Electric vehicle charging behavior guiding price mechanism method and system

Abstract

The invention discloses an electric vehicle charging behavior guide price mechanism method and system, and the method comprises the steps: firstly predicting the demand change of the charging power of an electric vehicle in a power distribution network, and judging whether the demand change exceeds a grid-connected point power fluctuation limit value or not; if yes, fixed delay time is set to adjust reserved buffer for the power generation side; then, dynamic delay time is calculated in combination with the line power limit and the power generation side adjusting capacity; distributing an active power set value for each charging station according to the distribution network topology and the real-time load, and further calculating the dynamic time delay of the space dimension and the time dimension; and finally, generating differentiated guide price signals by integrating various delays. By introducing a delay mechanism, power grid power impact caused by centralized charging of the electric vehicles during time-of-use electricity price switching is effectively avoided, and safe and stable operation of the system is guaranteed.

Description

Technical Field

[0001] This invention belongs to the technical field of market-oriented pricing design for electricity consumption behavior on the load side of the electricity market, and particularly relates to a method and system for a pricing mechanism to guide electric vehicle charging behavior. Background Technology

[0002] In recent years, with the rapid development of the new energy vehicle industry, the scale of charging infrastructure construction has continued to expand, and the technological level has been continuously improved. Relevant national departments have actively introduced policies to promote the high-quality development of charging facilities, explicitly proposing to promote the scientific layout and efficient construction of high-power charging facilities with a single charging gun power of no less than 250 kilowatts, in order to better support the popularization of new energy vehicles and industry upgrading. High-power charging technology has become an important direction for improving the user charging experience and alleviating range anxiety, and is also a key trend in the intelligent and large-scale development of charging infrastructure.

[0003] In existing technologies, the operation and control of high-power charging facilities mainly rely on orderly charging management, local power allocation strategies, and simple control methods based on fixed time or load signals. Some systems use site-level energy management systems (EMS) to monitor charging load in real time and dynamically allocate power according to preset power limits to avoid local overload. Meanwhile, many charging operation platforms have introduced incentive mechanisms based on time-of-use pricing, using price signals to encourage users to charge during off-peak hours to achieve peak shaving and valley filling.

[0004] However, existing technologies have a significant drawback: the lack of an effective market guidance and coordination control mechanism to address the concentrated start-up and shutdown charging behavior of a high proportion of high-power electric vehicles during time-of-use pricing transitions. Under the industrial and commercial time-of-use pricing policy, price transition points (such as from off-peak to peak or from peak to off-peak) can easily trigger a large number of electric vehicles to start or stop charging simultaneously, causing sudden and drastic power fluctuations in the distribution network and even the main power grid. This leads to prominent power angle stability issues in the grid, increases the risk of malfunction of protection components, and threatens the safe and stable operation of the system. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a pricing mechanism method for guiding electric vehicle charging behavior during the concentrated start-stop charging of high-power electric vehicles in time-of-use pricing periods, so as to alleviate instantaneous power fluctuations in the power grid and ensure the safe and stable operation of the system; on the other hand, it provides a system for guiding electric vehicle charging behavior pricing mechanism.

[0006] Technical solution: The electric vehicle charging behavior guidance pricing mechanism method of the present invention includes the following steps: S1. Obtain the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. S2. Based on the predicted value of the change in charging power demand, determine whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. S3. If the change in charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, it is determined that the power fluctuation exceeds the instantaneous power regulation capability of the generation side, and a fixed delay time is set. S4. Calculate the dynamic delay end time based on the predicted value of the charging power demand change, the preset power limit of the medium voltage transmission line, and the power change limit per unit time on the power generation side, and determine the required time length of the dynamic delay based on the fixed delay time and the dynamic delay end time. S5. Based on historical charging data and real-time load information, predict the charging power demand of each electric vehicle charging station in the next scheduling cycle, and allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. S6. Based on the required time length for dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side, calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the time dimension respectively. S7. Based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension, generate a guiding price signal corresponding to each charging station.

[0007] This invention predicts changes in electric vehicle charging power demand in medium- and low-voltage distribution networks, determines in real time whether power fluctuations exceed grid connection limits and generation-side regulation capabilities, and integrates fixed delay with dynamic delay mechanisms calculated based on power limits and regulation limits. It combines charging demand forecasting and topology constraints to allocate charging station power setpoints, further calculating dynamic delays from both spatial and temporal dimensions. Ultimately, it generates differentiated guiding price signals, effectively mitigating instantaneous power surges in the grid caused by concentrated charging starts and stops during time-of-use pricing transitions, improving generation-side power regulation margins, ensuring the safe and stable operation of the distribution network, and systematically guiding orderly charging of electric vehicles through the price mechanism to achieve spatiotemporal load balance optimization of the grid.

[0008] Preferably, step S1, which involves obtaining the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time, includes: Calculate the absolute value of the difference between the predicted changes in charging power demand of all electric vehicles connected to medium-voltage or low-voltage transmission and distribution lines between the current time t and the next time t+1, and use this as the total change in charging power demand of the line at the next time. Specifically, for medium-voltage or low-voltage transmission and distribution lines, the total change in charging power demand... The calculation formula is:

[0009] in, for t The next moment T Total change in charging power demand of connected electric vehicles under different voltage levels; , Charging piles i exist t Moment and the next moment t +1 power prediction value; n It refers to the number of charging piles in the area covered by the medium-voltage distribution network.

[0010] By calculating the absolute value of the difference between the predicted charging power values ​​of all charging piles on medium-voltage or low-voltage transmission lines at adjacent times, the change in the total charging power demand of the line at the next voltage level is accurately quantified. This provides a precise and reliable data basis for subsequent judgment on whether power fluctuations exceed limits and triggering guidance mechanisms, effectively improving the accuracy and timeliness of the system's perception of instantaneous power fluctuations in the power grid.

[0011] Preferably, the total change in charging power demand between the medium-voltage transmission and distribution lines and the low-voltage transmission and distribution lines satisfies the following power balance constraints: The total change in charging power demand of a medium-voltage transmission and distribution line at the next moment is equal to the sum of the total changes in charging power demand of all m low-voltage transmission and distribution lines under its jurisdiction at the same moment, that is:

[0012] in, for t The total change in charging power demand of the tram connected to the medium-voltage transmission line at the next moment; The first under the jurisdiction of medium voltage distribution network j Changes in charging pile power demand for a low-voltage transmission line; m It refers to the number of low-voltage transmission lines in the area covered by the medium-voltage distribution network.

[0013] By establishing a strict balance constraint on the total change in charging power demand between medium-voltage lines and their subordinate low-voltage lines, the data consistency and energy conservation of power fluctuation prediction across the distribution network level are ensured. This lays a solid model foundation for the system to accurately assess power fluctuations across the entire network and coordinate the formulation of hierarchical guidance strategies, effectively improving the overall integrity and reliability of dispatching decisions.

[0014] Preferably, the method further includes: A carbon emission intensity coefficient per unit of electricity is defined for the transmission and distribution lines in the distribution network. This coefficient is the sum of the following two proportions: The proportion of newly connected electricity generated from primary energy sources on this section of the power transmission and distribution line to the total newly connected electricity of the entire network; The proportion of total carbon emissions generated by all generating units from the power generation side to the transmission and distribution line section to their total transmitted electricity.

[0015] By defining a comprehensive coefficient that integrates the proportion of clean energy connected to the grid and the carbon emission intensity of the transmission link for the transmission and distribution lines in the distribution network, environmental protection indicators are precisely embedded into the charging guidance mechanism. This allows the final guidance price signal to not only smooth out power fluctuations but also encourage electric vehicles to charge during periods and on lines with a high proportion of clean energy and low carbon emissions from transmission. This simultaneously optimizes the economic efficiency and environmental friendliness of the power grid operation and promotes low-carbon electricity consumption.

[0016] Preferably, step S2, determining whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point, includes: The maximum power fluctuation at the grid connection point on the generation side is calculated using the following expression:

[0017] in, This represents the maximum power fluctuation at the grid connection point on the generation side. These are unit parameters, including attribute parameters such as unit status and unit type; The generating unit corresponding to the grid connection point on the power generation side k The instantaneous change in output power is determined by the current state and type of the generator set and its corresponding ramp / landslide rate parameters; k , y The first k Total y Each unit, t 0 is the value at the start time of the fixed delay. t 1 is the value of the end time of the fixed delay, and also the value of the start time of the spatial delay of the dynamic delay; The predicted value of the change in charging power demand is compared with For comparison, if the change in charging power demand for any line exceeds... If the change in charging power demand of the line exceeds the power fluctuation range limit of the grid connection point, then it is determined that the change exceeds the limit limit.

[0018] By comprehensively considering the type, status, and instantaneous output change capability of all generating units at the grid connection point on the power generation side, the upper limit of power fluctuation that the system can withstand is dynamically calculated, and it is compared with the predicted changes in charging power demand in real time. This enables accurate identification and early warning of grid power fluctuation risks, providing a scientific basis for subsequent triggering of delay guidance mechanisms, and significantly enhancing the system's ability to defend against sudden power shocks and its operational safety.

[0019] Preferably, the setting of the fixed delay time in step S3 includes: When it is determined that the change in charging power demand of medium-voltage or low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point, a fixed delay time is set. T 1. The calculation method is as follows:

[0020] in, T 1 represents the set fixed delay time; the fixed delay time T 1. Used to delay the charging start time of electric vehicles on the corresponding line, providing the necessary preparation time for the power generation side to adjust the power; Calculate the end time of the fixed delay based on the calculated fixed delay duration. t 1. The value of the end time of the fixed delay is also the value of the start time of the spatial delay of the dynamic delay. The calculation method is shown in the following formula: .

[0021] By setting a fixed delay time based on the generation-side adjustment needs immediately after detecting excessive power fluctuations, the charging start-up of electric vehicles on the corresponding line is forcibly delayed, reserving a crucial power adjustment window for the generation-side units. This effectively avoids instantaneous power surges in the power grid and significantly improves the system's robustness and stability in response to sudden load changes.

[0022] Preferably, the calculation of the required time length for dynamic delay in step S4 includes: Based on the predicted value of charging power demand change, the preset power limit of medium-voltage transmission lines and the power change limit per unit time on the generation side, power balance constraints and low-voltage distribution line transmission constraints are established. The power balance constraint is expressed as:

[0023] in, Connected to medium voltage transmission lines b The fluctuation power and, where b Indicates the first b One high-voltage line; x This represents the total number of lines. t 1 represents the start time of the dynamic delay. t 3 represents the end time value of the dynamic delay time dimension; The power transmission constraint of the low-voltage distribution line is expressed as follows:

[0024] in, Low-voltage transmission lines j Limits on fluctuation power variation. The minimum transmission capacity of a low-voltage transmission line is the maximum charging power variation of line j during the time period t1 to t3. The value of t3 is calculated based on the power balance constraint and the low-voltage power distribution line transmission constraint. t1-t3 is the time length T2 required for dynamic delay.

[0025] By establishing power balance constraints for medium-voltage lines and transmission capacity constraints for low-voltage lines, and based on predicted charging power, line limits, and generation-side regulation capabilities, the required duration of dynamic delay is accurately calculated. Thus, while ensuring that lines at all levels of the distribution network do not exceed limits, the shortest delay window for the generation side to smoothly absorb power fluctuations is scientifically determined, achieving the optimal balance between system safety constraints and regulation efficiency.

[0026] Preferably, the calculation of the dynamic delay time in the spatial dimension and the dynamic delay time in the temporal dimension in step S6 includes: Based on the electrical connection position of each charging station in the distribution network topology, the power distribution limit, and the power change limit per unit time on the power generation side, the dynamic active power distribution on each low-voltage distribution line is configured by the spatial distance between the low-voltage distribution line connection point and the medium-voltage connection point, and the power transmission power and fluctuation power constraints of the low-voltage distribution line. Active power control is then performed through the active power controller. The dynamic delay time in the spatial dimension is calculated based on the segmented distances along the power transmission path, and the calculation method is as follows:

[0027] in, For the first n +1 distribution network low-voltage connection point delayed. n The delay time of each low-voltage connected node in the distribution network; The speed of electrical energy transmission is a fixed value that is less than the speed of light. S n+1 and S n These represent the distances between the (n+1)th and nth segments of the distribution network; The dynamic delay time in the time dimension is calculated based on the power change demand of all connected electric vehicle charging piles on the low-voltage distribution line, the control active power value set by the active power controller, and the power constraint requirements of the upward-collecting transmission and distribution lines. The calculation method is as follows:

[0028]

[0029]

[0030]

[0031] in, t 2 represents the end time of the spatial dimension delay in the dynamic delay, and also the start time of the temporal dimension delay. t 3 represents the end time value of the dynamic delay's time dimension; The fluctuating power value of low-voltage line j; for j The active power configured in the low-voltage power distribution line, T22 and T21 are the dynamic delay time in the time dimension and the dynamic delay time in the spatial dimension, respectively.

[0032] By combining the spatial location relationships of charging stations in the distribution network topology with the physical delay characteristics of power transmission, the dynamic delay time in the spatial dimension is calculated, enabling peak-shaving control of charging load start-up and shutdown on different lines. Simultaneously, based on charging power demand, active power setpoints, and line power constraints, the dynamic delay time in the temporal dimension is calculated, finely adjusting the timing allocation of charging power. The synergistic effect of these two methods achieves hierarchical and coordinated control of charging loads in both space and time, effectively smoothing out fluctuations in aggregated power in the grid and improving the synergy between distribution line utilization efficiency and generation-side power regulation.

[0033] Preferably, step S7, generating the guiding price signal corresponding to each charging station, includes: Construct a price guidance function with fixed price guidance, spatially delayed price guidance, and time-delayed price guidance. This function consists of the following parts: (1) Fixed delay duration setting function: In the formula, U It is a unit step function; t , T These are the timing of action 1 and the immediate time of the delayed action, respectively; U ( t ) is a step function with a fixed delay, and its value is... T 1; (2) Spatial price-guided time decay function: In the formula, It is a first-order inertial delay function; k The spatial price attenuation coefficient is the one used for dynamic delay. It is a time constant; t For time; (3) Price-driven time decay function over time: In the formula, This is a decay function that varies with time; kThis is the time decay coefficient for dynamic delay; t For time; (4) Time-delay decay function of trolley charging service fee: Functions for delayed price changes:

[0034]

[0035] in, The instantaneous change in charging price at different times; The service benchmark fee for the charging station service company for the next period; The benchmark electricity price for charging companies before the price change; This represents the fixed delay duration within the overall delay range, considering the distribution network's resilience. For distribution network robustness coefficient; For the dynamic delay time in the spatial dimension, where t 1 represents the end time of the fixed delay, and also the start time of the spatial delay in the dynamic delay. t 2 represents the end time of the spatial dimension delay of the dynamic delay, and also the start time of the temporal dimension delay of the dynamic delay. It refers to the dynamic delay time in the time dimension. t 3 represents the end time value of the time dimension delay of the dynamic delay; k1 is the spatial dimension delay correction coefficient of the dynamic delay; k2 is the time dimension delay correction coefficient of the dynamic delay. Based on the fixed delay time, the dynamic delay time in the time dimension, and the dynamic delay time in the spatial dimension, a guiding price signal corresponding to each charging station is generated through the price guiding function.

[0036] By constructing a composite price guidance function that integrates fixed delay, spatial delay, and temporal delay, and introducing a refined price decay mechanism based on step function, inertial delay, and exponential decay, it is possible to generate differentiated and dynamically changing guidance price signals in time and space according to the actual impact on the power grid and adjustment needs. This effectively incentivizes electric vehicle users to actively adjust their charging behavior, ensuring the safe and stable operation of the distribution network while achieving optimized temporal and spatial allocation of charging load and precise pricing of power resources.

[0037] The electric vehicle charging behavior guidance pricing mechanism system of the present invention includes: The data acquisition module is used to acquire the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. The fluctuation judgment module is used to determine, based on the predicted value of the change in charging power demand, whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. A fixed delay setting module is used to determine that the power fluctuation exceeds the instantaneous power regulation capability of the generation side if the change in the charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, and to set a fixed delay time. The dynamic delay calculation module is used to calculate the end time of the dynamic delay based on the predicted value of the change in charging power demand, the preset power limit of medium voltage transmission lines and the power change limit per unit time on the generation side, and to determine the required time length of the dynamic delay based on the fixed delay time and the end time of the dynamic delay. The power allocation module is used to predict the charging power demand of each electric vehicle charging station in the next scheduling cycle based on historical charging data and real-time load information, and to allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. The multi-dimensional delay calculation module is used to calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the temporal dimension based on the time length required for the dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side. The price signal generation module is used to generate a guiding price signal corresponding to each charging station based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension.

[0038] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: 1. By predicting the potential surge in concentrated charging power during time-of-use pricing switching periods, a fixed delay mechanism is introduced to proactively delay the charging start-up time of some vehicles, reserving buffer time for power adjustment on the generation side. This effectively avoids instantaneous power exceeding the grid limit due to concentrated start-stop of electric vehicles, ensuring the safe and stable operation of the system; 2. The delay mechanism is expanded from a single time dimension to two dimensions: space and time. By calculating spatial dynamic delay and temporal dynamic delay, differentiated and refined power allocation and start-up can be performed for charging stations with different geographical locations and power demands based on grid topology, line capacity constraints, and generation side adjustment capabilities. 3. By introducing guiding price signals, a price gradient can be formed, incentivizing electric vehicle users to voluntarily shift their charging behavior from high-carbon-emission, high-load-pressure periods and lines to low-carbon-emission, high-new-energy-penetration periods and lines, thereby actively participating in grid peak shaving, promoting clean energy consumption and reducing the overall carbon footprint of the charging process; 4. When allocating the active power setpoints for each charging station, the distribution network topology and power constraints of the distribution lines are strictly followed, avoiding the risk of local line overload, balancing the load of each level of line, thereby meeting the charging needs of large-scale electric vehicles while reducing the pressure on power distribution equipment, delaying equipment upgrade investment, and significantly improving the reliability of regional power supply. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram illustrating the segmented calculation of the spatial dimension of distribution network delay price in this invention; Figures 3-4 This is a simulation diagram of the elastic price change curve under the dynamic delay parameters of the present invention; Figures 5-6 This is a simulation diagram of the elastic price change curves corresponding to different dynamic delay parameters of 10 low-voltage distribution lines in the regional distribution network of the present invention. Figure 7 This is a comparison chart showing the effectiveness of the "dual high" features of the present invention in guiding electric vehicle charging power. Detailed Implementation

[0040] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0041] This invention provides a method for a pricing mechanism to guide electric vehicle charging behavior, such as... Figure 1 As shown, it includes the following steps: S1. Obtain the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. S2. Based on the predicted value of the change in charging power demand, determine whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. S3. If the change in charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, it is determined that the power fluctuation exceeds the instantaneous power regulation capability of the generation side, and a fixed delay time is set. S4. Calculate the dynamic delay end time based on the predicted value of the charging power demand change, the preset power limit of the medium voltage transmission line, and the power change limit per unit time on the power generation side, and determine the required time length of the dynamic delay based on the fixed delay time and the dynamic delay end time. S5. Based on historical charging data and real-time load information, predict the charging power demand of each electric vehicle charging station in the next scheduling cycle, and allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. S6. Based on the required time length for dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side, calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the time dimension respectively. S7. Based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension, generate a guiding price signal corresponding to each charging station.

[0042] Furthermore, obtaining the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at predetermined times includes: Calculate the absolute value of the difference between the predicted changes in charging power demand of all electric vehicles connected to medium-voltage or low-voltage transmission and distribution lines between the current time t and the next time t+1, and use this as the total change in charging power demand of the line at the next time. Specifically, for medium-voltage or low-voltage transmission and distribution lines, the total change in charging power demand... The calculation formula is:

[0043] in, for t The next moment T Total change in charging power demand of connected electric vehicles under different voltage levels; , Charging piles i exist t Moment and the next moment t +1 power prediction value; n It refers to the number of charging piles in the area covered by the medium-voltage distribution network.

[0044] Furthermore, the total change in charging power demand between the medium-voltage transmission and distribution lines and the low-voltage transmission and distribution lines satisfies the following power balance constraints: The total change in charging power demand of a medium-voltage transmission and distribution line at the next moment is equal to the sum of the total changes in charging power demand of all m low-voltage transmission and distribution lines under its jurisdiction at the same moment, that is:

[0045] in, for t The total change in charging power demand of the tram connected to the medium-voltage transmission line at the next moment; The first under the jurisdiction of medium voltage distribution network j Changes in charging pile power demand for a low-voltage transmission line; m It refers to the number of low-voltage transmission lines in the area covered by the medium-voltage distribution network.

[0046] Furthermore, the present invention defines a carbon emission intensity coefficient per unit of electricity for transmission and distribution lines in the distribution network, the carbon emission intensity coefficient per unit of electricity being composed of the sum of the following two proportions: The proportion of newly connected electricity generated from primary energy sources on this section of the power transmission and distribution line to the total newly connected electricity of the entire network; The proportion of total carbon emissions generated by all generating units from the power generation side to the transmission and distribution line section to their total transmitted electricity.

[0047] Furthermore, determining whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point includes: The maximum power fluctuation at the grid connection point on the generation side is calculated using the following expression:

[0048] in, This represents the maximum power fluctuation at the grid connection point on the generation side. These are unit parameters, including attribute parameters such as unit status and unit type; The generating unit corresponding to the grid connection point on the power generation side k The instantaneous change in output power is determined by the current state and type of the generator set and its corresponding ramp / landslide rate parameters; k , y The first k Total y Each unit, t 0 is the value at the start time of the fixed delay. t 1 is the value of the end time of the fixed delay, and also the value of the start time of the spatial delay of the dynamic delay; The predicted value of the change in charging power demand is compared with For comparison, if the change in charging power demand for any line exceeds... If the change in charging power demand of the line exceeds the power fluctuation range limit of the grid connection point, then it is determined that the change exceeds the limit limit.

[0049] Furthermore, setting a fixed delay time includes: When it is determined that the change in charging power demand of medium-voltage or low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point, a fixed delay time is set. T 1. The calculation method is as follows:

[0050] in, T 1 represents the set fixed delay time; the fixed delay time T 1. Used to delay the charging start time of electric vehicles on the corresponding line, providing the necessary preparation time for the power generation side to adjust the power; Calculate the end time of the fixed delay based on the calculated fixed delay duration. t 1. The value of the end time of the fixed delay is also the value of the start time of the spatial delay of the dynamic delay. The calculation method is shown in the following formula: .

[0051] Furthermore, the calculation of the time required for dynamic delay includes: Based on the predicted value of charging power demand change, the preset power limit of medium-voltage transmission lines and the power change limit per unit time on the generation side, power balance constraints and low-voltage distribution line transmission constraints are established. The power balance constraint is expressed as:

[0052] in, Connected to medium voltage transmission lines b The fluctuation power and, where b Indicates the first b One high-voltage line; x This represents the total number of lines. t 1 represents the start time of the dynamic delay. t 3 represents the end time value of the dynamic delay time dimension; The power transmission constraint of the low-voltage distribution line is expressed as follows:

[0053] in, Low-voltage transmission lines j Limits on fluctuation power variation. The minimum transmission capacity of a low-voltage transmission line is the maximum charging power variation of line j during the time period t1 to t3. The value of t3 is calculated based on the power balance constraint and the low-voltage power distribution line transmission constraint. t1-t3 is the time length T2 required for dynamic delay.

[0054] Furthermore, the calculation of dynamic latency in the spatial dimension and dynamic latency in the temporal dimension includes: Based on the electrical connection position of each charging station in the distribution network topology, the power distribution limit, and the power change limit per unit time on the power generation side, the dynamic active power distribution on each low-voltage distribution line is configured by the spatial distance between the low-voltage distribution line connection point and the medium-voltage connection point, and the power transmission power and fluctuation power constraints of the low-voltage distribution line. Active power control is then performed through the active power controller. like Figure 2 As shown, the dynamic delay time in the spatial dimension is calculated based on the segmented distances along the power transmission path, and the calculation method is as follows:

[0055] in, For the first n +1 distribution network low-voltage connection point delayed. n The delay time of each low-voltage connected node in the distribution network; The speed of electrical energy transmission is a fixed value that is less than the speed of light. S n+1 and S n These represent the distances between the (n+1)th and nth segments of the distribution network; The dynamic delay time in the time dimension is calculated based on the power change demand of all connected electric vehicle charging piles on the low-voltage distribution line, the control active power value set by the active power controller, and the power constraint requirements of the upward-collecting transmission and distribution lines. The calculation method is as follows:

[0056]

[0057]

[0058]

[0059] in, t 2 represents the end time of the spatial dimension delay in the dynamic delay, and also the start time of the temporal dimension delay. t 3 represents the end time value of the dynamic delay's time dimension; This represents the fluctuating power value of low-voltage line j. for j The active power configured in the low-voltage power distribution line, T22 and T21 are the dynamic delay time in the time dimension and the dynamic delay time in the spatial dimension, respectively.

[0060] Furthermore, generating guiding price signals corresponding to each charging station includes: Construct a price guidance function with fixed price guidance, spatially delayed price guidance, and time-delayed price guidance. This function consists of the following parts: (1) Fixed delay duration setting function: In the formula, U It is a unit step function; t , T These are the timing of action 1 and the immediate time of the delayed action, respectively; U ( t ) is a step function with a fixed delay, and its value is... T 1; (2) Spatial price-guided time decay function: In the formula, It is a first-order inertial delay function; k The spatial price attenuation coefficient is the one used for dynamic delay. It is a time constant; t For time; (3) Price-driven time decay function over time: In the formula, This is a decay function that varies with time; k This is the time decay coefficient for dynamic delay; t For time; (4) Time-delay decay function of trolley charging service fee:

[0061] Functions for delayed price changes: ; ;in, The instantaneous change in charging price at different times; The service benchmark fee for the charging station service company for the next period; The benchmark electricity price for charging companies before the price change; This represents the fixed delay duration within the overall delay range, considering the distribution network's resilience. For distribution network robustness coefficient; For the dynamic delay time in the spatial dimension, where t 1 represents the end time of the fixed delay, and also the start time of the spatial delay in the dynamic delay. t2 represents the end time of the spatial dimension delay of the dynamic delay, and also the start time of the temporal dimension delay of the dynamic delay. It refers to the dynamic delay time in the time dimension. t 3 represents the end time value of the time dimension delay of the dynamic delay; k1 is the spatial dimension delay correction coefficient of the dynamic delay; k2 is the time dimension delay correction coefficient of the dynamic delay. Based on the fixed delay time, the dynamic delay time in the time dimension, and the dynamic delay time in the spatial dimension, a guiding price signal corresponding to each charging station is generated through the price guiding function.

[0062] Based on the spatial dimension delay and dynamic dimension delay duration requirements of fixed delay and dynamic delay in step 6, and combined with the electric vehicle charging price guidance method in step 7, data calculation and verification were conducted. The guiding price change trends during the transition from high-price periods to low-price periods and from low-price periods to high-price periods were calculated, as shown below. Figure 3 and Figure 4 As shown. The guiding price between the blue and red dashed lines remains unchanged, serving as a fixed delayed price, maintaining the previous time-of-use price and guiding electric vehicle charging to continue in its original charging state. The guiding price curve between the red and green curves represents the dynamic guiding price corresponding to the spatial dimension of dynamic delay. The slope of the guiding price change is set according to the electric vehicle charging rate, and the K1 value is adjusted accordingly. The curve to the right of the green dashed line represents the dynamic guiding price corresponding to the time dimension of dynamic delay. The slope of the guiding price change is set according to the electric vehicle charging rate, and the K2 value is adjusted accordingly. Through these three stages of guiding price changes, the "vehicle-grid interaction" between electric vehicle charging and the main power grid, distribution network, and charging stations under the "high-energy-consuming and high-polluting" characteristics is guided.

[0063] exist Figure 3 and Figure 4 Based on this, by adjusting the time dimension of fixed delay and dynamic delay, the starting time of the spatial dimension of dynamic delay, and the values ​​of guiding coefficients K1 and K2, the price guiding trend curves from low-price periods to high-price periods and from high-price periods to low-price periods are respectively as follows: Figure 5 , Figure 6 As shown, it can provide the necessary electric vehicle charging start-stop and delay support for different power grid conditions and power grid structures.

[0064] To verify this method, the actual electricity consumption curve (blue curve) of a city in East China was used as a basis to simulate the instantaneous power surge caused by charging electric vehicles with "high-voltage and high-efficiency" characteristics. Figure 7As shown by the green curve in the figure; according to the method proposed in this paper, by simulating the power guidance during the peak-valley transition period, as shown by the red curve in the figure, it can be seen that the red curve basically coincides with the blue curve, which guides and adjusts the consistent charging behavior caused by time-of-use pricing, thereby reducing the impact of the consistent charging behavior of "high-energy-consuming and high-demand" electric vehicles on the power grid.

[0065] Based on a similar inventive concept, this invention also provides an electric vehicle charging behavior guidance pricing mechanism system corresponding to the aforementioned electric vehicle charging behavior guidance pricing mechanism method, comprising: The data acquisition module is used to acquire the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. The fluctuation judgment module is used to determine, based on the predicted value of the change in charging power demand, whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. A fixed delay setting module is used to determine that the power fluctuation exceeds the instantaneous power regulation capability of the generation side if the change in the charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, and to set a fixed delay time. The dynamic delay calculation module is used to calculate the end time of the dynamic delay based on the predicted value of the change in charging power demand, the preset power limit of medium voltage transmission lines and the power change limit per unit time on the generation side, and to determine the required time length of the dynamic delay based on the fixed delay time and the end time of the dynamic delay. The power allocation module is used to predict the charging power demand of each electric vehicle charging station in the next scheduling cycle based on historical charging data and real-time load information, and to allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. The multi-dimensional delay calculation module is used to calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the temporal dimension based on the time length required for the dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side. The price signal generation module is used to generate a guiding price signal corresponding to each charging station based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension.

Claims

1. A pricing mechanism for guiding electric vehicle charging behavior, characterized in that, Includes the following steps: S1. Obtain the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. S2. Based on the predicted value of the change in charging power demand, determine whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. S3. If the change in charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, it is determined that the power fluctuation exceeds the instantaneous power regulation capability of the generation side, and a fixed delay time is set. S4. Calculate the dynamic delay end time based on the predicted value of the charging power demand change, the preset power limit of the medium voltage transmission line, and the power change limit per unit time on the power generation side, and determine the required time length of the dynamic delay based on the fixed delay time and the dynamic delay end time. S5. Based on historical charging data and real-time load information, predict the charging power demand of each electric vehicle charging station in the next scheduling cycle, and allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. S6. Based on the required time length for dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side, calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the time dimension respectively. S7. Based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension, generate a guiding price signal corresponding to each charging station.

2. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, Step S1, which involves obtaining the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time, includes: Calculate the absolute value of the difference between the predicted changes in charging power demand of all electric vehicles connected to medium-voltage or low-voltage transmission and distribution lines between the current time t and the next time t+1, and use this as the total change in charging power demand of the line at the next time. Specifically, for medium-voltage or low-voltage transmission and distribution lines, the total change in charging power demand... The calculation formula is: ;in, for t The next moment T Total change in charging power demand of connected electric vehicles under different voltage levels; , Charging piles i exist t Moment and the next moment t +1 power prediction value; n It refers to the number of charging piles in the area covered by the medium-voltage distribution network.

3. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, The total change in charging power demand of the medium-voltage transmission and distribution lines and the low-voltage transmission and distribution lines satisfies the following power balance constraints: The total change in charging power demand of a medium-voltage transmission and distribution line at the next moment is equal to the sum of the total changes in charging power demand of all m low-voltage transmission and distribution lines under its jurisdiction at the same moment, that is: ;in, for t The total change in charging power demand of the tram connected to the medium-voltage transmission line at the next moment; The first under the jurisdiction of medium voltage distribution network j Changes in charging pile power demand for a low-voltage transmission line; m It refers to the number of low-voltage transmission lines in the area covered by the medium-voltage distribution network.

4. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, The method further includes: A carbon emission intensity coefficient per unit of electricity is defined for the transmission and distribution lines in the distribution network. This coefficient is the sum of the following two proportions: The proportion of newly connected electricity generated from primary energy sources on this section of the power transmission and distribution line to the total newly connected electricity of the entire network; The proportion of total carbon emissions generated by all generating units from the power generation side to the transmission and distribution line section to their total transmitted electricity.

5. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, Step S2, which involves determining whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point, includes: The maximum power fluctuation at the grid connection point on the generation side is calculated using the following expression: ;in, This represents the maximum power fluctuation at the grid connection point on the generation side. These are unit parameters, including attribute parameters such as unit status and unit type; The generating unit corresponding to the grid connection point on the power generation side k The instantaneous change in output power is determined by the current state and type of the generator set and its corresponding ramp / landslide rate parameters; k , y The first k Total y Each unit, t 0 is the value at the start time of the fixed delay. t 1 is the value of the end time of the fixed delay, and also the value of the start time of the spatial delay of the dynamic delay; The predicted value of the change in charging power demand is compared with For comparison, if the change in charging power demand for any line exceeds... If the change in charging power demand of the line exceeds the power fluctuation range limit of the grid connection point, then it is determined that the change exceeds the limit limit.

6. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, The setting of the fixed delay time in step S3 includes: When it is determined that the change in charging power demand of medium-voltage or low-voltage transmission and distribution lines exceeds the power fluctuation range limit at the grid connection point, a fixed delay time is set. T 1. The calculation method is as follows: ;in, T 1 represents the set fixed delay time; the fixed delay time T 1. Used to delay the charging start time of electric vehicles on the corresponding line, providing the necessary preparation time for the power generation side to adjust the power; Calculate the end time of the fixed delay based on the calculated fixed delay duration. t 1. The value of the end time of the fixed delay is also the value of the start time of the spatial delay of the dynamic delay. The calculation method is shown in the following formula: 。 7. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, The calculation of the required time for dynamic delay in step S4 includes: Based on the predicted value of charging power demand change, the preset power limit of medium-voltage transmission lines and the power change limit per unit time on the generation side, power balance constraints and low-voltage distribution line transmission constraints are established. The power balance constraint is expressed as: ;in, Connected to medium voltage transmission lines b The fluctuation power and, where b Indicates the first b One high-voltage line; x This represents the total number of lines. t 1 represents the start time of the dynamic delay. t 3 represents the end time value of the dynamic delay time dimension; The power transmission constraint of the low-voltage distribution line is expressed as follows: ;in, Low-voltage transmission lines j Limits on fluctuation power variation. The minimum transmission capacity of a low-voltage transmission line is the maximum charging power variation of line j during the time period t1 to t3. The value of t3 is calculated based on the power balance constraint and the low-voltage power distribution line transmission constraint. t1-t3 is the time length T2 required for dynamic delay.

8. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, Step S6 involves calculating the dynamic delay time in the spatial dimension and the dynamic delay time in the temporal dimension, which includes: Based on the electrical connection position of each charging station in the distribution network topology, the power distribution limit, and the power change limit per unit time on the power generation side, the dynamic active power distribution on each low-voltage distribution line is configured by the spatial distance between the low-voltage distribution line connection point and the medium-voltage connection point, and the power transmission power and fluctuation power constraints of the low-voltage distribution line. Active power control is then performed through the active power controller. The dynamic delay time in the spatial dimension is calculated based on the segmented distances along the power transmission path, and the calculation method is as follows: ;in, For the first n +1 distribution network low-voltage connection point delayed. n The delay time of each low-voltage connected node in the distribution network; The speed of electrical energy transmission is a fixed value that is less than the speed of light. S n+1 and S n These represent the distances between the (n+1)th and nth segments of the distribution network; The dynamic delay time in the time dimension is calculated based on the power change demand of all connected electric vehicle charging piles on the low-voltage distribution line, the control active power value set by the active power controller, and the power constraint requirements of the upward-collecting transmission and distribution lines. The calculation method is as follows: ; ; ; ;in, t 2 represents the end time of the spatial dimension delay in the dynamic delay, and also the start time of the temporal dimension delay. t 3 represents the end time value of the dynamic delay's time dimension; The fluctuating power value of low-voltage line j; for j The active power configured in the low-voltage power distribution line, T22 and T21 are the dynamic delay time in the time dimension and the dynamic delay time in the spatial dimension, respectively.

9. The electric vehicle charging behavior guidance pricing mechanism method according to claim 1, characterized in that, Step S7, which involves generating a guiding price signal corresponding to each charging station, includes: Construct a price guidance function with fixed price guidance, spatially delayed price guidance, and time-delayed price guidance. This function consists of the following parts: (1) Fixed delay duration setting function: In the formula, U It is a unit step function; t , T These are the timing of action 1 and the immediate time of the delayed action, respectively; U ( t ) is a step function with a fixed delay, and its value is... T 1; (2) Spatial price-guided time decay function: In the formula, It is a first-order inertial delay function; k The spatial price attenuation coefficient is the one used for dynamic delay. It is a time constant; t For time; (3) Price-driven time decay function over time: In the formula, This is a decay function that varies with time; k This is the time decay coefficient for dynamic delay; t For time; (4) Time-delay decay function of trolley charging service fee: Functions for delayed price changes: ; ;in, The instantaneous change in charging price at different times; The service benchmark fee for the charging station service company for the next period; The benchmark electricity price for charging companies before the price change; This represents the fixed delay duration within the overall delay range, considering the distribution network's resilience. For distribution network robustness coefficient; For the dynamic delay time in the spatial dimension, where t 1 represents the end time of the fixed delay, and also the start time of the spatial delay in the dynamic delay. t 2 represents the end time of the spatial dimension delay of the dynamic delay, and also the start time of the temporal dimension delay of the dynamic delay. It refers to the dynamic delay time in the time dimension. t 3 represents the end time value of the time dimension delay of the dynamic delay; k1 is the spatial dimension delay correction coefficient of the dynamic delay; k2 is the time dimension delay correction coefficient of the dynamic delay. Based on the fixed delay time, the dynamic delay time in the time dimension, and the dynamic delay time in the spatial dimension, a guiding price signal corresponding to each charging station is generated through the price guiding function.

10. A pricing mechanism system for guiding electric vehicle charging behavior, characterized in that, include The data acquisition module is used to acquire the predicted changes in charging power demand of electric vehicles connected to medium-voltage and low-voltage transmission and distribution lines in the distribution network at a predetermined time. The fluctuation judgment module is used to determine, based on the predicted value of the change in charging power demand, whether the change in charging power demand of the medium-voltage and low-voltage transmission and distribution lines exceeds the limit of the power fluctuation range at the grid connection point. A fixed delay setting module is used to determine that the power fluctuation exceeds the instantaneous power regulation capability of the generation side if the change in the charging power demand of the medium-voltage or low-voltage transmission and distribution line exceeds the power fluctuation range limit of the grid connection point, and to set a fixed delay time. The dynamic delay calculation module is used to calculate the end time of the dynamic delay based on the predicted value of the change in charging power demand, the preset power limit of medium voltage transmission lines and the power change limit per unit time on the generation side, and to determine the required time length of the dynamic delay based on the fixed delay time and the end time of the dynamic delay. The power allocation module is used to predict the charging power demand of each electric vehicle charging station in the next scheduling cycle based on historical charging data and real-time load information, and to allocate active power setpoints to each charging station according to the distribution network topology and power constraints of the distribution lines. The multi-dimensional delay calculation module is used to calculate the dynamic delay time in the spatial dimension and the dynamic delay time in the temporal dimension based on the time length required for the dynamic delay, the spatial distribution of each charging station in the distribution network topology, the active power setting value, and the power change limit per unit time on the power generation side. The price signal generation module is used to generate a guiding price signal corresponding to each charging station based on the fixed delay time, the dynamic delay time in the spatial dimension, and the dynamic delay time in the time dimension.

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