Load aggregator response performance evaluation method, power market clearing method and device

Abstract

The invention discloses a load aggregator response performance evaluation method and a power market clearing method and device, and relates to the technical field of power. The load aggregator response performance evaluation method comprises the following steps: after one-time demand response is completed, determining the actual response capacity of the current demand response, and determining the effective response capacity of the load aggregator for the current demand response in combination with the bid-winning response capacity corresponding to the current demand response; and determining a deviation factor of the demand response so as to determine the single response accuracy of the load aggregator for the demand response and the overall response accuracy of the load aggregator. According to the method, the single response accuracy of each demand response of the load aggregator is obtained, the overall response accuracy of the load aggregator is obtained by using the single response accuracy data of the load aggregator, and the overall response accuracy can be used as an influence factor of clearing and bid winning of the power market. Therefore, the power market clearing reliability and the power grid stability are improved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a load aggregator response performance evaluation method, an electric power market clearing method and a device. Background Art

[0002] As the proportion of renewable energy generators increases, my country's power grid is becoming increasingly intermittent and energy supply volatility is increasing. A growing number of load aggregators are participating in energy management through power market regulation by integrating dispersed user resources. This allows the grid's massive demand-side load resources to proactively adjust electricity demand to address the uncertainties of renewable energy generation, achieving an immediate balance between power supply and demand, or what is known as power market clearing.

[0003] In the current electricity market clearing plan, it is usually done through bidding. Among the bidding load aggregators, the final winning load aggregator is determined based on the price and expected response capacity provided by each load aggregator.

[0004] However, when adopting the above-mentioned electricity market clearing scheme, the response accuracy of the load aggregator is less considered when determining the winning load aggregator. This leads to the load aggregators generally having a weak willingness to optimize response performance and improve accuracy, which in turn leads to insufficient reliability of electricity market clearing and poor grid stability. Summary of the Invention

[0005] The main purpose of this application is to propose a load aggregator response performance evaluation method, power market clearing method and device, aiming to improve the power market clearing reliability and grid stability.

[0006] In a first aspect, the present invention provides a method for evaluating the response performance of a load aggregator, comprising:

[0007] After completing a demand response, determining the actual response capacity of the demand response according to the baseline load of the load aggregator and the actual measured load for the demand response;

[0008] determining the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response;

[0009] Determining a deviation factor for the current demand response based on the effective response capacity and the winning response capacity;

[0010] determining, based on the deviation factor, a single response accuracy of the load aggregator for the current demand response;

[0011] According to the single response accuracy of each demand response of the load aggregator, the overall response accuracy of the load aggregator under the demand response is determined.

[0012] In an optional embodiment, determining the effective response capacity of the load aggregator for the current demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response includes:

[0013] Determining multiple response intervals corresponding to the current demand response according to a preset lower limit ratio of effective responses, a preset upper limit ratio of effective responses, and the winning response capacity;

[0014] determining, according to the actual response capacity, a target response interval in which the actual response capacity is located from the multiple response intervals, and determining a response type corresponding to the target response interval as a target response type;

[0015] The effective response capacity is determined according to the target response type.

[0016] In an optional embodiment, determining the effective response capacity according to the target response type includes:

[0017] If the target response type is an invalid response type, determining the valid response capacity to be zero;

[0018] If the target response type is a first effective response type, determining the effective response capacity according to the actual response capacity;

[0019] If the target response type is the second effective response type, the effective response capacity is determined according to the winning response capacity and a preset effective response capacity penalty factor.

[0020] In an optional embodiment, determining, based on the deviation factor, the single response accuracy of the load aggregator for the current demand response includes:

[0021] determining whether the load aggregator is participating in market clearing for the first time based on the total number of times the load aggregator has participated in market clearing;

[0022] If it is a load aggregator participating in market clearing for the first time, a preset lower limit of initial response performance is determined as the single response accuracy;

[0023] If the load aggregator is not participating in market clearing for the first time, the single response accuracy is determined based on the deviation factor and the preset initial response performance lower limit.

[0024] In an optional embodiment, determining the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator comprises:

[0025] Determining a recent response accuracy index of the load aggregator within the preset time window based on the single response accuracy of multiple demand responses of the load aggregator within the preset time window before the current clearing moment of the current demand response;

[0026] Determining the historical response accuracy of the load aggregator under the current demand response based on the single response accuracy of the current demand response and the comprehensive response accuracy of the single response accuracy of all historical demand responses of each demand response of the load aggregator;

[0027] The overall response accuracy of the load aggregator under the current demand response is determined based on the recent response accuracy index under the preset time window and the historical response accuracy under the current demand response.

[0028] In an optional embodiment, determining the recent response accuracy index of the load aggregator in the preset time window based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current clearing moment of the current demand response includes:

[0029] Determining, based on the number of times the load aggregator participates in market clearing within the preset time window and a preset time discount factor, a response influence weight of each demand response within the preset time window on the current demand response;

[0030] The recent response accuracy index is determined according to the response influence weight of each demand response on the current demand response and the single response accuracy of the multiple demand responses within the preset time window.

[0031] In an optional embodiment, the method further comprises:

[0032] Determining an initial response impact factor based on a total number of market clearing times of the total number of demand responses completed by the load aggregator and a preset initial number threshold;

[0033] According to the initial response impact factor, the overall response accuracy of the load aggregator under the current demand response is adjusted to obtain the final response accuracy of the load aggregator under the current demand response after adjustment.

[0034] In a second aspect, the present invention provides a method for clearing an electricity market, comprising:

[0035] Obtaining, based on the declared response capacities of the multiple load aggregators participating in the bidding and the response accuracy of each load aggregator, the estimated actual response capacities of the multiple load aggregators; wherein the response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the method described in any one of the preceding embodiments, or the final response accuracy of the load aggregator calculated according to the method described in the preceding embodiments;

[0036] determining a reliability constraint condition according to a preset allowable deviation threshold and the declared response capacities and the estimated actual response capacities of the plurality of load aggregators;

[0037] Determining that capacity satisfies a constraint condition based on a preset total clearing capacity and the estimated actual response capacities of the plurality of load aggregators;

[0038] An electricity market clearing operation is performed for the plurality of load aggregators according to the reliability constraint and the capacity satisfaction constraint.

[0039] In a third aspect, the present invention provides a load aggregator response performance evaluation device, comprising:

[0040] a capacity determination module configured to, after completing a demand response, determine the actual response capacity of the current demand response based on the baseline load of the load aggregator and the actual measured load for the current demand response; and determine the effective response capacity of the load aggregator for the current demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response;

[0041] a deviation determination module, configured to determine a deviation factor of the current demand response according to the effective response capacity and the winning response capacity;

[0042] The accuracy determination module is used to determine the single response accuracy of the load aggregator for the current demand response based on the deviation factor; and determine the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator.

[0043] In a fourth aspect, the present invention provides an electricity market clearing device, comprising:

[0044] an acquisition module, configured to respectively acquire the estimated actual response capacity of the multiple load aggregators participating in the bidding based on the declared response capacities of the multiple load aggregators and the response accuracy of each load aggregator; wherein the response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the method described in any one of the preceding embodiments, or the final response accuracy of the load aggregator calculated according to the method described in the preceding embodiments;

[0045] a constraint module, configured to determine a reliability constraint condition based on a preset allowable deviation threshold and the estimated actual response capacities of the plurality of load aggregators; and determine whether the capacity satisfies the constraint condition based on a preset total clearing capacity and the estimated actual response capacities of the plurality of load aggregators;

[0046] A clearing module is used to perform a power market clearing operation for the multiple load aggregators according to the reliability constraint condition and the capacity satisfaction constraint condition.

[0047] In a fifth aspect, the present application provides an electronic device comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, the processor and the storage medium communicate via the bus, and the processor executes the machine-readable instructions to perform a method as described in any of the foregoing embodiments.

[0048] In a sixth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, executes the method as described in any of the aforementioned embodiments.

[0049] The beneficial effects of this application are:

[0050] The load aggregator response performance evaluation method provided in the embodiment of the present application includes: after completing a demand response, determining the actual response capacity of the demand response according to the baseline load of the load aggregator and the actual measured load for this demand response; determining the effective response capacity of the load aggregator for this demand response according to the actual response capacity and the winning response capacity corresponding to the demand response; determining the deviation factor of the demand response according to the effective response capacity and the winning response capacity; determining the single response accuracy of the load aggregator for the demand response according to the deviation factor; and determining the overall response accuracy of the load aggregator according to the single response accuracy of each demand response of the load aggregator. The method obtains the load aggregator's baseline load and the actual measured load for this demand response, calculates the actual response capacity of the load aggregator for this demand response, and determines the load aggregator's effective response capacity for this demand response based on the above actual response capacity and the preset conditions based on the winning response capacity corresponding to this demand response. Then, based on the effective response capacity and the winning response capacity, the deviation factor of this demand response is calculated. The deviation factor can be used to reflect the degree of deviation between the effective response capacity and the winning response capacity. Finally, based on the deviation factor and the preset algorithm, the load aggregator's single response accuracy for the demand response is calculated, thereby achieving the calculation of the load aggregator's overall response accuracy based on the single response accuracy of each demand response of the load aggregator. The overall response accuracy can be used as an influencing factor for the corresponding load aggregator's winning bid when participating in the electricity market clearing, thereby improving the reliability of the electricity market clearing and the stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0052] Figure 1 A flow chart of a load aggregator response performance evaluation method according to an embodiment of the present application;

[0053] Figure 2 A flow chart of a load aggregator response performance evaluation method provided in another embodiment of the present application;

[0054] Figure 3 A flow chart of a load aggregator response performance evaluation method according to another embodiment of the present application;

[0055] Figure 4 A flow chart of a load aggregator response performance evaluation method provided in yet another embodiment of the present application;

[0056] Figure 5 A schematic diagram of a flow chart of a method for clearing the electricity market provided in one embodiment of the present application;

[0057] Figure 6 A schematic diagram of the structure of a load aggregator response performance evaluation device provided in an embodiment of the present application;

[0058] Figure 7 A schematic diagram of the structure of an electricity market clearing device provided in an embodiment of the present application;

[0059] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0061] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0062] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined or explained in subsequent figures. The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0063] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0064] In the current electricity market clearing scheme, load aggregators are mainly ranked according to their quotations participating in the electricity market clearing bidding, and then the winning load aggregators are selected in order from low to high price until the sum of the winning response capacities of the winning load aggregators can meet the total response capacity of the current electricity market clearing demand. However, although some load aggregators bid low, they cannot accurately complete the response according to their winning response capacity after winning the bid. The final actual response capacity does not meet the planning and expectations of the electricity market clearing. This leads to insufficient reliability of electricity market clearing and poor grid stability. Moreover, since quotations are the main basis for winning bids in the electricity market clearing bidding process, load aggregators are generally not willing to optimize the demand response performance and improve the accuracy of demand response in the electricity market clearing process. In this context, the main purpose of this application is to propose a load aggregator response performance evaluation method and an electricity market clearing method, aiming to improve the reliability of electricity market clearing and grid stability, and to encourage load aggregators to optimize their demand response performance and improve the accuracy of their demand response in the electricity market clearing process.

[0065] Figure 1 This is a flow chart of a load aggregator response performance evaluation method provided in one embodiment of the present application. The execution subject of the method may be, for example, a computer or other device with computing and processing capabilities, but is not limited thereto. Figure 1 As shown, the method may include:

[0066] S101. After completing a demand response, determine the actual response capacity of the demand response according to the baseline load of the load aggregator and the actual measured load for the demand response.

[0067] For example, each electricity market clearing can be divided into multiple cycles according to a preset duration, such as a cycle every 10 minutes, a cycle every 15 minutes, a cycle every 20 minutes, etc. The load aggregators participating in this electricity market clearing can be deemed to have completed a demand response after participating in each cycle. For example, if a certain electricity market clearing lasts for 8 hours, it can be divided according to the preset duration of 15 minutes / cycle, that is, 4 cycles per hour, then the 8-hour electricity market clearing can be divided into a total of 32 cycles, and the load aggregators participating in this electricity market clearing are deemed to have completed 32 demand responses. Of course, the above content is only a possible example. The duration of electricity market clearing is not limited to 8 hours, and the duration of each cycle is not limited to 10 minutes, 15 minutes, 20 minutes, etc. The specific electricity market clearing division method can be adjusted and determined according to actual conditions, and is not limited to the above example. It can be understood that an electricity market clearing should at least include one cycle, that is, one demand response.

[0068] The baseline load of the load aggregator mentioned above can be determined, for example, based on the historical electricity consumption of users in the power supply area managed by the load aggregator, and the specific determination method is not limited here. The actual measured load for this demand response can be collected and obtained, for example, by measuring equipment such as electricity meters, sensors, and monitors, but is not limited thereto. The collection of the actual measured load for this demand response can be, for example, periodic, and the collection period of the actual measured load for this demand response can be, for example, consistent with the period divided by the above-mentioned electricity market clearing, that is, each electricity market clearing period, or each time a demand response is completed, the actual measured load for this demand response is collected once. Of course, the actual method of collecting the actual measured load for this demand response may be different from the above-mentioned example, and is not limited here.

[0069] The actual response capacity of the current demand response is determined based on the baseline load of the load aggregator and the actual measured load for the current demand response, for example, according to the following formula:

[0070]

[0071] The above i can represent the i-th load aggregator, which can be understood as the number, identification code, etc. of the load aggregator. Correspondingly, the above i For example, it can represent the actual response capacity of load aggregator i in this demand response. For example, the baseline load of the load aggregator i during this demand response can be represented by For example, it may represent the actual measured load of the load aggregator i for this demand response. Of course, the above is only one possible implementation method for determining the actual response capacity of this demand response based on the load aggregator's baseline load and the actual measured load for this demand response. The actual implementation method for determining the actual response capacity of this demand response based on the load aggregator's baseline load and the actual measured load for this demand response is not limited to the above example.

[0072] S102. Determine the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to this demand response.

[0073] For example, the winning response capacity corresponding to this demand response may refer to the target response capacity, or task capacity, that the load aggregator should achieve per cycle or per demand response, derived from the ultimately winning response capacity when participating in the electricity market clearing bidding. Determining the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to this demand response may, for example, refer to converting the effective response capacity of the load aggregator for this demand response by a certain proportional coefficient based on the achievement rate of the actual response capacity relative to the winning response capacity corresponding to this demand response. Determining the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to this demand response may, for example, refer to defining multiple capacity value ranges based on the winning response capacity corresponding to this demand response, presetting a corresponding effective response capacity for each capacity value range, and then determining the effective response capacity of the load aggregator for this demand response based on the capacity value range within which the actual response capacity falls.

[0074] Of course, the above content is only a possible example. How to determine the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to this demand response can be adjusted and determined according to actual conditions, and is not limited to any of the determination methods in the above examples.

[0075] S103. Determine the deviation factor of the current demand response based on the effective response capacity and the winning response capacity.

[0076] Exemplarily, the deviation factor of the current demand response is determined based on the effective response capacity and the winning response capacity, for example, by the following formula:

[0077]

[0078] Among them, the above δ i For example, the deviation factor of the current demand response of load aggregator i can be expressed as follows: For example, it can represent the effective response capacity of load aggregator i in this demand response. For example, it can represent the winning response capacity of load aggregator i in this demand response. Of course, the above content is only an example, and the actual method of determining the deviation factor of this demand response may be different from the above content.

[0079] S104. Determine the single response accuracy of the load aggregator for the current demand response based on the deviation factor.

[0080] Continuing with the above example, the above determination of the single response accuracy of the load aggregator for the current demand response based on the above deviation factor can be achieved, for example, by the following formula:

[0081]

[0082] Among them, the above For example, it can represent the single response accuracy of load aggregator i for the above-mentioned demand response.

[0083] S105: Determine the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator.

[0084] Exemplarily, the overall response accuracy of the load aggregator is determined based on the single response accuracy of each demand response of the load aggregator. For example, it can refer to calculating the average value of the single response accuracy of each demand response of the load aggregator as the overall response accuracy of the load aggregator, or according to a certain weight, for example, the closer the load aggregator is to the current demand response, the higher the weight is set, and the more distant the load aggregator is from the current demand response, the lower the weight is set, thereby determining the overall response accuracy of the load aggregator, etc. How to determine the overall response accuracy of the load aggregator can be freely adjusted and determined according to actual conditions, and is not limited to the two determination methods exemplified above.

[0085] The load aggregator response performance evaluation method provided in the embodiment of the present application includes: after completing a demand response, determining the actual response capacity of the above-mentioned demand response based on the baseline load of the load aggregator and the actual measured load for this demand response. Determine the effective response capacity of the above-mentioned load aggregator for this demand response based on the above-mentioned actual response capacity and the winning response capacity corresponding to the above-mentioned demand response. Determine the deviation factor of the above-mentioned demand response based on the above-mentioned effective response capacity and the above-mentioned winning response capacity. Determine the single response accuracy of the above-mentioned load aggregator for the above-mentioned demand response based on the above-mentioned deviation factor. Determine the overall response accuracy of the above-mentioned load aggregator based on the single response accuracy of each demand response of the above-mentioned load aggregator. The method obtains the load aggregator's baseline load and the actual measured load for this demand response, calculates the actual response capacity of the load aggregator for this demand response, and determines the load aggregator's effective response capacity for this demand response based on the above actual response capacity and the preset conditions based on the winning response capacity corresponding to this demand response. Then, based on the effective response capacity and the winning response capacity, the deviation factor of this demand response is calculated. The deviation factor can be used to reflect the degree of deviation between the effective response capacity and the winning response capacity. Finally, based on the deviation factor and the preset algorithm, the single response accuracy of the load aggregator for the above demand response is calculated, thereby realizing the calculation of the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator. The overall response accuracy can be used as an influencing factor for the winning bid of the corresponding load aggregator when participating in the electricity market clearing, thereby improving the reliability of the electricity market clearing and the stability of the power grid.

[0086] Figure 2 For a flow chart of a load aggregator response performance evaluation method provided in another embodiment of the present application, please refer to Figure 2 , optionally, in the above Figure 1 Based on the embodiment, determining the effective response capacity of the load aggregator for the current demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response may include:

[0087] S201. Determine multiple response intervals corresponding to the current demand response based on a preset lower limit ratio of effective response, a preset upper limit ratio of effective response, and the above-mentioned successful bid response capacity.

[0088] For example, the above-mentioned preset effective response lower limit ratio and the preset effective response upper limit ratio can be, for example, a proportional coefficient less than 1, that is, less than 100%, such as 80%, and a proportional coefficient greater than 1, that is, greater than 100%, such as 120%, etc., but are not limited to these. Assuming that the above-mentioned preset effective response lower limit ratio is μ low, the above preset effective response upper limit ratio is μ up , then according to the preset effective response lower limit ratio, the preset effective response upper limit ratio and the above-mentioned winning response capacity, the multiple response intervals corresponding to the above-mentioned demand response can be determined as follows: ② ③ Of course, the above content is only a possible example. The actual preset lower limit ratio of effective response, the preset upper limit ratio of effective response, the actual number of intervals of multiple response intervals corresponding to this demand response, etc. can be the same as or different from the above content, and are not limited here.

[0089] S202: Determine, based on the actual response capacity, a target response interval in which the actual response capacity is located from the multiple response intervals, and determine a response type corresponding to the target response interval as a target response type.

[0090] Continuing with the content in the above example, the above target response types may include but are not limited to invalid responses, valid responses, etc., wherein the valid responses may be further divided into first valid responses, second valid responses, etc., and are not specifically limited here. It can be understood that the number of types of the above target response types will not exceed the number of the above response intervals. Taking the above-mentioned multiple response intervals corresponding to this demand response as divided into 3 response intervals as an example, the response types corresponding to the response intervals are at most 3 response types, that is, the above target response type is at most one of the above 3 response types.

[0091] S203. Determine the effective response capacity according to the target response type.

[0092] Exemplarily, based on the above-mentioned target response type, a corresponding effective response capacity algorithm can be preset. For example, for an invalid response, the corresponding effective response capacity algorithm is to directly record it as 0. That is, if the target response type corresponding to the target response interval where the actual response capacity is located is an invalid response, the effective response capacity of the above-mentioned load aggregator for this demand response is 0. For another example, for an effective response, the corresponding effective response capacity algorithm is to directly record it as the actual response capacity, or to convert the actual response capacity according to a certain ratio and coefficient to obtain the effective response capacity, etc. Of course, the actual effective response capacity determination method may also be different from the above-mentioned examples and is not limited to the above-mentioned content.

[0093] The load aggregator response performance evaluation method provided in the embodiment of the present application includes: determining the multiple response intervals corresponding to the above-mentioned demand response according to a preset lower limit ratio of effective response, a preset upper limit ratio of effective response and the above-mentioned winning response capacity. According to the above-mentioned actual response capacity, the target response interval where the above-mentioned actual response capacity is located is determined from the above-mentioned multiple response intervals, and the response type corresponding to the above-mentioned target response interval is determined as the target response type. According to the above-mentioned target response type, the above-mentioned effective response capacity is determined. This method delineates multiple response intervals by presetting the lower limit ratio of effective response, the preset upper limit ratio of effective response and the above-mentioned winning response capacity, and matches different response types and effective response capacity algorithms corresponding to the response types to each response interval, thereby realizing the determination of the effective response capacity of the above-mentioned load aggregator for this demand response according to the target response interval where the actual response capacity is located, thereby avoiding the actual response capacity that differs too much from the target response capacity from directly participating in the calculation of the deviation factor, etc., and reducing the interference of abnormal values ​​on the calculation of the deviation factor, etc.

[0094] Further, based on the above embodiment, the multiple response intervals corresponding to the above demand response are ① ② ③ Taking the target response types including the invalid response type, the first valid response type, and the second valid response type as an example, multiple response intervals and corresponding response types can be obtained as shown in Table 1 below:

[0095]

[0096] Table 1 Examples of multiple response intervals and corresponding response types

[0097] Please refer to Table 1 above. For example, the target response interval where the actual response capacity is located can be as follows: In this case, the corresponding response type is an invalid response type. For example, the target response interval where the actual response capacity is located can be the above ② In this case, the corresponding response type is the first valid response type. For example, the target response interval where the actual response capacity is located can be the above ③ In this case, the corresponding response type is the second valid response type.

[0098] On this basis, determining the effective response capacity according to the target response type may include, for example:

[0099] If the target response type is an invalid response type, the valid response capacity is determined to be zero.

[0100] If the target response type is the first effective response type, the effective response capacity is determined according to the actual response capacity.

[0101] If the target response type is the second effective response type, the effective response capacity is determined based on the winning response capacity and a preset effective response capacity penalty factor.

[0102] That is, the effective response capacity algorithm corresponding to the invalid response type is directly recorded as 0, the effective response capacity algorithm corresponding to the first valid response type is directly recorded as the actual response capacity, and the effective response capacity algorithm corresponding to the second valid response type is effective response capacity = the product of the winning response capacity and the preset effective response capacity penalty factor. In this way, the effective response capacity determination method shown in Table 2 below can be formed:

[0103]

[0104] Table 2 Examples of methods for determining effective response capacity

[0105] Please refer to Table 2, the above k eff For example, it may represent the above-mentioned preset effective response capacity penalty factor, and the preset effective response capacity penalty factor may be calibrated according to actual conditions, for example, it may be 120%, but is not limited thereto.

[0106] Figure 3 A flow chart of a load aggregator response performance evaluation method provided in another embodiment of the present application is provided. Optionally, as Figure 3 As shown in the above Figure 1 Based on the embodiment, determining the single response accuracy of the load aggregator for the current demand response based on the deviation factor may include:

[0107] S301. Determine whether the load aggregator is participating in market clearing for the first time based on the total number of times the load aggregator has participated in market clearing.

[0108] For example, if the load aggregator participates in market clearing for the first time, that is, the load aggregator has never completed a demand response before participating in this market clearing, then it is impossible to determine the deviation factor of the above-mentioned demand response based on the effective response capacity and the winning response capacity after the load aggregator completes a demand response, and then determine the single response accuracy of the above-mentioned load aggregator for the above-mentioned demand response based on the above-mentioned deviation factor.

[0109] S302: If the load aggregator is participating in market clearing for the first time, a preset lower limit of the initial response performance is determined as the above-mentioned single response accuracy.

[0110] Based on the above situation, an initial performance lower limit S can be preset for this type of load aggregator. acc,min , as the first single response accuracy of this type of load aggregator, the initial performance lower limit S acc,min The specific value of can be calibrated and adjusted according to actual conditions and is not limited here.

[0111] S303. If the load aggregator is not participating in market clearing for the first time, the single response accuracy is determined based on the deviation factor and the preset lower limit of the initial response performance.

[0112] Continuing with the example above, as the number of demand responses completed by the load aggregator increases, the single response accuracy of the load aggregator for each demand response can be determined, for example, by the following formula:

[0113]

[0114] Wherein, the above n may represent the total number of times that load aggregator i completes demand response, and the above max(S acc,min ,(1-δ i )) For example, it can represent the selection of S acc,min and (1-δ i 0 is the largest value among the two values. For example, the above formula can be expressed as follows: when load aggregator i has never completed demand response, the first single response accuracy of the load aggregator is S acc,min , when load aggregator i has completed at least one demand response, the deviation factor of the current demand response of load aggregator i can be determined, and then the single response accuracy of the current demand response of load aggregator i can be calculated. When the calculated single response accuracy of the current demand response of load aggregator i is less than the above initial performance lower limit S acc,min When the load aggregator i's single response accuracy of this demand response is still recorded as S acc,min , when the calculated single response accuracy of the load aggregator i for this demand response is greater than the above initial performance lower limit S acc,min When the load aggregator i's single response accuracy of this demand response is recorded as (1-δ i ).

[0115] The above formula for determining the single response accuracy of each demand response of the load aggregator takes into account the situation that the load aggregator has never completed demand response before participating in this market clearing, and sets an initial performance lower limit S for such load aggregators. acc,min , the initial performance lower limit S acc,min In addition to the first single response accuracy of the load aggregator, it can also be calculated after the load aggregator completes the demand response due to the deviation factor δ iThe value of is too large, resulting in (1-δ i ) calculated single response accuracy of the load aggregator i When the abnormality is low, the initial performance lower limit S acc,min Replace (1-δ i ) as the load aggregator's single response accuracy for this demand response, to prevent the single response accuracy of this demand response from having too much impact on the overall response accuracy of subsequent load aggregators.

[0116] The load aggregator response performance evaluation method provided in an embodiment of the present application includes: determining whether the load aggregator is a first-time market clearer based on the total number of times the load aggregator has participated in market clearing. If the load aggregator is a first-time market clearer, determining a preset initial response performance lower limit as the single response accuracy. If the load aggregator is not a first-time market clearer, determining the single response accuracy based on the deviation factor and the preset initial response performance lower limit. This method determines whether the load aggregator is a first-time market clearer based on the total number of times the load aggregator has participated in market clearing. This method uses different methods to determine the single response accuracy for first-time market clearers and non-first-time market clearers, thereby preventing first-time market clearers from having no single response accuracy for evaluation. It also prevents the single response accuracy of a particular demand response from significantly influencing the overall response accuracy of subsequent load aggregators, thereby improving the efficiency and reliability of determining data such as the single response accuracy and overall response accuracy of the load aggregator.

[0117] Figure 4 This is a flow chart of a load aggregator response performance evaluation method provided by another embodiment of the present application. Further, please refer to Figure 4 , in the aforementioned Figure 1 Based on the embodiment, determining the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator may include:

[0118] S401. Determine the recent response accuracy index of the load aggregator in the preset time window based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current demand response corresponding to the current clearing moment.

[0119] Illustratively, the preset time window may be used for sliding collection of demand responses according to time, and the length of the preset time window may represent, for example, the number of demand responses of a preset length in a certain area or range. For example, if the length of the preset time window is 10, then the single response accuracy of the multiple demand responses of the load aggregator within the preset time window before the current demand response corresponds to the current clearing moment may refer to the single response accuracy of the multiple demand responses of the load aggregator in the 10 demand responses before the current demand response corresponds to the current clearing moment. That is, the number of demand responses slidingly collected in the preset time window is not for a specific load aggregator, but for a certain area or range. If a load aggregator has participated in 5 demand responses in the 10 demand responses, then the single response accuracy of the multiple demand responses of the load aggregator in the 10 demand responses before the current demand response corresponds to the current clearing moment may refer to the single response accuracy of 5 demand responses of the load aggregator in the 10 demand responses before the current demand response corresponds to the current clearing moment. Of course, the above content is only a possible example. The actual length of the preset time window is not limited to 10 times, and can be selected and determined according to actual conditions. It can be understood that the maximum number of demand responses participated by a specific load aggregator within the preset time window may be that all demand responses within the preset time window have been participated in (that is, the load aggregator's multiple demand responses within the preset time window before the above-mentioned demand response corresponds to the current clearing moment = the length of the preset time window), and the minimum number of demand responses within the preset time window may be that no demand response has been participated in (that is, the load aggregator's multiple demand responses within the preset time window before the above-mentioned demand response corresponds to the current clearing moment = 0). The specific details should be based on actual conditions.

[0120] The recent response accuracy index of the load aggregator in the preset time window is determined based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current demand response corresponding to the current clearing time. For example, it can be determined by the following formula:

[0121]

[0122] Among them, the above For example, it can represent the above-mentioned recent response accuracy index (i.e., recent response accuracy), and the above-mentioned m can represent the length of the above-mentioned preset time window, so the above-mentioned For example, it can represent the recent response accuracy index of the load aggregator in the preset time window (length is m), and the above j can represent the number of demand responses, that is, it means that this demand response is the jth demand response of the load aggregator i in the preset time window. i,jFor example, it can represent the weighted comprehensive index corresponding to the jth demand response of load aggregator i within a preset time window, which can be used to ensure that the more recent demand response is used in calculating the above-mentioned recent response accuracy index. The greater the impact, the W i,j It can be determined according to actual conditions and is not specifically limited here.

[0123] S402: Determine the historical response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator.

[0124] Exemplarily, the historical response accuracy of the load aggregator is determined based on the single response accuracy of each demand response of the load aggregator, for example, by the following formula:

[0125]

[0126] Among them, the above For example, it can be expressed as: the historical response accuracy of load aggregator i determined based on the total number of completed demand responses n times by load aggregator i, that is, the historical response accuracy of the load aggregator mentioned above, if omitted as: The meaning of the latter can remain unchanged. It can represent the single response accuracy of the demand response completed by the load aggregator i for the kth time. It can be understood that 1≤k≤n.

[0127] S403: Determine the overall response accuracy of the load aggregator based on the recent response accuracy index within the preset time window and the historical response accuracy.

[0128] Exemplarily, determining the overall response accuracy of the load aggregator based on the recent response accuracy index within the preset time window and the historical response accuracy may refer to determining the overall response accuracy of the load aggregator based on a weighted approach of the recent response accuracy index within the preset time window and the historical response accuracy, such as the following formula:

[0129]

[0130] Among them, the above For example, it can represent the overall response accuracy of load aggregator i based on the total number of times n that load aggregator i completes demand response. If it is omitted, The meaning of the latter may remain unchanged. For example, the above α may represent the weight of the historical response accuracy, and (1-α) may represent the weight of the recent response accuracy in the above preset time window.

[0131] The load aggregator response performance evaluation method provided in the embodiment of the present application includes: determining the recent response accuracy index of the load aggregator in the preset time window based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current clearing moment of the current demand response. Determine the historical response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator. Determine the overall response accuracy of the load aggregator based on the recent response accuracy index in the preset time window and the historical response accuracy. This method calculates the recent response accuracy and historical response accuracy of the load aggregator separately, and realizes the joint determination of the overall response accuracy of the load aggregator by weighting the recent response accuracy and the historical response accuracy, thereby avoiding the problem that the use of historical response accuracy alone is difficult to well reflect the changes in the recent demand response of the load aggregator.

[0132] Further, based on the above embodiment, the determination of the recent response accuracy index of the load aggregator in the preset time window based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current demand response corresponding to the current clearing time may include:

[0133] Based on the number of times the above-mentioned load aggregator participates in market clearing within the above-mentioned preset time window and the preset time discount factor, the response impact weight of each demand response within the above-mentioned preset time window on the above-mentioned demand response is determined.

[0134] The recent response accuracy index is determined based on the response impact weights of the above-mentioned each demand response on the above-mentioned current demand response, and the single response accuracy of the above-mentioned multiple demand responses within the above-mentioned preset time window.

[0135] Exemplarily, the above-mentioned determination of the response influence weight of each demand response within the preset time window on the above-mentioned demand response is based on the number of times the above-mentioned load aggregator participates in the market clearing within the above-mentioned preset time window and the preset time discount factor. For example, it can refer to determining the weighted comprehensive index of the aforementioned embodiment. The response influence weight of each demand response within the above-mentioned preset time window on the above-mentioned demand response, that is, the weighted comprehensive index, can be determined, for example, by the following formula:

[0136]

[0137] Among them, the above M i For example, it can represent the number of times that the load aggregator i completes the demand response within the above-mentioned preset time window. The above-mentioned γ can represent the above-mentioned preset time discount factor, which can be selected and determined according to the actual situation. It can be understood that the above-mentioned W i,jThe method for determining is not limited to the formula in the above example, and can also be determined by any other reasonable method.

[0138] On this basis, combined with the above embodiments, The formula can be used to determine the recent response accuracy index based on the response influence weights of the above-mentioned demand responses on the above-mentioned current demand response and the single response accuracy of the above-mentioned multiple demand responses within the above-mentioned preset time window.

[0139] In addition, based on the technology of any of the above embodiments, the above method may further include:

[0140] The initial response impact factor is determined based on the total number of times the load aggregator completes demand response and the preset initial number threshold.

[0141] According to the initial response influencing factor, the overall response accuracy of the load aggregator is adjusted to obtain the final response accuracy of the load aggregator after adjustment.

[0142] Exemplarily, the determination of the initial response impact factor based on the total number of demand responses completed by the load aggregator and the preset initial number threshold may be achieved, for example, by the following formula:

[0143]

[0144] For example, the above η i For example, it can be expressed as the initial response impact factor applicable to load aggregator i. The above n lim For example, it can represent the above-mentioned preset initial number threshold. Of course, the above-mentioned formula for determining the initial response impact factor is only a possible example, and the actual method for determining the initial response impact factor is not limited to the above-mentioned formula.

[0145] On this basis, the overall response accuracy of the load aggregator is adjusted according to the initial response influencing factor to obtain the final response accuracy of the load aggregator after adjustment, which can be achieved, for example, by the following formula:

[0146]

[0147] Among them, the above For example, it can represent the final response accuracy of load aggregator i. Similar to the above embodiment, the above (n) can represent the final response accuracy of load aggregator i. It is also based on the total number of times n that load aggregator i completes demand response. If omitted, Of course, the specific method for obtaining the final response accuracy of the load aggregator can be determined based on actual conditions and is not limited to the content in the above example.

[0148] Figure 5 This is a flow chart of a method for clearing the electricity market provided in one embodiment of the present application. This method can be implemented based on the overall response accuracy of the load aggregator or the final response accuracy of the load aggregator determined by the load aggregator response performance evaluation method in the above embodiment. Please refer to Figure 5 , the method may include:

[0149] S501. Obtain the estimated actual response capacity of each of the multiple load aggregators participating in the bidding process based on the declared response capacities and the response accuracy of each load aggregator. The response accuracy of each load aggregator may be the overall response accuracy of the load aggregator calculated using the method described in any of the preceding embodiments, or the final response accuracy of the load aggregator calculated using the method described in any of the preceding embodiments.

[0150] Exemplarily, the above-mentioned method of obtaining the estimated actual response capacity of the multiple load aggregators based on the declared response capacity of the multiple load aggregators participating in the bidding and the response accuracy of each load aggregator can be implemented, for example, by the following formula:

[0151]

[0152] Among them, the above For example, the expected actual response capacity of load aggregator i can be expressed as follows: For example, the reported response capacity of load aggregator i can be expressed as follows: is the final response accuracy of load aggregator i, which can be replaced by the above That is, the overall response accuracy of load aggregator i.

[0153] On this basis, the minimum load aggregator declared cost can be obtained as:

[0154]

[0155] The above N can represent the total number of load aggregators participating in the bidding, for example. For example, it can represent the winning bid price of a load aggregator.

[0156] S502: Determine reliability constraints based on a preset allowable deviation threshold, the declared response capacities of the plurality of load aggregators, and the estimated actual response capacities.

[0157] For example, the above reliability constraint condition can be expressed as:

[0158]

[0159] The above θ may represent, for example, the preset allowable deviation threshold. This preset allowable deviation threshold may be calibrated based on actual conditions, for example, 15%, and is not limited here. Of course, the above content is only one possible reliability constraint condition, and actual reliability constraints may include other content, which is not limited here.

[0160] S503: Determine whether the capacity satisfies the constraint condition based on the preset total clearing capacity and the estimated actual response capacity of the plurality of load aggregators.

[0161] For example, the capacity satisfying the constraint condition can be expressed as:

[0162]

[0163] Among them, the above Q goal For example, the above-mentioned preset total clearing capacity can be represented. The preset total clearing capacity can be calibrated according to actual conditions and is not limited here. Of course, the above content is only one possible capacity constraint condition. The actual capacity constraint condition can also include other contents, which are not limited here.

[0164] S504: Execute power market clearing operations for the multiple load aggregators based on the reliability constraints and the capacity satisfaction constraints.

[0165] According to the above reliability constraints and the above capacity satisfaction constraints, executing the electricity market clearing operation for the above multiple load aggregators can ensure that the load aggregator selected from the above multiple load aggregators in this electricity market clearing operation is more reliable.

[0166] The electricity market clearing method provided in the embodiment of the present application includes: obtaining the estimated actual response capacity of the multiple load aggregators respectively according to the declared response capacity of the multiple load aggregators participating in the bidding and the response accuracy of each load aggregator. The response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the above method of any one of the above embodiments, or the final response accuracy of the load aggregator calculated according to the above method of the above embodiment. According to the preset allowable deviation threshold and the declared response capacity and the estimated actual response capacity of the above multiple load aggregators, the reliability constraint condition is determined. According to the preset total clearing capacity and the estimated actual response capacity of the above multiple load aggregators, it is determined that the capacity satisfies the constraint condition. According to the above reliability constraint condition and the above capacity satisfaction constraint condition, the electricity market clearing operation for the above multiple load aggregators is performed. This method obtains the load aggregator's estimated actual response capacity through the load aggregator's response accuracy calculation, and determines the reliability constraints and capacity satisfaction constraints based on this. After determining the reliability constraints and capacity satisfaction constraints, the load aggregator with the minimum cost is selected as the winning bidder, thus avoiding the selection of the winning load aggregator solely from the perspective of cost and quotation, and improving the reliability of power market clearing and grid stability.

[0167] Figure 6 This is a structural diagram of a load aggregator response performance evaluation device provided in an embodiment of the present application. The load aggregator response performance evaluation device can execute the above-mentioned load aggregator response performance evaluation method. The device can be integrated into a device with computing and processing functions such as the above-mentioned computer, such as Figure 6 As shown, the device may include:

[0168] Capacity determination module 610 is configured to, after a demand response is completed, determine the actual response capacity of the current demand response based on the load aggregator's baseline load and the actual measured load for the current demand response. Based on the actual response capacity and the winning response capacity corresponding to the current demand response, the load aggregator's effective response capacity for the current demand response is determined.

[0169] The deviation determination module 620 is used to determine the deviation factor of the current demand response according to the effective response capacity and the winning response capacity.

[0170] The accuracy determination module 630 is configured to determine the accuracy of the load aggregator's single response to the current demand response based on the deviation factor, and to determine the overall response accuracy of the load aggregator based on the accuracy of each demand response of the load aggregator.

[0171] The load aggregator response performance evaluation method provided in the embodiment of the present application includes: after completing a demand response, determining the actual response capacity of the above-mentioned demand response based on the baseline load of the load aggregator and the actual measured load for this demand response. Determine the effective response capacity of the above-mentioned load aggregator for this demand response based on the above-mentioned actual response capacity and the winning response capacity corresponding to the above-mentioned demand response. Determine the deviation factor of the above-mentioned demand response based on the above-mentioned effective response capacity and the above-mentioned winning response capacity. Determine the single response accuracy of the above-mentioned load aggregator for the above-mentioned demand response based on the above-mentioned deviation factor. Determine the overall response accuracy of the above-mentioned load aggregator based on the single response accuracy of each demand response of the above-mentioned load aggregator. The method obtains the load aggregator's baseline load and the actual measured load for this demand response, calculates the actual response capacity of the load aggregator for this demand response, and determines the load aggregator's effective response capacity for this demand response based on the above actual response capacity and the preset conditions based on the winning response capacity corresponding to this demand response. Then, based on the effective response capacity and the winning response capacity, the deviation factor of this demand response is calculated. The deviation factor can be used to reflect the degree of deviation between the effective response capacity and the winning response capacity. Finally, based on the deviation factor and the preset algorithm, the single response accuracy of the load aggregator for the above demand response is calculated, thereby realizing the calculation of the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator. The overall response accuracy can be used as an influencing factor for the winning bid of the corresponding load aggregator when participating in the electricity market clearing, thereby improving the reliability of the electricity market clearing and the stability of the power grid.

[0172] Optionally, the capacity determination module 610 is specifically configured to determine multiple response intervals corresponding to the current demand response based on a preset lower effective response limit ratio, a preset upper effective response limit ratio, and the winning response capacity. Based on the actual response capacity, a target response interval within which the actual response capacity falls is determined from the multiple response intervals, and the response type corresponding to the target response interval is determined as the target response type. Based on the target response type, the effective response capacity is determined.

[0173] Optionally, the capacity determination module 610 is specifically configured to determine the effective response capacity as zero if the target response type is an invalid response type; determine the effective response capacity based on the actual response capacity if the target response type is a first valid response type; and determine the effective response capacity based on the winning response capacity and a preset effective response capacity penalty factor if the target response type is a second valid response type.

[0174] Optionally, the accuracy determination module 630 is specifically configured to determine whether the load aggregator is participating in market clearing for the first time based on the total number of times the load aggregator has participated in market clearing. If the load aggregator is participating in market clearing for the first time, a preset lower limit of initial response performance is determined as the single response accuracy. If the load aggregator is not participating in market clearing for the first time, the single response accuracy is determined based on the deviation factor and the preset lower limit of initial response performance.

[0175] Optionally, the accuracy determination module 630 is specifically configured to determine a recent response accuracy index of the load aggregator within a preset time window based on the single response accuracy of multiple demand responses of the load aggregator within a preset time window before the current clearing moment of the current demand response. The historical response accuracy of the load aggregator for the current demand response is determined based on the single response accuracy of the current demand response and the combined response accuracy of the single response accuracy of all historical demand responses for each demand response of the load aggregator. The overall response accuracy of the load aggregator for the current demand response is determined based on the recent response accuracy index within the preset time window and the historical response accuracy for the current demand response.

[0176] Optionally, the accuracy determination module 630 is specifically configured to determine the response impact weight of each demand response within the preset time window on the current demand response based on the number of times the load aggregator participates in market clearing within the preset time window and a preset time discount factor. The recent response accuracy index is determined based on the response impact weight of each demand response on the current demand response and the accuracy of each of the multiple demand responses within the preset time window.

[0177] Optionally, the accuracy determination module 630 may also be configured to determine an initial response impact factor based on the total number of market clearings of the total number of demand responses completed by the load aggregator and a preset initial number threshold. Based on the initial response impact factor, the overall response accuracy of the load aggregator for the current demand response is adjusted to obtain a final response accuracy of the load aggregator for the current demand response.

[0178] The above-mentioned device is used to execute the method provided in the above-mentioned embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0179] Figure 7 The embodiment of the present application provides a power market clearing device, which can execute the above-mentioned power market clearing method. The device can be integrated into the above-mentioned computer or other equipment with computing and processing functions, such as Figure 7As shown, the device includes:

[0180] Acquisition module 710 is configured to acquire the estimated actual response capacity of each of the multiple load aggregators participating in the bidding based on the declared response capacities and the response accuracy of each load aggregator. The response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the method of any one of claims 1-6, or the final response accuracy of the load aggregator calculated according to the method of claim 7.

[0181] The constraint module 720 is configured to determine a reliability constraint condition based on a preset allowable deviation threshold and the estimated actual response capacities of the plurality of load aggregators, and to determine whether the capacity satisfies the constraint condition based on a preset total clearing capacity and the estimated actual response capacities of the plurality of load aggregators.

[0182] The clearing module 730 is configured to execute a power market clearing operation for the plurality of load aggregators according to the reliability constraint and the capacity satisfaction constraint.

[0183] The electricity market clearing method provided in the embodiment of the present application includes: obtaining the estimated actual response capacity of the multiple load aggregators respectively according to the declared response capacity of the multiple load aggregators participating in the bidding and the response accuracy of each load aggregator. The response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the above method of any one of the above embodiments, or the final response accuracy of the load aggregator calculated according to the above method of the above embodiment. According to the preset allowable deviation threshold and the declared response capacity and the estimated actual response capacity of the above multiple load aggregators, the reliability constraint condition is determined. According to the preset total clearing capacity and the estimated actual response capacity of the above multiple load aggregators, it is determined that the capacity satisfies the constraint condition. According to the above reliability constraint condition and the above capacity satisfaction constraint condition, the electricity market clearing operation for the above multiple load aggregators is performed. This method obtains the load aggregator's estimated actual response capacity through the load aggregator's response accuracy calculation, and determines the reliability constraints and capacity satisfaction constraints based on this. After determining the reliability constraints and capacity satisfaction constraints, the load aggregator with the minimum cost is selected as the winning bidder, thus avoiding the selection of the winning load aggregator solely from the perspective of cost and quotation, and improving the reliability of power market clearing and grid stability.

[0184] The above-mentioned device is used to execute the method provided in the above-mentioned embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0185] Figure 8This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may be a device with computing and processing functions such as the above-mentioned computer, server, etc. Figure 8 As shown, the device 800 includes:

[0186] Processor 810 , storage medium 820 and bus 830 . The processor 810 and storage medium 820 are communicatively connected via the bus 830 .

[0187] The storage medium 820 stores machine-readable instructions executable by the processor 810. When the electronic device is running, the processor 810 executes the above-mentioned machine-readable instructions to execute the above-mentioned load aggregator response performance evaluation method or electricity market clearing method.

[0188] It should be understood that Figure 8 The structure shown is only a schematic diagram of the structure of the electronic device. The electronic device may also include Figure 8 More or fewer components than shown, or with Figure 8 Different configurations shown. Figure 8 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0189] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program can be executed by a processor, it can implement the load aggregator response performance evaluation method or electricity market clearing method described in the above method embodiment.

[0190] The computer-readable storage medium can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium has storage space for program codes that execute any of the method steps of the above method. These program codes can be read from or written into one or more computer program products. The program code can be compressed, for example, in an appropriate form.

[0191] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a portion of code, and the module, program segment, or a portion of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0192] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0193] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0194] The above description is only a preferred embodiment of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application description and drawings under the inventive concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for evaluating the response performance of a load aggregator, characterized in that: include: After completing a demand response, determining the actual response capacity of the demand response according to the baseline load of the load aggregator and the actual measured load for the demand response; determining the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response; Determining a deviation factor for the current demand response based on the effective response capacity and the winning response capacity; determining, based on the deviation factor, a single response accuracy of the load aggregator for the current demand response; The overall response accuracy of the load aggregator is determined according to the single response accuracy of each demand response of the load aggregator.

2. The method according to claim 1, characterized in that Determining the effective response capacity of the load aggregator for the current demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response includes: Determining multiple response intervals corresponding to the current demand response according to a preset lower limit ratio of effective responses, a preset upper limit ratio of effective responses, and the winning response capacity; determining, according to the actual response capacity, a target response interval in which the actual response capacity is located from the multiple response intervals, and determining a response type corresponding to the target response interval as a target response type; The effective response capacity is determined according to the target response type.

3. The method according to claim 2, characterized in that The determining the effective response capacity according to the target response type includes: If the target response type is an invalid response type, determining the valid response capacity to be zero; If the target response type is a first effective response type, determining the effective response capacity according to the actual response capacity; If the target response type is the second effective response type, the effective response capacity is determined according to the winning response capacity and a preset effective response capacity penalty factor.

4. The method according to claim 1, wherein Determining the single response accuracy of the load aggregator for the current demand response based on the deviation factor includes: determining whether the load aggregator is participating in market clearing for the first time based on the total number of times the load aggregator has participated in market clearing; If it is a load aggregator participating in market clearing for the first time, a preset lower limit of initial response performance is determined as the single response accuracy; If the load aggregator is not participating in market clearing for the first time, the single response accuracy is determined based on the deviation factor and the preset initial response performance lower limit.

5. The method according to claim 1, wherein Determining the overall response accuracy of the load aggregator based on the single response accuracy of each demand response of the load aggregator includes: Determining a recent response accuracy index of the load aggregator within the preset time window based on the single response accuracy of multiple demand responses of the load aggregator within the preset time window before the current clearing moment of the current demand response; determining a historical response accuracy of the load aggregator based on a single response accuracy of each demand response of the load aggregator; The overall response accuracy of the load aggregator is determined according to the recent response accuracy index within the preset time window and the historical response accuracy.

6. The method according to claim 5, characterized in that Determining the recent response accuracy index of the load aggregator in the preset time window based on the single response accuracy of multiple demand responses of the load aggregator in the preset time window before the current clearing moment of the current demand response includes: Determining, based on the number of times the load aggregator participates in market clearing within the preset time window and a preset time discount factor, a response influence weight of each demand response within the preset time window on the current demand response; The recent response accuracy index is determined according to the response influence weight of each demand response on the current demand response and the single response accuracy of the multiple demand responses within the preset time window.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: determining an initial response impact factor based on a total number of demand responses completed by the load aggregator and a preset initial number threshold; The overall response accuracy of the load aggregator is adjusted according to the initial response impact factor to obtain the final response accuracy of the load aggregator after adjustment.

8. A method for clearing electricity market, characterized in that: include: Obtaining, based on the declared response capacities of multiple load aggregators participating in the bidding and the response accuracy of each load aggregator, the estimated actual response capacities of each of the multiple load aggregators; wherein the response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the method of any one of claims 1 to 6, or the final response accuracy of the load aggregator calculated according to the method of claim 7; determining a reliability constraint condition according to a preset allowable deviation threshold and the declared response capacities and the estimated actual response capacities of the plurality of load aggregators; Determining that capacity satisfies a constraint condition based on a preset total clearing capacity and the estimated actual response capacities of the plurality of load aggregators; An electricity market clearing operation is performed for the plurality of load aggregators according to the reliability constraint and the capacity satisfaction constraint.

9. A load aggregator response performance evaluation device, characterized in that: include: A capacity determination module is configured to determine, after completing a demand response, an actual response capacity of the demand response according to a baseline load of a load aggregator and an actual measured load for the demand response; determining the effective response capacity of the load aggregator for this demand response based on the actual response capacity and the winning response capacity corresponding to the current demand response; a deviation determination module, configured to determine a deviation factor of the current demand response according to the effective response capacity and the winning response capacity; an accuracy determination module, configured to determine the accuracy of a single response of the load aggregator to the current demand response based on the deviation factor; The overall response accuracy of the load aggregator is determined according to the single response accuracy of each demand response of the load aggregator.

10. An electricity market clearing device, characterized in that: include: an acquisition module, configured to respectively acquire the estimated actual response capacity of the multiple load aggregators participating in the bidding based on the declared response capacities of the multiple load aggregators and the response accuracy of each load aggregator; wherein the response accuracy of each load aggregator is the overall response accuracy of the load aggregator calculated according to the method of any one of claims 1 to 6, or the final response accuracy of the load aggregator calculated according to the method of claim 7; a constraint module, configured to determine a reliability constraint condition based on a preset allowable deviation threshold and the estimated actual response capacities of the plurality of load aggregators; and determine whether the capacity satisfies the constraint condition based on a preset total clearing capacity and the estimated actual response capacities of the plurality of load aggregators; A clearing module is used to perform a power market clearing operation for the multiple load aggregators according to the reliability constraint condition and the capacity satisfaction constraint condition.

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