Peak-valley period division method based on low-speed electric vehicle charging and new energy power generation

Abstract

The present application relates to a peak-valley period division method based on low-speed electric vehicle charging and new energy power generation, and belongs to the technical field of power grid regulation. The new energy data in the measured area and the historical data of low-speed electric vehicle charging load of residents in the measured area are obtained, the low-speed electric vehicle charging activity and the green electricity adequacy of the area are calculated, the coupling index between the characteristics of low-speed electric vehicle charging and new energy power generation is constructed according to the obtained low-speed electric vehicle charging activity and green electricity adequacy, the peak-valley period division model is constructed according to the coupling index, the low-speed electric vehicle is guided to charge in the green electricity adequacy period through the peak-valley period division model, and the peak-valley difference of the power grid is reduced. The present application combines the charging start time, end time, charging power, charging activity, green electricity adequacy and other characteristics, establishes the peak-valley period division model based on the coupling index, dynamically updates the peak-valley period, and matches the green electricity adequacy and charging demand, so as to improve the new energy consumption efficiency and the power grid load balancing ability.

Description

Technical Field

[0001] This invention belongs to the field of power grid control technology, and in particular to a method for dividing peak, flat and valley periods based on low-speed electric vehicle charging and new energy power generation. Background Technology

[0002] With the continuous growth of the number of low-speed electric vehicles owned by residents, their charging behavior has gradually become an important factor affecting the regional power grid load. These vehicles offer relatively flexible charging times and dispersed power distribution, but the randomness and concentration of their charging demand (such as concentrated charging at night) can exacerbate the peak-valley difference in the power grid, posing a challenge to the stable operation of the grid. Meanwhile, the proportion of renewable energy generation in the region is constantly increasing, but its output is intermittent and fluctuating. During periods of abundant green electricity, wind and solar power curtailment often occurs due to a lack of matching charging demand, while during peak charging demand, insufficient green electricity supply may lead to reliance on traditional thermal power, resulting in low energy utilization efficiency. Existing peak-valley electricity pricing time-sharing mechanisms are mostly based on rough fluctuations in traditional load or renewable energy generation, failing to fully couple the charging characteristics of low-speed electric vehicles with the characteristics of renewable energy generation, making it difficult to achieve synergy between green electricity consumption and grid load optimization. Therefore, a targeted time-sharing scheme is urgently needed to balance the needs of all parties.

[0003] Currently, the division of peak-valley electricity pricing periods is mainly based on the peak-valley difference of grid load or the fluctuations in renewable energy generation, and is specifically manifested as follows: (1) Based on the traditional power grid load, such as the peak and valley time division of industrial electricity and residential daily electricity, the spatiotemporal distribution characteristics of low-speed electric vehicle charging load are not considered. (2) Some schemes incorporate new energy power generation data, but only set the off-peak period as a fixed time period such as the daytime when photovoltaic power is abundant, without dynamically linking the actual charging behavior of low-speed electric vehicles; (3) There is a lack of quantitative analysis on the synergistic relationship between new energy power generation capacity and low-speed electric vehicle charging demand, and no coupling mechanism between the two has been established, resulting in a low degree of matching between time period division and actual supply and demand.

[0004] Therefore, the existing technology has the following problems: (1) The intermittency and volatility of new energy power generation do not match the randomness of low-speed electric vehicle charging load. When green electricity is abundant, the charging demand is low, and when the charging demand is high, green electricity is insufficient. (2) The charging load of low-speed electric vehicles is concentrated in a specific period of time, which may exacerbate the peak-valley difference of the power grid. The existing time period division cannot guide the charging period to coincide with the period of abundant green electricity through dynamic adjustment. (3) The division of time periods lacks quantitative basis and relies only on experience or a single factor, making it impossible to accurately balance the consumption of new energy, grid stability and user charging costs. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a peak-valley time period division method based on low-speed electric vehicle charging and new energy power generation. Combining features such as charging start time, end time, charging power, charging activity, and green energy sufficiency, a peak-valley time period division model is established based on coupling indicators. By dynamically updating the peak-valley time periods, the green energy sufficiency and charging demand are matched to improve the efficiency of new energy absorption and the grid load balancing capability.

[0006] The technical problem solved by this invention is achieved through the following technical solution: The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation includes the following steps: Step 1: Obtain data on renewable energy generation capacity, grid load, and initial peak-valley electricity price time periods within the measured area; Step 2: Obtain historical data on the charging load of low-speed electric vehicles in the measured area and calculate the total charging power; Step 3: Calculate the charging activity of low-speed electric vehicles based on grid load data and historical charging load data of low-speed electric vehicles. Step 4: Calculate the green energy sufficiency of the region based on the new energy power generation capacity and grid load data; Step 5: Based on the obtained low-speed electric vehicle charging activity and green energy sufficiency, construct a coupling index between low-speed electric vehicle charging and new energy power generation characteristics. Step 6: Construct a peak-valley-normal-time division model based on coupling indices. Guide low-speed electric vehicles to charge during periods of abundant green electricity through the peak-valley-normal-time division model, while reducing the peak-valley difference of the power grid.

[0007] Furthermore, the specific implementation method of step 1 is as follows: obtain the power generation capacity of new energy sources in the measured area. G ( t and grid load data B ( t The initial peak-valley electricity price period setting includes fixed time ranges for peak, off-peak, and flat periods.

[0008] Furthermore, the historical charging load data for low-speed electric vehicles in step 2 includes the charging start time. t s,i End time t e,i and charging power P i ( t ),in i =1,2,3..., N The total charging power is calculated as follows:

[0009] Where N represents the number of households.

[0010] Furthermore, the specific implementation method of step 3 is as follows:

[0011] in, t Indicates the time.

[0012] Furthermore, the specific implementation method of step 4 is as follows: .

[0013] Furthermore, the specific implementation method of step 5 is as follows: constructing a coupling index between low-speed electric vehicle charging and new energy power generation characteristics: green electricity and charging matching degree. M ( t ):

[0014] in, α and β These are weighting coefficients used to adjust the new energy power generation capacity and the low-speed electric vehicle charging capacity.

[0015] Furthermore, the specific implementation method of step 6 is as follows: based on the coupling index of green electricity and charging matching degree M ( t The time period is dynamically updated for each time point. t Define time period rules: like M ( t )> e Then t The time period is divided into off-peak periods; like M ( t )<- e Then t The time period is divided into peak periods; like- e ≤ M ( t )≤ e Then t The time period is divided into regular periods; in, e This is the threshold used to divide peak, flat, and valley periods.

[0016] The advantages and positive effects of this invention are: 1. This invention acquires new energy data and historical data on low-speed electric vehicle (LSEV) charging load within the measured area to calculate the LEV charging activity and the green energy sufficiency of the area. Based on the obtained LEV charging activity and green energy sufficiency, a coupling index is constructed between LEV charging and new energy power generation characteristics. A peak-valley / normal-hour period segmentation model is built based on this coupling index to guide LEVs to charge during periods of abundant green energy, thereby reducing the peak-valley difference in the power grid. This invention combines features such as charging start time, end time, charging power, charging activity, and green energy sufficiency to establish a peak-valley period segmentation model based on the coupling index. By dynamically updating peak-valley periods, it matches green energy sufficiency with charging demand, thereby improving the efficiency of new energy absorption and the grid load balancing capacity.

[0017] 2. This invention dynamically divides time periods by designing a coupling index between green electricity sufficiency and charging activity, guiding low-speed electric vehicles to charge during periods of abundant green electricity. It also reduces the peak-valley difference in the power grid by utilizing time period division signals. Furthermore, this method is simple to calculate, easy to operate, and suitable for real-time power grid management.

[0018] 3. This invention balances the power generation and charging capacity of new energy sources through weighting coefficients and quantifies the supply and demand relationship using coupled indicators. This allows the time period division to take into account the stability of the power grid, the consumption of new energy sources, and the power users, making the consideration of factors more comprehensive and improving the overall energy efficiency. Attached Figure Description

[0019] Figure 1 This is a flowchart of the present invention. Detailed Implementation

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

[0021] A method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation, such as... Figure 1 As shown, it includes the following steps: Step 1: Obtain data on new energy power generation, grid load, and initial peak-valley electricity price time periods within the measured area.

[0022] Obtain the power generation capacity of new energy sources in the measured area G ( t and grid load data B ( t The initial peak-valley electricity price period setting includes fixed time ranges for peak, off-peak, and flat periods.

[0023] Step 2: Obtain historical data on the charging load of low-speed electric vehicles in the measured area and calculate the total charging power.

[0024] Historical charging load data for low-speed electric vehicles includes charging start time.t s,i End time t e,i and charging power P i ( t ),in i =1,2,3..., N The total charging power is calculated as follows:

[0025] Where N represents the number of households.

[0026] Step 3: Calculate the charging activity of low-speed electric vehicles based on grid load data and historical charging load data of low-speed electric vehicles.

[0027]

[0028] Where t represents time.

[0029] Step 4: Calculate the green energy sufficiency of the region based on the power generation capacity of new energy sources and the grid load data.

[0030] .

[0031] Step 5: Based on the obtained low-speed electric vehicle charging activity and green energy sufficiency, construct a coupling index between low-speed electric vehicle charging and new energy power generation characteristics.

[0032] Constructing a coupling index between low-speed electric vehicle charging and new energy power generation characteristics: Green electricity and charging matching degree M ( t ):

[0033] Step 6: Construct a peak-valley-normal-time division model based on coupling indices. Guide low-speed electric vehicles to charge during periods of abundant green electricity through the peak-valley-normal-time division model, while reducing the peak-valley difference of the power grid.

[0034] Based on the coupling index of green electricity and charging matching degree M ( t The time period is dynamically updated for each time point. t Define time period rules: like M ( t )> e Then t The time period is divided into off-peak periods; like M ( t )<- e Then t The time period is divided into peak periods; like- e ≤ M ( t )≤ e Then t The time period is divided into regular periods; in, e This is the threshold used to divide peak, flat, and valley periods.

[0035] It should be emphasized that the embodiments described in this invention are illustrative rather than limiting. Therefore, this invention includes, but is not limited to, the embodiments described in the specific implementation. Any other implementations derived by those skilled in the art based on the technical solutions of this invention are also within the scope of protection of this invention.

Claims

1. A method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation, characterized by: Includes the following steps: Step 1: Obtain data on renewable energy generation capacity, grid load, and initial peak-valley electricity price time periods within the measured area; Step 2: Obtain historical data on the charging load of low-speed electric vehicles in the measured area and calculate the total charging power; Step 3: Calculate the charging activity of low-speed electric vehicles based on grid load data and historical charging load data of low-speed electric vehicles. Step 4: Calculate the green energy sufficiency of the region based on the new energy power generation capacity and grid load data; Step 5: Based on the obtained low-speed electric vehicle charging activity and green energy sufficiency, construct a coupling index between low-speed electric vehicle charging and new energy power generation characteristics. Step 6: Construct a peak-valley-normal-time division model based on coupling indices. Guide low-speed electric vehicles to charge during periods of abundant green electricity through the peak-valley-normal-time division model, while reducing the peak-valley difference of the power grid.

2. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 1, characterized in that: The specific implementation method of step 1 is as follows: obtain the power generation capacity of new energy sources in the measured area. G ( t and grid load data B ( t The initial peak-valley electricity price period setting includes fixed time ranges for peak, off-peak, and flat periods.

3. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 1, characterized in that: The historical charging load data for low-speed electric vehicles in step 2 includes the charging start time. t s,i End time t e,i and charging power P i ( t ),in i =1,2,3..., N。 4. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 2, characterized in that: The specific implementation method of step 3 is as follows: ； in, t Indicates the time.

5. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 3, characterized in that: The specific implementation method of step 4 is as follows: 。 6. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 4, characterized in that: The specific implementation method of step 5 is as follows: Construct a coupling index between low-speed electric vehicle charging and new energy power generation characteristics: green electricity and charging matching degree. M ( t ): ； in, α and β These are weighting coefficients used to adjust the new energy power generation capacity and the low-speed electric vehicle charging capacity.

7. The method for dividing peak, flat, and valley periods based on low-speed electric vehicle charging and new energy power generation according to claim 1, characterized in that: The specific implementation method of step 6 is as follows: based on the coupling index of green electricity and charging matching degree M ( t The time period is dynamically updated for each time point. t Define time period rules: like M ( t )> ε Then t The time period is divided into off-peak periods; like M ( t )<- ε Then t The time period is divided into peak periods; like- ε ≤ M ( t )≤ ε Then t The time period is divided into regular periods; in, ε This is the threshold used to divide peak, flat, and valley periods.

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