Virtual power plant regulation capability test and evaluation method and device, medium and equipment

Abstract

The invention discloses a virtual power plant regulation capability test and evaluation method and device, a medium and equipment, and relates to the technical field of power systems. The method comprises the following steps: firstly, determining test indexes for evaluating the adjustment capability of the virtual power plant, wherein the types of the test indexes comprise a resource physical attribute index, a market law index, an enterprise production and operation index and a climate and weather index; then constructing a test evaluation model based on the test indexes, obtaining test data of the virtual power grid, and calculating to obtain a plurality of index test results based on the test evaluation model; and finally, performing weighted calculation on each index test result to obtain a test evaluation result of the virtual power plant regulation capability. The method is more in line with the actual operation condition of the virtual power plant, and the obtained test evaluation result of the adjustment capability of the virtual power plant is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, device, medium and equipment for testing and evaluating the regulation capability of a virtual power plant. Background Art

[0002] With the digital construction and intelligent level of power grid, virtual power plant technology is increasingly becoming a key technology for new power systems that tap into flexible resources on the load side and support high-proportion new energy access. Virtual power plants use advanced technologies such as digitalization and intelligence to aggregate, coordinate and optimize adjustable loads, distributed power sources, and energy storage resources in a certain area on the demand side, and combine them with corresponding power market mechanisms to form a system with the ability to respond to power grid operation and regulation. As a new energy management and operation model, virtual power plants play an increasingly important role in the power market, so it is necessary to test and evaluate the regulation capabilities of virtual power plants. The traditional virtual power plant regulation capability test is relatively single and one-sided, mainly focusing on the physical parameter factors of resources and market clearing constraints. It is an idealized result under specific test conditions and has poor accuracy for actual conditions. Summary of the invention

[0003] In view of this, the present application provides a virtual power plant regulation capability test and evaluation method, device, medium and equipment, the main purpose of which is to solve the technical problem of poor accuracy of traditional virtual power plant regulation capability test.

[0004] According to a first aspect of the present invention, a method for testing and evaluating the regulation capability of a virtual power plant is provided, the method comprising:

[0005] Determine test indicators for evaluating the regulation capability of virtual power plants, where the types of test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators;

[0006] Building a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model;

[0007] A weighted calculation is performed on each of the indicator test results to obtain a test evaluation result of the virtual power plant regulation capability.

[0008] According to a second aspect of the present invention, a virtual power plant regulation capability test and evaluation device is provided, the device comprising:

[0009] An indicator determination module, used to determine test indicators for evaluating the regulation capability of the virtual power plant, wherein the types of test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators;

[0010] A test evaluation module, used to construct a test evaluation model based on the test indicators, obtain test data of the virtual power grid, and calculate multiple indicator test results based on the test evaluation model;

[0011] The result calculation module is used to perform weighted calculation on each of the indicator test results to obtain a test evaluation result of the virtual power plant regulation capability.

[0012] According to a third aspect of the present invention, there is provided a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the above-mentioned virtual power plant regulation capability test and evaluation method.

[0013] According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned virtual power plant regulation capability test and evaluation method when executing the program.

[0014] The present invention provides a method, device, medium and equipment for testing and evaluating the regulation capacity of a virtual power plant. First, the test indicators for evaluating the regulation capacity of the virtual power plant are determined. The types of the test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators and climate and meteorological indicators; then, a test evaluation model is constructed based on the test indicators, the test data of the virtual power grid is obtained, and multiple indicator test results are calculated based on the test evaluation model; finally, each of the indicator test results is weighted to obtain the test evaluation results of the regulation capacity of the virtual power plant. By means of the above technical scheme, the virtual power plant is tested based on multiple dimensions of resource physical properties, market laws, production and operation, and climate and meteorology, and the regulation capacity of the virtual power plant is evaluated based on the test conditions and the test evaluation model. The determination of the test indicators comprehensively considers the joint effects of multiple factors in the actual operation of the virtual power grid. Compared with specific conditions or a single evaluation dimension, the above test evaluation method is more in line with the actual situation, and the test evaluation results of the regulation capacity of the virtual power plant obtained are also more accurate.

[0015] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 A schematic diagram of a flow chart of a method for testing and evaluating the regulation capability of a virtual power plant provided by an embodiment of the present invention is shown;

[0018] Figure 2 A schematic diagram of the structure of a virtual power plant regulation capability testing and evaluation device provided by an embodiment of the present invention is shown;

[0019] Figure 3 A schematic structural diagram of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0020] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. In each embodiment of the present application, the first, second and various digital numbers are only used to distinguish for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0021] In one embodiment, Figure 1 As shown, a virtual power plant regulation capability test and evaluation method is provided, comprising the following steps:

[0022] 101. Determine the test indicators used to evaluate the regulation capability of virtual power plants. The types of test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators.

[0023] 102. Construct a test evaluation model based on the test indicators, obtain test data of the virtual power grid, and calculate multiple indicator test results based on the test evaluation model.

[0024] 103. Perform weighted calculation on each of the indicator test results to obtain a test evaluation result of the regulation capability of the virtual power plant.

[0025] Virtual power plants are systems that use advanced technologies such as digitalization and intelligence to aggregate, coordinate, and optimize adjustable loads, distributed power sources, energy storage, and other resources in a certain area on the demand side, combined with corresponding power market mechanisms, to form systems with the ability to respond to grid operation and regulation. Each link of virtual power plant market access, operation management, and transaction settlement involves regulation performance indicators, so it is necessary and meaningful to test and evaluate the regulation capabilities of virtual power plants. At present, there is no unified and scientific verification test method in related technologies. The market access test conditions, the test logic of regulation capability indicators, and the focus of calculation algorithms are also different. The test indicators mainly focus on regulation capacity, regulation speed, and regulation accuracy, and mainly focus on the regulation characteristics of a single resource / load, and then superimpose or aggregate. This type of test method meets the requirements for resource regulation capability testing in some scenarios, and mainly focuses on the physical parameter factors of resources and market clearing constraints. It is an idealized result under specific test conditions. When virtual power plants actually participate in market-based transactions, their regulation capabilities are not just physical regulation capabilities, but more of a game and balance of multiple factors such as physical regulation capabilities, market rules, production and operation decisions, and marginal costs.

[0026] In order to ensure that the resource regulation capacity and the ability to respond to grid instructions of load-type virtual power plants after grid connection meet the requirements of the grid, while taking into account the benefits of virtual power plants responding to market-oriented transactions, this embodiment proposes a virtual power plant regulation capacity test and evaluation method. Specifically, first, based on the actual situation when the virtual power plant participates in market-oriented transactions, the test indicators used to evaluate the regulation capacity of the virtual power plant are determined, which may include resource physical property indicators, market law indicators, enterprise production indicators, and climate and meteorological indicators. Then, based on the actual situation of the operation of the virtual power plant, a test evaluation model for calculating various test indicators is constructed. And the test data of the corresponding virtual power plant is obtained, and the indicator test results corresponding to each indicator are calculated by the test evaluation model. Then the indicator test results are weighted to obtain the final test evaluation results of the regulation capacity of the virtual power plant. The above method can make up for the single-sided limitations of the traditional virtual power plant access capacity test, and improve the physical regulation capacity of the virtual power plant and the market law, enterprise production and operation costs, marginal costs, future income and other adaptation capabilities, tracking capabilities and balancing capabilities.

[0027] The virtual power plant regulation capacity test and evaluation method provided in this embodiment first determines the test indicators used to evaluate the regulation capacity of the virtual power plant, and the types of the test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators; then, a test evaluation model is constructed based on the test indicators, the test data of the virtual power grid is obtained, and multiple indicator test results are calculated based on the test evaluation model; finally, each of the indicator test results is weighted to obtain the test evaluation results of the regulation capacity of the virtual power plant. By means of the above technical scheme, the virtual power plant is tested based on multiple dimensions such as resource physical properties, market laws, production and operation, and climate and meteorology, and the regulation capacity of the virtual power plant is evaluated based on the test conditions and the test evaluation model. The determination of the test indicators comprehensively considers the joint effects of multiple factors in the actual operation of the virtual power grid. Compared with specific conditions or a single evaluation dimension, the above test evaluation method is more in line with the actual situation, and the test evaluation results of the regulation capacity of the virtual power plant obtained are also more accurate.

[0028] Furthermore, in order to fully illustrate the implementation process of this embodiment, the specific implementation methods of the above embodiment are refined and expanded below. Specifically, in one embodiment, the resource physical attribute indicators include resource capacity adjustable rate, resource duration adjustment rate, plan curve tracking rate, communication qualification rate, adjustment response accuracy, adjustment response rate, renewable resource consumption rate, and adjustment execution accuracy; the market law indicators include comprehensive power market prices, agent power purchase prices, and virtual power plant adjustment response prices; the enterprise-generated operating indicators include planned outage index, unplanned outage index, and production line start-up and shutdown costs; the climate and meteorological indicators include long-term and short-term comprehensive climate indexes.

[0029] In the above embodiment, the test indicators can be classified according to different dimensions, that is, the test indicators can be divided into two levels, and each category of test indicators is used as a first-level test indicator, that is, in the above embodiment, the first-level test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators. The specific test indicators contained in each first-level test indicator are used as second-level test indicators. The virtual power plant is tested according to the second-level test indicators and the regulation capacity is evaluated.

[0030] In one embodiment, the step 102 of building a test evaluation model based on the test index, acquiring the test data of the virtual power grid, and calculating multiple index test results based on the test evaluation model can be implemented in the following ways:

[0031] The resource capacity adjustable rate is obtained according to the ratio of the adjustable power of the virtual power plant resources to the sum of the rated power of the aggregated resources of the virtual power plant. The calculation formula of the resource capacity adjustable rate includes:

[0032]

[0033]

[0034] Pam(t)=P am1 (t)+P am2 (t); (3)

[0035]

[0036] P am2 (t)=|P iact (t)-P(j,t)|; (5)

[0037]

[0038] Where Ram(t) represents the adjustable rate of resource capacity; Aam(t) represents the sum of the rated powers of the aggregated resources of the virtual power plant; Pam(t) represents the adjustable power of the virtual power plant resources; t represents the time period within the statistical period; Spc i represents the rated power of resource i aggregated by the virtual power plant; i represents the resources of the virtual power plant; n represents the number of resources in the virtual power plant; P am1 (t) represents the adjustable power of resources in the electric energy market; P am2 (t) represents the adjustable power of resources in the peak load ancillary service market; P imax (t) represents the upper limit operating power curve of virtual power plant resource i within the statistical period; P imin (t) represents the lower limit operating power curve of virtual power plant resource i within the statistical period; P iact (t) represents the actual power curve of the virtual power plant in the t period according to the two directions of peak shaving and valley filling; P(j,t) represents the baseline power value of the virtual power plant resources in the t period on the jth test day; Pr(jd,t) represents the power value in the t period on the dth reference day before the jth test day; N represents the total number of reference days; A d Represents the weight coefficient corresponding to the dth reference day.

[0039] Wherein, for formula (6), in a specific example, the total number of reference days N can be 5, and then 5 consecutive normal production days for users to implement load management measures and demand response can be selected from the jth test day as the baseline reference day. If an abnormal production day occurs, it can be recursively counted from that day until a normal production day appears as a reference day, wherein the number of days recursively counted forward does not exceed 30 days. Accordingly, the weight coefficient A corresponding to the first reference day to the fifth reference day is dThe values ​​may be 50%, 25%, 12.5%, 6.25% and 3.125% in sequence. It should be noted that the above values ​​are only used as an example to illustrate this solution, and the specific values ​​may be determined according to actual needs.

[0040] The resource duration adjustment rate is obtained according to the ratio of the actual adjustable duration of the virtual power plant to the theoretical adjustable duration. The calculation formula of the resource duration adjustment rate includes:

[0041]

[0042] Among them, T ui (t) represents the resource duration adjustment rate of the virtual power plant; T ci (t) represents the actual adjustable duration of resource i in period t; T ai (t) represents the theoretical adjustable duration of resource i in period t.

[0043] According to the proportion of the points where the actual power of the virtual power plant resources meets the planned power, the planned curve tracking rate is obtained. The calculation formula of the planned curve following the power includes:

[0044]

[0045] Among them, R N (t) represents the planning curve tracking rate of the virtual power plant resources in the period t; N p (t) represents the number of points where the actual power curve of the virtual power plant resource meets the planned power curve in the period t; N U (t) represents the total number of points of the actual power curve of the virtual power plant resources in period t.

[0046] The communication qualification rate is obtained according to the ratio of the time length during which the virtual power plant communication meets the requirements to the effective communication time length. The calculation formula of the communication qualification rate includes:

[0047]

[0048] Among them, R T (t) represents the communication qualification rate of the virtual power plant in period t; T Q (t) represents the duration of the virtual power plant's communication meeting the requirements in period t; T A (t) represents the effective duration of the virtual power plant communication in period t.

[0049] The regulation response accuracy is calculated according to the difference between the target power and the actual power of the virtual power plant. The calculation formula of the regulation response accuracy includes:

[0050]

[0051] Among them, δ1 represents the regulation response accuracy of the electric energy market; P tag (t) represents the target power curve of the electric energy market; P act (t) represents the actual power curve of the electric energy market, where the target power curve can be determined based on the result of the simulation clearing of the quantity-price curve.

[0052]

[0053] Among them, δ2 represents the regulation response accuracy of the peak load ancillary service market; P tag represents the target regulation power value of the peak load ancillary service market; P as (k) represents the actual regulated power value of the peak-shaving auxiliary service market at time k when it has the regulation capability; n1 represents the total number of recorded actual regulated power values.

[0054] The regulation response rate is obtained according to the ratio of the regulation power to the regulation time of the virtual power plant. The calculation formula of the regulation response rate includes:

[0055]

[0056] Where cos represents the regulation response rate of the virtual power plant; S ip Indicates 90% of the target power; F ip Indicates 10% of the target power; S it Indicates the time when the power of the virtual power plant reaches 90% of the target power; F it Indicates the time when the virtual power plant power reaches 10% of the target power.

[0057] Among them, during the statistical period, when the output of the virtual power plant changes to two load points with a change range of 10% and 90% of the dispatch instruction target, the absolute value of the slope of the connecting line is calculated as the regulation response rate.

[0058] The renewable energy consumption is obtained according to the ratio of the renewable energy power generation of the virtual power plant to the total power generation. The calculation formula of the renewable energy consumption includes:

[0059]

[0060] Among them, N er (t) represents the renewable energy consumption of the virtual power plant; N eg (t) represents the renewable energy power generation of the virtual power plant during the period t; W eg (t) represents the amount of renewable energy wasted; O eg (t) represents the power generation of other energy sources; V eg (t) represents the virtual power generation of adjustable load.

[0061] The regulation execution accuracy is obtained according to the ratio of the number of times the virtual power plant accurately executes instructions to the total number of instructions. The calculation formula of the regulation execution accuracy includes:

[0062]

[0063] Among them, R ti (t) represents the accuracy of virtual power plant regulation execution; N ai (t) represents the number of times resource i executes instructions accurately, P de (t) represents the total number of instructions; n represents the number of resources i.

[0064] The above method is used to calculate the index test results of the specific secondary test indicators corresponding to the resource physical attribute indicators, so as to realize the test and evaluation of the resource physical attribute dimension of the virtual power plant. Among them, the resources of the virtual power plant refer to user loads such as chemical industry, material production and manufacturing, smelting, textile, electrical machinery and equipment manufacturing.

[0065] In one embodiment, the step 102 of constructing a test evaluation model based on the test index, acquiring the test data of the virtual power grid, and calculating multiple index test results based on the test evaluation model further includes:

[0066] According to the medium- and long-term market prices and the spot time price of the electricity market, the comprehensive price of the electricity market is obtained. The calculation formula of the comprehensive price of the electricity market includes:

[0067] C tot =δ1C zcq +δ2C rq +δ3C rn +δ4C ss ; (15)

[0068] Among them, C tot represents the comprehensive price of electricity market; C zcq Indicates medium and long term market price; C rq represents the day-ahead market price; C rn Indicates intraday market price; C ss represents the real-time market price; δ1 represents the coefficient corresponding to the medium- and long-term market price, δ2 represents the coefficient corresponding to the day-ahead market price, δ3 represents the coefficient corresponding to the intraday market price, and δ4 represents the coefficient corresponding to the real-time market price.

[0069] The proxy electricity purchase price is obtained according to the electricity price, the basic electricity price and the power factor adjustment fee. The calculation formula of the proxy electricity purchase price includes:

[0070] C d(t) = C dd (t)+C jb (t)+C gltz (t); (16)

[0071] Among them, C d (t) represents the power purchase price of the agent; C dd (t) represents the electricity price (peak, flat and valley) during the statistical period; C jb (t) represents the basic electricity price (monthly capacity demand electricity price); C gltz (t) represents the power factor adjustment fee.

[0072] The virtual power plant response price is obtained according to the transaction price, and the calculation formula of the virtual power plant response price includes:

[0073] C yi (t) = C pi (t); (17)

[0074] Among them, C yi (t) represents the virtual power plant regulation response price; C pi (t) represents the transaction price published by the load management center. pi (t) represents the transaction price of the trading product pi released by the load management center in the t period. That is, the response price of the virtual power plant participating in the regulation is determined according to the trading product and transaction price released by the load management center.

[0075] In one embodiment, in step 102, the step of constructing a test evaluation model based on the test index, acquiring test data of the virtual power grid, and calculating multiple index test results based on the test evaluation model further includes:

[0076] The planned outage index is calculated according to the ratio of the planned outage duration to the effective working duration of the virtual power plant. The calculation formula of the planned outage index includes:

[0077]

[0078] Among them, P io (t) represents the planned outage index; P it (t) represents the planned downtime duration; A it (t) represents the effective working time.

[0079] According to the ratio of the unplanned outage time to the effective working time of the virtual power plant, the unplanned outage index is calculated, and the calculation formula of the unplanned outage index includes:

[0080]

[0081] Among them, Uio (t) represents the unplanned outage index; U it (t) represents the duration of unplanned downtime; A it (t) represents the effective working time.

[0082] According to the start-up and shutdown costs of each production line of the virtual power plant, the total start-up and shutdown costs of the production line are calculated. The calculation formula of the total start-up and shutdown costs of the production line includes:

[0083]

[0084] Among them, C tot (t) represents the total cost of starting and stopping the production line; C i2 (t) represents the start-up and stop costs of production line i2; n2 represents the number of production lines i2.

[0085] In one embodiment, in step 102, the step of constructing a test evaluation model based on the test index, acquiring test data of the virtual power grid, and calculating multiple index test results based on the test evaluation model further includes:

[0086] The long- and short-term comprehensive climate index is calculated based on seasonal weather factors and short-term weather factors. The calculation formula of the long- and short-term comprehensive climate index includes:

[0087] W(t)=W(αW qh ,βW tq ); (twenty one)

[0088] Where W(t) represents the long-term and short-term comprehensive climate index; W represents the weight matrix; W qh represents seasonal climate factor; W tq represents the short-term weather factor; α and β are coefficients.

[0089] Specifically, W qh and W tq They represent regional seasonal climate factors (long time scale) and regional short-term weather conditions, including temperature, radiation intensity, wind speed, weather conditions, etc. Thus, the impact of climate and weather on load and photovoltaic power generation is taken into account in the test evaluation.

[0090] In the above embodiment, in step 103, weighted calculation is performed on each of the index test results to obtain the test evaluation result of the virtual power plant regulation capability, which can be specifically achieved in the following manner:

[0091] Each of the index test results is standardized to obtain a standardized index test result. Since the statistical dimensions, calculation methods, and values ​​of the various test indicators are not in the same dimension, it is necessary to standardize the index test results. Specifically, a normalization method can be used to set the range of the index test results between [0, 1].

[0092] The standardized index test results are weighted to obtain the test evaluation results of the virtual power plant regulation capability. The calculation formula of the test evaluation results includes:

[0093]

[0094] Where, API(t) represents the test evaluation result; P u represents the weight of the u-th test indicator; X uv Indicates the standardized index test results; Q v It represents the weight of the test result of the vth indicator; u represents the category number of the test indicator; v represents the number of the indicator test result; m represents the total number of test indicators.

[0095] Specifically, the regulation capability of the virtual power plant can be quantified by testing the evaluation results API(t). The larger the API(t), the stronger the regulation capability of the virtual power plant.

[0096] The virtual power plant regulation capability test and evaluation method provided in this embodiment can, under the premise of meeting the requirements for the virtual power plant to participate in market-based transactions, enable users to meet production requirements and maximize profits, and achieve a win-win situation on both the supply and demand sides, thereby solving the problem of the shortcomings of the single concrete testing dimension of the traditional model. The setting of the test indicators is more in line with the actual operation of the virtual power plant, and the obtained test evaluation results are more accurate. Based on the virtual power plant regulation capability test and evaluation method provided in the embodiment of the present application, it is possible to achieve a market model in which the interests of various market entities are maximized and multiple parties are win-win by rationally allocating resources and linking production and operation decisions to meet the needs of the electricity market and ancillary service market in different time periods and regions.

[0097] Further, as Figure 1 As well as the specific implementation of the method shown in the above embodiment, this embodiment provides a virtual power plant regulation capability test and evaluation device, such as Figure 2 As shown, the device includes: an indicator determination module 31, a test evaluation module 32, and a result calculation module 33.

[0098] The indicator determination module 31 can be used to determine the test indicators for evaluating the regulation capability of the virtual power plant, and the types of the test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators;

[0099] A test evaluation module 32, which can be used to construct a test evaluation model based on the test indicators, obtain test data of the virtual power grid, and calculate multiple indicator test results based on the test evaluation model;

[0100] The result calculation module 33 can be used to perform weighted calculation on each of the indicator test results to obtain a test evaluation result of the virtual power plant regulation capability.

[0101] In a specific application scenario, the test indicators determined by the indicator determination module 31 specifically include: the resource physical property indicators include resource capacity adjustable rate, resource duration adjustment rate, planned curve tracking rate, communication qualification rate, adjustment response accuracy, adjustment response rate, renewable resource consumption rate, and adjustment execution accuracy; the market law indicators include comprehensive electricity market price, agent power purchase price, and virtual power plant adjustment response price; the enterprise-generated operating indicators include planned outage index, unplanned outage index, and total cost of production line start-up and shutdown; the climate and meteorological indicators include long- and short-term comprehensive climate index.

[0102] In a specific application scenario, a test evaluation model is constructed based on the test index, test data of the virtual power grid is obtained, and multiple index test results are calculated based on the test evaluation model. The test evaluation module 32 can be specifically used to obtain the resource capacity adjustable rate according to the ratio of the adjustable power of the virtual power plant resources to the sum of the rated power of the aggregated resources of the virtual power plant. The calculation formula of the resource capacity adjustable rate includes:

[0103]

[0104] Pam(t)=P am1 (t)+P am2 (t);

[0105]

[0106] P am2 (t)=|P iact (t)-P(j,t)|;

[0107]

[0108] Where Ram(t) represents the adjustable rate of resource capacity; Aam(t) represents the sum of the rated powers of the aggregated resources of the virtual power plant; Pam(t) represents the adjustable power of the virtual power plant resources; t represents the time period within the statistical period; Spc i represents the rated power of resource i aggregated by the virtual power plant; i represents the resources of the virtual power plant; n represents the number of resources in the virtual power plant; P am1 (t) represents the adjustable power of resources in the electric energy market; Pam2 (t) represents the adjustable power of resources in the peak load ancillary service market; P imax (t) represents the upper limit operating power curve of virtual power plant resource i within the statistical period; P imin (t) represents the lower limit operating power curve of virtual power plant resource i within the statistical period; P iact (t) represents the actual power curve of the virtual power plant in the t period according to the two directions of peak shaving and valley filling; P(j,t) represents the baseline power value of the virtual power plant resources in the t period on the jth test day; Pr(jd,t) represents the power value in the t period on the dth reference day before the jth test day; N represents the total number of reference days; A d represents the weight coefficient corresponding to the dth reference day;

[0109] The resource duration adjustment rate is obtained according to the ratio of the actual adjustable duration of the virtual power plant to the theoretical adjustable duration. The calculation formula of the resource duration adjustment rate includes:

[0110]

[0111] Among them, T ui (t) represents the resource duration adjustment rate of the virtual power plant; T ci (t) represents the actual adjustable duration of resource i in period t; T ai (t) represents the theoretical adjustable duration of resource i in period t;

[0112] According to the proportion of the points where the actual power of the virtual power plant resources meets the planned power, the planned curve tracking rate is obtained. The calculation formula of the planned curve following the power includes:

[0113]

[0114] Among them, R N (t) represents the planning curve tracking rate of the virtual power plant resources in the period t; N p (t) represents the number of points where the actual power curve of the virtual power plant resource meets the planned power curve in the period t; N U (t) represents the total number of points of the actual power curve of the virtual power plant resources in time period t;

[0115] The communication qualification rate is obtained according to the ratio of the time length during which the virtual power plant communication meets the requirements to the effective communication time length. The calculation formula of the communication qualification rate includes:

[0116]

[0117] Among them, R T (t) represents the communication qualification rate of the virtual power plant in period t; T Q(t) represents the duration of the virtual power plant's communication meeting the requirements in period t; T A (t) represents the effective duration of the virtual power plant communication in period t;

[0118] The regulation response accuracy is calculated according to the difference between the target power and the actual power of the virtual power plant. The calculation formula of the regulation response accuracy includes:

[0119]

[0120] Among them, δ1 represents the regulation response accuracy of the electric energy market; P tag (t) represents the target power curve of the electric energy market; P act (t) represents the actual power curve of the electric energy market;

[0121]

[0122] Among them, δ2 represents the regulation response accuracy of the peak load ancillary service market; P tag represents the target regulation power value of the peak load ancillary service market; P as (k) represents the actual regulated power value of the peak load auxiliary service market at time k when it has the regulation capability; n1 represents the total number of recorded actual regulated power values;

[0123] The regulation response rate is obtained according to the ratio of the regulation power to the regulation time of the virtual power plant. The calculation formula of the regulation response rate includes:

[0124]

[0125] Where cos represents the regulation response rate of the virtual power plant; S ip Indicates 90% of the target power; F ip Indicates 10% of the target power; S it Indicates the time when the power of the virtual power plant reaches 90% of the target power; F it Indicates the time when the power of the virtual power plant reaches 10% of the target power;

[0126] The renewable energy consumption is obtained according to the ratio of the renewable energy power generation of the virtual power plant to the total power generation. The calculation formula of the renewable energy consumption includes:

[0127]

[0128] Among them, N er (t) represents the renewable energy consumption of the virtual power plant; N eg (t) represents the renewable energy power generation of the virtual power plant during the period t; W eg(t) represents the amount of renewable energy wasted; O eg (t) represents the power generation of other energy sources; V eg (t) represents the virtual power generation of adjustable load;

[0129] The regulation execution accuracy is obtained according to the ratio of the number of times the virtual power plant accurately executes instructions to the total number of instructions. The calculation formula of the regulation execution accuracy includes:

[0130]

[0131] Among them, R ti (t) represents the accuracy of virtual power plant regulation execution; N ai (t) represents the number of times resource i executes instructions accurately, P de (t) represents the total number of instructions; n represents the number of resources i.

[0132] In a specific application scenario, a test evaluation model is constructed based on the test index, test data of the virtual power grid is obtained, and multiple index test results are calculated based on the test evaluation model. The test evaluation module 32 can be specifically used to obtain the comprehensive price of the power market according to the medium- and long-term market price and the spot time price of the power market. The calculation formula of the comprehensive price of the power market includes:

[0133] C tot =δ1C zcq +δ2C rq +δ3C rn +δ4C ss ;

[0134] Among them, C tot represents the comprehensive price of electricity market; C zcq Indicates medium and long term market price; C rq represents the day-ahead market price; C rn Indicates intraday market price; C ss represents the real-time market price; δ1, δ2, δ3, and δ4 represent the corresponding coefficients respectively;

[0135] The proxy electricity purchase price is obtained according to the electricity price, the basic electricity price and the power factor adjustment fee. The calculation formula of the proxy electricity purchase price includes:

[0136] C d (t) = C dd (t)+C jb (t)+C gltz (t);

[0137] Among them, C d (t) represents the power purchase price of the agent; C dd(t) represents the electricity price; C jb (t) represents the basic electricity price; C gltz (t) represents the power factor adjustment fee;

[0138] The virtual power plant response price is obtained according to the transaction price, and the calculation formula of the virtual power plant response price includes:

[0139] C yi (t) = C pi (t);

[0140] Among them, C yi (t) represents the virtual power plant regulation response price; C pi (t) represents the transaction price published by the load management center.

[0141] In a specific application scenario, a test evaluation model is constructed based on the test index, test data of the virtual power grid is obtained, and multiple indicator test results are calculated based on the test evaluation model. The test evaluation module 32 can be specifically used to calculate the planned outage index according to the ratio of the planned outage duration to the effective working duration of the virtual power plant. The calculation formula of the planned outage index includes:

[0142]

[0143] Among them, P io (t) represents the planned outage index; P it (t) represents the planned downtime duration; A it (t) represents the effective working time;

[0144] According to the ratio of the unplanned outage time to the effective working time of the virtual power plant, the unplanned outage index is calculated, and the calculation formula of the unplanned outage index includes:

[0145]

[0146] Among them, U io (t) represents the unplanned outage index; U it (t) represents the duration of unplanned downtime; A it (t) represents the effective working time;

[0147] According to the start-up and shutdown costs of each production line of the virtual power plant, the total start-up and shutdown costs of the production line are calculated. The calculation formula of the total start-up and shutdown costs of the production line includes:

[0148]

[0149] Among them, C tot (t) represents the total cost of starting and stopping the production line; Ci2 (t) represents the start-up and stop costs of production line i2; n2 represents the number of production lines i2.

[0150] In a specific application scenario, a test evaluation model is constructed based on the test index, test data of the virtual power grid is obtained, and multiple index test results are calculated based on the test evaluation model. The test evaluation module 32 can be specifically used to calculate the long- and short-term comprehensive climate index according to seasonal weather factors and short-term weather factors. The calculation formula of the long- and short-term comprehensive climate index includes:

[0151] W(t)=W(αW qh ,βW tq );

[0152] Where W(t) represents the long-term and short-term comprehensive climate index; W represents the weight matrix; W qh represents seasonal climate factor; W tq represents the short-term weather factor; α and β are coefficients.

[0153] In a specific application scenario, the weighted calculation is performed on each of the index test results to obtain a test evaluation result of the virtual power plant regulation capability. The result calculation module 33 can be specifically used to perform standardization processing on each of the index test results to obtain a standardized index test result.

[0154] The standardized index test results are weighted to obtain the test evaluation results of the virtual power plant regulation capability. The calculation formula of the test evaluation results includes:

[0155]

[0156] Where, API(t) represents the test evaluation result; P u represents the weight of the u-th test indicator; X uv Indicates the standardized index test results; Q v It represents the weight of the test result of the vth indicator; u represents the category number of the test indicator; v represents the number of the indicator test result; m represents the total number of test indicators.

[0157] It should be noted that for other corresponding descriptions of the functional units involved in the virtual power plant regulation capability test and evaluation device provided in this embodiment, reference can be made to Figure 1 As well as the corresponding descriptions in the above embodiments, they will not be repeated here.

[0158] The present application also provides a computer device, such as Figure 3As shown, the computer device can specifically be a personal computer, a server, a network device, etc. The computer device includes a system bus, a processor, a memory and a communication interface, and can also include an input and output interface and a display device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store location information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in each method embodiment are implemented.

[0159] Those skilled in the art will appreciate that the structure of the above-mentioned computer device is only a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components, or combine certain components, or have a different arrangement of components.

[0160] In one embodiment, a computer-readable storage medium is provided. The computer-readable storage medium may be non-volatile or volatile, and stores a computer program thereon. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0161] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0162] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0163] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for testing and evaluating the regulation capability of a virtual power plant, characterized in that: The method comprises: Determine test indicators for evaluating the regulation capability of virtual power plants, where the types of test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators; Building a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model; A weighted calculation is performed on each of the indicator test results to obtain a test evaluation result of the virtual power plant regulation capability.

2. The method according to claim 1, characterized in that The resource physical attribute indicators include resource capacity adjustable rate, resource duration adjustment rate, plan curve tracking rate, communication qualification rate, adjustment response accuracy, adjustment response rate, renewable resource consumption rate, and adjustment execution accuracy; The market law indicators include comprehensive power market prices, proxy power purchase prices, and virtual power plant regulation response prices; The enterprise generates operating indicators including a planned downtime index, an unplanned downtime index, and a total cost of starting and stopping a production line; The climate and meteorological indicators include long-term and short-term comprehensive climate indices.

3. The method according to claim 2, characterized in that The step of constructing a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model includes: The resource capacity adjustable rate is obtained according to the ratio of the adjustable power of the virtual power plant resources to the sum of the rated power of the aggregated resources of the virtual power plant. The calculation formula of the resource capacity adjustable rate includes: Pam(t)=P am1 (t)+P am2 (t); P am2 (t)=|P iact (t)-P(j,t)|; Where Ram(t) represents the adjustable rate of resource capacity; Aam(t) represents the sum of the rated powers of the aggregated resources of the virtual power plant; Pam(t) represents the adjustable power of the virtual power plant resources; t represents the time period within the statistical period; Spc i represents the rated power of resource i aggregated by the virtual power plant; i represents the resources of the virtual power plant; n represents the number of resources in the virtual power plant; P am1 (t) represents the adjustable power of resources in the electric energy market; P am2 (t) represents the adjustable power of resources in the peak load ancillary service market; P imax (t) represents the upper limit operating power curve of virtual power plant resource i within the statistical period; P imin (t) represents the lower limit operating power curve of virtual power plant resource i within the statistical period; P iact (t) represents the actual power curve of the virtual power plant in the t period according to the two directions of peak shaving and valley filling; P(j,t) represents the baseline power value of the virtual power plant resources in the t period on the jth test day; Pr(jd,t) represents the power value in the t period on the dth reference day before the jth test day; N represents the total number of reference days; A d represents the weight coefficient corresponding to the dth reference day; The resource duration adjustment rate is obtained according to the ratio of the actual adjustable duration of the virtual power plant to the theoretical adjustable duration. The calculation formula of the resource duration adjustment rate includes: Among them, T ui (t) represents the resource duration adjustment rate of the virtual power plant; T ci (t) represents the actual adjustable duration of resource i in period t; T ai (t) represents the theoretical adjustable duration of resource i in period t; According to the proportion of the points where the actual power of the virtual power plant resources meets the planned power, the planned curve tracking rate is obtained. The calculation formula of the planned curve following the power includes: Among them, R N (t) represents the planning curve tracking rate of the virtual power plant resources in the period t; N p (t) represents the number of points where the actual power curve of the virtual power plant resource meets the planned power curve in the period t; N U (t) represents the total number of points of the actual power curve of the virtual power plant resources in time period t; The communication qualification rate is obtained according to the ratio of the time length during which the virtual power plant communication meets the requirements to the effective communication time length. The calculation formula of the communication qualification rate includes: Among them, R T (t) represents the communication qualification rate of the virtual power plant in period t; T Q (t) represents the duration of the virtual power plant's communication meeting the requirements in period t; T A (t) represents the effective duration of the virtual power plant communication in period t; The regulation response accuracy is calculated according to the difference between the target power and the actual power of the virtual power plant. The calculation formula of the regulation response accuracy includes: Among them, δ1 represents the regulation response accuracy of the electric energy market; P tag (t) represents the target power curve of the electric energy market; P act (t) represents the actual power curve of the electric energy market; Among them, δ2 represents the regulation response accuracy of the peak load ancillary service market; P tag represents the target regulation power value of the peak load ancillary service market; P as (k) represents the actual regulated power value of the peak load auxiliary service market at time k when it has the regulation capability; n1 represents the total number of recorded actual regulated power values; The regulation response rate is obtained according to the ratio of the regulation power to the regulation time of the virtual power plant. The calculation formula of the regulation response rate includes: Where cos represents the regulation response rate of the virtual power plant; S ip Indicates 90% of the target power; F ip Indicates 10% of the target power; S it Indicates the time when the power of the virtual power plant reaches 90% of the target power; F it Indicates the time when the power of the virtual power plant reaches 10% of the target power; The renewable energy consumption is obtained according to the ratio of the renewable energy power generation of the virtual power plant to the total power generation. The calculation formula of the renewable energy consumption includes: Among them, N er (t) represents the renewable energy consumption of the virtual power plant; N eg (t) represents the renewable energy power generation of the virtual power plant during the period t; W eg (t) represents the amount of renewable energy wasted; O eg (t) represents the power generation of other energy sources; V eg (t) represents the virtual power generation of adjustable load; The regulation execution accuracy is obtained according to the ratio of the number of times the virtual power plant accurately executes instructions to the total number of instructions. The calculation formula of the regulation execution accuracy includes: Among them, R ti (t) represents the accuracy of virtual power plant regulation execution; N ai (t) represents the number of times resource i executes instructions accurately, P de (t) represents the total number of instructions; n represents the number of resources i.

4. The method according to claim 2, characterized in that: The step of constructing a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model includes: According to the medium- and long-term market prices and the spot time price of the electricity market, the comprehensive price of the electricity market is obtained. The calculation formula of the comprehensive price of the electricity market includes: C tot =δ1C zcq +δ2C rq +δ3C rn +δ4C ss ; Among them, C tot represents the comprehensive price of electricity market; C zcq Indicates medium and long term market price; C rq represents the day-ahead market price; C rn Indicates intraday market price; C ss represents the real-time market price; δ1, δ2, δ3, and δ4 represent the corresponding coefficients respectively; The proxy electricity purchase price is obtained according to the electricity price, the basic electricity price and the power factor adjustment fee. The calculation formula of the proxy electricity purchase price includes: C d (t)=C dd (t)+C jb (t)+C gltz (t); Among them, C d (t) represents the power purchase price of the agent; C dd (t) represents the electricity price; C jb (t) represents the basic electricity price; C gltz (t) represents the power factor adjustment fee; The virtual power plant response price is obtained according to the transaction price, and the calculation formula of the virtual power plant response price includes: C yi (t)=C pi (t); Among them, C yi (t) represents the virtual power plant regulation response price; C pi (t) represents the transaction price published by the load management center.

5. The method according to claim 2, characterized in that: The step of constructing a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model includes: The planned outage index is calculated according to the ratio of the planned outage duration to the effective working duration of the virtual power plant. The calculation formula of the planned outage index includes: Among them, P io (t) represents the planned outage index; P it (t) represents the planned downtime duration; A it (t) represents the effective working time; According to the ratio of the unplanned outage time to the effective working time of the virtual power plant, the unplanned outage index is calculated, and the calculation formula of the unplanned outage index includes: Among them, U io (t) represents the unplanned outage index; U it (t) represents the duration of unplanned downtime; A it (t) represents the effective working time; According to the start-up and shutdown costs of each production line of the virtual power plant, the total start-up and shutdown costs of the production line are calculated. The calculation formula of the total start-up and shutdown costs of the production line includes: Among them, C tot (t) represents the total cost of starting and stopping the production line; C i2 (t) represents the start-up and stop costs of production line i2; n2 represents the number of production lines i2.

6. The method according to claim 2, characterized in that The step of constructing a test evaluation model based on the test indicators, acquiring test data of the virtual power grid, and calculating multiple indicator test results based on the test evaluation model includes: The long- and short-term comprehensive climate index is calculated based on seasonal weather factors and short-term weather factors. The calculation formula of the long- and short-term comprehensive climate index includes: W(t)=W(αW qh ,βW tq ); Where W(t) represents the long-term and short-term comprehensive climate index; W represents the weight matrix; W qh represents seasonal climate factor; W tq represents the short-term weather factor; α and β are coefficients.

7. The method according to claim 1, characterized in that The weighted calculation of each of the indicator test results to obtain the test evaluation result of the virtual power plant regulation capability includes: Performing standardization processing on each of the index test results to obtain a standardized index test result; The standardized index test results are weighted to obtain the test evaluation results of the virtual power plant regulation capability. The calculation formula of the test evaluation results includes: Where, API(t) represents the test evaluation result; P u represents the weight of the u-th test indicator; X uv Indicates the standardized index test results; Q v It represents the weight of the test result of the vth indicator; u represents the category number of the test indicator; v represents the number of the indicator test result; m represents the total number of test indicators.

8. A virtual power plant regulation capability testing and evaluation device, characterized in that: The device comprises: An indicator determination module, used to determine test indicators for evaluating the regulation capability of the virtual power plant, wherein the types of test indicators include resource physical property indicators, market law indicators, enterprise production and operation indicators, and climate and meteorological indicators; A test evaluation module, used to construct a test evaluation model based on the test indicators, obtain test data of the virtual power grid, and calculate multiple indicator test results based on the test evaluation model; The result calculation module is used to perform weighted calculation on each of the indicator test results to obtain a test evaluation result of the virtual power plant regulation capability.

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

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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