Charging pile charging revenue scheduling method, system and equipment

Abstract

The invention belongs to the technical field of charging pile electricity price formulating, and particularly relates to a charging pile charging income scheduling method, system and equipment, target power of each pile is calculated based on a zone area load rate, when an actual power deviation exceeds a threshold value, a power adjustment step length is adaptively calculated according to the load rate, and power increasing / decreasing adjustment is executed according to a rule; synchronously generating a power regulation influence factor; combining the adjustment power, the rated power and the real-time electricity price data to construct an income objective function fusing the busy degree, the power grid state and the unit gross profit; a pricing strategy is selected in a grading mode according to the income target function value, the target electricity price of the next time period is dynamically formulated through the current electricity price, the power deviation rate and the regulation and control influence factors, and closed-loop linkage of accurate power control and income self-adaptive optimization is achieved. And dynamic regulation and control are realized by monitoring the load rate of the transformer area and the running state of the charging pile in real time.

Description

Technical Field

[0001] This invention belongs to the technical field of charging pile electricity pricing, specifically relating to a charging pile charging revenue scheduling method, system, and equipment. Background Technology

[0002] With the increasing popularity of electric vehicles, charging infrastructure faces a contradiction between large fluctuations in grid load and unstable operating revenue of charging stations. A large number of charging piles may exacerbate the grid burden during peak hours, while underutilization occurs during off-peak hours, making it difficult for operators to balance safety, efficiency, and profitability.

[0003] Existing charging pile scheduling solutions mostly use fixed sampling periods, failing to adjust in real time according to changes in grid load. This results in a sluggish perception of grid conditions, making it easy to miss critical fluctuations and leading to uneven power distribution or safety hazards. Power regulation mechanisms are simplistic and ignore multiple constraints. Existing methods often only limit power based on the current output, easily causing overload risks or low charging efficiency, affecting hardware lifespan and user charging experience. Most existing solutions only consider electricity costs and basic profit margins, failing to achieve dynamic revenue, leading to inaccurate pricing and large revenue fluctuations for operators in different scenarios. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, and device for scheduling charging revenue from charging piles.

[0005] A method for scheduling charging revenue from charging piles includes the following steps: S1. Obtain the rated power and output power of each charging pile, and the load rate of the transformer area where the charging pile is located; S2. Based on the load factor and rated power of the transformer substation, obtain the target power of the charging pile, calculate the deviation rate between the output power and the target power, and if the deviation rate exceeds the deviation threshold, calculate the power adjustment step size of the charging pile based on the load factor of the transformer substation. If the output power is greater than the target power, the output power is subtracted from the adjustment step size to obtain the adjustment power and the power regulation influence factor. If the output power is less than the target power, it is determined whether the load factor of the transformer area exceeds the load threshold of the transformer area. If it does not exceed the threshold, the output power is increased by the adjustment step size to obtain the adjustment power and the power control influence factor. If it exceeds the threshold, the output power is decreased by the adjustment step size to obtain the adjustment power and the power control influence factor. S3. Based on the adjusted power and rated power, obtain the busyness weight, and construct the revenue objective function by weighted summation of busyness weight, transformer area load rate, and unit gross profit; S4. Calculate the revenue objective function value for each charging pile. Based on the magnitude of the revenue objective function value, select the target electricity price calculation method for the next period. Based on the current electricity price, deviation rate, and power regulation influencing factor, formulate the target electricity price for the next period.

[0006] In S4, the target electricity price calculation method for the next time period is selected based on the magnitude of the revenue objective function value, specifically as follows: If the profit objective function value is less than the first threshold, the target electricity price for the next period... for: , in, The current electricity price is given, k is the power regulation influencing factor, and G is the distribution area load factor. , This is the price reduction adjustment coefficient; If the first threshold ≤ the revenue objective function value < the second threshold, the target electricity price for the next period for: ,in, , To optimize the adjustment coefficient; if the second threshold is less than or equal to the revenue objective function value, the target electricity price for the next period is... for: ,in, , This is an upward adjustment factor.

[0007] In S3, the busyness weight is obtained based on the difference between the adjusted power and the rated power, specifically as follows: , Among them, P rated Rated power, To adjust the power.

[0008] The objective function for profit in S3 is as follows: , Among them, E ref For reference electricity prices, E current Let E(t) be the current revenue and E(t) be the cost electricity price. The normalized unit gross profit is given by G, where G is the transformer load factor. α is the weight of busyness, β is the weight of unit gross profit, β is the weight coefficient of busyness, and γ is the weight of grid load security.

[0009] In S2, the power adjustment step size is calculated based on the transformer area load factor: , in, Adjust the step size based on the base. The minimum attenuation coefficient, G is the attenuation slope, and G is the load factor of the transformer area. This is the threshold for the initial decay.

[0010] The specific calculation method for the target power in S2: , Among them, P rated Where G is the rated power and G is the load factor of the transformer substation. Safety margin coefficient.

[0011] When the difference between two consecutive measurements of the load rate of the charging station's area exceeds the preset sampling deviation threshold, the subsequent sampling frequency is adjusted based on the difference.

[0012] The target electricity price for the next period also needs to be limited. Specifically: if the target electricity price for the next period is lower than the cost price, the current electricity price will be used as the target electricity price for the next period; if the target electricity price for the next period is more than twice the current electricity price, twice the current electricity price will be used as the target electricity price for the next period.

[0013] A charging pile revenue scheduling system, used to implement the above-mentioned charging pile revenue scheduling method, includes: The data acquisition module acquires the rated power and output power of each charging pile, as well as the load rate of the transformer area where the charging pile is located. The power adjustment module, based on the substation load rate and rated power, obtains the target power of the charging pile, calculates the deviation rate between the output power and the target power, and if the deviation rate exceeds the deviation threshold, calculates the power adjustment step size of the charging pile based on the substation load rate. If the output power is greater than the target power, the output power is subtracted from the adjustment step size to obtain the adjustment power and the power regulation influence factor. If the output power is less than the target power, it is determined whether the load factor of the transformer area exceeds the load threshold of the transformer area. If it does not exceed the threshold, the output power is increased by the adjustment step size to obtain the adjustment power and the power control influence factor. If it exceeds the threshold, the output power is decreased by the adjustment step size to obtain the adjustment power and the power control influence factor. The revenue construction module obtains the busyness weight based on the adjusted power and rated power, and constructs the revenue objective function by weighted summation of the busyness weight, the transformer area load rate, and the unit gross profit. The electricity pricing module calculates the revenue objective function value for each charging pile. Based on the magnitude of the revenue objective function value, it selects the target electricity price calculation method for the next period and sets the target electricity price for the next period according to the current electricity price, deviation rate, and power regulation influence factor.

[0014] Compared with the prior art, this application has the following beneficial effects: This application is based on electricity price regulation and further realizes the scheduling of charging pile revenue.

[0015] The core innovation of this invention lies in breaking down the barriers between power dispatch and electricity pricing. By using power regulation influencing factors, the step size and deviation of power adjustment are directly quantified into key inputs for electricity pricing. The pricing strategy, in turn, affects user demand and indirectly influences future power load, thus forming a complete closed loop.

[0016] This invention introduces data acquisition based on changes in transformer load factor, power adjustment step size based on load factor, and a differentiated pricing model based on the revenue objective function value. These mechanisms enable sensitive and refined adaptation to grid conditions, equipment conditions, and market conditions at every stage, from data perception and power execution to business decision-making.

[0017] The revenue objective function of this invention creatively integrates core dimensions such as unit gross profit, charging pile activity weight, and grid load, and balances them through configurable weight coefficients. This upgrades revenue assessment from a single price difference model to a comprehensive evaluation system encompassing operational efficiency, resource status, and external constraints. Pricing decisions based on this model can more accurately identify the current operational status and adopt targeted pricing strategies, thereby achieving a better solution for overall revenue. Detailed Implementation

[0018] To further understand the content of this invention, the invention will be described in detail with reference to the embodiments.

[0019] This invention relates to a method for scheduling charging revenue from charging piles, which includes the following steps: S1. Obtain the rated power and output power of each charging pile, and the load rate of the transformer substation where the charging pile is located.

[0020] Specifically, the following core data needs to be obtained, with the specific parameters as follows: Rated power P of charging pile rated The information is written to the system during the registration of the charging pile, and the system only responds to and triggers the modification when the charging pile changes.

[0021] The output power P is collected in real time by the built-in sensor of the charging pile.

[0022] Minimum output power guarantee value P min .

[0023] The cost electricity price E(t) is obtained through the system's interface with the power grid marketing platform.

[0024] Electricity sales price E current The current electricity sales price is obtained from the backend of the charging pile management system.

[0025] The load factor G of the transformer area is obtained through the interface of the power grid company's electricity information collection system, and its range is [0, 1].

[0026] When the difference between two consecutive measurements of the load rate of the charging station's area exceeds the preset sampling deviation threshold, the subsequent sampling frequency is adjusted based on the difference.

[0027] The data sampling frequency T is automatically adjusted based on the transformer area load rate G. base It includes the following parameters: Basic sampling period T base The preset time is 30 seconds, T min The shortest sampling period is preset to 10 seconds by the system. prev The load factor of the transformer area in the last sampling, ΔG, is obtained from the absolute value of |G - Gprev|.

[0028] During order initialization, data is collected once and temporarily stored, and the basic sampling period T is set. base Shortest sampling period T min and set G prev = G.

[0029] Obtain the current load factor G of the transformer area and calculate ΔG = |G - Gprev|.

[0030] Update the next sampling period T based on the load change. b When the load factor of the transformer area changes slightly, 0 ≤ ΔG < 0.4, T b = T base When the load factor of the transformer area varies moderately, and 0.4 ≤ ΔG ≤ 0.8, T b = max(T base ×0.5,T min When the load factor of the transformer area changes drastically, and ΔG > 0.8, T b = T min .

[0031] Update historical load factor G prev This is used for comparison in the next cycle.

[0032] Update the data of the temporarily stored S1 parameters and enter the S2 power dynamic adjustment step, and prepare to enter the next trigger cycle adjustment.

[0033] In summary, firstly, the core data includes the charging pile's rated power, output power, cost electricity price, sales electricity price, and transformer area load rate, which are acquired through built-in sensors, system interfaces, or the backend to ensure real-time performance. Secondly, the sampling cycle operates according to a set rule: upon order initialization, all core data is collected and temporarily stored, and the basic sampling cycle, minimum sampling cycle, and historical transformer area load rate are set. Subsequently, data collection is triggered every current sampling cycle to obtain the real-time transformer area load rate and calculate changes. Based on these changes, the sampling cycle is updated according to different scenarios, and the collected data is synchronized to the subsequent S2 power dynamic adjustment steps, preparing for the next sampling cycle trigger.

[0034] S2. Based on the load factor and rated power of the transformer substation, obtain the target power of the charging pile, calculate the deviation rate between the output power and the target power, and if the deviation rate exceeds the deviation threshold, calculate the power adjustment step size of the charging pile based on the load factor of the transformer substation. If the output power is greater than the target power, the output power is subtracted from the adjustment step size to obtain the adjustment power and the power regulation influence factor. If the output power is less than the target power, it is determined whether the load factor of the transformer area exceeds the load threshold of the transformer area. If it does not exceed the threshold, the output power is increased by the adjustment step size to obtain the adjustment power and the power regulation influence factor. If it exceeds the threshold, the output power is decreased by the adjustment step size to obtain the adjustment power and the power regulation influence factor.

[0035] Specifically, the target power is calculated as follows: , Among them, P rated Where G is the rated power and G is the load factor of the transformer substation. Safety margin coefficient.

[0036] After obtaining the target power of the charging pile, calculate the deviation rate between the output power and the target power: , Furthermore, if ε ≥ 5%, the power adjustment step size of the charging pile is calculated based on the load factor of the transformer area: , in, Adjust the step size based on the base. The minimum attenuation coefficient, G is the attenuation slope, and G is the load factor of the transformer area. This is the threshold for the initial decay.

[0037] Preferably, Using 40 as the basic power adjustment step size allows for rapid adjustment during normal periods, resulting in low user perception. Using 0.02 as the minimum attenuation coefficient, even in extreme cases where G ≥ 98%, a fine-tuning capability of 40 × 0.02 = 0.8W is still retained to avoid complete jamming. A slope of 12 is too small; for example, with 8, the step size is still too large when G reaches 92%, and there's not enough time to decrease it. A slope of 16 is too large; G becomes too conservative just reaching 88%, slowing down the charging process. 10 to 14 are acceptable, with 12 being the most recommended value. The attenuation threshold is set to 0.86, representing the braking point at which the power grid begins to feel pressure.

[0038] If the output power is greater than the target power, reduce the power by subtracting the adjustment step size from the output power to obtain the adjusted power. and power regulation influence factor k; , , in, This is a reference value for the deviation rate, ranging from 5% to 10%.

[0039] If the output power is less than the target power, it is determined whether the load factor of the transformer area exceeds the load threshold of the transformer area. If it does not exceed the threshold, the output power is increased by the adjustment step size to obtain the adjustment power and the power regulation influence factor. , If the value exceeds the limit, subtract the adjustment step size from the output power to obtain the adjustment power and the power control influence factor. .

[0040] If the output power equals the target power, no adjustment is made, and the current output power is directly used as the adjustment power, and S3 is executed.

[0041] S3. Based on the adjusted power and rated power, obtain the busyness weight. Based on the busyness weight, the load factor of the transformer area, and the unit gross profit, calculate the weighted sum to construct the revenue objective function.

[0042] The busyness weight is obtained as follows: , Among them, P rated Rated power, To adjust the power.

[0043] The objective function for profit is as follows: , Among them, E ref For reference electricity prices, E current Let E(t) be the current revenue and E(t) be the cost electricity price. The normalized unit gross profit is given by G, where G is the transformer load factor. α is the weight of busyness, β is the weight of unit gross profit, β is the weight coefficient of busyness, and γ is the weight of grid load security.

[0044] S4. Calculate the revenue objective function value for each charging pile. Based on the magnitude of the revenue objective function value, select the target electricity price calculation method for the next period. Based on the current electricity price, deviation rate, and power regulation influencing factor, formulate the target electricity price for the next period.

[0045] Based on the magnitude of the revenue objective function value, the target electricity price calculation method for the next time period is selected as follows: If the profit objective function value is less than the first threshold, in scenarios of low profit margin, idle charging piles, and ample grid load, or low profit margin, busy charging piles, and tight grid load, electricity prices tend to decrease. The target electricity price for the next period is... for: , in, The current electricity price is given, k is the power regulation influencing factor, and G is the distribution area load factor. , This is the price reduction adjustment coefficient; If the first threshold ≤ the profit objective function value < the second threshold, and the scenario is characterized by normal gross profit, moderate utilization, stable grid load, or high gross profit, moderate utilization, ample grid load, or normal gross profit, busy charging piles, and ample grid load, then the electricity price will be moderately increased, and the target electricity price for the next period will be determined accordingly. for: , in, , To optimize the adjustment coefficient; If the second threshold is less than or equal to the profit objective function value, high gross profit, busy charging stations, and a relaxed power grid lead to a large increase in electricity prices. The target electricity price for the next period is... for: , in, , This is an upward adjustment factor.

[0046] The target electricity price for the next period also needs to be limited. Specifically: if the target electricity price for the next period is lower than the cost price, the current electricity price will be used as the target electricity price for the next period; if the target electricity price for the next period is more than twice the current electricity price, twice the current electricity price will be used as the target electricity price for the next period.

[0047] The revenue objective function of this invention creatively integrates core dimensions such as unit gross profit, charging pile activity weight, and grid load, and balances them through configurable weight coefficients. This upgrades revenue assessment from a single price difference model to a comprehensive evaluation system encompassing operational efficiency, resource status, and external constraints. Pricing decisions based on this model can more accurately identify the current operational status and adopt targeted pricing strategies, thereby achieving a better solution for overall revenue.

[0048] A charging pile revenue scheduling system, used to implement the above-mentioned charging pile revenue scheduling method, includes: The data acquisition module acquires the rated power and output power of each charging pile, as well as the load rate of the transformer area where the charging pile is located. The power adjustment module, based on the substation load rate and rated power, obtains the target power of the charging pile, calculates the deviation rate between the output power and the target power, and if the deviation rate exceeds the deviation threshold, calculates the power adjustment step size of the charging pile based on the substation load rate. If the output power is greater than the target power, the output power is subtracted from the adjustment step size to obtain the adjustment power and the power regulation influence factor. If the output power is less than the target power, it is determined whether the load factor of the transformer area exceeds the load threshold of the transformer area. If it does not exceed the threshold, the output power is increased by the adjustment step size to obtain the adjustment power and the power control influence factor. If it exceeds the threshold, the output power is decreased by the adjustment step size to obtain the adjustment power and the power control influence factor. The revenue construction module obtains the busyness weight based on the adjusted power and rated power, and constructs the revenue objective function by weighted summation of the busyness weight, the transformer area load rate, and the unit gross profit. The electricity pricing module calculates the revenue objective function value for each charging pile. Based on the magnitude of the revenue objective function value, it selects the target electricity price calculation method for the next period and sets the target electricity price for the next period according to the current electricity price, deviation rate, and power regulation influence factor.

[0049] A charging pile charging revenue scheduling device includes a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the charging pile charging revenue scheduling method.

[0050] This invention can achieve dynamic interaction between charging piles and the power grid in two ways: first, it can deeply connect with the power grid's electricity consumption information collection system to obtain key indicators such as the load factor of the distribution area in real time; second, it can connect with the power grid's marketing platform interface to dynamically obtain cost electricity price and sales electricity price parameters, thereby realizing the joint control of the charging pile's output power and electricity price.

[0051] At the on-site execution level, this invention uses the charging pile controller and the back-end management system as the core execution units. By integrating multi-source data acquisition of built-in sensors, system interfaces and back-end parameters, and combining an adaptive sampling cycle adjustment mechanism based on load changes, it achieves high-frequency and accurate perception of the power grid status.

[0052] At the resource scheduling level, this invention integrates a dynamic power adjustment method based on collected parameters, which combines hardware limiting, distribution area target constraints, minimum guaranteed power, and grid load direction locking. This allows the charging pile output power to approach the distribution area target power in real time, while strictly meeting multiple hard constraints such as hardware safety, grid safety, and minimum guaranteed power.

[0053] At the operational level, this invention constructs an automated closed-loop process for data acquisition, power regulation, revenue calculation, and electricity price adjustment. In the electricity price optimization stage, it pioneers a normalized revenue objective function R and its weight design method that integrates unit gross profit, busyness, and grid redundancy (1-G). Combined with a final electricity price segmentation adjustment strategy based on R-value segmentation, grid load hard constraint correction, triple limit, and special scenario fallback, it achieves revenue-oriented fluctuation of electricity prices within the cost floor and policy price limit range. Furthermore, it improves operational stability and user experience through user mini-programs and APP push notifications.

[0054] A charging pile charging revenue scheduling device includes a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the charging pile charging revenue scheduling method.

Claims

1. A charging pile charging revenue scheduling method, characterized in that, The method comprises the following steps: S1, obtaining the rated power and output power of each charging pile, and the load rate of the area where the charging pile is located; S2, based on the load rate of the area and the rated power, obtaining the target power of the charging pile, calculating the deviation rate of the output power and the target power, if the deviation rate exceeds the deviation threshold, based on the load rate of the area, calculating the power adjustment step of the charging pile, if the output power is greater than the target power, the output power is reduced by the adjustment step to obtain the adjusted power and the power control influence factor; if the output power is less than the target power, it is judged whether the load rate of the area exceeds the load threshold of the area, if not, the output power is added to the adjustment step to obtain the adjusted power and the power control influence factor, if it exceeds, the output power is reduced by the adjustment step to obtain the adjusted power and the power control influence factor; S3, based on the adjusted power and the rated power, obtaining the busy degree weight, based on the busy degree weight, the load rate of the area, and the weighted sum of unit gross profit, constructing a revenue target function; S4, calculating the revenue target function value of each charging pile, based on the size of the revenue target function value, selecting the target electricity price calculation mode of the next period, and formulating the target electricity price of the next period according to the current electricity price, the deviation rate and the power control influence factor. 2.The charging income scheduling method of claim 1, wherein, In S4, based on the size of the revenue target function value, the target electricity price calculation method of the next period is selected, specifically: if the revenue target function value < first threshold value, the target electricity price of the next period is calculated by the first method is: , wherein, is the current electricity price, k is the power regulation influence factor, G is the load rate of the transformer area, , is the price reduction adjustment coefficient; if the first threshold value < the revenue objective function value < the second threshold value, the target electricity price of the next period is: wherein, , is an optimization adjustment coefficient; if the second threshold value < the revenue objective function value, the target electricity price of the next period is: wherein, , is an upward adjustment coefficient. 3.The charging income scheduling method of claim 1, wherein, In S3, the busy degree weight is obtained based on the adjusted power and the rated power, and the specific process is as follows: ， where P rated is the rated power, is the adjusted power.

4. The charging income scheduling method of claim 1, wherein, In S3, the revenue target function is as follows: ， Wherein, E ref is the reference price, E current is the current income, E(t) is the cost price, is the normalized unit gross profit, G is the load rate of the transformer area, is the busy weight, α is the unit gross profit weight, β is the busy weight coefficient, and γ is the power grid load safety weight.

5. The charging income scheduling method of claim 1, wherein, In S2, the power adjustment step of the charging pile is calculated based on the load rate of the area: ， wherein, is a base adjustment step size, is a minimum decay coefficient, is a decay slope, G is a substation load rate, is a decay start threshold.

6. The charging income scheduling method of claim 1, wherein, In S2, the target power is calculated as follows: ， where P is the rated power, G is the load rate of the transformer substation, and P rated is the rated power, G is the load rate of the transformer substation, safety margin coefficient.

7. The charging income scheduling method of claim 1, wherein, When the difference between the load rates of the areas where the charging piles are located obtained continuously for two times is greater than a preset sampling deviation threshold, the subsequent sampling frequency is adjusted according to the difference. 8.The charging income scheduling method of claim 1, wherein, The target electricity price of the next period also needs to be limited, specifically: if the formulated target electricity price of the next period is lower than the cost electricity price, the current electricity price is taken as the target electricity price of the next period, and if the target electricity price of the next period is greater than twice the current electricity price, twice the current electricity price is taken as the target electricity price of the next period.

9. A charging pile charging revenue scheduling system for implementing the charging pile charging revenue scheduling method of claims 1-8, characterized in that, It comprises: The data acquisition module obtains the rated power and output power of each charging pile, and the load rate of the area where the charging pile is located; The power adjustment module, based on the load rate of the area and the rated power, obtains the target power of the charging pile, calculates the deviation rate of the output power and the target power, if the deviation rate exceeds the deviation threshold, based on the load rate of the area, calculates the power adjustment step of the charging pile, if the output power is greater than the target power, the output power is reduced by the adjustment step to obtain the adjusted power and the power control influence factor; if the output power is less than the target power, it is judged whether the load rate of the area exceeds the load threshold of the area, if not, the output power is added to the adjustment step to obtain the adjusted power and the power control influence factor, if it exceeds, the output power is reduced by the adjustment step to obtain the adjusted power and the power control influence factor; The revenue construction module, based on the adjusted power and the rated power, obtains the busy degree weight, based on the busy degree weight, the load rate of the area, and the weighted sum of unit gross profit, constructs a revenue target function; The electricity price setting module calculates a benefit objective function value of each charging pile, selects a target electricity price calculation mode of a next time period based on the size of the benefit objective function value, and sets the target electricity price of the next time period according to the current electricity price, a deviation rate and a power regulation influence factor.

10. A charging pile charging revenue scheduling device, characterized in that, The charging pile charging benefit scheduling method comprises a processor and a memory, wherein the processor implements the charging pile charging benefit scheduling method according to any one of claims 1-8 when executing a computer program stored in the memory.

Images