Regulation and control method for realizing power grid demand side response based on pure electric heavy truck load aggregation

Abstract

The invention discloses a regulation and control method for realizing power grid demand side response based on pure electric heavy truck load aggregation, and the method comprises the steps: firstly, carrying out the analysis of a load aggregation group, and analyzing the historical baseline load, response capability, power supply price and electricity selling price of a pure electric heavy truck; according to a load aggregation group analysis result, selecting a response load, calculating a predicted income and a price subsidy, and forming an optimal response strategy to be issued; then, receiving a power grid dispatching instruction for a charging station and a pure electric heavy truck user, and implementing demand response; and finally, counting real-time loads, historical baseline loads, loads to be responded and response implementation conditions of different charging stations under different response dates, and realizing demand response monitoring. The load of the pure electric heavy truck serves as the drainage load to participate in power grid demand side management, peak clipping and valley filling of the power grid are effectively promoted, reasonable layout of charging facilities is promoted, the bidirectional interaction capacity of the pure electric heavy truck and the power grid is improved, and the supply and demand balance capacity of the power grid and the energy utilization efficiency are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid demand side response regulation and control, and specifically to a regulation and control method for realizing power grid demand side response based on pure electric heavy truck load aggregation. Background Art

[0002] At present, there are a large number of pure electric heavy-duty trucks and a great demand for charging, and the single load power of charging piles is large. With the development of intelligent control and Internet of Things technology, pure electric heavy-duty trucks, as a large-scale electric vehicle group, have gradually increased their ability to participate in grid regulation based on the characteristics of load interruption and have a large response capacity, which can provide a higher flexibility and adjustment space when responding to grid needs.

[0003] With the rapid development of information and communication technology, related research at home and abroad is mainly carried out from the aspects of charging station management system, charging and discharging strategy determination method and source, storage and load coordination method, using big data and artificial intelligence analysis technology to realize user load scheduling based on data-driven mode.

[0004] The patent application number is "CN202410303402.2" and its name is "Source-load interactive flexible peak shaving and valley filling method based on deep learning and multi-objective optimization algorithm". It uses multi-dimensional feature analysis, preprocessing, charging capacity prediction based on reinforcement learning, and peak shaving and valley filling calculation based on particle swarm algorithm to fully utilize charging stations and help charging stations maximize profitability and user absorption.

[0005] In addition, the dispatching system of pure electric heavy trucks in the prior art can intelligently adjust the vehicle's charging strategy and driving mode by real-time monitoring of the battery status and energy consumption of pure electric heavy trucks to achieve optimal energy management and cost control; or intelligently adjust the vehicle's charging time and power by real-time monitoring of the energy consumption of pure electric heavy trucks and the supply and demand of the power grid to achieve optimal power grid load regulation and energy management.

[0006] However, the above-mentioned prior art has the following problems: data processing is performed on the data of the charging gun, but there is no specific implementation method for scheduling the actual power consumption of the power grid; on the one hand, there is no systematic method for utilizing the load of pure electric heavy trucks to perform grid demand-side response regulation, and centralized regulation of pure electric heavy trucks is difficult; on the other hand, due to the disorderly charging of pure electric heavy trucks, peak loads that are unfavorable to the power grid are caused. The orderly charging of the pure electric heavy truck load group participates in the power system regulation to achieve the minimum peak-to-valley difference, which is generally only for charging stations. There is no regulation on the actual charging vehicle users, and users cannot be better mobilized to participate in the demand-side response.

[0007] Therefore, we proposed a control method based on pure electric heavy truck load aggregation to achieve grid demand-side response, which can solve the above problems well. Summary of the invention

[0008] The purpose of the present invention is to provide a control method for realizing grid demand-side response based on pure electric heavy truck load aggregation, so as to solve the problem of centralized control of pure electric heavy truck load resources in the current market proposed by the above background technology.

[0009] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a control method for realizing power grid demand-side response based on pure electric heavy truck load aggregation, including: load aggregation group analysis, response strategy issuance, demand response implementation and demand response monitoring;

[0010] The load aggregation group analysis is to analyze the historical baseline load, response capability, power supply price and power selling price of pure electric heavy trucks;

[0011] The response strategy is issued by selecting the response load according to the load aggregation group analysis results, calculating the expected revenue and price subsidy, and forming the optimal response strategy for issuance;

[0012] The implementation of demand response is to accept grid dispatching instructions for charging stations and pure electric heavy truck users to implement demand response;

[0013] The demand response monitoring is to count the real-time load, historical baseline load, load that should be responded and response implementation status of different charging stations on different response dates to achieve demand response monitoring;

[0014] The load aggregation group analyzes and issues a response strategy, implements demand response after the response strategy is issued, and monitors demand response.

[0015] Preferably, the load aggregation group analysis establishes a data processing center based on the charging pile load data to analyze the historical baseline load, response capability, power supply price and power selling price of pure electric heavy trucks;

[0016] Furthermore, the historical baseline load analysis analyzes the baseline load characteristics of pure electric heavy trucks based on the collected historical load data of charging stations, including load size, load change trend, load peak value and load valley value, as a basis for formulating response strategies;

[0017] Furthermore, the response capability analysis is performed based on the charging needs of pure electric heavy truck users, the idle state of charging piles at charging stations, and the charging load, as a basis for formulating response strategies;

[0018] Furthermore, the power supply price and power selling price analysis is used as a basis for formulating a response strategy based on the type of power price, power price level, and power price change trend.

[0019] Preferably, the demand response implementation includes the charging station obtaining the response strategy implementation, the charging station obtaining the response strategy and determining whether to issue the strategy;

[0020] Furthermore, the charging station disagrees with issuing the policy for implementation, and the response policy stops being implemented;

[0021] Furthermore, the charging stations agreed to issue strategies for implementation and simultaneously provide timely charging information sharing services;

[0022] Among them, the charging information sharing service includes: updating the location of the charging station, the idle status of the charging piles at the charging station, and the charging price of the charging station, forming a recommended list of distance, number of idle charging piles and price, and pushing it to pure electric heavy truck users.

[0023] Preferably, the demand response implementation includes the implementation of a response strategy for pure electric heavy-duty truck users, and the pure electric heavy-duty truck users obtain a response strategy, synchronously obtain the shared information provided by the charging station, respond to the demand that needs to be filled in the valley, make reasonable arrangements, select the location, time, and price of the charging station, and realize orderly charging.

[0024] Preferably, the control method for realizing power grid demand side response based on pure electric heavy truck load aggregation performs demand side response control in different areas and groups according to demand response implementation;

[0025] Furthermore, the zoning and grouping control is that the charging piles correspond to the peak shaving and valley filling response types according to the preferential strategies given by the power grid, match the load curve, allocate charging capacity from top to bottom, provide electricity prices, recommend charging time, and adjust charging information in time to perform peak shaving response control and valley filling response control.

[0026] Further, preferably, the peak shaving response regulation forms a recommended peak shaving response strategy and issues it, the charging station responds to the demand response and provides timely charging and discharging information sharing services for pure electric heavy truck users, and starts demand response monitoring; the specific steps include:

[0027] Step 1-1: Query the demand response invitation response;

[0028] Step 1-2: Query baseline load, response capability, response strategy, and analyze based on load aggregation groups;

[0029] Step 1-3: It is recommended to issue a peak shaving response strategy;

[0030] Step 1-4: The charging station responds to the transaction;

[0031] Steps 1-5: Perform response monitoring;

[0032] Step 1-6: Notify pure electric heavy truck users.

[0033] Further, preferably, the valley filling response regulation notifies the pure electric heavy truck user according to the valley filling demand. After the pure electric heavy truck user responds to charge, a demand response is formed and sent to the charging station. The charging station responds to the demand response and provides the pure electric heavy truck user with timely charging and discharging information sharing services, and starts demand response monitoring. The specific steps include:

[0034] Step 2-1: Query the demand response invitation response;

[0035] Step 2-2: Query baseline load, response capability, response strategy, and analyze based on load aggregation groups;

[0036] Step 2-3: The charging station obtains a valley filling demand response;

[0037] Step 2-4: Electric heavy truck users receive notifications and confirm charging;

[0038] Step 2-5: Issue valley filling response strategy, and charging station responds to the transaction;

[0039] Step 2-6: Notify pure electric heavy truck users;

[0040] Step 2-7: Perform response monitoring.

[0041] Preferably, the demand-side response control for the sub-regions and groups starts real-time demand response when the regional power grid is in a tight supply and demand situation, including adjusting the opening of charging stations and charging piles and adjusting the electricity consumption strategy of pure electric heavy truck users;

[0042] Furthermore, the charging station charging piles are adjusted, and the charging station charging piles are changed through a demand response strategy, so as to guide the charging station to interrupt part of the charging load in the area and seal the number of available charging piles;

[0043] Furthermore, the electricity consumption strategy of pure electric heavy truck users is adjusted, and the customers are guided to change the charging time through demand response strategy, or to charge in power supply areas with sufficient power supply capacity to realize load transfer.

[0044] Preferably, the demand response monitoring specifically includes:

[0045] The real-time load statistics include real-time statistics of the total load and time-divided load of different charging stations;

[0046] The historical baseline load statistics are used to obtain the historical baseline loads of different charging stations for demand response evaluation;

[0047] The load statistics that should be responded to are the load statistics that respond according to the preset demand response plan, which are used to evaluate the implementation of the demand response plan;

[0048] The response implementation statistics include the response time, response amplitude and response success rate of the demand response, which are used for evaluating and optimizing the implementation effect of the demand response.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention uses the pure electric heavy truck load as a divertable load to participate in the demand side management of the power grid, solving the problem of centralized regulation of pure electric heavy truck load resources; adopts reasonable and feasible means to encourage pure electric heavy truck users to actively participate in demand side response, realize load transfer in the power supply area, guide orderly charging, effectively promote peak shaving and valley filling of the power grid, alleviate the tension between power grid supply and demand, promote the reasonable layout of charging facilities, and effectively reduce network losses, thereby improving the two-way interactive capability of pure electric heavy trucks and the power grid, and enhancing the power grid's supply and demand balancing capability and energy utilization efficiency.

[0050] The specific contents are as follows:

[0051] (1) The present invention creates a "fast on / off" load group response resource through load aggregation group analysis, giving full play to the interruptible load characteristics of pure electric heavy trucks, flexibly adjusting, encouraging users to actively participate in demand-side response, and realizing fast demand-side response and load monitoring;

[0052] (2) The present invention generates a response strategy through load aggregation group analysis, with the goal of peak shaving and valley filling, matches the load curve, allocates charging capacity from top to bottom, provides electricity prices, recommends charging time, and adjusts charging information in a timely manner, thereby realizing charging load scheduling through zone and group control, effectively reducing network losses and improving grid energy utilization;

[0053] (3) The demand-side response control based on regional and grouping described in the present invention initiates real-time demand response when supply and demand tension occurs in the regional power grid, adjusts the opening of charging stations and charging piles and the electricity consumption strategy of pure electric heavy truck users, realizes orderly charging, alleviates short-term regional power grid supply and demand tension, improves the two-way interaction capability between pure electric heavy trucks and the power grid, and enhances the power grid supply and demand balance capability;

[0054] (4) The present invention provides timely information sharing services for pure electric heavy truck users, avoiding the situation where there are vehicles but no stations, stations but no vehicles, and redundant charging piles, and provides services for the reasonable planning of charging points, thereby optimizing the operating environment of charging stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a process flow chart of the control method of the present invention;

[0056] Figure 2 This is a flow chart for implementing the peak shaving response control of the present invention;

[0057] Figure 3 This is a flow chart for implementing the valley filling response regulation of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Embodiment 1:

[0060] See also Figure 1 The control method for realizing power grid demand-side response based on pure electric heavy truck load aggregation described in the present invention includes: load aggregation group analysis 10, response strategy issuance 11, demand response implementation 12 and demand response monitoring 13; after load aggregation group analysis 10, response strategy issuance 11 is executed, and then demand response implementation 12 is performed, and demand response monitoring 13 is started to perform data statistics.

[0061] The load aggregation group analysis 10 establishes a data processing center 100 based on the charging pile load data, and performs historical baseline load analysis 101, response capability analysis 102 and power supply and sales price analysis 103;

[0062] The historical baseline load analysis 101 analyzes the baseline load characteristics of the pure electric heavy truck based on the collected historical load data of the charging station, including load size, load change trend, load peak value and load valley value, as a basis for formulating the response strategy; specifically, the acquired load data can be used to form a load change curve, and a response strategy can be formulated to determine the demand response target of reducing the load peak value and increasing the valley value;

[0063] The response capability analysis 102 is analyzed according to the charging demand of pure electric heavy truck users, the idle state of charging piles at charging stations and the charging load, as a basis for formulating a response strategy; specifically, the response strategy is formulated with the goal of recommending to pure electric heavy truck users when the charging piles at charging stations are idle, and promptly informing charging stations to adjust the distribution points, interrupt the load, and transfer the load during the charging peak period;

[0064] The power supply and sales price analysis 103 is based on the type of power price, power price level, and power price change trend as the basis for formulating the response strategy; specifically, the response strategy is formulated with the peak-valley power price difference as the goal of recommending to pure electric heavy truck users to adjust the charging time to achieve power grid supply and demand balance.

[0065] The response strategy is issued 11, and according to the result of the load aggregation group analysis 10, the response load is selected, the expected income and price subsidy are calculated, and the optimal response strategy is formed and issued;

[0066] Specifically, different electricity price strategies can be formulated according to the charging time period of pure electric heavy truck users. During peak electricity consumption periods, electricity prices can be increased to encourage users to reduce electricity consumption, or during low electricity consumption periods, electricity prices can be reduced to encourage users to increase electricity consumption.

[0067] Specifically, according to the peak or underestimated electricity consumption of the charging station, different time periods can be given to regulate the charging time of pure electric heavy truck users and realize load transfer.

[0068] The demand response implementation 12 includes: pure electric heavy truck users 120 obtain response strategy implementation and charging station 121 obtain response strategy implementation;

[0069] Among them, the pure electric heavy truck user 120 obtains the response strategy implementation, the pure electric heavy truck user 120 obtains the response strategy, synchronously obtains the shared information provided by the charging station 121, responds to the needs of valley filling and consumption, makes reasonable arrangements, selects the charging station location, charging time, charging price, and realizes orderly charging;

[0070] Among them, the charging station 121 obtains the response strategy implementation. If the charging station 121 does not agree to issue the strategy implementation, the response strategy stops being implemented; if the charging station 121 agrees to issue the strategy implementation, it simultaneously provides timely charging information sharing services, updates the charging station location, the idle status of the charging piles at the charging station, and the charging price of the charging station, and forms a recommended list of distances, the number of idle charging piles, and prices, which is pushed to the pure electric heavy truck user 120.

[0071] The demand response monitoring 13 corresponds to different response dates for different charging stations, including: historical baseline load statistics 130, real-time load statistics 131, response implementation statistics 132 and load statistics that should be responded to 133;

[0072] The historical baseline load statistics 130 are used to obtain the historical baseline loads of different charging stations for demand response evaluation;

[0073] The real-time load statistics 131 include real-time statistics of the total load and time-divided load of different charging stations;

[0074] The response implementation statistics 132 include statistics on the response time, response amplitude, and response success rate of the demand response, which are used for evaluating and optimizing the implementation effect of the demand response;

[0075] The load statistics 133 that should be responded to are load statistics that respond according to a preset demand response plan, and are used to evaluate the implementation of the demand response plan.

[0076] Embodiment 2:

[0077] The control method for realizing grid demand-side response based on pure electric heavy truck load aggregation can implement demand-side response control in different regions and groups according to demand response implementation. Charging piles correspond to peak shaving and valley filling response types according to preferential strategies given by the power grid, match load curves, allocate charging capacity from top to bottom, provide electricity prices, recommend charging time, and adjust charging information in time to perform peak shaving response control and valley filling response control, so as to achieve the situation that charging stations and charging piles are opened and the electricity consumption strategy of pure electric heavy truck users by using demand response when supply and demand are tight in the regional power grid;

[0078] The charging station charging piles are adjusted to change the charging station charging piles through demand response strategies, guiding the charging station to interrupt part of the charging load in the area, and sealing the number of available charging piles;

[0079] Among them, the electricity consumption strategy of pure electric heavy truck users is adjusted, and customers are guided to change charging time through demand response strategy, or to charge in power supply areas with sufficient power supply capacity to realize load transfer.

[0080] Embodiment three:

[0081] See also Figure 2 The peak shaving response regulation is formed between the pure electric heavy truck cluster control platform 20, the provincial smart energy platform 21, the charging station 121 and the pure electric heavy truck user 120, and the implementation steps include:

[0082] Step 201: the electric heavy-duty truck cluster centralized control platform 20 queries the provincial smart energy platform 21 for a demand response invitation, and the provincial smart energy platform 21 responds to the electric heavy-duty truck cluster centralized control platform 20;

[0083] Step 202: The electric heavy truck cluster centralized control platform 20 queries the provincial smart energy platform 21 for baseline load, response capability, and response strategy, and uses the data processing center 100 to perform load aggregation group analysis 10;

[0084] Step 203: The electric heavy truck cluster centralized control platform 20 generates a peak shaving response strategy and sends it to the charging station 121, which is pushed to the person in charge of the charging station 121 in the form of a text message link;

[0085] Step 204: The charging station 121 responds to the invitation and notifies the provincial smart energy platform 21 and the electric heavy truck cluster control platform 20. The provincial smart energy platform 21 and the charging station 121 complete the transaction and respond to the execution. The charging station 121 makes an in-station announcement.

[0086] Step 205: the charging station 121 uploads the response implementation status to the pure electric heavy truck cluster centralized control platform 20, and the pure electric heavy truck cluster centralized control platform 20 performs response monitoring, queries the real-time load, historical baseline load and load that should be responded to under the execution strategy of the corresponding charging station 121, and monitors the invitation status in real time;

[0087] Step 206: The pure electric heavy-duty truck cluster centralized control platform 20 provides the pure electric heavy-duty truck user 120 with timely charging and discharging information sharing service.

[0088] Embodiment 4:

[0089] See also Figure 3 The valley filling response regulation is formed between the pure electric heavy truck cluster control platform 20, the provincial smart energy platform 21, the charging station 121 and the pure electric heavy truck user 120, and the implementation steps include:

[0090] Step 301: the electric heavy truck cluster centralized control platform 20 queries the provincial smart energy platform 21 for a demand response invitation, and the provincial smart energy platform 21 responds to the electric heavy truck cluster centralized control platform 20;

[0091] Step 302: The electric heavy truck cluster centralized control platform 20 queries the provincial smart energy platform 21 for baseline load, response capability, and response strategy, and uses the data processing center 100 to perform load aggregation group analysis 10;

[0092] Step 303: the charging station 121 obtains the valley filling demand of the pure electric heavy truck cluster control platform 20 and gives a response;

[0093] Step 304: the electric heavy-duty truck cluster centralized control platform 20 notifies the electric heavy-duty truck user 120, and the electric heavy-duty truck user 120 confirms charging;

[0094] Step 305: The electric heavy-duty truck cluster centralized control platform 20 generates a valley-filling response strategy by analyzing the charging information selected by the electric heavy-duty truck user 121 and sends it to the charging station 121, and pushes it to the person in charge of the charging station 121 in the form of a text message link. The charging station 121 responds to the invitation and notifies the provincial smart energy platform 21. The provincial smart energy platform 21 and the charging station 121 complete the response execution, and the charging station 121 uploads the response implementation status to the electric heavy-duty truck cluster centralized control platform 20;

[0095] Step 306: the electric heavy-duty truck cluster centralized control platform 20 notifies the electric heavy-duty truck user 120 and provides the electric heavy-duty truck user 120 with a timely charging and discharging information sharing service;

[0096] Step 307: The electric heavy truck cluster centralized control platform 20 performs response monitoring, and the corresponding charging station 121 queries the real-time load, the historical baseline load and the load that should be responded to under the execution strategy, and monitors the invitation status in real time.

[0097] For those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A control method for realizing power grid demand side response based on pure electric heavy truck load aggregation, characterized in that: It includes load aggregation group analysis, response strategy issuance, demand response implementation and demand response monitoring. After load aggregation group analysis, response strategy is issued, demand response is implemented after response strategy issuance, and demand response monitoring is performed to realize zoned and grouped demand-side response regulation based on demand response implementation.

2. According to claim 1, a control method for realizing grid demand side response based on pure electric heavy truck load aggregation is characterized by: The load aggregation group analysis establishes a data processing center based on the charging pile load data to analyze the historical baseline load, response capability, power supply price and power sales price of pure electric heavy trucks.

3. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 1 is characterized in that: The response strategy is issued, and according to the analysis results of the load aggregation group, the response load is selected, the expected revenue and price subsidy are calculated, and the optimal response strategy is formed and issued.

4. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 1 is characterized in that: The demand response implementation is to accept grid dispatch instructions for charging stations and pure electric heavy truck users to implement demand response.

5. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 1 is characterized in that: The demand response monitoring is implemented by counting the real-time load, historical baseline load, load that should be responded to and response implementation status of different charging stations on different response dates, so as to realize demand response monitoring.

6. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 1 is characterized in that: The regionalized and grouped demand-side response control is for charging piles to correspond to peak shaving and valley filling response types according to the preferential strategies given by the power grid, match the load curve, allocate charging capacity from top to bottom, provide electricity prices, recommend charging time, and adjust charging information in time to perform peak shaving response control and valley filling response control.

7. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 4 is characterized by: The demand response implementation includes the charging station obtaining the response strategy implementation, the charging station obtaining the response strategy and determining whether to issue the strategy; If the charging station disagrees with the implementation of the policy, the response policy will be stopped; The charging stations agree to issue strategy implementation and simultaneously provide timely charging information sharing services.

8. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 4 is characterized in that: The demand response implementation includes the implementation of a response strategy for pure electric heavy-duty truck users. Pure electric heavy-duty truck users obtain a response strategy, synchronously obtain shared information provided by charging stations, respond to demand that needs to be filled in the valley, make reasonable arrangements, select the location, time, and price of the charging station, and achieve orderly charging.

9. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 6 is characterized by: The peak shaving response regulation forms a recommended peak shaving response strategy and issues it. The charging station responds to the demand response and provides timely charging and discharging information sharing services for pure electric heavy truck users, and starts demand response monitoring.

10. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 6 is characterized in that: The valley filling response regulation notifies the pure electric heavy truck user according to the valley filling demand. After the pure electric heavy truck user responds to charge, a demand response is formed and sent to the charging station. The charging station responds to the demand response and provides the pure electric heavy truck user with timely charging and discharging information sharing services, and starts demand response monitoring.

11. The control method for realizing grid demand side response based on pure electric heavy truck load aggregation according to claim 7 is characterized in that: The charging information sharing service updates the location of the charging station, the idle status of the charging piles at the charging station, and the charging price of the charging station to form a recommended list of distances, the number of idle charging piles, and prices, and pushes it to pure electric heavy truck users.

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