Risk-considered method for responding to peak regulation and frequency modulation requirements of power grid by charging and swapping resources

Abstract

The invention discloses a multi-user aggregation participation demand response method considering user characteristics, and the method specifically comprises the steps: carrying out the analysis of the behavior characteristics of charging resources and the extraction of typical power utilization characteristics, and precisely describing the specific performances of the resources in a power grid. Therefore, accurate baseline data can be provided for the operation of the power grid, and the high efficiency of scheduling is ensured; by establishing an aggregation model of charging and battery swap resources, power limitation of charging and discharging can be effectively managed, and necessary peak regulation and frequency modulation responses are provided for a power grid. In the process, the historical operation data of the power grid and the transaction electricity price of the power auxiliary service market are combined, and the flexible regulation and control capability of the power grid is enhanced; and the constructed aggregation charging resource model meets the peak regulation and frequency modulation requirements of the corresponding power grid. The model considers the fluctuation of the price of the power market, and provides a risk assessment method, thereby enhancing the stability and economic benefits of the power grid, and providing important technical support for the sustainable development of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power system demand response, and in particular to a method for charging and swapping power resources to respond to power grid peak regulation and frequency regulation demands in consideration of risks. Background Art

[0002] With the support of national policies and the development of electric vehicle technology, the number of electric vehicles in my country continues to grow. The disorderly charging of a large number of electric vehicles will have a negative impact on the power grid. Local governments have issued various guiding policies to encourage electric vehicles to charge when the power grid load is low by providing charging subsidies during corresponding time periods, which has alleviated the negative impact to a certain extent. At the same time, with the development of charging piles, the emergence of vehicle-to-grid (V2G) technology allows electric vehicles to discharge back to the power grid. Therefore, if electric vehicles can be aggregated, they can participate in various types of power grid assistance as a whole, while providing various needs for the power grid and obtaining corresponding benefits.

[0003] Nowadays, mainstream electric vehicles are divided into rechargeable electric vehicles and battery-swap electric vehicles. After rechargeable electric vehicles are connected to the charging pile, they can directly participate in regulation and control, and accept guidance to adjust the charging and discharging power. After the battery-swap electric vehicles enter the battery swap station, the battery can be replaced in a relatively short time. The replaced low-power batteries will be transported to the battery charging station for unified charging. Similarly, the batteries charged uniformly in the battery charging station can also accept guidance to adjust the charging and discharging power to respond to the needs of the power grid.

[0004] In recent years, with the continuous access of renewable energy to the power grid, the proportion of traditional thermal power units in the power grid has decreased. The power generation of new energy is volatile and unpredictable, which has led to an increase in the peak-to-valley difference of the power grid load and increased the peak-shaving demand of the power grid. At the same time, the randomness and uncertainty of user electricity demand have led to fluctuations in the power grid load, and frequency regulation is needed to maintain the stable operation of the power grid. Therefore, we respond to the peak-shaving and frequency regulation needs of the power grid by aggregating charging and swapping resources. At the same time, considering the volatility of power grid demand, we take it into account as a risk in the objective function. Summary of the invention

[0005] In order to solve the above-mentioned technical problems, a method for charging and swapping resources to respond to the peak and frequency regulation needs of the power grid is proposed with risk consideration.

[0006] The design objectives of the present invention are implemented through the following technical solutions:

[0007] A method for responding to power grid peak load and frequency regulation requirements with charging and swapping resources taking into account risks is provided, comprising the following steps:

[0008] S1: Collect data on charging and swapping resources connected to the power grid, and extract the behavioral characteristics of the charging and swapping resources, including the amount of power connected to the power grid, access time, and departure time of the charging and swapping resources. Based on this data, extract the typical power consumption characteristics of the charging and swapping resources, determine the charging power of the charging and swapping resources without a dispatch instruction, and thus determine the baseline power.

[0009] S2: Establish a charging and swapping resource aggregation model to determine the upper and lower limits of charging and discharging power at each moment. Collect historical grid operation data to determine the peak load and frequency regulation requirements of the grid at different times as the target for charging and discharging resources to respond after flexible regulation; collect transaction price information in the power auxiliary service market as an incentive price for participating in peak load and frequency regulation responses.

[0010] S3: Establish an optimization model for the response of aggregated charging and swapping resources to the peak and frequency regulation needs of the power grid, taking into account constraints such as charging and discharging power and energy; consider the fluctuations in the incentive price for participating in peak and frequency regulation, and establish a method for charging and swapping resources to respond to the peak and frequency regulation needs of the power grid with risks.

[0011] As a further improvement, the behavior characteristics of the charging and swapping resources include the time when the electric vehicle enters the charging station, the battery level when entering, and the time when it leaves the charging station, the battery level, access time, and departure time of the centralized charging station for battery swapping; the charging and swapping resource aggregation model includes the joint aggregation of charging and swapping resources.

[0012] As a further improvement, the historical operation data of the power grid and the peak-shaving and frequency regulation demands of the power grid in different time periods include the peak-shaving and frequency regulation demands of the power grid at every moment of every day on a given date; the power ancillary service market transaction electricity price information includes the average clearing prices of the peak-shaving market and the frequency regulation market at every moment of every day on a given date.

[0013] As a further improvement, the optimization model of the charging and swapping resources responding to the peak and frequency regulation needs of the power grid includes taking the maximum profit of the charging and swapping resource aggregator as the goal, considering the charging power, discharge power, battery energy, and other constraints, and solving the optimal charging and discharging action; the method of establishing the charging and swapping resources considering the risk to respond to the peak and frequency regulation needs of the power grid includes adding the charging and swapping resource aggregator with the risk deviation value to participate in the peak and frequency regulation response. The method proposed by the present invention for the aggregation of multiple users participating in demand response considering user characteristics has the following technical effects:

[0014] (1) By analyzing the behavioral characteristics of charging and swapping resources and extracting typical power consumption characteristics, we can accurately describe the specific performance of these resources in the power grid, such as access power, access and departure time. This helps to provide accurate baseline data for power grid operations and ensure efficient scheduling.

[0015] (2) By establishing an aggregation model of charging and swapping resources, the power limits of charging and discharging can be effectively managed to provide the necessary peak load and frequency regulation response for the power grid. In this process, combining the historical operation data of the power grid and the transaction electricity prices in the power auxiliary service market not only enhances the flexible regulation capability of the power grid, but also provides an incentive mechanism for market participants.

[0016] (3) The constructed aggregated charging and swapping resource model will support the grid’s demand response at multiple time scales, including the optimization response strategy for peak load and frequency regulation. This model takes into account the fluctuation of electricity market prices and provides a risk assessment method, thereby enhancing the stability and economic benefits of the grid, while also providing important technical support for the sustainable development of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is an overall flow chart of a method provided by the present invention for responding to grid peak and frequency regulation demands with charging and swapping resources taking risks into consideration.

[0018] Figure 2 Flowchart of the method for aggregating charging and swapping resources and determining adjustment requirements provided by the present invention.

[0019] Figure 3 This is a modeling flow chart of the charging and swapping resource optimization model that takes risks into consideration provided by the present invention. DETAILED DESCRIPTION

[0020] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0021] Combination Figure 1 As shown, a method for charging and swapping resources to respond to grid peak and frequency regulation requirements taking into account risks provided by an embodiment of the present invention includes the following steps:

[0022] S1: Collect data on charging and swapping resources connected to the power grid, and extract the behavioral characteristics of the charging and swapping resources, including the amount of power connected to the power grid, access time, and departure time of the charging and swapping resources. Based on this data, extract the typical power consumption characteristics of the charging and swapping resources, determine the charging power of the charging and swapping resources without a dispatch instruction, and thus determine the baseline power.

[0023] S2: Establish a charging and swapping resource aggregation model to determine the upper and lower limits of charging and discharging power at each moment. Collect historical grid operation data to determine the peak load and frequency regulation requirements of the grid at different times as the target for charging and discharging resources to respond after flexible regulation; collect transaction price information in the power auxiliary service market as an incentive price for participating in peak load and frequency regulation responses.

[0024] S3: Establish an optimization model for the response of aggregated charging and swapping resources to the peak and frequency regulation needs of the power grid, taking into account constraints such as charging and discharging power and energy; consider the fluctuations in the incentive price for participating in peak and frequency regulation, and establish a method for charging and swapping resources to respond to the peak and frequency regulation needs of the power grid with risks.

[0025] Combination Figure 2 As shown, the charging and swapping resource aggregation modeling method provided by the present invention, the specific steps of determining the peak load and frequency regulation demand and compensation price are as follows:

[0026] S21: Based on the amount of electricity, access time, and departure time of the charging and swapping resources collected in S1, a charging and swapping resource aggregation model is established as follows:

[0027] Using variable X i,t Characterizes whether rechargeable electric vehicles are connected to the power grid and whether the batteries of battery-swappable electric vehicles are connected to the power grid through battery charging stations.

[0028]

[0029] in represents the time when the i-th electric vehicle or battery is connected to the grid, It represents the time when the i-th electric vehicle or battery leaves the grid.

[0030] The charging and discharging power aggregation model of the battery of a plug-in electric vehicle or a battery-swappable electric vehicle can be expressed as:

[0031]

[0032] in represents the discharge power of the i-th electric vehicle or battery at time t; Represents the charging power of the i-th electric car or battery at time t.

[0033] and and The following constraints must be met:

[0034]

[0035] in represents the maximum discharge power of the i-th electric vehicle or battery at time t; represents the maximum charging power of the i-th electric vehicle or battery at time t; constraint It means that electric vehicles or batteries cannot be charged and discharged at the same time.

[0036] Therefore, the charging and discharging aggregation model of plug-in electric vehicles is established as follows:

[0037]

[0038] in is the total maximum charging power, is the total maximum discharge power; SoC t is the total battery power of the electric vehicle after aggregation at time t, SoC min,total and SoC max,total are the minimum and maximum values ​​of the total battery power of electric vehicles after aggregation; η c and η d are the charging and discharging efficiencies of electric vehicles respectively.

[0039] The charging and discharging aggregation model of battery-swap electric vehicles is established as follows:

[0040]

[0041] in is the total maximum charging power, is the total maximum discharge power; SoC t is the total battery power of the electric vehicle after aggregation at time t, SoC min,total and SoC max,total are the minimum and maximum values ​​of the total battery power of electric vehicles after aggregation; η c and η d They are respectively the charging and discharging efficiency of electric vehicles; ΔSoC t The total battery capacity change is caused by removing the fully charged battery and connecting the battery to be charged; and are the number of batteries that leave and connect to the grid after being fully charged at time t; and are the average battery capacity when leaving and connecting to the grid after being fully charged at time t.

[0042] S22: Based on the historical peak-shaving and frequency-regulation demands of the power grid and the historical transaction price information of the power auxiliary service market, determine the peak-shaving and frequency-regulation demands of the power grid that the charging and swapping resources need to respond to, as well as the compensation price provided by the power grid.

[0043] Combination Figure 3 As shown in FIG. 1 , the specific steps of establishing a method for responding to the peak load and frequency regulation requirements of the power grid by charging and swapping resources with risk considerations are as follows:

[0044] S31: Use the model described in S21 as a constraint on charging and swapping resources.

[0045] S32: Establishing a charging and swapping resource response model for the peak load and frequency regulation of the power grid is as follows:

[0046] The objective function is:

[0047] maxF=F 1 +F 2 +F3

[0048]

[0049] There are K frequency modulation periods in time t, F 1 is the frequency regulation capacity gain, and is the capacity price adjusted up or down at time t, and To increase or decrease the capacity at time t, the following conditions must be met:

[0050]

[0051] Where P t,base It is the basic load of the charging and swapping resources before participating in peak load regulation and frequency regulation at time t.

[0052] In the objective function, F 2 is the frequency modulation mileage income, where D t is the frequency modulation mileage at time t, η t is the accuracy at time t, defined as:

[0053]

[0054] Where P dem,k is the power adjustment demand of the system for the charging and swapping resource aggregator due to the frequency regulation demand in the k period within time t, P res,k The FM power that the aggregator responds to.

[0055] The actual power of time segment k at time t becomes:

[0056] P k =P k,base +P res,k

[0057] S33: Considering the volatility of the price incentives for peak-shaving and frequency-regulation ancillary services provided by the power grid, the mean-variance method is introduced into the objective function to measure the risk of charging and swapping aggregated resources participating in peak-shaving and frequency-regulation needs. The objective function becomes:

[0058] maxF=F 1 +F 2 +F 3 -β·Var

[0059]

[0060] Where β is the risk aversion coefficient, and Var is the variance caused by the volatility of the price incentives for peak-shaving and frequency-regulation ancillary services. The constraints are as described in S21, and the other variables are as described in S22.

[0061] The above is a detailed introduction to a method for charging and swapping resources that take risks into account and respond to grid peak and frequency regulation requirements provided by an embodiment of the present invention. This article introduces the principles of the present invention using specific examples to illustrate the core idea of ​​the present invention. The content of this specification cannot be understood as limiting the scope of protection of the present invention.

Claims

1. A method for charging and swapping resources to respond to grid peak and frequency regulation needs with consideration of risk, characterized in that: The following steps are involved: S1: Collect data on charging and swapping resources connected to the power grid, and extract the behavioral characteristics of the charging and swapping resources, including the amount of power connected to the power grid, access time, and departure time of the charging and swapping resources. Based on this data, extract the typical power consumption characteristics of the charging and swapping resources, determine the charging power of the charging and swapping resources without a dispatch instruction, and thus determine the baseline power. S2: Establish a charging and swapping resource aggregation model to determine the upper and lower limits of charging and discharging power at each moment. Collect historical grid operation data to determine the peak load and frequency regulation requirements of the grid at different times as the target for charging and discharging resources to respond after flexible regulation; collect transaction price information in the power auxiliary service market as an incentive price for participating in peak load and frequency regulation responses. S3: Establish an optimization model for the aggregated charging and swapping resources to respond to the peak and frequency regulation needs of the power grid, taking into account constraints such as charging and discharging power and energy; Taking into account the fluctuations in the incentive prices for participating in peak-shaving and frequency regulation, a method for using charging and swapping resources to respond to the peak-shaving and frequency regulation needs of the power grid is established with risk considerations.

2. A method for responding to grid peak load and frequency regulation requirements with charging and swapping resources taking into account risks as claimed in claim 1, characterized in that: The behavior characteristics of the charging and swapping resources include the time when the electric vehicle enters the charging station, the battery level when entering, and the time when it leaves the charging station, the battery level, access time, and departure time of the centralized charging station for battery swapping; the charging and swapping resource aggregation model includes the joint aggregation of charging and swapping resources.

3. A method for responding to grid peak load and frequency regulation requirements with charging and swapping resources taking into account risks as claimed in claim 1, characterized in that: The historical operation data of the power grid and the peak-shaving and frequency regulation demands of the power grid in different time periods include the peak-shaving and frequency regulation demands of the power grid at every moment of every day on a given date; the transaction electricity price information of the power auxiliary service market includes the average clearing price of the peak-shaving market and the frequency regulation market at every moment of every day on a given date.

4. A method for responding to grid peak load and frequency regulation requirements with charging and swapping resources taking into account risks as claimed in claim 1, characterized in that: The optimization model for the charging and swapping resources to respond to the peak and frequency regulation needs of the power grid includes taking the maximization of the profits of the charging and swapping resource aggregators as the goal, considering the charging power, discharging power, battery energy, and other constraints, and solving the optimal charging and discharging actions; the method for establishing the charging and swapping resources to respond to the peak and frequency regulation needs of the power grid taking into account the risks includes adding the charging and swapping resource aggregators with risk deviation values ​​to participate in the peak and frequency regulation response.

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