Virtual power plant power supply optimization control method based on supply-demand balance

Abstract

The invention relates to the field of power dispatching control, in particular to a virtual power plant power supply optimization control method based on supply-demand balance. The method comprises the following steps: firstly, obtaining the generating capacity and the power consumption of different power supply areas in each historical period, obtaining the environmental data of different environmental indexes in each historical period, obtaining the power supply priority of the power supply areas according to the difference between the predicted generating capacity and the predicted power consumption of a target power supply area, and selecting the supply-demand imbalance time period of the power supply areas; analyzing the correlation between the generating capacity and the environmental data of the power supply area in the supply-demand imbalance time period, obtaining the environmental influence sensitivity of the supply-demand imbalance time period, and obtaining the schedulable potential value of the power supply area in combination with the environmental influence sensitivity and length of each supply-demand imbalance time period of the power supply area and the power supply priority; and the power supply of each power supply area is optimally controlled. The method can improve the power supply optimization control effect of the virtual power plant, and avoids the imbalance of power supply and demand.

Description

Technical Field

[0001] The present invention relates to the field of power dispatching control, and particularly to an optimized control method for power supply of a virtual power plant based on supply-demand balance. Background Art

[0002] As an emerging distributed energy aggregation and coordinated dispatching mechanism, a virtual power plant can uniformly manage numerous distributed energy sources by integrating distributed power sources, energy storage systems, and adjustable loads, enabling the power supply and demand in the power system to reach equilibrium, ensuring the stability of the grid frequency, voltage, and operation reliability. To achieve the supply-demand balance of the virtual power plant, power supply is usually based on load forecasting and real-time power resource monitoring, and an optimized control algorithm is adopted to dynamically dispatch various resources in the virtual power plant to achieve the optimal control strategy for meeting the grid supply-demand balance.

[0003] In related technologies, the virtual power plant dynamically dispatches distributed power supply energy and resources by real-time monitoring of power load changes such as power generation and user-side power consumption in the distributed power supply area, and based on the prediction of the power supply-demand level to meet the supply-demand balance of power supply. However, among many power supply areas, there are some that rely on renewable energy sources such as wind energy and solar energy for power supply. These power supply methods are easily affected by environmental factors, resulting in large prediction errors for power loads, and further leading to poor effects of the virtual power plant on optimizing power supply control and causing power supply-demand imbalance. Summary of the Invention

[0004] In order to solve the technical problem that the power supply area relying on renewable energy is easily affected by environmental factors, resulting in large prediction errors for power loads, and further leading to poor effects of the virtual power plant on optimizing power supply control and causing power supply-demand imbalance, the purpose of the present invention is to provide an optimized control method for power supply of a virtual power plant based on supply-demand balance, and the specific technical solutions adopted are as follows: The present invention proposes an optimized control method for power supply of a virtual power plant based on supply-demand balance, and the method includes: Obtain the power generation and power consumption of different power supply areas in each historical period, and at the same time obtain the environmental data of different environmental indicators in each historical period; Take any power supply area as the target power supply area, and predict the predicted power generation and predicted power consumption of the target power supply area in the future period according to the power generation and power consumption of the target power supply area in each historical period; obtain the power supply priority of the target power supply area according to the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period; According to the differences in power generation and power consumption in the target power supply area in each historical period, obtain the power supply and demand balance degree of the target power supply area in each historical period; based on the power supply and demand balance degrees of the target power supply area in each historical period, obtain multiple supply and demand imbalance time periods of the target power supply area; according to the correlation between the power generation and the environmental data of environmental indicators in each historical period in each supply and demand imbalance time period of the target power supply area, and the distribution of the power supply and demand balance degrees in each historical period, obtain the environmental impact sensitivity of each supply and demand imbalance time period of the target power supply area; according to the environmental impact sensitivity and length of each supply and demand imbalance time period of the target power supply area, and the power supply priority of the target power supply area, obtain the dispatchable potential value of the target power supply area; Based on the dispatchable potential values of each power supply area, optimize and control the power supply of each power supply area.

[0005] Further, the predicting of the predicted power generation and predicted power consumption of the target power supply area in the future period includes: Input the power generation of the target power supply area in each historical period into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted power generation of the target power supply area in the future period; Input the power consumption of the target power supply area in each historical period into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted power consumption of the target power supply area in the future period, where the length of the future period is the same as the length of a single historical period.

[0006] Further, the obtaining of the power supply priority of the target power supply area includes: Take the sum of the predicted power generation of the target power supply area in the future period and the current stored power as the total available power of the target power supply area in the future period; Normalize the difference between the total available power and the predicted power consumption of the target power supply area in the future period to obtain the power supply priority of the target power supply area.

[0007] Further, the obtaining of the power supply and demand balance degree of the target power supply area in each historical period includes: Perform negative-correlated normalization on the absolute value of the difference between the power generation and power consumption of the target power supply area in each historical period to obtain the power supply and demand balance degree of the target power supply area in each historical period.

[0008] Further, the obtaining of multiple supply and demand imbalance time periods of the target power supply area includes: For the target power supply area, regard the historical periods with the power supply and demand balance degree less than the preset balance degree threshold as the candidate historical periods of the target power supply area; Take adjacent and consecutive candidate historical periods as the supply-demand imbalance time periods of the target power supply area.

[0009] Further, obtaining the environmental impact sensitivity of each supply-demand imbalance time period of the target power supply area includes: Take any supply-demand imbalance time period of the target power supply area as the target supply-demand imbalance time period, and take the sequence composed of the power generation amounts of all historical periods in the target supply-demand imbalance time period as the power generation time series of the target supply-demand imbalance time period; Take the sequence composed of the environmental data of the same environmental indicator in all historical periods in the target supply-demand imbalance time period as the environmental data time series of the target supply-demand imbalance time period for each environmental indicator; Analyze the correlation between the power generation time series of the target supply-demand imbalance time period and the environmental data time series for each environmental indicator to obtain the environmental correlation degree of the target supply-demand imbalance time period; Analyze the overall level of the power supply-demand balance degree of all historical periods of the target power supply area to obtain the first overall supply-demand balance degree of the target power supply area, and analyze the overall level of the power supply-demand balance degree of all historical periods of the target supply-demand imbalance time period to obtain the second overall supply-demand balance degree of the target supply-demand imbalance time period; Take the difference between the second overall supply-demand balance degree and the first overall supply-demand balance degree as the power supply-demand imbalance degree of the target supply-demand imbalance time period; Integrate the environmental correlation degree and the power supply-demand imbalance degree of the target supply-demand imbalance time period to obtain the environmental impact sensitivity of the target supply-demand imbalance time period.

[0010] Further, obtaining the environmental correlation degree of the target supply-demand imbalance time period includes: Take the absolute value of the Pearson correlation coefficient between the power generation time series of the target supply-demand imbalance time period and the environmental data time series for each environmental indicator as the correlation parameter of the target supply-demand imbalance time period for each environmental indicator; Take the average value of the correlation parameters of the target supply-demand imbalance time period for all environmental indicators as the environmental correlation degree of the target supply-demand imbalance time period.

[0011] Further, obtaining the dispatchable potential value of the target power supply area includes: Obtain the power supply stability of the target power supply area according to the environmental impact sensitivity and length of all supply-demand imbalance time periods of the target power supply area; Integrate and normalize the power supply stability and the power supply priority of the target power supply area to obtain the dispatchable potential value of the target power supply area.

[0012] Further, the obtaining of the power supply stability degree of the target power supply area includes: After comprehensively considering the environmental impact sensitivity and length of each power supply and demand imbalance time period in the target power supply area and performing a negative correlation mapping, the power supply and demand imbalance recovery coefficient of each power supply and demand imbalance time period in the target power supply area is obtained; Taking the average value of the power supply and demand imbalance recovery coefficients of all power supply and demand imbalance time periods in the target power supply area as the power supply stability degree of the target power supply area.

[0013] Further, the optimizing and controlling of the power supply of each power supply area based on the dispatchable potential values of each power supply area includes: Taking the dispatchable potential values of each power supply area as the added items of the objective function used in the dynamic particle swarm optimization algorithm, and inputting the power generation and consumption of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period into the dynamic particle swarm optimization algorithm, and the dynamic particle swarm optimization algorithm outputs the preferred sequence of power supply areas; Based on the preferred sequence of power supply areas, the power supply of each power supply area is optimized and dispatched.

[0014] The present invention has the following beneficial effects: The present invention takes into account that the power supply areas relying on renewable energy are vulnerable to environmental factors, resulting in large prediction errors in power load forecasting, and further leading to poor effects of the virtual power plant on optimizing and controlling power supply, causing power supply and demand imbalance. Therefore, the present invention first obtains the power generation and consumption of different power supply areas in each historical period, and at the same time obtains the environmental data of different environmental indicators in each historical period, and preliminarily forecasts the power generation and consumption of the target power supply area in the future period. The power resource supply capacity of the target power supply area in the future period is reflected by the obtained power supply priority, so that the resources with sufficient electric energy are preferentially utilized during power supply, thereby reducing the risk of supply-demand mismatch. Aiming at the prediction errors and power supply and demand imbalance caused by environmental factors, the influence degree of environmental factors on the power supply area is analyzed in different power supply and demand imbalance time periods, which helps to quantify the influence of environmental factors on the power supply of the power supply area, so as to formulate targeted compensation or standby strategies, improve the fault tolerance of the power system, and then optimize and control the power supply of each power supply area based on the dispatchable potential values of each power supply area and in combination with an optimization algorithm, improve the effect of the virtual power plant on optimizing and controlling power supply, avoid power supply and demand imbalance, and enhance the stability and flexibility of the power supply of the virtual power plant. Description of the Drawings

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 Flowchart of an optimal control method for virtual power plant power supply based on supply-demand balance provided by an embodiment of the present invention. Detailed implementation manners

[0017] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, describe in detail the specific implementation manners, structures, features, and effects of an optimal control method for virtual power plant power supply based on supply-demand balance proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0019] The following will specifically describe the specific solution of an optimal control method for virtual power plant power supply based on supply-demand balance provided by the present invention with reference to the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of an optimal control method for virtual power plant power supply based on supply-demand balance provided by an embodiment of the present invention. The method includes: Step S1: Obtain the power generation and power consumption in each historical period of different power supply areas, and at the same time obtain the environmental data of different environmental indicators in each historical period.

[0021] A virtual power plant can generally control and integrate various types of power supply areas, such as photovoltaic power supply areas, wind power supply areas, adjustable loads, etc. These power supply areas are usually deployed in a distributed structure to provide power support for different power consumption areas. And the power system of each power supply area can automatically record its power generation in different time periods and the power consumption of the user side it serves. Therefore, in the embodiments of the present invention, first, the power generation and power consumption of each power supply area in each historical period are collected from the power system of each power supply area. Among them, the units of power generation and power consumption are usually kilowatt-hours, and the length of each time period is usually 10 to 30 minutes. In an embodiment of the present invention, the length of the historical period is set to 15 minutes. The specific length of the historical period can also be set by the implementer according to the specific implementation scenario and is not limited herein.

[0022] Since there are many power supply methods relying on renewable energy such as wind and solar energy in the power supply areas integrated by the virtual power plant, and these power supply areas are easily affected by environmental and weather factors, etc. Therefore, subsequently, in order to analyze the degree of influence of the power supply area by environmental factors, it is also necessary to obtain the environmental data of different environmental indicators in each historical period through a weather station or a third-party API. Among them, the environmental indicators include, for example, wind speed, light intensity, temperature, humidity, etc. The types of environmental indicators can be set by the implementer according to the specific implementation scenario and are not limited herein.

[0023] It should be noted that for the convenience of subsequent calculations, the embodiments of the present invention also need to preprocess the various data collected, including operations such as data cleaning, outlier removal, missing value filling, and standardization processing. Among them, data preprocessing is a well-known technical means for those skilled in the art and will not be elaborated herein.

[0024] Step S2: Take any power supply area as the target power supply area, and predict the predicted power generation and predicted power consumption of the target power supply area in the future period according to the power generation and power consumption of the target power supply area in each historical period; obtain the power supply priority of the target power supply area according to the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period.

[0025] When managing distributed power supply areas, in order to achieve dynamic balance between power supply and demand, the virtual power plant needs to orderly dispatch various types of distributed power supply areas. Based on the operating status and historical data of each power supply area, the virtual power plant predicts the power supply and demand situation in the future period and judges the adequacy of power reserves to ensure the efficient operation and stable supply of the overall power system. Therefore, first, any power supply area is analyzed, any power supply area is taken as the target power supply area, and the predicted power generation and predicted power consumption of the target power supply area in the future period are predicted according to the power generation and power consumption of the target power supply area in each historical period.

[0026] Preferably, in an embodiment of the present invention, the method for obtaining the predicted power generation and predicted power consumption of the target power supply area in the future period specifically includes: Input the power generation of the target power supply area in each historical period into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted power generation of the target power supply area in the future period.

[0027] Similarly, input the power consumption of the target power supply area in each historical period into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted power consumption of the target power supply area in the future period, where the length of the future period is the same as the length of a single historical period.

[0028] Among them, the time series prediction algorithm can select existing autoregressive integrated moving average algorithm or exponential smoothing algorithm, etc., which is not limited here.

[0029] Through the results output by the prediction model, the virtual power plant can obtain the power generation and power consumption of the target power supply area in the short term in the future. By comparing the predicted power generation and predicted power consumption of the target power supply area in the future period, it is evaluated whether the overall supply capacity of the target power supply area meets the predicted load demand. If the predicted power generation of the target power supply area is larger than the predicted power consumption, it means that the stored power of the target power supply area is more sufficient, so it is suitable to be given priority as a power generation unit for power supply. Therefore, the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period can be analyzed, and the power supply priority obtained reflects the power resource supply capacity and the priority level of power supply of the target power supply area in the future period, so as to preferentially utilize the resources with sufficient electric energy during power supply, thereby reducing the risk of supply-demand mismatch.

[0030] Preferably, in an embodiment of the present invention, the method for obtaining the predicted power generation and predicted power consumption of the target power supply area in the future period specifically includes: Take the sum of the predicted power generation of the target power supply area in the future period and the current stored power as the total available power of the target power supply area in the future period. The larger the total available power, the more available power the target power supply area has in the future period. Among them, the current stored power of the target power supply area can also be obtained from the corresponding power system.

[0031] Normalize the difference between the total available power and the predicted power consumption of the target power supply area in the future period, and limit the calculation result within a range, so as to obtain the power supply priority of the target power supply area.

[0032] In other embodiments of the present invention, the total power supply amount of the target power supply area in a future period can also be used as the numerator, the predicted power consumption amount of the target power supply area in the future period as the denominator, and the ratio is normalized to obtain the power supply priority of the target power supply area.

[0033] In one embodiment of the present invention, the normalization process can be, for example, the maximum-minimum normalization process, and the normalization in subsequent steps can all adopt the maximum-minimum normalization process. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of values, which will not be elaborated here.

[0034] As an example, in one embodiment of the present invention, the expression of the power supply priority of the target power supply area can be, for example: Wherein, represents the power supply priority of the target power supply area; represents the predicted power generation amount of the target power supply area in a future period; represents the current power storage amount of the target power supply area; represents the total power supply amount of the target power supply area in a future period; represents the predicted power consumption amount of the target power supply area in a future period; represents the normalization function for normalization processing.

[0035] So far, the prediction of the power generation amount and power consumption amount of the target power supply area has been completed, and the power supply priority of the target power supply area has been obtained.

[0036] Step S3: Obtain the power supply and demand balance degree of the target power supply area in each historical period according to the difference between the power generation amount and power consumption amount of the target power supply area in each historical period; based on the power supply and demand balance degrees of the target power supply area in each historical period, obtain multiple power supply and demand imbalance time periods of the target power supply area; according to the correlation between the power generation amount and the environmental data of the environmental indicators in each historical period in each power supply and demand imbalance time period of the target power supply area, and the distribution of the power supply and demand balance degrees in each historical period, obtain the environmental impact sensitivity of each power supply and demand imbalance time period of the target power supply area; according to the environmental impact sensitivity and length of each power supply and demand imbalance time period of the target power supply area, and the power supply priority of the target power supply area, obtain the adjustable potential value of the target power supply area.

[0037] A virtual power plant integrates various distributed power supply areas such as photovoltaic, wind power, energy storage, and adjustable load to achieve unified management of multi-source heterogeneous energy. To achieve power supply-demand balance, it relies on a prediction model to provide short-term power supply-demand levels. However, since power supply areas relying on renewable energy are vulnerable to environmental factors, among which renewable energy represented by photovoltaic and wind power is easily affected by environmental factors such as extreme weather, it is difficult to accurately predict the short-term power supply quantity, which is prone to prediction errors. Therefore, it is necessary to analyze the impact of changes in real-time monitored environmental data on the power supply-demand balance of the target power supply area and evaluate the power supply stability of each power supply area, so as to determine the dispatchable potential value of each power supply area, improve the effect of the virtual power plant on optimizing power supply control, and avoid power supply-demand imbalance.

[0038] Since environmental factors can affect the actual power generation of the target power supply area, resulting in significant fluctuations in its power generation capacity, and further leading to the phenomenon of power supply-demand imbalance in the target power supply area in each historical period. The smaller the difference between the power generation and power consumption of the target power supply area in a certain historical period, the more balanced the power supply-demand in that historical period. Therefore, in the embodiments of the present invention, first, according to the difference between the power generation and power consumption of the target power supply area in each historical period, the power supply-demand balance degree of the target power supply area in each historical period is obtained. The power supply-demand balance degree reflects the balance degree of the power supply-demand of the target power supply area in each historical period. Subsequently, based on the power supply-demand balance degrees of each historical period, the time periods of supply-demand imbalance of the target power supply area can be selected, and the influence degree of environmental factors on the target power supply area can be analyzed in the time periods of supply-demand imbalance.

[0039] Preferably, in an embodiment of the present invention, the method for obtaining the power supply-demand balance degree of the target power supply area in each historical period specifically includes: Perform negative-correlation normalization processing on the absolute value of the difference between the power generation and power consumption of the target power supply area in each historical period, and limit the calculation result within the range to obtain the power supply-demand balance degree of the target power supply area in each historical period.

[0040] In the embodiments of the present invention, a negative-exponential function with the natural constant e as the base or a function form of can be used to implement the negative-correlation normalization processing, which is not limited here. Among them,

[0041] As an example, in an embodiment of the present invention, the expression of the power supply-demand balance degree of the target power supply area in each historical period can be specifically, for example: Among them, represents the target power supply area at the The power supply - demand balance degree of a historical period; Indicates the power generation amount of the target power supply area in the th historical period; Indicates the power consumption amount of the target power supply area in the th historical period; Indicates the negative - exponential function with the natural constant as the base, which is used for the normalization process of negative correlation.

[0042] The smaller the power supply - demand balance degree of a certain historical period is, it indicates that the target power supply area is more significantly affected by environmental factors during this historical period, resulting in the imbalance of power supply and demand in the target power supply area during this historical period. Therefore, based on the power supply - demand balance degrees of the target power supply area in each historical period, multiple power supply - demand imbalance time periods of the target power supply area can be obtained.

[0043] Preferably, in an embodiment of the present invention, the method for obtaining multiple power supply - demand imbalance time periods of the target power supply area specifically includes: For the target power supply area, the historical periods with the power supply - demand balance degree less than the preset balance degree threshold are used as the candidate historical periods of the target power supply area. Then, the adjacent and consecutive candidate historical periods are used as the power supply - demand imbalance time periods of the target power supply area. That is to say, multiple adjacent and consecutive candidate historical periods form a relatively long power supply - demand imbalance time period. Among them, the value range of the preset balance degree threshold is , in an embodiment of the present invention, the preset balance degree threshold is set to 0.5. The specific value of the preset balance degree threshold can also be set by the implementer according to the specific implementation scenario, and is not limited herein.

[0044] The time period of supply-demand imbalance in the target power supply area is severely affected by environmental factors. The stronger the correlation between the power generation and the environmental data of environmental indicators in each historical period within a certain supply-demand imbalance time period in the target power supply area, and the more the distribution of the power supply-demand balance degree in each historical period of this supply-demand imbalance time period deviates from the overall level of the power supply-demand balance degree of all historical periods in the target power supply area, it indicates that the power generation situation in the target power supply area during this supply-demand imbalance time period is more easily affected by environmental factors. Therefore, based on the correlation between the power generation and the environmental data of environmental indicators in each historical period within each supply-demand imbalance time period in the target power supply area, and the distribution of the power supply-demand balance degree in each historical period, the environmental impact sensitivity of each supply-demand imbalance time period in the target power supply area can be obtained. The environmental impact sensitivity reflects the sensitivity of each supply-demand imbalance time period in the target power supply area to environmental factors. The greater the environmental impact sensitivity of a certain supply-demand imbalance time period in the target power supply area, the more easily the power generation level in the target power supply area during this supply-demand imbalance time period is affected by environmental factors. Subsequently, based on the environmental impact sensitivity of each supply-demand imbalance time period in the target power supply area, the dispatchable potential value of the target power supply area can be accurately calculated and analyzed, thereby realizing the effective dispatch of each power supply area and improving the effect of the virtual power plant on optimizing the control of power supply, and avoiding power supply-demand imbalance.

[0045] Preferably, in an embodiment of the present invention, the method for obtaining the environmental impact sensitivity of each supply-demand imbalance time period in the target power supply area specifically includes: First, take any supply-demand imbalance time period in the target power supply area as the target supply-demand imbalance time period, take the sequence composed of the power generation of all historical periods in the target supply-demand imbalance time period as the power generation time series of the target supply-demand imbalance time period, and then take the sequence composed of the environmental data of the same environmental indicator in all historical periods in the target supply-demand imbalance time period as the environmental data time series of the target supply-demand imbalance time period for each environmental indicator.

[0046] Then, analyze the correlation between the power generation time series of the target supply-demand imbalance time period and the environmental data time series for each environmental indicator to obtain the environmental correlation degree of the target supply-demand imbalance time period. The greater the environmental correlation degree, the stronger the correlation between the power generation and each environmental indicator in the target supply-demand imbalance time period, and further indicates that the target supply-demand imbalance time period is more easily affected by environmental factors.

[0047] Preferably, in an embodiment of the present invention, the method for obtaining the environmental correlation degree of the target supply-demand imbalance time period specifically includes: The Pearson correlation coefficient between the power generation time series in the target power supply and demand imbalance time period and the environmental data time series for each environmental indicator is used as the correlation parameter for each environmental indicator in the target power supply and demand imbalance time period. The larger the correlation parameter for a certain environmental indicator in the target power supply and demand imbalance time period, the stronger the correlation between the power generation in the target power supply and demand imbalance time period and this environmental indicator. Furthermore, the average value of the correlation parameters for all environmental indicators in the target power supply and demand imbalance time period can be used as the environmental correlation degree of the target power supply and demand imbalance time period.

[0048] Next, analyze the overall level of the power supply and demand balance degree for all historical time periods in the target power supply area to obtain the first overall power supply and demand balance degree of the target power supply area. Analyze the overall level of the power supply and demand balance degree for all historical time periods in the target power supply and demand imbalance time period to obtain the second overall power supply and demand balance degree of the target power supply and demand imbalance time period. The greater the difference between the second overall power supply and demand balance degree and the first overall power supply and demand balance degree, the more the overall distribution level of the power supply and demand balance degree for each historical time period in the target power supply and demand imbalance time period deviates from the overall distribution level of the power supply and demand balance degree for each historical time period in the target power supply area. Furthermore, the difference between the second overall power supply and demand balance degree and the first overall power supply and demand balance degree is used as the degree of power supply and demand imbalance in the target power supply and demand imbalance time period.

[0049] In an embodiment of the present invention, statistical quantities such as the average value, mode, or median of the power supply and demand balance degrees for all historical time periods in the target power supply area can be used as the first overall power supply and demand balance degree of the target power supply area to realize the analysis of the overall level of the power supply and demand balance degrees for all historical time periods in the target power supply area. Similarly, statistical quantities such as the average value, mode, or median of the power supply and demand balance degrees for all historical time periods in the target power supply and demand imbalance time period can be used as the second overall power supply and demand balance degree of the target power supply and demand imbalance time period to realize the analysis of the overall level of the power supply and demand balance degrees for all historical time periods in the target power supply and demand imbalance time period, which is not limited here.

[0050] In an embodiment of the present invention, the absolute value of the difference between the second overall power supply and demand balance degree and the first overall power supply and demand balance degree can be used as the degree of power supply and demand imbalance in the target power supply and demand imbalance time period to realize the analysis of the difference between the two.

[0051] Furthermore, comprehensively combine the environmental correlation degree and the degree of power supply and demand imbalance in the target power supply and demand imbalance time period to obtain the environmental impact sensitivity of the target power supply and demand imbalance time period.

[0052] In an embodiment of the present invention, the sum value or product value of the environmental correlation degree and the degree of power supply and demand imbalance in the target power supply and demand imbalance time period can be used as the environmental impact sensitivity of the target power supply and demand imbalance time period to realize the combination of the two, which is not limited here.

[0053] As an example, in an embodiment of the present invention, the expression of the environmental impact sensitivity of the target supply-demand imbalance time period can be specifically, for example: Wherein, represents the environmental impact sensitivity of the target supply-demand imbalance time period; represents the Pearson correlation coefficient between the power generation time series of the target supply-demand imbalance time period and the environmental data time series regarding the th environmental indicator; represents the correlation parameter regarding the th environmental indicator in the target supply-demand imbalance time period; represents the environmental correlation degree of the target supply-demand imbalance time period; represents the number of environmental indicators; represents the first overall supply-demand balance degree of the target power supply area; represents the second overall supply-demand balance degree of the target supply-demand imbalance time period; represents the degree of power supply-demand imbalance in the target supply-demand imbalance time period.

[0054] Through the above same method, the environmental impact sensitivity of each supply-demand imbalance time period of the target power supply area can be obtained. The smaller the environmental impact sensitivity of each supply-demand imbalance time period of the target power supply area, the less likely the power generation situation of the target power supply area is affected by environmental factors. At the same time, the shorter the length of each supply-demand imbalance time period of the target power supply area, the shorter the duration of each power supply-demand imbalance in the target power supply area, and the stronger its recovery ability. Furthermore, it indicates that the power supply of the target power supply area is more stable. Therefore, based on the environmental impact sensitivity and length of each supply-demand imbalance time period of the target power supply area, as well as the power supply priority of the target power supply area, the dispatchable potential value of the target power supply area can be obtained. Subsequently, based on the dispatchable potential value and combined with an optimization algorithm, the power supply of each power supply area integrated by the virtual power plant can be optimized and controlled to avoid power supply-demand imbalance.

[0055] Preferably, in an embodiment of the present invention, the method for obtaining the dispatchable potential value of the target power supply area specifically includes: First, according to the environmental impact sensitivity and length of all supply-demand imbalance time periods of the target power supply area, the power supply stability of the target power supply area is obtained.

[0056] Preferably, in an embodiment of the present invention, the method for obtaining the power supply stability of the target power supply area specifically includes: After comprehensively considering the environmental impact sensitivity and duration of each supply-demand imbalance period in the target power supply area and performing a negative correlation mapping, the supply-demand imbalance recovery coefficient for each supply-demand imbalance period in the target power supply area is obtained. The larger the supply-demand imbalance recovery coefficient for a certain supply-demand imbalance period, the stronger the recovery ability of the target power supply area during that supply-demand imbalance period, indicating more stable power supply. Furthermore, the average value of the supply-demand imbalance recovery coefficients for all supply-demand imbalance periods in the target power supply area can be used as the power supply stability of the target power supply area.

[0057] In an embodiment of the present invention, the comprehensive consideration of the two can be achieved by calculating the sum or product value of the environmental impact sensitivity and duration of each supply-demand imbalance period in the target power supply area, and no limitation is made here.

[0058] As an example, in an embodiment of the present invention, the expression for the power supply stability of the target power supply area can be specifically, for example: Wherein, represents the power supply stability of the target power supply area; represents the environmental impact sensitivity of the th supply-demand imbalance period in the target power supply area; represents the duration of the th supply-demand imbalance period in the target power supply area; represents the supply-demand imbalance recovery coefficient for each supply-demand imbalance period in the target power supply area; represents the number of supply-demand imbalance periods in the target power supply area.

[0059] The more stable the power supply in the target power supply area and the stronger the power supply capacity in the short term in the future, the greater the dispatchable potential of the target power supply area. Therefore, the power supply stability and power supply priority of the target power supply area can be comprehensively considered and normalized, and the calculation result is limited within to obtain the dispatchable potential value of the target power supply area.

[0060] In an embodiment of the present invention, the comprehensive consideration of the two can be achieved by calculating the sum or product value of the power supply stability and power supply priority of the target power supply area, and no limitation is made here.

[0061] As an example, in an embodiment of the present invention, the expression for the dispatchable potential value of the target power supply area can be specifically, for example: Wherein, represents the dispatchable potential value of the target power supply area; represents the power supply stability of the target power supply area; Indicates the power supply priority of the target power supply area; Indicates a normalization function for normalization processing.

[0062] By the same method as above, the dispatchable potential values of each power supply area can be obtained.

[0063] Step S4: Based on the dispatchable potential values of each power supply area, optimize and control the power supply of each power supply area.

[0064] The larger the dispatchable potential value of a certain power supply area, the more it needs to be preferentially dispatched in power dispatch. Therefore, based on the dispatchable potential values of each power supply area, the power supply of each power supply area can be optimized and controlled to improve the effect of the virtual power plant on optimizing and controlling the power supply and avoid the imbalance between power supply and demand.

[0065] Preferably, in an embodiment of the present invention, the method for optimizing and controlling the power supply of each power supply area specifically includes: Taking the dispatchable potential values of each power supply area as the added items of the objective function used in the dynamic particle swarm optimization algorithm, and inputting the power generation and consumption of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period into the dynamic particle swarm optimization algorithm. The dynamic particle swarm optimization algorithm outputs the preferred sequence of power supply areas, and then based on the preferred sequence of power supply areas, the power supply of each power supply area is optimized and dispatched. Among them, the dynamic particle swarm optimization algorithm is a well-known technical means in the art and will not be elaborated here.

[0066] Specifically, the virtual power plant first receives the preferred sequence of power supply areas output by the dynamic particle swarm optimization algorithm. At the same time, the virtual power plant platform continuously collects and monitors the real-time power operation data of each energy node, including key indicators such as power generation power, active / reactive power, energy storage status, voltage frequency, etc., to provide basic data support for subsequent control and correction.

[0067] In the control module, the virtual power plant converts the optimal power supply plan into set values that can be executed by each energy unit according to the optimized dispatching results of the distributed power supply area, such as the charge and discharge rate of the energy storage system, the start-stop timing of the adjustable load, the output limit of wind power / solar power, etc. The system generates an accurate control instruction sequence and synchronizes and confirms it through a communication mechanism with time stamps to ensure that all instructions can be accurately issued to the corresponding distributed energy terminal devices according to the plan, so as to realize the distributed energy providing power output according to the optimized path and stably support the load change of the power grid.

[0068] The virtual power plant management system continuously performs multi-source fusion and real-time monitoring on the operation data of the distributed power supply area, and executes rapid short-term re-optimization in each control cycle to cope with the prediction errors caused by emergencies such as sudden weather changes. When the actual deviation of the power supply-demand balance exceeds the set threshold, the system will automatically trigger the fast restart dynamic particle swarm optimization algorithm to recalculate and deploy a new optimal scheduling plan, ensuring that the virtual power plant can quickly adapt to changes and restore the power supply-demand balance state, thereby significantly improving the flexibility, robustness of the system and the stability of power supply.

[0069] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0070] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for optimizing the power supply control of a virtual power plant based on supply-demand balance, characterized in that, The method includes: Obtaining the power generation and power consumption of different power supply areas in each historical period, and at the same time obtaining the environmental data of different environmental indicators in each historical period; Taking any one power supply area as the target power supply area, predicting the predicted power generation and predicted power consumption of the target power supply area in the future period according to the power generation and power consumption of the target power supply area in each historical period; obtaining the power supply priority of the target power supply area according to the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period; Obtaining the power supply and demand balance degree of the target power supply area in each historical period according to the difference between the power generation and power consumption of the target power supply area in each historical period; obtaining multiple power supply and demand imbalance time periods of the target power supply area based on the power supply and demand balance degrees of the target power supply area in each historical period; obtaining the environmental impact sensitivity of each power supply and demand imbalance time period of the target power supply area according to the correlation between the power generation and the environmental data of environmental indicators in each historical period within each power supply and demand imbalance time period of the target power supply area, and the distribution of the power supply and demand balance degrees in each historical period; obtaining the dispatchable potential value of the target power supply area according to the environmental impact sensitivity and length of each power supply and demand imbalance time period of the target power supply area, and the power supply priority of the target power supply area; Based on the dispatchable potential values of each power supply area, optimizing and controlling the power supply of each power supply area.

2. The optimal control method for power supply of a virtual power plant based on supply-demand balance according to claim 1, wherein The predicting the predicted power generation and predicted power consumption of the target power supply area in the future period includes: Inputting the power generation of the target power supply area in each historical period into a time series prediction algorithm, and outputting the predicted power generation of the target power supply area in the future period by the time series prediction algorithm; Inputting the power consumption of the target power supply area in each historical period into a time series prediction algorithm, and outputting the predicted power consumption of the target power supply area in the future period by the time series prediction algorithm, where the length of the future period is the same as the length of a single historical period.

3. A method for optimizing the power supply control of a virtual power plant based on supply-demand balance according to claim 1, characterized in that, The obtaining the power supply priority of the target power supply area includes: Taking the sum value of the predicted power generation of the target power supply area in the future period and the current stored power as the total available power of the target power supply area in the future period; Normalizing the difference between the total available power of the target power supply area in the future period and the predicted power consumption to obtain the power supply priority of the target power supply area.

4. A method for optimizing the power supply control of a virtual power plant based on supply-demand balance according to claim 1, characterized in that, The obtaining the power supply and demand balance degree of the target power supply area in each historical period includes: Performing negative correlation normalization on the absolute value of the difference between the power generation and power consumption of the target power supply area in each historical period to obtain the power supply and demand balance degree of the target power supply area in each historical period.

5. The optimal control method for power supply of a virtual power plant based on supply-demand balance according to claim 1, wherein The obtaining multiple power supply and demand imbalance time periods of the target power supply area includes: For the target power supply area, taking the historical periods in which the power supply and demand balance degree is less than a preset balance degree threshold as the candidate historical periods of the target power supply area; Taking adjacent and consecutive candidate historical periods as the power supply and demand imbalance time periods of the target power supply area.

6. The optimized control method for power supply of a virtual power plant based on supply-demand balance according to claim 1, characterized in that, The obtaining the environmental impact sensitivity of each power supply and demand imbalance time period of the target power supply area includes: Take any power supply and demand imbalance time period in the target power supply area as the target power supply and demand imbalance time period, and take the sequence composed of the power generation amounts of all historical periods in the target power supply and demand imbalance time period as the power generation time series sequence of the target power supply and demand imbalance time period; Take the sequence composed of the environmental data of the same environmental indicator in all historical periods in the target power supply and demand imbalance time period as the environmental data time series sequence of the target power supply and demand imbalance time period for each environmental indicator; Analyze the correlation between the power generation time series sequence of the target power supply and demand imbalance time period and the environmental data time series sequence for each environmental indicator, and obtain the environmental correlation degree of the target power supply and demand imbalance time period; Analyze the overall level of the power supply and demand balance degree of all historical periods in the target power supply area to obtain the first overall power supply and demand balance degree of the target power supply area, and analyze the overall level of the power supply and demand balance degree of all historical periods in the target power supply and demand imbalance time period to obtain the second overall power supply and demand balance degree of the target power supply and demand imbalance time period; Take the difference between the second overall power supply and demand balance degree and the first overall power supply and demand balance degree as the degree of power supply and demand imbalance of the target power supply and demand imbalance time period; Integrate the environmental correlation degree and the degree of power supply and demand imbalance of the target power supply and demand imbalance time period to obtain the environmental impact sensitivity of the target power supply and demand imbalance time period.

7. The optimized control method for power supply of a virtual power plant based on supply-demand balance according to claim 6, characterized in that The obtaining of the environmental correlation degree of the target power supply and demand imbalance time period includes: Take the absolute value of the Pearson correlation coefficient between the power generation time series sequence of the target power supply and demand imbalance time period and the environmental data time series sequence for each environmental indicator as the correlation parameter of the target power supply and demand imbalance time period for each environmental indicator; Take the average value of the correlation parameters of the target power supply and demand imbalance time period for all environmental indicators as the environmental correlation degree of the target power supply and demand imbalance time period.

8. A method for optimizing the power supply control of a virtual power plant based on supply-demand balance according to claim 1, characterized in that, The obtaining of the dispatchable potential value of the target power supply area includes: Obtain the power supply stability of the target power supply area according to the environmental impact sensitivity and length of all power supply and demand imbalance time periods of the target power supply area; Integrate and normalize the power supply stability and the power supply priority of the target power supply area to obtain the dispatchable potential value of the target power supply area.

9. The optimized control method for power supply of a virtual power plant based on supply-demand balance according to claim 8, characterized in that The obtaining of the power supply stability of the target power supply area includes: Integrate and perform negative correlation mapping on the environmental impact sensitivity and length of each power supply and demand imbalance time period of the target power supply area to obtain the supply and demand imbalance recovery coefficient of each power supply and demand imbalance time period of the target power supply area; Take the average value of the supply and demand imbalance recovery coefficients of all power supply and demand imbalance time periods of the target power supply area as the power supply stability of the target power supply area.

10. The optimal control method for power supply of a virtual power plant based on supply-demand balance according to claim 1, wherein, The optimizing control of the power supply of each power supply area based on the dispatchable potential values of each power supply area includes: Take the dispatchable potential values of each power supply area as the added items of the objective function used in the dynamic particle swarm optimization algorithm, and input the power generation amount, power consumption amount of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period into the dynamic particle swarm optimization algorithm, and the dynamic particle swarm optimization algorithm outputs the preferred sequence of power supply areas; Based on the above-mentioned preferred sequence of power supply areas, optimize the dispatching of power supply for each power supply area.

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