Virtual power plant resource redundancy configuration method, device and equipment and storage medium

Abstract

The invention discloses a virtual power plant resource redundancy configuration method, device and equipment and a storage medium. The method comprises the following steps: determining a virtual power plant operation evaluation index, and performing mathematical modeling on a current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree; performing simulation prediction on the current virtual power plant by using the fault tree to obtain a simulation result, and determining redundant equipment according to the simulation result; and determining a second predicted occurrence probability according to the redundant device, and determining a compensation price of the redundant device according to the first predicted occurrence probability and the second predicted occurrence probability. According to the technical scheme provided by the embodiment of the invention, the redundant equipment is accurately determined, the compensation mechanism of the redundant equipment is reasonably determined based on the market mechanism, the price mechanism guidance is performed on the redundant equipment in advance, and the enthusiasm of redundant standby participation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plants, and in particular to a method, device, equipment and storage medium for configuring redundant resources of a virtual power plant. Background Art

[0002] With the increase in the penetration rate of new energy, virtual power plants have become a new direction for the development of integrated energy business with their advantage of low initial fixed asset investment costs. At present, many provinces and cities have completed the construction of public management platforms for virtual power plants. Virtual power plant operators can use their own operating platforms to conduct pre-response plan declarations and post-evaluation settlements with provincial and municipal public management platforms. Improving the intelligence level of the operating platform is of great significance to lowering the technical threshold of virtual power plants and improving the management level of operators.

[0003] At present, in order to standardize the market management of virtual power plants, various regions have successively issued technical rules for the operation and management of virtual power plants, and proposed benchmarks such as the response capability and dynamic characteristics of virtual power plant systems. For virtual power plant operators, if they can reasonably redundancy invite load-side resources within the scope of technical rules, they can reduce the possibility of response deviation caused by low system reliability.

[0004] However, in actual work, when formulating the redundant invitation mechanism of virtual power plants, we often encounter the problem of poor effectiveness of redundant configuration strategies due to the difficulty in quantifying the value of redundant standby units. Summary of the invention

[0005] The present invention provides a virtual power plant resource redundancy configuration method, device, equipment and storage medium to solve the problem of poor effect of redundant configuration strategy.

[0006] In a first aspect, the present invention provides a method for configuring resource redundancy of a virtual power plant, comprising:

[0007] Determine a virtual power plant operation evaluation index, and perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree contains a cause-and-effect relationship of an operation revenue deviation event occurring in the current virtual power plant;

[0008] Using the fault tree to simulate and predict the current virtual power plant to obtain simulation results, and determining redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event;

[0009] A second predicted occurrence probability is determined based on the redundant equipment, and a compensation price for the redundant equipment is determined based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

[0010] In a second aspect, the present invention provides a virtual power plant resource redundancy configuration device, comprising:

[0011] A modeling module, used to determine the virtual power plant operation evaluation index, and to perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree contains the cause and effect relationship of the operation profit deviation event of the current virtual power plant;

[0012] A redundant equipment determination module, configured to use the fault tree to perform simulation prediction on the current virtual power plant to obtain simulation results, and determine redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event;

[0013] A compensation price determination module is used to determine a second predicted occurrence probability based on the redundant equipment, and to determine the compensation price of the redundant equipment based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

[0014] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0015] at least one processor;

[0016] and a memory communicatively coupled to the at least one processor;

[0017] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the virtual power plant resource redundancy configuration method of the first aspect mentioned above.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, which are used to enable a processor to implement the virtual power plant resource redundancy configuration method of the first aspect when executed.

[0019] The virtual power plant resource redundancy configuration scheme provided by the present invention uses a fault tree to simulate and predict the current virtual power plant, accurately determines the redundant equipment based on the simulation results, and evaluates the reliability value of the redundant configuration by using the first predicted probability of occurrence before the redundant equipment is put into use and the second predicted probability of occurrence after it is put into use, thereby accurately determining the compensation price of the redundant equipment. This scheme not only accurately determines the redundant equipment, but also reasonably determines the compensation mechanism for the redundant equipment based on the market mechanism, realizes the price mechanism guidance of the redundant equipment in advance, and enhances the enthusiasm of redundant standby participation.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0022] Figure 1 is a schematic diagram of a virtual power plant system architecture provided according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of a virtual power plant resource redundancy configuration method provided according to Embodiment 1 of the present invention;

[0024] Figure 3 A fault tree diagram provided according to the first embodiment of the present invention;

[0025] Figure 4 is a flow chart of a virtual power plant resource redundancy configuration method provided according to Embodiment 2 of the present invention;

[0026] Figure 5 It is a structural schematic diagram of a virtual power plant resource redundancy configuration device provided according to Embodiment 3 of the present invention;

[0027] Figure 6 It is a schematic diagram of the structure of an electronic device provided according to Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In the description of the present invention, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are an "or" relationship. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment 1

[0031] The realization of virtual power plant technology requires the aggregation and coordination of load-side energy such as distributed photovoltaics, energy storage systems, heat pumps, electric vehicles, cold and heat storage, and flexible loads on the user side through advanced communication technologies and software systems. For centralized energy power stations, virtual power plants have low reliability and high management costs. Figure 1 Figure 1 is a schematic diagram of a virtual power plant system architecture. Figure 1 As shown, the virtual power plant system can be a "cloud-edge-end" architecture. In the process of virtual power plant operation and management, after receiving the dispatch instruction, the operator of the virtual power plant needs to actively invite corporate customers (i.e., the owners of the equipment) to participate in specific activities such as peak load regulation and frequency regulation, and monitor whether the load-side resources of corporate customers respond according to the established plan. The planned invitation equipment can be understood as the set of equipment that executes the virtual power plant dispatch this time, and the redundant equipment can be understood as the set of equipment that is hot-backed up during the execution of the plan.

[0032] Figure 2A flowchart of a method for redundant configuration of virtual power plant resources is provided for embodiment 1 of the present invention. This embodiment is applicable to the situation where redundant configuration of resources of a virtual power plant is performed. The method can be executed by a virtual power plant resource redundant configuration device. The virtual power plant resource redundant configuration device can be implemented in the form of hardware and / or software. The virtual power plant resource redundant configuration device can be configured in an electronic device. The electronic device can be composed of two or more physical entities or one physical entity.

[0033] like Figure 2 As shown, a virtual power plant resource redundancy configuration method provided in the first embodiment of the present invention specifically includes the following steps:

[0034] S101. Determine an operation evaluation index of a virtual power plant, and perform mathematical modeling on the current virtual power plant according to the operation evaluation index of the virtual power plant to obtain a fault tree, wherein the fault tree includes a cause-and-effect relationship of an operation profit deviation event occurring in the current virtual power plant.

[0035] Optionally, the virtual power plant operation evaluation indicators include: the virtual power plant's regulation capacity indicator, response duration indicator, regulation rate indicator, response time indicator, regulation time indicator and regulation accuracy indicator.

[0036] In this embodiment, by interpreting the operation and management specifications of the virtual power plant, the virtual power plant can be mathematically modeled according to the technical specifications. At present, the published operation and management specifications for virtual power plants include the "Virtual Power Plant Management Specifications" and so on. Although there may be differences in the operation and management specifications issued by various regions, the basic principle is to guide virtual power plants to be managed in accordance with power supply modes such as centralized wind, solar and energy storage. Therefore, the operation evaluation indicators of virtual power plants can be roughly divided into two categories: static resource aggregation capability indicators and dynamic adjustment response capability indicators, as shown in Table 1 below: Virtual power plant operation evaluation indicator information table:

[0037] Table 1 Virtual power plant operation evaluation index information table

[0038]

[0039] Among them, if the static resource aggregation capacity of the virtual power plant cannot reach the minimum threshold for market access, there will be no profit, and in serious cases, it may be forced to delist. If the dynamic actual execution effect of the virtual power plant has serious deviations in the dynamic adjustment response capability index, there will be no profit, and in serious cases, it may be forced to delist. Therefore, the operating profit coefficient prof of the virtual power plant can be expressed as:

[0040]

[0041] in:

[0042] 1) The situations in which virtual power plants meet the market access threshold include: (actual regulation capacity > market access regulation capacity) AND (actual response time > market access response time) AND (actual regulation rate > market access regulation rate) AND (actual response time < market access response time) AND (actual regulation time < market access regulation time).

[0043] 2) In the general market, if the actual regulation accuracy is lower than the minimum standard (such as 50%), it is considered that the response instruction is not executed, and prof = 0. Therefore, for the operation of virtual power plants, the regulation accuracy should be guaranteed to be within the reasonable range required by the market.

[0044] In summary, when the virtual power plant system fails to meet any of the market access thresholds, or the regulation accuracy is lower than the minimum standard (at this time, it is considered that the operating income is completely lost), redundant load-side resources with risks should be invited to make up for the shortcomings. Therefore, when evaluating whether the virtual power plant system has the risk of operating income deviation, the impact of various faults on the virtual power plant operation evaluation indicators should be analyzed, such as the impact on the regulation capacity, response time, regulation rate, response time, regulation time and regulation accuracy. The event that affects the virtual power plant operation evaluation index can be determined according to the virtual power plant operation evaluation index, which is the cause event that causes the current virtual power plant to have an operating income deviation event. Among them, the cause event can include direct cause events and indirect cause events, and the indirect cause event can cause the direct cause event to occur. These cause events can be used to mathematically model the current virtual power plant to obtain a fault tree, and the nodes in the fault tree can be events. For example, the vertex of the fault tree is the operating income deviation event, the remaining nodes are cause events, and the branches in the fault tree are the causal relationship between events.

[0045] S102. Use the fault tree to simulate and predict the current virtual power plant to obtain simulation results, and determine redundant equipment based on the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event.

[0046] In this embodiment, according to the cause-effect relationship in the fault tree, the fault tree can be simplified by Boolean algebra to obtain the minimum cut set, so that the probability of the top event, that is, the probability of the occurrence of the operating profit deviation event, can be obtained. The bottom events can be regarded as independent events. The cause-effect relationship in the fault tree can be used to simulate and predict the current virtual power plant, so as to obtain the (first) predicted probability of the occurrence of the operating profit deviation event, and the probability of the event that triggers the occurrence of the operating profit deviation event, such as the probability of the first-level event described above. Redundancy design can be performed for events with a high probability of occurrence. Therefore, redundant equipment can be determined based on the simulation results. For example, if the first predicted probability of occurrence is greater than the first set value, the equipment whose probability of occurrence of the first-level event is greater than the second set value can be screened out, and the equipment is determined as redundant equipment.

[0047] S103. Determine a second predicted occurrence probability based on the redundant equipment, and determine a compensation price for the redundant equipment based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

[0048] In this embodiment, the number of redundant devices can be determined by predicting the predicted probability of occurrence of operating profit deviation events after the redundant devices are added to the current virtual power plant. In actual application scenarios, redundant devices will lose opportunity costs during hot backup, so it is necessary to formulate a redundant price mechanism to stimulate corporate customers to participate in redundant backup. For the operator of the virtual power plant, the value of redundant backup is approximately equal to the benefits obtained by reducing the failure rate of the virtual power plant. Therefore, the compensation price of redundant equipment can be determined based on the gap between the first predicted probability of occurrence and the second predicted probability of occurrence. For example, it is determined by performing a preset operation on the first predicted probability of occurrence and the second predicted probability of occurrence.

[0049] The technical solution of the embodiment of the present invention uses a fault tree to simulate and predict the current virtual power plant, accurately determines the redundant equipment based on the simulation results, and evaluates the reliability value of the redundant configuration by using the first predicted probability of occurrence before the redundant equipment is put into use and the second predicted probability of occurrence after it is put into use, thereby accurately determining the compensation price of the redundant equipment. This solution not only accurately determines the redundant equipment, but also reasonably determines the compensation mechanism for the redundant equipment based on the market mechanism, realizes the price mechanism guidance of the redundant equipment in advance, and enhances the enthusiasm of redundant standby participation.

[0050] Optionally, mathematical modeling of the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree includes: determining a target event according to the virtual power plant operation evaluation index, wherein the target event includes an event that directly triggers the operation profit deviation event; determining an intermediate event and a bottom event according to the target event, wherein the intermediate event is an event that directly triggers the target event, and the bottom event is an event that directly triggers the intermediate event; and mathematically modeling the current virtual power plant using the target event, the intermediate event and the bottom event to obtain a fault tree.

[0051] Exemplarily, the events that trigger the operating income deviation event may include a first-level event, an intermediate event, and a bottom event. The first-level event is a target event, the intermediate event is an event that causes the first-level event to occur, and the bottom event is an event that causes the intermediate event to occur. The first-level events specifically include the first-level event list in Table 2 below:

[0052] Table 2 List of Level 1 Events

[0053]

[0054] Among them, DO is the operating income deviation event. The intermediate events specifically include the intermediate events list in Table 3 below:

[0055] Table 3 Intermediate event list

[0056] Serial number serial number Event Description causation 1 M1 Network communication system failure Leading to F1, F2 2 M2 Local Energy Management System Failure Leading to F1, F2 3 M3 Photovoltaic system failure Lead to F2 4 M4 Energy storage system failure Leading to F3, F4, F5 5 M5 Charging system failure Leading to F1, F3 6 M6 Air conditioning system failure Leading to F1, F2, F6 7 M7 Failure of the cold and heat storage system Leading to F1, F2, F6 8 M8 Flexible load system failure Leading to F1, F2, F6

[0057] The bottom events specifically include the following bottom event list in Table 4:

[0058] Table 4 Bottom Event List

[0059]

[0060]

[0061] Among them, the equipment failure rate can be obtained by investigating equipment manufacturers and other means. Figure 3 A fault tree diagram is shown in Figure 1. Figure 3 The OR in the expression represents a logical relationship or. Figure 3As shown, the red line of M1 pointing to F1 and F2 indicates that M1 can cause F1 and F2 to occur, the black line of M2 pointing to F1 and F2 indicates that M2 can cause F1 and F2 to occur, the green line of M3 pointing to F2 indicates that M3 can cause F2 to occur, the purple line of M4 pointing to F3, F4 and F5 indicates that M4 can cause F3, F4 and F5, the orange line of M5 pointing to F1 and F5 indicates that M5 can cause F1 and F5, the blue dotted line of M6 pointing to F1, F2 and F6 indicates that M6 can cause F1, F2 and F6, the orange dotted line of M7 pointing to F1, F2 and F6 indicates that M7 can cause F1, F2 and F6, and the blue line of M8 pointing to F1, F2 and F6 indicates that M8 can cause F1, F2 and F6.

[0062] Optionally, the use of the fault tree to simulate and predict the current virtual power plant to obtain simulation results includes: using the Monte Carlo method and the fault tree to simulate and predict the current virtual power plant to obtain simulation results, wherein the simulation results include the first predicted probability of occurrence of the operating profit deviation event and the probability of occurrence of a target event, and the target event includes an event that directly triggers the operating profit deviation event.

[0063] Specifically, the Monte Carlo method is a computational simulation method that evaluates complex systems by generating random numbers. The Monte Carlo method can be used to generate simulation parameters. The simulation parameters include: time interval m = 1, which means that a random number is generated every hour, the maximum operating time T_MAX = 175200, which means the total operating hours of the virtual power plant in 20 years, and the number of simulations NS = 1000, which means that a total of 1000 simulation calculations are performed. Through Monte Carlo simulation, the number of times each bottom event in the fault tree causes a first-level event can be obtained, thereby obtaining the probability of occurrence of the target event SFR. i , that is, the probability of a first-level event occurring, specifically expressed as:

[0064]

[0065] Among them, NK i is the total number of occurrences of the i-th level 1 event.

[0066] Through Monte Carlo simulation, we can also get the number of top events caused by each bottom event, so as to get the first predicted probability SFR of the operating profit deviation event. D0 , which can be specifically expressed as:

[0067]

[0068] Among them, NK d0 The total number of operating profit deviation events.

[0069] Embodiment 2

[0070] Figure 4 A flowchart of a method for redundant configuration of virtual power plant resources is provided for the second embodiment of the present invention. The technical solution of the embodiment of the present invention is further optimized on the basis of the above-mentioned optional technical solutions, and a specific method for redundant configuration of resources of the virtual power plant is given.

[0071] Optionally, the determination of redundant equipment according to the simulation results includes: when the first predicted occurrence probability in the simulation results is greater than a first preset frequency, determining a target occurrence probability greater than a second preset frequency from the occurrence probability of the event that triggers the operating income deviation event in the simulation results, and determining the operating equipment associated with the target event corresponding to the target occurrence probability as redundant equipment, wherein the target event includes an event that directly triggers the operating income deviation event. The advantage of such a setting is that the first predicted occurrence probability is used to accurately assess the timing when redundant backup equipment is needed, and redundant equipment is determined for high-probability events in the events that trigger the operating income deviation event, thereby ensuring the rationality of redundant equipment.

[0072] Optionally, the second predicted probability of occurrence is determined based on the redundant equipment, including: increasing the number of redundant equipment by using preset equipment increments, predicting the predicted probability of triggering the operation revenue deviation event after different numbers of redundant equipment are added to the operation; when the predicted probability is less than or equal to the first predicted probability of occurrence, determining the predicted probability as the second predicted probability of occurrence. The advantage of this setting is that by gradually increasing the number of redundant equipment, the upper limit value of the failure probability that satisfies the reliable operation of the virtual power plant is determined.

[0073] Optionally, determining the compensation price of the redundant equipment according to the first predicted probability of occurrence and the second predicted probability of occurrence includes: determining the total amount of funds using the first predicted probability of occurrence and the second predicted probability of occurrence, wherein the total amount of funds is the total amount of funds that can be paid to customers corresponding to the redundant equipment; for each type of redundant equipment, determining the payable amount of the current type of redundant equipment using the total amount of funds and the target ratio, and determining the compensation price of each redundant equipment using the payable amount, wherein the target ratio is the ratio of the number of redundant equipment of the current type to the number of operating equipment of the current type. The advantage of such a setting is that the economic value of the redundant equipment is evaluated using the first predicted probability of occurrence and the second predicted probability of occurrence, and compensation prices are determined for different types of redundant equipment according to the scarcity of the redundant equipment, thereby guiding corporate customers to participate in redundant standby through a price mechanism.

[0074] like Figure 4As shown, a virtual power plant resource redundancy configuration method provided by Embodiment 2 of the present invention specifically includes the following steps:

[0075] S201. Determine the virtual power plant operation evaluation index; determine the target event according to the virtual power plant operation evaluation index; determine the intermediate event and the bottom event according to the target event; use the target event, the intermediate event and the bottom event to mathematically model the current virtual power plant to obtain a fault tree.

[0076] The target event includes the event that directly triggers the operating income deviation event, the intermediate event is the event that directly triggers the target event, and the bottom event is the event that directly triggers the intermediate event.

[0077] S202: Use the Monte Carlo method and the fault tree to perform simulation prediction on the current virtual power plant to obtain simulation results.

[0078] The simulation result includes a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of a target event, and the target event includes an event that directly triggers the operating profit deviation event.

[0079] S203. When the first predicted occurrence probability in the simulation result is greater than the first preset frequency, a target occurrence probability greater than a second preset frequency is determined from the occurrence probability of the event that triggers the operating profit deviation event in the simulation result, and the operating equipment associated with the target event corresponding to the target occurrence probability is determined as redundant equipment.

[0080] The target event includes an event that directly triggers the operating profit deviation event.

[0081] Specifically, in a virtual power plant, various load-side resources such as photovoltaic storage usually operate as relatively independent systems. Therefore, from the perspective of the load-side resources aggregated by the operator of the virtual power plant, the probability of the bottom event can be regarded as the parallel probability between the equipment sets. In actual business, it is necessary to consider the cost investment of redundant equipment to avoid the waste of equipment resources caused by excessive redundancy. Operators can configure redundant backup as much as possible within the acceptable cost range to reduce the probability of the first predicted occurrence, that is, reduce the value of the first predicted probability of occurrence within an acceptable range. In order to improve the overall reliability of the virtual power plant, the main factors affecting the failure rate should be solved first. Therefore, the probabilities of the first-level events can be sorted by size, and the equipment corresponding to the first-level events with high probabilities can be redundantly backed up first. Therefore, when the probability of the first predicted occurrence is greater than the first preset frequency, the target probability of occurrence greater than the second preset frequency can be determined from the probability of occurrence of the event that triggers the operation income deviation event, and the operating equipment associated with the target event corresponding to the target probability of occurrence can be determined as redundant equipment.

[0082] S204: increasing the number of redundant devices by using a preset device increment, and predicting the probability of triggering the operation revenue deviation event after different numbers of redundant devices are added to the operation.

[0083] Specifically, the probability of the bottom event can be expressed as the product of the failure probabilities of the planned invitation device and the redundant device. Then the probability of the bottom event can be expressed as q i :

[0084]

[0085] Among them, q i is the probability of the i-th bottom event occurring, x t is the failure rate of the tth device, n j and n k are the number of planned invitation devices and redundant devices, respectively, and Π represents cumulative multiplication. It can be seen from this that the more redundant devices corresponding to the bottom event, the smaller the probability of the bottom event, and thus the higher the reliability of the virtual power plant. After determining the first-level event whose probability of occurrence needs to be reduced, it is necessary to calculate the redundant reliability of the equipment corresponding to the first-level event. The number of redundant devices can be gradually increased with a step size of 1% of the number of planned invitation devices (i.e., the preset device increment), and q can be recalculated. i The virtual power plant is then simulated to obtain the predicted probability of triggering an operating revenue deviation event after redundant equipment is added to the operation. In the actual scenario, the number of redundant equipment is less than or equal to the upper limit of the number of equipment aggregated by the operator.

[0086] S205. When the predicted probability is less than or equal to the first predicted occurrence probability, determine the predicted probability as the second predicted occurrence probability.

[0087] Specifically, by flexibly setting the first preset probability, the complex environment faced by operators in actual business scenarios can be approximated. After multiple rounds of redundant configuration iterations, if the predicted probability is less than or equal to the first preset probability, it means that the number of redundantly configured devices is the minimum, that is, the optimal solution, and the predicted probability can be determined as the second predicted occurrence probability.

[0088] S206. Determine the total amount of funds using the first predicted probability of occurrence and the second predicted probability of occurrence.

[0089] The total amount of funds is the total amount of funds that can be paid to the customers corresponding to the redundant devices.

[0090] For example, the total amount of funds is sum It can be expressed as:

[0091] mony sum =(SFR D0-初始 -SFRD0-冗余 )*mony in *μ

[0092] Among them, mony in is the expected revenue of the virtual power plant, SFR D0-初始 and SFR D0-冗余 are the first predicted probability of occurrence and the second predicted probability of occurrence respectively, μ(0<μ≤1) is the constant coefficient, which means that the operator can consider sharing the revenue with corporate customers in proportion.

[0093] S207 . For each type of redundant equipment, determine the payable amount of the current type of redundant equipment using the total amount of funds and the target ratio, and determine the compensation price of each redundant equipment using the payable amount.

[0094] The target ratio is the ratio of the number of redundant devices of the current type to the number of operating devices of the current type.

[0095] Specifically, under the market mechanism, scarce load-side resource types can obtain more funds, so the total funds can be allocated according to the target ratio for each type of redundant equipment. For example, the smaller the target ratio, the more funds can be allocated, thereby obtaining the payable amount for each type of redundant equipment. The payable amount is redistributed according to the number of redundant equipment of the same type, thereby obtaining the compensation price for each redundant equipment.

[0096] For example, the amount payable for redundant equipment is load It can be expressed as:

[0097]

[0098] Among them, the total number of redundant devices is numb load_sum , numb load is the number of redundant devices of the load type, and load_type is the total number of redundant device types.

[0099] Optionally, the method of using the payable amount to determine the compensation price of each redundant device includes: for each redundant device of each type, determining the product of the payable amount, the preset customer priority coefficient, the preset redundant device priority coefficient and the target ratio as the compensation price of the current redundant device of the current type, wherein the preset redundant device priority coefficient is related to the failure rate of the current redundant device. The advantage of such a setting is that the scarcity of redundant standby resources and the priority of corporate customers are used to differentiate the compensation price of redundant devices, thereby reasonably stimulating corporate customers to participate in redundant standby.

[0100] Specifically, for each redundant device of the same type, the payable amount can be further allocated according to the reliability of the device and the type of enterprise customer.

[0101] For example, the compensation price of redundant equipment is cust The determination method can be:

[0102]

[0103] Among them, γ is the preset customer priority coefficient, and δ is the preset redundant equipment priority coefficient. The preset customer priority coefficient may be related to whether the customer enterprise has been invited. If the equipment of the customer enterprise is already a planned invitation equipment, that is, the equipment of the enterprise has responded to the dispatch and participated in the operation, then the priority coefficient of the enterprise customer (such as 1.2) is greater than the enterprise customer of the non-planned invitation equipment (such as 1). Based on the equipment failure rate data provided by each equipment manufacturer, equipment with a lower failure rate should be invited first among the same type of equipment. Therefore, among the same type of redundant equipment, the failure rate can be normalized with the average failure rate as the benchmark value. For example, the value range of δ can be greater than or equal to 0.5 and less than or equal to 1.5.

[0104] The virtual power plant resource redundancy configuration method provided by the embodiment of the present invention uses the first predicted probability of occurrence to accurately evaluate the time when redundant backup equipment is needed, and determines redundant equipment for high-probability events in events that trigger operating profit deviation events, thereby ensuring the rationality of redundant equipment. By gradually increasing the number of redundant equipment, the upper limit of the failure probability that satisfies the reliable operation of the virtual power plant is determined, and the economic value of the redundant equipment is evaluated using the first predicted probability of occurrence and the second predicted probability of occurrence. Compensation prices are determined for different types of redundant equipment based on the scarcity of redundant equipment, and corporate customers are guided to participate in redundant standby through a price mechanism. This method has good engineering application practical significance, helps virtual power plant operators to accurately improve system reliability, and effectively avoid losses caused by equipment failure risks.

[0105] Embodiment 3

[0106] Figure 5 This is a schematic diagram of the structure of a virtual power plant resource redundancy configuration device provided in Embodiment 3 of the present invention. Figure 5 As shown, the device includes: a modeling module 301, a redundant equipment determination module 302 and a compensation price determination module 303, wherein:

[0107] A modeling module, used to determine the virtual power plant operation evaluation index, and to perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree contains the cause and effect relationship of the operation profit deviation event of the current virtual power plant;

[0108] A redundant equipment determination module, configured to use the fault tree to perform simulation prediction on the current virtual power plant to obtain simulation results, and determine redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event;

[0109] A compensation price determination module is used to determine a second predicted occurrence probability based on the redundant equipment, and to determine the compensation price of the redundant equipment based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

[0110] The virtual power plant resource redundancy configuration device provided by the embodiment of the present invention uses a fault tree to simulate and predict the current virtual power plant, accurately determines the redundant equipment based on the simulation results, and evaluates the reliability value of the redundant configuration by using the first predicted probability of occurrence before the redundant equipment is put into use and the second predicted probability of occurrence after it is put into use, thereby accurately determining the compensation price of the redundant equipment. This solution not only accurately determines the redundant equipment, but also reasonably determines the compensation mechanism for the redundant equipment based on the market mechanism, realizes the price mechanism guidance of the redundant equipment in advance, and enhances the enthusiasm of redundant standby participation.

[0111] Optionally, the redundant device determination module includes:

[0112] A redundant equipment determination unit is used to determine a target occurrence probability greater than a second preset frequency from the occurrence probability of the event that triggers the operating profit deviation event in the simulation result when the first predicted occurrence probability in the simulation result is greater than a first preset frequency, and determine the operating equipment associated with the target event corresponding to the target occurrence probability as a redundant equipment, wherein the target event includes an event that directly triggers the operating profit deviation event.

[0113] A probability prediction unit, configured to increase the number of redundant devices by using a preset device increment, and predict the probability of triggering the operation revenue deviation event after different numbers of redundant devices are added to the operation;

[0114] The second predicted occurrence probability determining unit is used to determine the predicted probability as a second predicted occurrence probability when the predicted probability is less than or equal to the first predicted occurrence probability.

[0115] Optionally, the compensation price determination module includes:

[0116] a fund sum determination unit, configured to determine a fund sum by using the first predicted probability of occurrence and the second predicted probability of occurrence, wherein the fund sum is a total fund that can be paid to a customer corresponding to the redundant device;

[0117] A compensation price determination unit is used to determine, for each type of redundant equipment, a payable amount of the current type of redundant equipment using the total amount of funds and a target ratio, and to determine a compensation price for each of the redundant equipment using the payable amount, wherein the target ratio is the ratio of the number of redundant equipment of the current type to the number of operating equipment of the current type.

[0118] Optionally, using the payable amount to determine the compensation price of each of the redundant devices includes: for each redundant device of each type, multiplying the payable amount, a preset customer priority coefficient, a preset redundant device priority coefficient and the target ratio to determine the compensation price of the current redundant device of the current type, wherein the preset redundant device priority coefficient is related to the failure rate of the current redundant device.

[0119] Optionally, the virtual power plant operation evaluation indicators include: the virtual power plant's regulation capacity indicator, response duration indicator, regulation rate indicator, response time indicator, regulation time indicator and regulation accuracy indicator.

[0120] Optional modeling modules include:

[0121] A target event determination unit, configured to determine a target event according to the virtual power plant operation evaluation index, wherein the target event includes an event that directly triggers the operation revenue deviation event;

[0122] An event determination unit, configured to determine an intermediate event and a bottom event according to the target event, wherein the intermediate event is an event that directly triggers the target event, and the bottom event is an event that directly triggers the intermediate event;

[0123] The fault tree determination unit is used to perform mathematical modeling on the current virtual power plant using the target event, the intermediate event and the bottom event to obtain a fault tree.

[0124] Optionally, the redundant device determination module includes:

[0125] A simulation unit is used to perform simulation prediction on the current virtual power plant using the Monte Carlo method and the fault tree to obtain a simulation result, wherein the simulation result includes a first predicted probability of occurrence of the operating profit deviation event and the probability of occurrence of a target event, and the target event includes an event that directly triggers the operating profit deviation event.

[0126] The virtual power plant resource redundancy configuration device provided in the embodiment of the present invention can execute the virtual power plant resource redundancy configuration method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] Embodiment 4

[0128] Figure 6 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0129] like Figure 6 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0130] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0131] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as a virtual power plant resource redundancy configuration method.

[0132] In some embodiments, the virtual power plant resource redundancy configuration method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the virtual power plant resource redundancy configuration method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the virtual power plant resource redundancy configuration method in any other appropriate manner (e.g., by means of firmware).

[0133] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0134] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0135] The computer device provided above can be used to execute the virtual power plant resource redundancy configuration method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0136] Embodiment 5

[0137] In the context of the present invention, a computer-readable storage medium may be a tangible medium, wherein the computer-executable instructions, when executed by a computer processor, are used to perform a virtual power plant resource redundancy configuration method, the method comprising:

[0138] Determine a virtual power plant operation evaluation index, and perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree contains a cause-and-effect relationship of an operation revenue deviation event occurring in the current virtual power plant;

[0139] Using the fault tree to simulate and predict the current virtual power plant to obtain simulation results, and determining redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event;

[0140] A second predicted occurrence probability is determined based on the redundant equipment, and a compensation price for the redundant equipment is determined based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

[0141] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by an instruction execution system, device or equipment or used with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0142] The computer device provided above can be used to execute the virtual power plant resource redundancy configuration method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0143] It is worth noting that in the embodiment of the above-mentioned virtual power plant resource redundancy configuration device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0144] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for configuring redundant resources of a virtual power plant, characterized in that: include: Determine a virtual power plant operation evaluation index, and perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree includes a cause-and-effect relationship of an operation revenue deviation event occurring in the current virtual power plant; Using the fault tree to simulate and predict the current virtual power plant to obtain simulation results, and determining redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event; A second predicted occurrence probability is determined based on the redundant equipment, and a compensation price for the redundant equipment is determined based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

2. The method according to claim 1, characterized in that The determining of redundant devices according to the simulation results includes: When the first predicted occurrence probability in the simulation result is greater than the first preset frequency, a target occurrence probability greater than a second preset frequency is determined from the occurrence probability of the event that triggers the operating profit deviation event in the simulation result, and the operating equipment associated with the target event corresponding to the target occurrence probability is determined as redundant equipment, wherein the target event includes an event that directly triggers the operating profit deviation event.

3. The method according to claim 1, characterized in that Determining the second predicted occurrence probability according to the redundant device includes: By increasing the number of the redundant devices by using a preset device increment, the predicted probability of triggering the operation revenue deviation event after different numbers of the redundant devices are added to the operation is predicted; When the predicted probability is less than or equal to the first predicted occurrence probability, the predicted probability is determined as the second predicted occurrence probability.

4. The method according to any one of claims 1 to 3, characterized in that The determining the compensation price of the redundant equipment according to the first predicted occurrence probability and the second predicted occurrence probability includes: Determine a total amount of funds using the first predicted probability of occurrence and the second predicted probability of occurrence, wherein the total amount of funds is the total amount of funds that can be paid to the customer corresponding to the redundant device; For each type of redundant equipment, the total amount of funds and the target ratio are used to determine the payable amount of the current type of redundant equipment, and the compensation price of each of the redundant equipment is determined using the payable amount, wherein the target ratio is the ratio of the number of redundant equipment of the current type to the number of operating equipment of the current type.

5. The method according to claim 4, characterized in that The determining the compensation price of each redundant device by using the payable amount includes: For each redundant device of each type, the product of the payable amount, the preset customer priority coefficient, the preset redundant device priority coefficient and the target ratio is determined as the compensation price of the current redundant device of the current type, wherein the preset redundant device priority coefficient is related to the failure rate of the current redundant device.

6. The method according to claim 1, characterized in that The virtual power plant operation evaluation indicators include: the virtual power plant's regulation capacity indicator, response time indicator, regulation rate indicator, response time indicator, regulation time indicator and regulation accuracy indicator.

7. The method according to claim 1 or 6, characterized in that: The mathematical modeling of the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree includes: Determining a target event according to the virtual power plant operation evaluation index, wherein the target event includes an event that directly triggers the operation revenue deviation event; Determine an intermediate event and a bottom event according to the target event, wherein the intermediate event is an event that directly triggers the target event, and the bottom event is an event that directly triggers the intermediate event; The target event, the intermediate event and the bottom event are used to perform mathematical modeling on the current virtual power plant to obtain a fault tree.

8. The method according to claim 1 or 6, characterized in that: The using the fault tree to simulate and predict the current virtual power plant to obtain a simulation result includes: The current virtual power plant is simulated and predicted using the Monte Carlo method and the fault tree to obtain simulation results, wherein the simulation results include the first predicted probability of occurrence of the operating profit deviation event and the probability of occurrence of the target event, and the target event includes the event that directly triggers the operating profit deviation event.

9. A virtual power plant resource redundancy configuration device, characterized in that: include: A modeling module, used to determine the virtual power plant operation evaluation index, and to perform mathematical modeling on the current virtual power plant according to the virtual power plant operation evaluation index to obtain a fault tree, wherein the fault tree contains the cause and effect relationship of the operation profit deviation event of the current virtual power plant; A redundant equipment determination module, configured to use the fault tree to perform simulation prediction on the current virtual power plant to obtain simulation results, and determine redundant equipment according to the simulation results, wherein the simulation results include a first predicted probability of occurrence of the operating profit deviation event and a probability of occurrence of an event that triggers the operating profit deviation event; A compensation price determination module is used to determine a second predicted occurrence probability based on the redundant equipment, and to determine the compensation price of the redundant equipment based on the first predicted occurrence probability and the second predicted occurrence probability, wherein the second predicted occurrence probability is the predicted occurrence probability of the operating profit deviation event after the redundant equipment is added to the operation.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the virtual power plant resource redundancy configuration method described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the virtual power plant resource redundancy configuration method according to any one of claims 1 to 8 when executed.

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