A method for aggregating distributed energy storage to participate in system peak shaving demand response

Abstract

The application discloses a kind of distributed energy storage participates system peak shaving demand response aggregation method, for the different types of distributed energy storage resources such as vehicle-mounted energy storage, net side distributed energy storage, user side energy storage and the differentiated characteristics that they have, hierarchical partition aggregation topology is used, aggregator is set between demand response implementation agency and distributed energy storage equipment, different types of distributed energy storage resources are classified and aggregated, and an effective technical means is provided for distributed energy storage resources facing power grid demand to participate in power grid system peak shaving demand response;For the randomness of electric vehicle aggregation potential in time and scale, a device response urgency sorting method is proposed to ensure the reliability of vehicle-mounted energy storage group aggregation resources in time sequence and scale.

Description

Technical Field

[0001] This invention relates to the field of electrical engineering technology, and more specifically to a method for integrating distributed energy storage with system peak-shaving demand response. Background Technology

[0002] With the transformation of the power grid, the development of energy storage will overcome the traditional supply and demand contradictions in electricity across time and space. However, given the still relatively high cost of energy storage, aggregating existing energy storage resources to meet grid demand is a feasible technical approach. In recent years, with the economic advancements of various energy storage technologies, distributed energy storage resources, represented by electric vehicles, user-side energy storage, and grid-side distributed energy storage, have developed rapidly. Distributed energy storage resources are characterized by small individual capacity, unstable aggregation potential, wide spatial distribution, and large aggregation capacity, which limits their application to the power grid. Among existing technologies, the concept of multi-point wide-area aggregation based on energy internet technology is attracting increasing attention, providing an effective technical approach for the application of distributed energy storage resources to the power grid. Summary of the Invention

[0003] This invention primarily addresses the limitations of distributed energy storage resources in grid applications due to their characteristics such as small individual capacity, unstable aggregation potential, wide spatial distribution, and large aggregation capacity. It provides an aggregation method for distributed energy storage to participate in grid peak-shaving demand response. Considering the differentiated characteristics of various types of distributed energy storage resources, including vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage, a hierarchical and partitioned aggregation topology is adopted. Aggregators are set up between the demand response implementation agency and the distributed energy storage devices to classify and aggregate different types of distributed energy storage resources. This provides an effective technical means for distributed energy storage resources to participate in grid peak-shaving demand response. Furthermore, to address the temporal and scale-related randomness of the aggregation potential of electric vehicles, a device response urgency ranking method is proposed to ensure the reliability of vehicle-mounted energy storage group aggregation resources in terms of timing and scale.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] An aggregation method for distributed energy storage to participate in system peak-shaving demand response employs a hierarchical and partitioned aggregation topology, setting up aggregators between demand response implementation agencies and distributed energy storage devices to achieve classified aggregation, including the following steps:

[0006] Step S1: The aggregator signs a contract with the equipment users under its jurisdiction;

[0007] Step S2: Device users under the aggregator report basic data related to the aggregation potential for the next day;

[0008] Step S3: Aggregators calculate aggregation potential and report demand response time, capacity, and price;

[0009] Step S4: Real-time aggregation control by aggregators;

[0010] This invention aims to aggregate distributed energy storage resources, including on-board energy storage for electric vehicles, grid-side distributed energy storage, and user-side energy storage, to participate in peak-shaving demand response of the power grid. It proposes an aggregation method for distributed energy storage to participate in peak-shaving demand response. Addressing the differentiated characteristics of various types of distributed energy storage resources, a hierarchical and partitioned aggregation topology is adopted. A resource aggregator role is established between the demand response implementation agency and the distributed energy storage equipment to classify and aggregate different types of distributed energy storage resources. Furthermore, considering the stochastic nature of the aggregation potential of electric vehicles in terms of time and scale, a method for prioritizing equipment response urgency is proposed to ensure the reliability of the aggregated resources of the on-board energy storage group in terms of time and scale.

[0011] Preferably, the distributed energy storage includes, but is not limited to, vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage. A hierarchical, partitioned, and aggregated topology is adopted to address the differentiated characteristics of different types of distributed energy storage resources, such as vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage.

[0012] Preferably, in step S2, for vehicle-mounted energy storage, the basic data related to aggregation potential includes the expected grid connection and disconnection time, the expected grid connection and disconnection SOC value, the rated capacity, and the rated power of each vehicle-mounted energy storage.

[0013] Preferably, in step S2, for grid-side distributed energy storage and user-side energy storage, the basic data related to aggregation potential include the rated power, rated capacity, real-time SOC value, upper limit SOC value, and lower limit SOC value of the grid-side distributed energy storage system and the user-side energy storage system.

[0014] Preferably, step S3 includes the following steps:

[0015] Step S31: The aggregator calculates the aggregation potential based on the basic data related to the aggregation potential for the next day;

[0016] Step S32: The aggregator assesses its own demand response resource competitiveness based on historical demand response data and determines the aggregation potential of the aggregator's equipment. If the aggregation potential is poor, proceed to step S33; otherwise, proceed to step S34.

[0017] Step S33: The aggregator publishes the expected electricity price to guide the equipment users to modify the distributed energy storage aggregation data. The equipment users then submit the basic data related to the aggregation potential for the second time, and the aggregator calculates the aggregation potential for the second time.

[0018] Step S34: Aggregators report demand response time, capacity, and price;

[0019] Step S35: The demand response implementation agency determines the subsidy unit price and the winning capacity of the aggregator based on the principles of "price priority, capacity priority, and time priority";

[0020] This invention incentivizes users to modify basic data related to aggregation potential by incentivizing electricity prices.

[0021] Preferably, in step S3, for vehicle-mounted energy storage, the aggregation potential is calculated based on the equipment response urgency prioritization method, and the vehicle-mounted energy storage is arranged to participate in the dynamic prioritization process of demand response, satisfying the objective function of the maximum aggregable constant discharge power:

[0022]

[0023] in, Let t be the total power of the on-board energy storage group participating in the system demand response at time t;

[0024] This invention addresses the need to describe the aggregated resources of vehicle-mounted energy storage aggregators using several indicators, such as power support capacity, energy support capacity, and aggregation time period. These indicators are strongly correlated with vehicle travel distance and the grid connection simultaneity of each aggregated vehicle, and are subject to availability time period limitations. The invention proposes a device response urgency ranking method (i.e., vehicle-mounted energy storage demand response ranking method) to ensure the reliability of aggregated resources in terms of timing and scale for vehicle-mounted energy storage groups (i.e., equipment / electric vehicle groups under the vehicle-mounted energy storage aggregator).

[0025] As a preferred option, in addition to meeting the constraints of its own physical model, each on-board energy storage device must also meet the following constraints:

[0026]

[0027] in, Let be the time-series discharge power matrix of the nth vehicle at time t. Let t be the aggregate power of the on-board energy storage group. The interval of power commands issued by the aggregator. This represents the aggregated power matrix of each vehicle within the onboard energy storage group. Let t represent the grid connection status of the nth vehicle at time t, where 1 represents grid connection and 0 represents non-grid connection; The maximum aggregate power of the nth vehicle; Let n be the rated power of the nth vehicle; Let n be the rated capacity of the nth vehicle; For the grid-connected SOC of the nth vehicle; Let the off-grid SOC of the nth vehicle be ; Let SOC be the state of charge (SOC) of the nth vehicle at time t.

[0028] Preferably, in step S3, for both grid-side distributed energy storage and user-side energy storage, the charging and discharging power value of each device in the grid-side distributed energy storage system or user-side energy storage system during the demand response period is calculated based on the relevant basic data on aggregation potential. Then, the charging and discharging power values ​​of the devices under the aggregator are summed to obtain the aggregator's aggregation potential. Since the devices in the grid-side distributed energy storage system and user-side energy storage system are always in a grid-connected state, the charging and discharging power of the devices can be directly calculated based on the relevant basic data on aggregation potential, thereby obtaining the aggregation potential.

[0029] Preferably, in step S4, for on-board energy storage, the aggregator updates the remaining aggregation potential of its subordinate devices in real time and dynamically prioritizes device response urgency based on the remaining aggregation potential of its subordinate devices. The aggregator calculates the charging and discharging power of its subordinate devices, issues control commands, and controls the subordinate devices to charge and discharge according to the calculated charging and discharging power. Here, subordinate devices refer to each electric vehicle. The on-board energy storage aggregator prioritizes the on-board energy storage (i.e., electric vehicles) according to the remaining aggregation time and remaining aggregation capacity. During the demand response period, the goal is to achieve maximum aggregation potential and constant power aggregation, with priority given to charging and discharging of on-board energy storage with higher urgency, and the safe and stable operation boundary of on-board energy storage as constraints. "Dynamically prioritizing device response urgency" refers to arranging when and at what power each electric vehicle charges and discharges.

[0030] Preferably, in step S4, the aggregator issues control commands to both grid-side distributed energy storage and user-side energy storage, directly controlling the subordinate devices to charge and discharge according to the calculated charging and discharging power. Here, "subordinate devices" refers to each device in the grid-side distributed energy storage system or the user-side energy storage system.

[0031] Therefore, the advantages of the present invention are:

[0032] (1) In view of the differentiated characteristics of different types of distributed energy storage resources such as vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage, a hierarchical and partitioned aggregation topology is adopted. Aggregators are set up between the demand response implementation agency and the distributed energy storage equipment to classify and aggregate different types of distributed energy storage resources, providing an effective technical means for distributed energy storage resources to meet grid demand and participate in the peak-shaving demand response of the grid system.

[0033] (2) In view of the randomness of the potential for electric vehicle aggregation in terms of time and scale, a method for prioritizing equipment response urgency is proposed to ensure the reliability of on-board energy storage cluster aggregation resources in terms of time and scale. Attached Figure Description

[0034] Figure 1 This is a flowchart of an aggregation method for distributed energy storage to participate in system peak-shaving demand response, as described in Embodiment 1 of the present invention.

[0035] Figure 2 This is the distributed energy storage hierarchical partitioning aggregation topology diagram in Embodiment 2 of the present invention.

[0036] Figure 3 This is a flowchart of the aggregation strategy (day-ahead forecasting stage) for vehicle-mounted energy storage to participate in demand response in Embodiment 2 of the present invention.

[0037] Figure 4 This is a flowchart of the aggregation strategy (intraday control phase) for vehicle-mounted energy storage to participate in demand response in Embodiment 2 of the present invention.

[0038] 1. Demand response implementation agency 2. Aggregator 3. Electric vehicle 4. User-side energy storage system 5. Grid-side distributed energy storage system. Detailed Implementation

[0039] The present invention will now be further described with reference to the accompanying drawings and specific embodiments.

[0040] Example 1:

[0041] An aggregation method for distributed energy storage to participate in grid peak-shaving demand response is proposed. This method employs a hierarchical and partitioned aggregation topology, establishing an aggregator between the demand response implementation agency and the distributed energy storage devices. Different types of distributed energy storage resources are categorized and aggregated, providing an effective technical means for distributed energy storage resources to participate in grid peak-shaving demand response. Distributed energy storage resources include vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage, etc. Figure 1 As shown, it includes the following steps:

[0042] Step S1: The aggregator signs a contract with the equipment users under its jurisdiction;

[0043] Step S2: Device users under the aggregator report basic data related to the aggregation potential for the next day;

[0044] Step S3: Aggregators calculate aggregation potential and report demand response time, capacity, and price;

[0045] Step S4: Real-time aggregation control by aggregators;

[0046] This embodiment aims to aggregate distributed energy storage resources, including on-board energy storage for electric vehicles, grid-side distributed energy storage, and user-side energy storage, to participate in grid system peak-shaving demand response. It proposes an aggregation method for distributed energy storage to participate in system peak-shaving demand response. Addressing the differentiated characteristics of different types of distributed energy storage resources (on-board, grid-side, and user-side), a hierarchical and partitioned aggregation topology is adopted. A resource aggregator role is established between the demand response implementation agency and the distributed energy storage equipment to classify and aggregate different types of distributed energy storage resources. Furthermore, considering the stochastic nature of the aggregation potential of electric vehicles in terms of time and scale, a method for prioritizing equipment response urgency is proposed to ensure the reliability of the aggregated resources of the on-board energy storage group in terms of time and scale.

[0047] In step S2, for vehicle-mounted energy storage, the basic data related to aggregation potential include the expected grid connection and off-grid time, the expected grid connection and off-grid SOC value, the rated capacity, and the rated power of each vehicle-mounted energy storage.

[0048] In step S2, for grid-side distributed energy storage and user-side energy storage, the basic data related to aggregation potential include the rated power, rated capacity, real-time SOC value, upper limit SOC value, and lower limit SOC value of the grid-side distributed energy storage system and the user-side energy storage system.

[0049] The specific process of step S3 includes the following steps:

[0050] Step S31: The aggregator calculates the aggregation potential based on the basic data related to the aggregation potential for the next day;

[0051] Step S32: The aggregator assesses its own demand response resource competitiveness based on historical demand response data and determines the aggregation potential of the aggregator's equipment. If the aggregation potential is poor, proceed to step S33; otherwise, proceed to step S34.

[0052] Step S33: The aggregator publishes the expected electricity price to guide the equipment users to modify the distributed energy storage aggregation data. The equipment users then submit the basic data related to the aggregation potential for the second time, and the aggregator calculates the aggregation potential for the second time.

[0053] Step S34: Aggregators report demand response time, capacity, and price;

[0054] Step S35: The demand response implementation agency determines the subsidy unit price and the winning capacity of the aggregator based on the principles of "price priority, capacity priority, and time priority";

[0055] This embodiment incentivizes users to modify basic data related to aggregation potential by using electricity price incentives.

[0056] In step S3, for vehicle-mounted energy storage, the aggregation potential is calculated based on the equipment response urgency prioritization method, and the vehicle-mounted energy storage is arranged to participate in the dynamic prioritization process of demand response, satisfying the objective function of the maximum aggregable constant discharge power:

[0057]

[0058] in, Let t be the total power of the on-board energy storage group participating in the system demand response at time t;

[0059] This embodiment describes the resources that vehicle-mounted energy storage aggregators can aggregate using several indicators such as power support capacity, energy support capacity, and aggregation time period. These indicators are strongly correlated with vehicle travel and the grid connection simultaneity of each aggregated vehicle, and are subject to availability time period limitations. Therefore, a device response urgency ranking method (i.e., vehicle-mounted energy storage demand response ranking method) is proposed to ensure the reliability of aggregated resources in terms of timing and scale of vehicle-mounted energy storage groups (i.e., equipment / electric vehicle groups under the vehicle-mounted energy storage aggregator).

[0060] In addition to meeting the constraints of their own physical model, each on-board energy storage device must also meet the following constraints:

[0061]

[0062] in, Let be the time-series discharge power matrix of the nth vehicle at time t. Let t be the aggregate power of the on-board energy storage group. The interval of power commands issued by the aggregator. This represents the aggregated power matrix of each vehicle within the onboard energy storage group. Let t represent the grid connection status of the nth vehicle at time t, where 1 represents grid connection and 0 represents non-grid connection; The maximum aggregate power of the nth vehicle; Let n be the rated power of the nth vehicle; Let n be the rated capacity of the nth vehicle; For the grid-connected SOC of the nth vehicle; Let the off-grid SOC of the nth vehicle be ; Let SOC be the state of charge (SOC) of the nth vehicle at time t.

[0063] In step S3, for both grid-side distributed energy storage and user-side energy storage, the charging and discharging power of each device in the grid-side distributed energy storage system or user-side energy storage system during the demand response period is calculated based on the relevant basic data on aggregation potential. Then, the charging and discharging power values ​​of the devices under the aggregator are summed to obtain the aggregator's aggregation potential. Since the devices in both the grid-side distributed energy storage system and the user-side energy storage system are always connected to the grid, the charging and discharging power of the devices can be directly calculated based on the relevant basic data on aggregation potential, thus obtaining the aggregation potential.

[0064] In step S4, for on-board energy storage, the aggregator updates the remaining aggregation potential of its subordinate devices in real time and dynamically prioritizes device response urgency based on this remaining aggregation potential. The aggregator calculates the charging and discharging power of its subordinate devices and issues control commands to control the devices to charge and discharge according to the calculated power. Here, "subordinate devices" refers to each electric vehicle. The on-board energy storage aggregator prioritizes on-board energy storage (i.e., electric vehicles) based on remaining aggregation time and capacity, aiming to maximize aggregation potential and achieve constant power aggregation during demand response periods. Prioritizing the charging and discharging of on-board energy storage with higher urgency and adhering to the safe and stable operation boundaries of on-board energy storage are used as constraints. "Dynamically prioritizing device response urgency" refers to scheduling when and at what power each electric vehicle charges and discharges.

[0065] In step S4, the aggregator issues control commands to both grid-side distributed energy storage and user-side energy storage, directly controlling the subordinate devices to charge and discharge according to the calculated charging and discharging power. Here, "subordinate devices" refers to each device in the grid-side distributed energy storage system or the user-side energy storage system.

[0066] Example 2:

[0067] To address the differentiated characteristics of various distributed energy storage resources, such as on-board energy storage for electric vehicles, grid-side distributed energy storage, and user-side energy storage, a hierarchical and partitioned aggregation topology is adopted, such as... Figure 2 As shown, a resource aggregator 2 role is set up between the demand response implementation agency 1 and distributed energy storage equipment resources (including electric vehicles 3, user-side energy storage systems 4 and grid-side distributed energy storage systems 5) to classify and aggregate different types of distributed energy storage resources.

[0068] This paper considers aggregated distributed energy storage resources, including vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage. Taking vehicle-mounted energy storage as an example, this paper introduces the aggregation method of distributed energy storage.

[0069] The aggregation method is divided into three time scales: the long-term time scale of the contract signed between the aggregator and the electric vehicle owner, the day-ahead forecast time scale, and the short-term time scale of real-time control.

[0070] Car owners who are willing to participate in grid aggregation form a stable aggregation resource by signing a long-term agreement. Car owners connect to the grid after arriving at their workplace in the morning or their residence in the evening. During the grid connection period, the right to control the on-board energy storage belongs to the aggregator in the corresponding area. The aggregator generates income for the car owners by controlling the on-board energy storage to participate in grid aggregation, and collects management fees by taking a percentage of the car owners' income. Car owners and aggregators form a community of interests.

[0071] The main steps of aggregation include: (1) contract signing; (2) reporting of day-ahead aggregation potential data; (3) distribution of aggregation price and capacity; and (4) real-time aggregation control. In terms of time, it is mainly divided into the day-ahead forecasting stage and the intraday control stage. Aggregation strategies include... Figure 3 and Figure 4 As shown.

[0072] During the current forecast phase, the demand response implementation agency invites aggregators within the demand response resource pool. Aggregators submit basic data on their equipment's aggregation potential for the following day. Aggregators calculate aggregation potential (including demand response time and capacity) based on a ranking method for equipment response urgency. Aggregators assess their own demand response resource competitiveness based on historical demand response data. Aggregators determine the aggregation potential of vehicle-mounted energy storage clusters. If they deem the aggregation potential poor, they can guide vehicle owners to modify their vehicle-mounted energy storage aggregation data by publishing a projected electricity price. Vehicle owners then submit basic data on vehicle-mounted energy storage aggregation potential a second time. Aggregators recalculate the aggregation potential (including demand response time and capacity). Aggregators then report demand response time, capacity, and price. The demand response implementation agency determines the subsidy unit price and the aggregator's winning bid capacity based on the principles of "price priority, capacity priority, and time priority."

[0073] During the demand response day control phase, aggregators update the remaining aggregation potential of their subordinate vehicle-mounted energy storage in real time. Based on the real-time remaining aggregation potential of their subordinate devices, aggregators dynamically prioritize vehicle response urgency. They calculate the charging and discharging power commands for their subordinate devices, issue control commands, and control the charging and discharging of the devices.

[0074] In the day-ahead forecasting calculation process of aggregators, because it is different from grid-side distributed energy storage systems and user-side energy storage systems, the resources that vehicle-mounted energy storage aggregators can aggregate need to be described by several indicators such as the power support capacity, the electricity support capacity, and the aggregation period. These indicators are strongly correlated with vehicle travel and the grid connection simultaneity rate of each aggregating vehicle, and are subject to availability period limitations.

[0075] First, basic information such as the expected grid connection and disconnection time, expected grid connection and disconnection SOC value, rated capacity, and rated power of each vehicle-mounted energy storage is collected before the day. The day-ahead aggregation potential of the vehicle-mounted energy storage group is calculated. Then, the aggregator sorts the vehicle-mounted energy storage according to the remaining aggregation time and remaining aggregation capacity. During the demand response period, the goal is to achieve the maximum aggregation potential and constant power aggregation. The vehicle-mounted energy storage with higher urgency is given priority in charging and discharging, and the safe and stable operation boundary of the vehicle-mounted energy storage is used as a constraint. The aggregation potential data is calculated and reported.

[0076] The aggregation methods for grid-side distributed energy storage and user-side energy storage are consistent with those for vehicle-mounted energy storage. The difference lies in the interaction information between aggregators and their subordinate devices. The information exchanged between aggregators and vehicle-mounted energy storage groups (electric vehicle groups) includes the expected grid connection and disconnection time, expected grid connection and disconnection SOC values, rated capacity, and rated power of each vehicle-mounted energy storage system. The information exchanged between aggregators and grid-side distributed energy storage systems and user-side energy storage systems includes the rated power, rated capacity, real-time SOC value, upper limit SOC value, and lower limit SOC value of grid-side distributed energy storage systems and user-side energy storage systems.

[0077] In the current forecast phase, for grid-side distributed energy storage systems and user-side energy storage systems, since these two types of devices are always in a grid-connected state, aggregators can calculate the charging and discharging power of each device during the demand response period based on the collected rated power, rated capacity, real-time SOC value, upper SOC value, and lower SOC value of the energy storage system. Taking participation in system peak shaving demand response as an example, the discharge power value of the energy storage system during the demand response period = min[rated power, rated capacity * (real-time SOC value - lower SOC value) / demand response duration]. Then, by summing the charging and discharging power values ​​of each device under the aggregator's jurisdiction, the aggregator's aggregation potential can be obtained.

[0078] During the demand response day control phase, for grid-side distributed energy storage systems and user-side energy storage systems, since these two types of equipment are always in grid-connected state, the aggregator can directly control the charging and discharging of the equipment according to the charging and discharging power values ​​calculated on the previous day.

[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for aggregating distributed energy storage to participate in system peak-shaving demand response, employing a hierarchical and partitioned aggregation topology, and setting up aggregators between demand response implementation agencies and distributed energy storage devices to achieve classified aggregation, characterized in that, Includes the following steps: Step S1: The aggregator signs a contract with the equipment users under its jurisdiction; Step S2: Device users under the aggregator report basic data related to the aggregation potential for the next day; Step S3: Aggregators calculate aggregation potential and report demand response time, capacity, and price; Step S31: The aggregator calculates the aggregation potential based on the basic data related to the aggregation potential for the next day; Step S32: The aggregator assesses its own demand response resource competitiveness based on historical demand response data and determines the aggregation potential of the aggregator's equipment. If the aggregation potential is poor, proceed to step S33. Otherwise, proceed to step S34; Step S33: The aggregator publishes the expected electricity price to guide the equipment users to modify the distributed energy storage aggregation data. The equipment users submit basic data related to aggregation potential for the second time, and the aggregator calculates the aggregation potential for the second time. Step S34: The aggregator reports the demand response time, capacity and price. Step S35: The demand response implementation agency determines the subsidy unit price and the winning capacity of the aggregator based on the principles of "price priority, capacity priority, and time priority"; Step S4: Real-time aggregation control by aggregators.

2. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 1, characterized in that, The distributed energy storage includes, but is not limited to, vehicle-mounted energy storage, grid-side distributed energy storage, and user-side energy storage. It adopts a hierarchical and partitioned aggregation topology, and sets up a resource aggregator role between the demand response implementation agency and the distributed energy storage equipment resources to classify and aggregate different types of distributed energy storage resources.

3. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 2, characterized in that, In step S2, for vehicle-mounted energy storage, the basic data related to aggregation potential includes the expected grid connection and off-grid time, the expected grid connection and off-grid SOC value, rated capacity, and rated power.

4. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 2, characterized in that, In step S2, for grid-side distributed energy storage and user-side energy storage, the basic data related to aggregation potential include rated power, rated capacity, real-time SOC value, upper limit of SOC value, and lower limit of SOC value.

5. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 1, characterized in that, The aggregation method for on-vehicle energy storage is divided into three time scales: the long-term time scale of the contract signed between the aggregator and the electric vehicle owner, the day-ahead forecast time scale, and the short-term time scale of real-time control.

6. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 2, characterized in that, In step S3, for vehicle-mounted energy storage, the aggregation potential is calculated based on the equipment response urgency prioritization method, and the vehicle-mounted energy storage is arranged to participate in the dynamic prioritization process of demand response, satisfying the objective function of the maximum aggregable constant discharge power: in, Let t be the total power of the on-board energy storage group participating in the system demand response.

7. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 6, characterized in that, In addition to meeting the constraints of their own physical model, each on-board energy storage device must also meet the following constraints: in, Let be the time-series discharge power matrix of the nth vehicle at time t. Let t be the aggregate power of the on-board energy storage group. The interval of power commands issued by the aggregator. This represents the aggregated power matrix of each vehicle within the onboard energy storage group. Let t represent the grid connection status of the nth vehicle at time t, where 1 represents grid connection and 0 represents non-grid connection; The maximum aggregate power of the nth vehicle; Let n be the rated power of the nth vehicle; Let n be the rated capacity of the nth vehicle; For the grid-connected SOC of the nth vehicle; Let the off-grid SOC of the nth vehicle be ; Let SOC be the state of charge (SOC) of the nth vehicle at time t.

8. The aggregation method for distributed energy storage participating in system peak-shaving demand response according to claim 2, characterized in that, In step S3, for grid-side distributed energy storage and user-side energy storage, the charging and discharging power value of each device in the grid-side distributed energy storage system or user-side energy storage system during the demand response period is calculated based on the basic data related to aggregation potential. Then, the charging and discharging power values ​​of the devices under the aggregator are summed to obtain the aggregation potential of the aggregator.

9. A method for aggregating distributed energy storage participation in system peak-shaving demand response according to claim 2 or 7, characterized in that, In step S4, for vehicle-mounted energy storage, the aggregator updates the remaining aggregation potential of its subordinate devices in real time and dynamically prioritizes the devices based on their remaining aggregation potential. The aggregator calculates the charging and discharging power of its subordinate devices, issues control commands, and controls the subordinate devices to charge and discharge according to the calculated charging and discharging power.

10. A method for aggregating distributed energy storage participation in system peak-shaving demand response according to claim 2 or 8, characterized in that, In step S4, for grid-side distributed energy storage and user-side energy storage, the aggregator issues control commands to directly control the subordinate devices to charge and discharge according to the calculated charging and discharging power.

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