Optimal control method of power supply in virtual power plant based on supply and demand balance

Abstract

The present invention relates to the field of power dispatching and control, and in particular to a method for optimizing power supply control of a virtual power plant based on supply and demand balance. The method first obtains the power generation and power consumption of different power supply areas in each historical period, and obtains environmental data of different environmental indicators in each historical period. According to the difference between the predicted power generation and predicted power consumption of the target power supply area, the power supply priority of the power supply area is obtained, the supply and demand imbalance time period of the power supply area is selected, the correlation between the power generation and environmental data of the power supply area in the supply and demand imbalance time period is analyzed, the environmental impact sensitivity of the supply and demand imbalance time period is obtained, and the environmental impact sensitivity and length of each supply and demand imbalance time period of the power supply area and the power supply priority are combined to obtain the dispatchable potential value of the power supply area, and optimize the power supply of each power supply area. The present invention can improve the effect of optimizing power supply control of the virtual power plant and avoid power supply and demand imbalance.

Description

Technical Field

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

[0002] As an emerging distributed energy aggregation and coordinated scheduling mechanism, virtual power plants can unify the management of numerous distributed energy sources by integrating distributed power sources, energy storage systems and adjustable loads, so as to achieve a balance between power supply and demand in the power system and ensure the stability of grid frequency, voltage and operational reliability. To achieve the supply and demand balance of virtual power plants, power supply is usually based on load forecasting and real-time power resource monitoring, and adopts optimized control algorithms to dynamically schedule various resources in virtual power plants to achieve the optimal control strategy that meets the supply and demand balance of the grid.

[0003] In related technologies, virtual power plants monitor the changes in power loads such as power generation and user-side power consumption in distributed power supply areas in real time, and dynamically dispatch distributed power supply energy and resources based on the prediction of power supply and demand levels to meet the supply and demand balance of power supply. However, many power supply areas rely on renewable energy such as wind and solar energy for power supply. These power supply methods are easily affected by environmental factors, resulting in large errors in the prediction of power loads, which in turn leads to poor optimization and control of power supply by virtual power plants, resulting in an imbalance in power supply and demand. Summary of the Invention

[0004] In order to solve the technical problem that power supply areas relying on renewable energy are easily affected by environmental factors, resulting in large errors in power load prediction, which in turn leads to poor optimization and control of power supply by virtual power plants, resulting in an imbalance between power supply and demand, the present invention aims to provide a method for optimizing and controlling power supply of virtual power plants based on supply and demand balance. The technical solutions adopted are as follows:

[0005] The present invention proposes a virtual power plant power supply optimization control method based on supply and demand balance, the method comprising:

[0006] Obtain the power generation and power consumption of different power supply areas in each historical period, and obtain environmental data of different environmental indicators in each historical period;

[0007] Taking any power supply area as the target power supply area, based on the power generation and power consumption of the target power supply area in each historical period, the predicted power generation and predicted power consumption of the target power supply area in the future period are predicted; based on the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period, the power supply priority of the target power supply area is obtained;

[0008] According to the difference between the power generation and power consumption of the target power supply area in each historical period, the power supply and demand balance degree of the target power supply area in each historical period is obtained; based on the power supply and demand balance degree of the target power supply area in each historical period, multiple supply and demand imbalance time periods of the target power supply area are obtained; according to the correlation between the power generation and 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 degree in each historical period, the environmental impact sensitivity of each supply and demand imbalance time period of the target power supply area is obtained; 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, the dispatchable potential value of the target power supply area is obtained;

[0009] Based on the dispatchable potential value of each power supply area, the power supply of each power supply area is optimized and controlled.

[0010] Furthermore, the predicted power generation and power consumption of the target power supply area in the future period includes:

[0011] The power generation of the target power supply area in each historical period is input 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;

[0012] The electricity consumption of the target power supply area in each historical period is input into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted electricity 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.

[0013] Furthermore, obtaining the power supply priority of the target power supply area includes:

[0014] The sum of the predicted power generation and the current power storage capacity of the target power supply area in the future period is used as the total power supply available for the target power supply area in the future period;

[0015] Normalizing the difference between the total power supply available for 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.

[0016] Furthermore, obtaining the power supply and demand balance degree of the target power supply area in each historical period includes:

[0017] The absolute value of the difference between the power generation and power consumption of the target power supply area in each historical period is normalized to obtain the power supply and demand balance of the target power supply area in each historical period.

[0018] Furthermore, obtaining multiple supply-demand imbalance time periods in the target power supply area includes:

[0019] For the target power supply area, the historical period in which the power supply and demand balance is less than the preset balance threshold is used as a candidate historical period for the target power supply area;

[0020] Adjacent and continuous historical time periods to be selected are used as supply and demand imbalance time periods in the target power supply area.

[0021] Furthermore, obtaining the environmental impact sensitivity of each supply-demand imbalance time period in the target power supply area includes:

[0022] Any supply and demand imbalance period in the target power supply area is used as the target supply and demand imbalance period, and the sequence composed of the power generation of all historical periods in the target supply and demand imbalance period is used as the power generation time series sequence of the target supply and demand imbalance period;

[0023] The sequence of environmental data of the same environmental indicator in all historical periods during the target supply-demand imbalance period is used as the time series sequence of environmental data for each environmental indicator during the target supply-demand imbalance period;

[0024] Analyzing the correlation between the power generation time series during the target supply-demand imbalance time period and the environmental data time series for each environmental indicator to obtain an environmental correlation degree during the target supply-demand imbalance time period;

[0025] Analyzing the overall level of the power supply and demand balance in all historical periods of the target power supply area to obtain a first overall supply and demand balance in the target power supply area, and analyzing the overall level of the power supply and demand balance in all historical periods of the target supply and demand imbalance time period to obtain a second overall supply and demand balance in the target supply and demand imbalance time period;

[0026] using the difference between the second overall supply and demand balance degree and the first overall supply and demand balance degree as the power supply and demand imbalance degree in the target supply and demand imbalance time period;

[0027] The environmental relevance and the degree of power supply and demand imbalance during the target supply and demand imbalance period are integrated to obtain the environmental impact sensitivity during the target supply and demand imbalance period.

[0028] Furthermore, obtaining the environmental relevance of the target supply-demand imbalance time period includes:

[0029] The absolute value of the Pearson correlation coefficient between the power generation time series during the target supply-demand imbalance period and the environmental data time series for each environmental indicator is used as a correlation parameter for each environmental indicator during the target supply-demand imbalance period;

[0030] The average value of the correlation parameters of the target supply-demand imbalance time period with respect to all environmental indicators is used as the environmental relevance of the target supply-demand imbalance time period.

[0031] Furthermore, obtaining the dispatchable potential value of the target power supply area includes:

[0032] Obtaining power supply stability of the target power supply area based on the environmental impact sensitivity and length of all supply-demand imbalance time periods in the target power supply area;

[0033] The power supply stability and the power supply priority of the target power supply area are integrated and normalized to obtain a dispatchable potential value of the target power supply area.

[0034] Furthermore, obtaining the power supply stability of the target power supply area includes:

[0035] The environmental impact sensitivity and length of each supply and demand imbalance time period in the target power supply area are integrated and negatively correlated to obtain a supply and demand imbalance recovery coefficient for each supply and demand imbalance time period in the target power supply area;

[0036] An average value of the supply-demand imbalance recovery coefficients in all supply-demand imbalance time periods in the target power supply area is used as the power supply stability of the target power supply area.

[0037] Furthermore, the optimizing control of the power supply of each power supply area based on the dispatchable potential value of each power supply area includes:

[0038] The dispatchable potential value of each power supply area is used as an additional term of the objective function used by the dynamic particle swarm optimization algorithm, and the power generation and power consumption of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period are input into the dynamic particle swarm optimization algorithm, and the dynamic particle swarm optimization algorithm outputs the optimal sequence of power supply areas;

[0039] Based on the preferred sequence of power supply areas, the power supply of each power supply area is optimized and scheduled.

[0040] The present invention has the following beneficial effects:

[0041] The present invention takes into account that power supply areas relying on renewable energy are susceptible to environmental factors, resulting in large prediction errors for power loads, which in turn leads to poor optimization and control of power supply by virtual power plants, resulting in an imbalance in power supply and demand. Therefore, the present invention first obtains the power generation and power consumption of different power supply areas in each historical period, and at the same time obtains environmental data of different environmental indicators in each historical period, and preliminarily predicts the power generation and power consumption of the target power supply area in the future period. The obtained power supply priority reflects the power resource supply capacity of the target power supply area in the future period, so that resources with sufficient electric energy are given priority when supplying power, thereby reducing the risk of supply and demand mismatch. In view of the prediction error and power supply and demand imbalance caused by environmental factors, the degree of impact of environmental factors on the power supply area is analyzed in different supply and demand imbalance time periods, which helps to quantify the impact of environmental factors on the power supply of the power supply area, thereby formulating targeted compensation or backup strategies, and improving the fault tolerance capacity of the power system. Then, based on the dispatchable potential value of each power supply area and combined with the optimization algorithm, the power supply of each power supply area is optimized and controlled, thereby improving the effect of virtual power plant on power supply optimization and control, avoiding power supply and demand imbalance, and improving the stability and flexibility of the power supply of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 A flow chart of a method for optimizing power supply control of a virtual power plant based on supply and demand balance provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] To further illustrate the technical means and effects employed by the present invention to achieve the intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effects of a virtual power plant power supply optimization control method based on supply and demand balance proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0045] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0046] The following describes in detail a specific scheme of a virtual power plant power supply optimization control method based on supply and demand balance provided by the present invention with reference to the accompanying drawings.

[0047] See also Figure 1 , which shows a flow chart of a virtual power plant power supply optimization control method based on supply and demand balance provided by one embodiment of the present invention, the method comprising:

[0048] Step S1: Obtain the power generation and power consumption of different power supply areas in each historical period, and simultaneously obtain environmental data of different environmental indicators in each historical period.

[0049] Virtual power plants can usually 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 own power generation in different time periods and the power consumption of the user side it serves. Therefore, the embodiment of the present invention first collects the power generation and power consumption of each power supply area in each historical time period from the power system of each power supply area, where the unit of power generation and power consumption is usually kilowatt-hour, and the length of each time period is usually 10 to 30 minutes. In one embodiment of the present invention, the length of the historical time period is set to 15 minutes. The specific length of the historical time period can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0050] Since there are many power supply areas integrated by virtual power plants that rely on renewable energy sources such as wind and solar energy, and these power supply areas are easily affected by environmental and weather factors, in order to analyze the extent to which the power supply areas are affected by environmental factors, it is also necessary to obtain environmental data of different environmental indicators in each historical period through meteorological stations or third-party APIs. Among them, environmental indicators include wind speed, light intensity, temperature and humidity, etc. The type of environmental indicators can be set by the implementer according to the specific implementation scenario and is not limited here.

[0051] It should be noted that, for the convenience of subsequent calculations, the embodiments of the present invention also require preprocessing of the various collected data, including data cleaning, outlier removal, missing value filling and standardization operations. Among them, data preprocessing is a technical means well known to those skilled in the art and will not be elaborated here.

[0052] 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 time period based on the power generation and power consumption of the target power supply area in each historical time period; obtain the power supply priority of the target power supply area based on the difference between the predicted power generation and predicted power consumption of the target power supply area in the future time period.

[0053] When a virtual power plant manages distributed power supply areas, in order to achieve a dynamic balance between power supply and demand, it is necessary to orderly dispatch various 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, any power supply area is first analyzed and any power supply area is taken as the target power supply area. Based on the power generation and power consumption of the target power supply area in each historical period, the predicted power generation and predicted power consumption of the target power supply area in the future period are predicted.

[0054] Preferably, in one 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:

[0055] The power generation of the target power supply area in each historical period is input 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.

[0056] Similarly, the power consumption of the target power supply area in each historical period is input 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.

[0057] The time series prediction algorithm may be an existing autoregressive integrated moving average algorithm or an exponential smoothing algorithm, etc., which is not limited here.

[0058] 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 can evaluate 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 power storage capacity of the target power supply area is more sufficient, and it is suitable to be the power generation unit with priority as 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. The obtained power supply priority reflects the power resource supply capacity and the priority level of power supply of the target power supply area in the future period, so that resources with sufficient electricity can be used first when supplying power, thereby reducing the risk of supply and demand mismatch.

[0059] Preferably, in one 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:

[0060] The sum of the predicted power generation and current storage capacity of the target power supply area in the future period is taken as the total power supply available in the target power supply area in the future period. The larger the total power supply available, the more available power the target power supply area will have in the future period. The current storage capacity of the target power supply area can also be obtained from the corresponding power system.

[0061] Normalize the difference between the total power supply available in the target power supply area and the predicted power consumption in the future period, and limit the calculation result to range, thereby obtaining the power supply priority of the target power supply area.

[0062] In other embodiments of the present invention, the total amount of power that can be supplied to the target power supply area in the future period can be used as the numerator, the predicted power consumption of the target power supply area in the future period can be used as the denominator, and the comparison value can be normalized to obtain the power supply priority of the target power supply area.

[0063] In one embodiment of the present invention, the normalization processing can be specifically, for example, maximum and minimum value normalization processing, and the normalization in subsequent steps can all adopt maximum and minimum value normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of numerical values, which will not be repeated here.

[0064] As an example, in one embodiment of the present invention, the expression of the power supply priority of the target power supply area may be specifically, for example, as follows:

[0065]

[0066] in, Indicates the power supply priority of the target power supply area; Indicates the predicted power generation of the target power supply area in the future period; Indicates the current power storage capacity of the target power supply area; Indicates the total amount of power available in the target power supply area in the future period; Indicates the predicted power consumption of the target power supply area in the future period; Represents the normalization function, used for normalization processing.

[0067] At this point, the prediction of power generation and power consumption in the target power supply area has been completed, and the power supply priority of the target power supply area has been obtained.

[0068] Step S3: Based on the difference between the power generation and power consumption of the target power supply area in each historical period, obtain the power supply and demand balance of the target power supply area in each historical period; based on the power supply and demand balance of the target power supply area in each historical period, obtain multiple supply and demand imbalance time periods of the target power supply area; based on the correlation between the power generation and 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 power supply and demand balance in each historical period, obtain the environmental impact sensitivity of each supply and demand imbalance time period of the target power supply area; based on 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.

[0069] Virtual power plants achieve unified management of multi-source heterogeneous energy by integrating various distributed power supply areas such as photovoltaic, wind power, energy storage and adjustable loads. In order to achieve a balance between electricity supply and demand, it is necessary to rely on forecasting models to provide short-term electricity supply and demand levels. However, since power supply areas relying on renewable energy are easily affected by environmental factors, among which renewable energy represented by photovoltaic and wind power are easily affected by environmental factors such as extreme weather, short-term electricity supply is difficult to accurately predict, which can easily lead to forecast errors. Therefore, it is necessary to analyze the impact of real-time monitored environmental data changes on the balance of electricity supply and demand in 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 virtual power plants on optimizing power supply control, and avoid imbalance in electricity supply and demand.

[0070] Since environmental factors will affect the actual power generation of the target power supply area, resulting in significant fluctuations in its power generation capacity, and further leading to an imbalance in power supply and demand 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 its power supply and demand in the historical period. Therefore, the embodiment of the present invention first obtains the power supply and demand balance degree of the target power supply area in each historical period based on the difference between the power generation and power consumption of the target power supply area in each historical period, and reflects the degree of balance of power supply and demand in the target power supply area in each historical period through the power supply and demand balance degree. Subsequently, based on the power supply and demand balance degree of each historical period, the supply and demand imbalance time period of the target power supply area can be selected, and the degree of influence of environmental factors on the target power supply area in the supply and demand imbalance time period can be analyzed.

[0071] Preferably, in one embodiment of the present invention, the method for obtaining the power supply and demand balance degree of the target power supply area in each historical period specifically includes:

[0072] The absolute value of the difference between the power generation and power consumption in each historical period of the target power supply area is normalized to negative correlation, and the calculation result is limited to range, thereby obtaining the power supply and demand balance of the target power supply area in each historical period.

[0073] In the embodiment of the present invention, a negative exponential function with the natural constant e as the base or The negative correlation normalization is realized by the functional form of , which is not limited here, where Represents the normalization function.

[0074] As an example, in one embodiment of the present invention, the expression for the power supply and demand balance degree of the target power supply area in each historical period can be specifically, for example, as follows:

[0075]

[0076] in, Indicates that the target power supply area is in The balance degree of electricity supply and demand in a historical period; Indicates that the target power supply area is in Power generation in each historical period; Indicates that the target power supply area is in Electricity consumption in each historical period; Expressed as a natural constant A negative exponential function with as base is used to normalize negative correlation.

[0077] The smaller the power supply and demand balance in a certain historical period, the more significantly the target power supply area is affected by environmental factors during the historical period, resulting in an imbalance in power supply and demand in the target power supply area during the historical period. Therefore, based on the power supply and demand balance of the target power supply area in each historical period, multiple supply and demand imbalance time periods of the target power supply area can be obtained.

[0078] Preferably, in one embodiment of the present invention, the method for obtaining multiple supply-demand imbalance time periods in the target power supply area specifically includes:

[0079] For the target power supply area, the historical period in which the power supply and demand balance is less than the preset balance threshold is used as the target power supply area candidate historical period, and then the adjacent and continuous candidate historical periods are used as the supply and demand imbalance period of the target power supply area. That is to say, multiple adjacent and continuous candidate historical periods constitute a relatively long supply and demand imbalance period, where the preset balance threshold value range is In one embodiment of the present invention, the preset balance threshold is set to 0.5. The specific value of the preset balance threshold can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0080] The target power supply area is more seriously affected by environmental factors during the supply and demand imbalance period. The stronger the correlation between the power generation and environmental data of environmental indicators in each historical period of a supply and demand imbalance period in the target power supply area, and the more the distribution of power supply and demand balance in each historical period of the supply and demand imbalance period deviates from the overall level of power supply and demand balance in all historical periods of the target power supply area, the more easily the power generation in the target power supply area during the supply and demand imbalance period is affected by environmental factors. Therefore, the power generation in the target power supply area during the supply and demand imbalance period can be determined based on the correlation between the power generation and environmental data of environmental indicators in each historical period of each supply and demand imbalance period in the target power supply area, as well as the power supply and demand balance in each historical period. The distribution of the measurement is used to obtain the environmental impact sensitivity of each supply and demand imbalance time period in the target power supply area. The environmental impact sensitivity reflects the sensitivity of each supply and demand imbalance time period in the target power supply area to the influence of environmental factors. The greater the environmental impact sensitivity of a certain supply and demand imbalance time period in the target power supply area, the more susceptible the power generation level of the target power supply area in this supply and demand imbalance time period is to the influence of environmental factors. Subsequently, based on the environmental impact sensitivity of each supply and 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 effective scheduling of each power supply area, improving the effect of virtual power plant on optimizing power supply and avoiding power supply and demand imbalance.

[0081] Preferably, in one 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:

[0082] First, any supply and demand imbalance time period in the target power supply area is taken as the target supply and demand imbalance time period, and the sequence composed of the power generation in all historical time periods in the target supply and demand imbalance time period is taken as the power generation time series sequence of the target supply and demand imbalance time period. Then, the sequence composed of the environmental data of the same environmental indicator in all historical time periods in the target supply and demand imbalance time period is taken as the environmental data time series sequence of each environmental indicator in the target supply and demand imbalance time period.

[0083] Then, the correlation between the power generation time series of the target supply and demand imbalance time period and the environmental data time series of each environmental indicator is analyzed to obtain the environmental correlation of the target supply and demand imbalance time period. The greater the environmental correlation, the stronger the correlation between the power generation and the environmental indicators in the target supply and demand imbalance time period, which further indicates that the target supply and demand imbalance time period is more susceptible to the impact of environmental factors.

[0084] Preferably, in one embodiment of the present invention, the method for obtaining the environmental relevance of the target supply-demand imbalance time period specifically includes:

[0085] The Pearson correlation coefficient between the power generation time series of the target supply and demand imbalance time period and the environmental data time series of each environmental indicator is used as the correlation parameter of the target supply and demand imbalance time period with respect to each environmental indicator. The larger the correlation parameter of the target supply and demand imbalance time period with respect to a certain environmental indicator, the stronger the correlation between the power generation of the target supply and demand imbalance time period and the environmental indicator. The average value of the correlation parameters of the target supply and demand imbalance time period with respect to all environmental indicators can be used as the environmental correlation degree of the target supply and demand imbalance time period.

[0086] Next, the overall level of power supply and demand balance in all historical periods of the target power supply area is analyzed to obtain the first overall supply and demand balance in the target power supply area, and the overall level of power supply and demand balance in all historical periods of the target supply and demand imbalance time period is analyzed to obtain the second overall supply and demand balance in the target supply and demand imbalance time period. The greater the difference between the second overall supply and demand balance and the first overall supply and demand balance, the more the overall distribution level of power supply and demand balance in each historical period of the target supply and demand imbalance time period deviates from the overall distribution level of power supply and demand balance in each historical period of the target power supply area. The difference between the second overall supply and demand balance and the first overall supply and demand balance is used as the degree of power supply and demand imbalance in the target supply and demand imbalance time period.

[0087] In an embodiment of the present invention, the average value, mode, median or other statistical quantities of the power supply and demand balance of all historical time periods in the target power supply area can be used as the first overall supply and demand balance of the target power supply area, so as to realize the analysis of the overall level of the power supply and demand balance of all historical time periods in the target power supply area. Similarly, the average value, mode, median or other statistical quantities of the power supply and demand balance of all historical time periods in the target supply and demand imbalance time period can be used as the second overall supply and demand balance of the target supply and demand imbalance time period, so as to realize the analysis of the overall level of the power supply and demand balance of all historical time periods in the target supply and demand imbalance time period. This is not limited here.

[0088] In one embodiment of the present invention, the absolute value of the difference between the second overall supply and demand balance degree and the first overall supply and demand balance degree may be used as the degree of power supply and demand imbalance in the target supply and demand imbalance time period to analyze the difference between the two.

[0089] Then, the environmental relevance and the degree of power supply and demand imbalance during the target supply and demand imbalance period are integrated to obtain the environmental impact sensitivity during the target supply and demand imbalance period.

[0090] In an embodiment of the present invention, the sum or product of the environmental correlation degree and the power supply and demand imbalance degree of the target supply and demand imbalance time period can be used as the environmental impact sensitivity of the target supply and demand imbalance time period to achieve a combination of the two, which is not limited here.

[0091] As an example, in one embodiment of the present invention, the expression of the environmental impact sensitivity of the target supply-demand imbalance time period may be specifically, for example, as follows:

[0092]

[0093] in, Indicates the sensitivity of environmental impact during the target supply-demand imbalance period; The time series of power generation during the target supply-demand imbalance period and the time series of the Pearson correlation coefficient between the environmental data time series of the environmental indicators; Indicates the target supply-demand imbalance period with respect to the Correlation parameters of environmental indicators; Indicates the environmental relevance during the target supply-demand imbalance period; Indicates the number of environmental indicators; Indicates the first overall supply and demand balance degree of the target power supply area; Indicates the second overall supply and demand balance degree during the target supply and demand imbalance period; Indicates the degree of power supply and demand imbalance during the target supply and demand imbalance time period.

[0094] The same method as above can be used to obtain the environmental impact sensitivity of each supply and demand imbalance time period in the target power supply area. The smaller the environmental impact sensitivity of each supply and demand imbalance time period in the target power supply area, the less likely the power generation situation in the target power supply area is to be disturbed by environmental factors. At the same time, the shorter the length of each supply and demand imbalance time period in the target power supply area, the shorter the duration of each power supply and demand imbalance in the target power supply area, and the stronger its recovery ability, which further indicates that the power supply in the target power supply area is more stable. Therefore, the dispatchable potential value of the target power supply area can be obtained based on the environmental impact sensitivity and length of each supply and demand imbalance time period in the target power supply area, as well as the power supply priority of the target power supply area. Subsequently, based on the dispatchable potential value and combined with the 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 and demand imbalance.

[0095] Preferably, in one embodiment of the present invention, the method for obtaining the dispatchable potential value of the target power supply area specifically includes:

[0096] First, the power supply stability of the target power supply area is obtained according to the environmental impact sensitivity and length of all supply-demand imbalance time periods in the target power supply area.

[0097] Preferably, in one embodiment of the present invention, the method for acquiring the power supply stability of the target power supply area specifically includes:

[0098] After integrating the environmental impact sensitivity and length of each supply and demand imbalance time period in the target power supply area and performing negative correlation mapping, the supply and demand imbalance recovery coefficient of each supply and demand imbalance time period in the target power supply area is obtained. The larger the supply and demand imbalance recovery coefficient of a certain supply and demand imbalance time period, the stronger the recovery ability of the target power supply area in this supply and demand imbalance time period, and the more stable the power supply. The average value of the supply and demand imbalance recovery coefficients of all supply and demand imbalance time periods in the target power supply area can be used as the power supply stability of the target power supply area.

[0099] In an embodiment of the present invention, the integration of the two can be achieved by calculating the sum or product of the environmental impact sensitivity and length of each supply-demand imbalance time period in the target power supply area, which is not limited here.

[0100] As an example, in one embodiment of the present invention, the power supply stability of the target power supply area may be expressed as follows:

[0101]

[0102] in, Indicates the power supply stability of the target power supply area; Indicates the target power supply area. Sensitivity to environmental impact during a period of supply-demand imbalance; Indicates the target power supply area. The length of the period of supply-demand imbalance; The supply and demand imbalance recovery coefficient for each supply and demand imbalance period in the target power supply area; Indicates the number of time periods in which supply and demand are unbalanced in the target power supply area.

[0103] The more stable the power supply in the target power supply area is and the stronger the power supply capacity in the short term in the future is, the greater the dispatch potential of the target power supply area is. Therefore, the power supply stability and power supply priority of the target power supply area can be integrated and normalized, and the calculation results can be limited to range, thereby obtaining the dispatchable potential value of the target power supply area.

[0104] In the embodiment of the present invention, the power supply stability and the power supply priority of the target power supply area may be integrated by calculating the sum or product of the two, which is not limited here.

[0105] As an example, in one embodiment of the present invention, the expression of the dispatchable potential value of the target power supply area may be specifically, for example, as follows:

[0106]

[0107] in, Indicates the dispatchable potential value of the target power supply area; Indicates the power supply stability of the target power supply area; Indicates the power supply priority of the target power supply area; Represents the normalization function, used for normalization processing.

[0108] The dispatchable potential value of each power supply area can be obtained by the same method as above.

[0109] Step S4: Based on the dispatchable potential value of each power supply area, optimize the power supply of each power supply area.

[0110] The larger the dispatchable potential value of a power supply area, the more priority the power supply area needs in power dispatching. Therefore, based on the dispatchable potential value of each power supply area, the power supply of each power supply area can be optimized and controlled, thereby improving the effect of virtual power plants on optimizing power supply and avoiding imbalance between power supply and demand.

[0111] Preferably, in one embodiment of the present invention, the method for optimizing and controlling the power supply of each power supply area specifically includes:

[0112] The dispatchable potential value of each power supply area is used as an additional term in the objective function used by the dynamic particle swarm optimization algorithm. The power generation and power consumption of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period are input into the dynamic particle swarm optimization algorithm. The dynamic particle swarm optimization algorithm outputs the optimal sequence of power supply areas. Then, based on the optimal sequence of power supply areas, the power supply of each power supply area is optimized and scheduled. The dynamic particle swarm optimization algorithm is a technical means well known to those skilled in the art and will not be described in detail here.

[0113] Specifically, the virtual power plant first receives the optimal 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 and frequency, providing basic data support for subsequent control and correction.

[0114] In the control module, the virtual power plant converts the optimal power supply plan into executable set values ​​for each energy unit based on the optimized distributed power supply area scheduling results, such as the charging and discharging rate of the energy storage system, the start and stop timing of the adjustable load, and the wind power / photovoltaic output limit. The system generates a precise control instruction sequence and synchronizes and confirms it through a timestamp communication mechanism to ensure that all instructions can be accurately issued to the corresponding distributed energy terminal equipment as planned, so that distributed energy can provide power output according to the optimized path, thereby stably supporting the changes in grid load.

[0115] The virtual power plant management system continuously integrates multi-source data and conducts real-time monitoring of the operating data of the distributed power supply area, and performs rapid short-term re-optimization within each control cycle to cope with prediction errors caused by sudden events such as weather changes. When the actual deviation of the power supply and demand balance exceeds the set threshold, the system will automatically trigger a rapid restart of the dynamic particle swarm optimization algorithm, recalculate and deploy a new optimal scheduling plan, ensuring that the virtual power plant can quickly adapt to changes and restore the power supply and demand balance, thereby significantly improving the system's flexibility, robustness and power supply stability.

[0116] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0117] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A virtual power plant power supply optimization control method based on supply and demand balance, characterized in that: The method comprises: Obtain the power generation and power consumption of different power supply areas in each historical period, and obtain environmental data of different environmental indicators in each historical period; Taking any power supply area as the target power supply area, based on the power generation and power consumption of the target power supply area in each historical period, the predicted power generation and predicted power consumption of the target power supply area in the future period are predicted; based on the difference between the predicted power generation and predicted power consumption of the target power supply area in the future period, the power supply priority of the target power supply area is obtained; According to the difference between the power generation and power consumption of the target power supply area in each historical period, the power supply and demand balance degree of the target power supply area in each historical period is obtained; based on the power supply and demand balance degree of the target power supply area in each historical period, multiple supply and demand imbalance time periods of the target power supply area are obtained; according to the correlation between the power generation and 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 degree in each historical period, the environmental impact sensitivity of each supply and demand imbalance time period of the target power supply area is obtained; 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, the dispatchable potential value of the target power supply area is obtained; Based on the dispatchable potential value of each power supply area, optimizing and controlling the power supply of each power supply area; Obtaining the environmental impact sensitivity of each supply-demand imbalance time period in the target power supply area includes: Any supply and demand imbalance period in the target power supply area is used as the target supply and demand imbalance period, and the sequence composed of the power generation of all historical periods in the target supply and demand imbalance period is used as the power generation time series sequence of the target supply and demand imbalance period; The sequence of environmental data of the same environmental indicator in all historical periods during the target supply-demand imbalance period is used as the time series sequence of environmental data for each environmental indicator during the target supply-demand imbalance period; Analyzing the correlation between the power generation time series during the target supply-demand imbalance time period and the environmental data time series for each environmental indicator to obtain an environmental correlation degree during the target supply-demand imbalance time period; Analyzing the overall level of the power supply and demand balance in all historical periods of the target power supply area to obtain a first overall supply and demand balance in the target power supply area, and analyzing the overall level of the power supply and demand balance in all historical periods of the target supply and demand imbalance time period to obtain a second overall supply and demand balance in the target supply and demand imbalance time period; using the difference between the second overall supply and demand balance degree and the first overall supply and demand balance degree as the power supply and demand imbalance degree in the target supply and demand imbalance time period; The environmental relevance and the degree of power supply and demand imbalance during the target supply and demand imbalance period are integrated to obtain the environmental impact sensitivity during the target supply and demand imbalance period.

2. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: The predicted power generation and power consumption of the target power supply area in the future period include: The power generation of the target power supply area in each historical period is input 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; The electricity consumption of the target power supply area in each historical period is input into the time series prediction algorithm, and the time series prediction algorithm outputs the predicted electricity 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.

3. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: Obtaining the power supply priority of the target power supply area includes: The sum of the predicted power generation and the current power storage capacity of the target power supply area in the future period is used as the total power supply available for the target power supply area in the future period; The difference between the total power supply available for the target power supply area in the future period and the predicted power consumption is normalized to obtain the power supply priority of the target power supply area.

4. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: Obtaining the power supply and demand balance degree in the target power supply area in each historical period includes: The absolute value of the difference between the power generation and power consumption of the target power supply area in each historical period is normalized to obtain the power supply and demand balance of the target power supply area in each historical period.

5. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: The obtaining of multiple supply-demand imbalance time periods in the target power supply area includes: For the target power supply area, the historical period in which the power supply and demand balance is less than the preset balance threshold is used as a candidate historical period for the target power supply area; Adjacent and continuous historical time periods to be selected are used as supply and demand imbalance time periods in the target power supply area.

6. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: Obtaining the environmental relevance of the target supply-demand imbalance time period includes: The absolute value of the Pearson correlation coefficient between the power generation time series during the target supply-demand imbalance period and the environmental data time series for each environmental indicator is used as a correlation parameter for each environmental indicator during the target supply-demand imbalance period; The average value of the correlation parameters of the target supply-demand imbalance time period with respect to all environmental indicators is used as the environmental relevance of the target supply-demand imbalance time period.

7. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: Obtaining the dispatchable potential value of the target power supply area includes: Obtaining power supply stability of the target power supply area based on the environmental impact sensitivity and length of all supply-demand imbalance time periods in the target power supply area; The power supply stability and the power supply priority of the target power supply area are integrated and normalized to obtain a dispatchable potential value of the target power supply area.

8. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 7, characterized in that: Obtaining the power supply stability of the target power supply area includes: The environmental impact sensitivity and length of each supply and demand imbalance time period in the target power supply area are integrated and negatively correlated to obtain a supply and demand imbalance recovery coefficient for each supply and demand imbalance time period in the target power supply area; An average value of the supply-demand imbalance recovery coefficients in all supply-demand imbalance time periods in the target power supply area is used as the power supply stability of the target power supply area.

9. The method for optimizing power supply of a virtual power plant based on supply and demand balance according to claim 1, characterized in that: The optimizing control of the power supply of each power supply area based on the dispatchable potential value of each power supply area includes: The dispatchable potential value of each power supply area is used as an additional term of the objective function used by the dynamic particle swarm optimization algorithm, and the power generation and power consumption of each power supply area in each historical period and the environmental data of different environmental indicators in each historical period are input into the dynamic particle swarm optimization algorithm, and the dynamic particle swarm optimization algorithm outputs the optimal 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 scheduled.

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