human judgment. When the first power supply line or the power supply end to which it is connected is abnormal, the scheme can quickly identify and trigger the line switching, thereby ensuring that the load end can obtain power from the backup power supply end in time and reduce the power outage time. Through the power conversion process, the scheme can automatically adjust the power supply configuration when necessary to ensure the effective use of power resources. This helps to avoid power waste and improve the overall efficiency of the power supply system. Through real-time monitoring and rapid response, it helps to enhance the stability of the power supply system. Even in the face of faults or abnormal situations, the system can quickly recover and maintain stable operation. The above power supply configuration scheme has clear and reasonable line switching conditions, can respond to faults in time, optimize resource allocation, enhance system stability, improve user experience, and is easy to implement and maintain. It further improves the performance, reliability and user satisfaction of the power supply system.

[0096] In one implementation, the method further includes: step S202, collecting actual status information of each power supply end, load end and energy storage end at the current moment. For example, the actual power generation power of each power generation device, the actual operating power of the load end, and the actual charge state of the energy storage end can be collected and monitored in real time.

[0097] Step S231.1 determines at least based on the fitting state information whether each power supply terminal, load terminal and energy storage terminal are in a normal state at the current moment, and also includes: step S231.1a, fusing the fitting state information with the corresponding actual state information to obtain fused state information. Step S231.2b, determines whether each power supply terminal, load terminal and energy storage terminal are in a normal state at the current moment based on the fused state information.

[0098] For each of the power supply end, load end and energy storage end in the distribution network, a variety of suitable data fusion methods can be used to fit the calculated fitting state information and the actual state information actually monitored to obtain the fused state information. For example, the difference between the two can be compared first. When the difference is small, the weighted fusion and Kalman filtering methods can be used to determine the fused state information. In the case of large differences, difference analysis can be performed to evaluate the significance and directionality of the differences. And the system characteristics and historical data can be combined to analyze the causes of the differences, such as the inaccuracy of the prediction model, the error of the monitoring equipment, etc. Then, according to the analysis results, the more accurate one can be selected from the fitting state information and the actual state information as the fused state information. Afterwards, it can be accurately determined whether the end is in a normal state at the current moment based on the fused state information of each end.

[0099] In the above scheme, combined with the actual state information of the source, load and storage monitored in real time, the state of the source, load and storage can be captured more accurately, and the actual state information monitored and the fitted state information are integrated, which can significantly improve the accuracy of the power supply configuration.

[0100] For example, after performing a difference analysis on the fitted state information and the actual state information of the source, load and storage, the fitted power generation output model can be tuned according to the difference analysis results to improve the accuracy of subsequent predictions. In this way, a real-time feedback mechanism is established to continuously adjust and optimize the power supply configuration strategy according to the actual operation of the system to ensure the effectiveness and stability of the strategy.

[0101] In one implementation, the line status information includes the voltage and current in the line. Step S231.2 determines whether the power supply line is in a normal state according to the line status information of the power supply line, including:

[0102] Step S231.2a, determining whether there is a voltage abnormality in the power supply line according to the voltage of the power supply line and at least one voltage threshold, wherein the voltage abnormality includes at least one of a voltage imbalance abnormality, an overvoltage abnormality, and a low voltage abnormality;

[0103] Step S231.2b, determining whether there is an overcurrent abnormality in the power supply line according to the current and the current threshold of the power supply line;

[0104] Step S231.2c, when it is determined that there is no voltage abnormality and no overcurrent abnormality in the power supply line, it is determined that the power supply line is in a normal state; otherwise, it is determined that the power supply line is in an abnormal state.

[0105] The power supply line includes Figure 3 Taking line 1 and line 2 in the example, line 1 may be the power supply line of the host power supply, and line 2 may be the power supply line of the standby power supply. The line status information collected in step S220 may include the information in Table 1 below. In this example, the line status information may include switch combination status information in addition to the voltage and current in the power supply line.

[0106] Table 1 Line status information list

[0107]

[0108] It should be noted that the execution order of the above steps S231.2a and S231.2b can be arbitrary. The voltage threshold and the current threshold can be reasonably set according to actual needs. For example, the voltage threshold for judging voltage imbalance abnormality, overvoltage abnormality, and low voltage abnormality can be 10V. The current threshold for judging overcurrent abnormality can be 1.2A.

[0109] It can be understood that voltage and current are two important indicators that reflect the status of the power supply line. Monitoring them at the same time can more comprehensively evaluate the health of the power supply line. In the above scheme, by setting the voltage threshold and current threshold, the voltage anomaly (such as voltage imbalance, overvoltage, low voltage) and overcurrent anomaly in the power supply line can be accurately identified. The voltage and current information of the power supply line is obtained in real time, and the status is judged immediately. This real-time performance ensures that the power supply system can respond quickly to changes in the line status, so as to take necessary measures in time. The scheme is based on the existing voltage and current monitoring technology and is relatively simple to implement. At the same time, by setting clear thresholds and judgment logic, the status judgment process is more standardized and automated. By comprehensively monitoring the voltage and current information of the power supply line and setting the corresponding thresholds for accurate judgment, it has the advantages of comprehensive monitoring, accurate judgment, real-time performance, improved reliability, reduced maintenance costs and easy implementation, which further improves the performance and reliability of the power supply system.

[0110] In a specific example, if Figure 5b As shown, the fitting state information of the host source end, the host energy storage end, the standby source end, the standby energy storage end, and the load end in the distribution network can be calculated at each moment, and the actual state information of the host source end, the host energy storage end, the standby source end, the standby energy storage end, and the load end can be monitored in real time through software and hardware. At each moment, the fitting state information and the actual state information of each end can be fused to obtain the fused state information. Then, according to the fused state information, it can be determined whether the fused state information of each end is normal. After that, it can be determined whether the host remote end and the energy storage end are both normal. If not, a prompt message indicating that the host remote end and the energy storage end are abnormal can be output, and a maintenance prompt can be prompted. Then, continue to determine whether the standby source end and the energy storage end are both normal. If not, a prompt message indicating that the standby source end / energy storage end is abnormal can also be output. After that, it can be determined whether the load end is normal. If so, continue to determine whether the voltage of line 1 is abnormal. If so, further determine whether the voltage of line 2 is normal. If so, continue to determine whether there is an overcurrent abnormality in line 1. If yes, it is further determined whether there is no overcurrent abnormality in line 2. If yes, it is timed, and when the counted time reaches the preset time (such as 2 seconds), the above-mentioned line state determination process is executed again to further verify whether the current line switching conditions are met. If yes, it enters process B, that is, the control process corresponding to the power conversion strategy is executed. Specifically, after the automatic transfer switch meets the start-up conditions, the circuit breaker of line 1 can be controlled to trip first. If the setting time has not arrived, that is, the circuit breaker of line 1 has not successfully tripped, it is determined whether the number of trips has reached 3 times. If not, try to trip again. If yes, it means that the tripping failed, line 1 sends a conversion failure signal, and the host sends a process abnormality signal. When the setting time of the circuit breaker of line 1 is reached, it means that line 1 has successfully tripped. After that, the circuit breaker of line 2 can be controlled to close. When the closing time is reached, the circuit breaker of line 2 is closed successfully, and line 2 sends a normal signal. That is, the line is automatically converted successfully and a success signal is sent. If the circuit breaker of line 2 fails to close three times, line 2 sends a conversion failure signal and a process abnormality signal.

[0111] In addition, the power supply configuration method of the embodiment of the present application also establishes a fast communication model between various lines and modules. Figure 7bAs shown in the figure, based on the three-layer communication module, the link layer performs fast position change message interaction. The physical address is sent using the packet address, and 5 messages are sent repeatedly at 4 time points. The sending time interval is designed to be 500ms, 2ms, 2ms, and 8ms, and the message survival time is designed to be 4ms, 4ms, 8ms, and 16ms. When there is no switch position change signal, the host uses a fixed interval period to send, in order to maintain the existing link. When there is a switch position change signal, the position change event is sent quickly, and after stabilization, the interval period becomes longer. Configurable interval sending can effectively ensure the reliability of fast communication, and can perform multicast sending in the shortest time, effectively ensuring the real-time nature of fast communication.

[0112] According to the embodiment of the present application, a corresponding distribution network calculation model can also be designed according to the distribution network line, dynamic simulation verification can be performed according to the actual distribution network parameters, and the above-mentioned power supply configuration method of the embodiment of the present application can be optimized according to the verification results. Figure 6 As shown, the example model can include two three-phase power supply lines, an energy storage module and a load end. Each power supply line includes: a three-phase power supply, a three-phase transformer, a three-phase circuit breaker, a three-phase measurement module and an oscilloscope. Among them, the three-phase power supply is used to simulate the power supply end, and the three-phase measurement module is used to measure the line status information of line 1, specifically for measuring the voltage and current in the line. The oscilloscope is used to display the waveform of the voltage and current in the line changing with time. The energy storage module in the example model is connected to the load end and the power supply line, and can be used in the charging and discharging process to dynamically adjust the load balance. As shown Figure 6 As shown, the power supply line currently connected to the three-phase power supply 1 is the main power supply line, which is connected to the energy storage module and the load end. The power supply line currently connected to the three-phase power supply 2 is the standby power supply line. The example model also includes an automatic conversion subsystem and a logic operation module. The automatic conversion subsystem can be specifically an automatic conversion switch. The automatic conversion switch is connected to the three-phase circuit breaker 1 and the three-phase circuit breaker 2 respectively. It can be understood that when the three-phase measurement module 1 detects that there is an abnormality in the main power supply line and the standby power supply line is normal, the automatic conversion switch can control the three-phase circuit breaker 1 to trip and control the three-phase circuit breaker 2 to close.

[0113] like Figure 7aAs shown, the monitoring results of the oscilloscope in the above-mentioned example model show that the voltage waveform of phase A is normal in the time period of 0 to 0.1s after the three-phase power supply 1 starts monitoring, but after 0.1s, the voltage waveform of phase A becomes abnormal when encountering a fault. At this time, the system can detect the above-mentioned fault in time by using the above-mentioned power supply configuration method of the embodiment of the present application, and make a line switching decision in time. The switch between power supply line 1 and the load end was successfully disconnected before 0.11 seconds, and the switch between power supply line 2 and the load end was closed, so that the switching of the power supply line was realized in time and accurately. It can be seen that according to the above-mentioned power supply configuration method of the embodiment of the present application, when the uncertainty of source, load and storage is taken into account, when the main power supply line fails, it can be automatically, quickly and accurately switched to the backup power supply line, thereby realizing rapid fault isolation and line recovery, which verifies the superiority of the power supply configuration method of the embodiment of the present application.

[0114] like Figure 8 As shown, the power supply configuration device 800 provided in the embodiment of the present application includes:

[0115] A fitting module 810 is used to determine the fitting state information of multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment according to the values ​​of multiple variables that affect the source-load-storage state in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal;

[0116] The first determination module 820 is used to determine the line status information of each power supply line in the distribution network at the current moment, wherein each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to at least one backup power supply end;

[0117] The configuration module 830 is used to determine the power supply configuration strategy at the current moment according to the fitting state information and the line state information, and execute the control process corresponding to the power supply configuration strategy.

[0118] like Fig. 9 As shown, the terminal device 900 provided in the embodiment of the present application includes: at least one processor 910 ( Fig. 9 Only one processor is shown in the figure), a memory 920, and a computer program 930 stored in the memory 920 and executable on at least one processor 910. When the processor 910 executes the computer program 930, the steps of the above-mentioned power supply configuration method are implemented.

[0119] The terminal device may include but is not limited to a processor and a memory. Fig. 9It is only an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown in the figure, or combine certain components, or different components. The processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0120] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0121] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The functional modules in the embodiment can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. In addition, the specific names of the functional modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0122] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned power supply configuration method can be implemented.

[0123] An embodiment of the present application provides a computer program product. When the computer program product is executed on a terminal device, the terminal device can implement the steps in the above-mentioned power supply configuration method.

[0124] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A power supply configuration method, characterized in that: include: Determine, according to the values ​​of multiple variables that affect the source-load-storage state in the distribution network at the current moment, respective fitting state information of multiple power supply terminals, load terminals, and energy storage terminals in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal; Determine the line status information of each power supply line in the power distribution network at the current moment, wherein the each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to the at least one standby power supply end; The power supply configuration strategy at the current moment is determined according to the fitting state information and the line state information, and a control process corresponding to the power supply configuration strategy is executed.

2. The power supply configuration method according to claim 1, characterized in that: The plurality of variables include a first variable, a second variable and a third variable, and the method further includes: Fitting the power generation output model of at least one power supply end, the load model of the load end, and the energy storage model of the energy storage end respectively, wherein the power generation output model is used to describe the dependency relationship between the first variable and the fitted power generation power of the power supply end, the load model is used to describe the dependency relationship between the second variable and the fitted operating power of each electrical device at the load end, and the energy storage model is used to describe the dependency relationship between the third variable and the fitted state of charge of the energy storage end; The determining of the fitting state information of each of the plurality of power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment includes: Matching the value of the first variable at the current moment with the power generation output model to determine the fitted power generation power of each power supply terminal in the power distribution network at the current moment; Matching the value of the second variable at the current moment with the load model to determine the fitted operating power of the load end at the current moment; The value of the third variable at the current moment is matched with the energy storage model to determine the fitted state of charge of the energy storage end at the current moment.

3. The power supply configuration method according to claim 2, characterized in that: The respectively fitting of the power generation output model of the at least one power supply end, the load model of the load end and the energy storage model of the energy storage end comprises fitting the load model of the load end using the following formula: Where a represents each electrical equipment at the interruptible load end, It indicates the maximum charging power of the energy storage node equivalent to the interruptible load end at time t, It represents the maximum discharge power of the interruptible load end equivalent to the energy storage node at time t, P a,t represents the operating power of device a at time t, P a,e It represents the average power of device a in normal operation, P a.max Indicates the maximum active power that can be withdrawn by device a in the interruptible load, X a,t represents the value of the second variable corresponding to device a at time t, X a,min The minimum value of the second variable corresponding to device a.

4. The power supply configuration method according to any one of claims 1 to 3, characterized in that: The power supply configuration strategy includes a power conversion strategy, and the power supply configuration strategy at the current moment is determined according to the fitting state information and the line state information, and a control process corresponding to the power supply configuration strategy is executed, including: Determining whether a line switching condition is currently met according to the fitting state information and the line state information; If yes, then determining that the power supply configuration strategy at the current moment is the power conversion strategy; and A power conversion process is executed to control one of the at least one second power supply line to be connected to the load end.

5. The power supply configuration method according to claim 4, characterized in that: The determining whether a line switching condition is currently met according to the fitting state information and the line state information includes: At least according to the fitting state information, determining whether each of the power supply end, the load end and the energy storage end is in a normal state at the current moment; For each power supply line, determining whether the power supply line is in a normal state according to the line state information of the power supply line; In the case where the power supply end connected to the first power supply line is in an abnormal state, the power supply end connected to the second reference power supply line is in a normal state, the load end and the energy storage end are both in a normal state, and the first power supply line is in an abnormal state and the second reference power supply line is in a normal state, determining that the line switching condition is currently met, wherein the second reference power supply line is any one of the at least one second power supply line; The power conversion process includes: The first power supply line is disconnected from the load end, and the second reference power supply line is controlled to be conductively connected to the load end.

6. The power supply configuration method according to claim 5, characterized in that: The method further comprises: Collecting the actual status information of each power supply end, load end and energy storage end at the current moment; The step of determining whether each of the power supply end, the load end, and the energy storage end is in a normal state at the current moment at least according to the fitting state information, further includes: Fusing the fitted state information with the corresponding actual state information to obtain fused state information; According to the fusion status information, it is determined whether each of the power supply end, the load end and the energy storage end is in a normal state at the current moment.

7. The power supply configuration method according to claim 5, characterized in that: The line status information includes voltage and current in the line, and determining whether the power supply line is in a normal state according to the line status information of the power supply line includes: Determine whether there is a voltage abnormality in the power supply line according to the voltage of the power supply line and at least one voltage threshold, wherein the voltage abnormality includes at least one of a voltage imbalance abnormality, an overvoltage abnormality, and a low voltage abnormality; Determine whether there is an overcurrent abnormality in the power supply line according to the current and the current threshold of the power supply line; When it is determined that there is no voltage abnormality and no overcurrent abnormality in the power supply line, it is determined that the power supply line is in a normal state; otherwise, it is determined that the power supply line is in an abnormal state.

8. A power supply configuration device, characterized in that: include: A fitting module, used to determine the fitting state information of each of the multiple power supply terminals, load terminals and energy storage terminals in the distribution network at the current moment according to the values ​​of multiple variables affecting the source-load-storage state in the distribution network at the current moment, wherein each variable corresponds to an uncertainty factor, and the multiple power supply terminals include a host power supply terminal and at least one standby power supply terminal; A first determination module is used to determine the line status information of each power supply line in the power distribution network at the current moment, wherein the each power supply line includes: a first power supply line respectively connected to the host power supply end and the load end at the current moment, and at least one second power supply line respectively connected to the at least one standby power supply end; A configuration module is used to determine a power supply configuration strategy at a current moment according to the fitting state information and the line state information, and execute a control process corresponding to the power supply configuration strategy.

9. A terminal device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the power supply configuration method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the power supply configuration method according to any one of claims 1 to 7 are implemented.

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