Charging pile layout optimization method and system for tea area

Abstract

The invention discloses a tea area-oriented charging pile layout optimization method and system, and the method comprises the steps: respectively building objective functions through minimizing the multi-main-body comprehensive cost of an electric vehicle charging service provider, a power grid company and a user, maximizing the utilization rate of a charging facility, and maximizing the local consumption rate of new energy; and by taking the charging facility type selection, the charging facility scale and the charging facility space layout as decision variables, constructing a tea area charging pile layout optimization model according to a plurality of objective functions, the decision variables and constraint conditions, and solving the tea area charging pile layout optimization model to obtain an optimal tea area charging pile layout optimization scheme. According to the method, the multi-subject economy is fully considered, multi-objective optimization is realized, and safe, economic and green development requirements are considered, so that the problem of seasonal heavy overload in a tea area is effectively solved while the local charging requirement is fully met, and the requirements of green tea making and photovoltaic local absorption are met.

Description

Technical Field

[0001] The present invention relates to the field of charging pile layout, and in particular to a charging pile layout optimization method and system for tea areas. Background Art

[0002] New energy sources such as distributed photovoltaics have been widely developed. The development of the "tea-photovoltaic complementary" model has promoted the rapid development of distributed photovoltaics in tea areas. The trend of automobile electrification transformation has accelerated the demand for charging network construction in tea areas. The electricity load in the tea area is an obvious seasonal load. The peak load during the tea picking season is about 10 times the daily average load. After the end of the tea picking season, the load in the substation drops sharply. The distribution transformers in the tea area often show obvious seasonal heavy overloads, but the equipment utilization rate is low throughout the year. Therefore, how to optimize the layout planning of charging piles in the tea area, take into account the local consumption of photovoltaic resources, alleviate the problem of seasonal heavy overload of electricity in the tea area, and achieve the comprehensive goals of safety, economy, and greenness is a problem that needs to be considered in the future layout planning of charging networks in tea areas.

[0003] At present, the layout planning of my country's charging infrastructure is more focused on areas with intensive charging demand, such as urban areas and industrial parks, and has not yet effectively covered remote areas such as tea-growing areas. The existing charging pile construction and operation plans in tea-growing areas do not fully consider the electricity consumption characteristics and charging needs of tea-growing areas. The configuration of charging piles cannot meet the charging needs of tea-growing areas, resulting in low utilization rates of some charging piles and insufficient configuration of charging piles in some areas. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a charging pile layout optimization method and system for tea-growing areas, which can effectively solve the seasonal heavy overload problem in tea-growing areas while fully meeting local charging needs, and meet the needs of green tea making and local photovoltaic consumption.

[0005] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0006] A charging pile layout optimization method for tea areas, comprising the steps of:

[0007] The first objective function is established with the goal of minimizing the comprehensive cost of multiple entities including electric vehicle charging service providers, power grid companies and users, and the second objective function is established with the goal of maximizing the utilization rate of charging facilities;

[0008] The third objective function is established with the goal of maximizing the local consumption rate of new energy, and the selection of charging facilities, the scale of charging facilities, and the spatial layout of charging facilities are used as decision variables;

[0009] Establishing constraint conditions, and constructing a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraint conditions;

[0010] The tea area charging pile layout optimization model is solved to obtain the optimal tea area charging pile layout optimization plan.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] A charging pile layout optimization system for tea areas includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0013] The first objective function is established with the goal of minimizing the comprehensive cost of multiple entities including electric vehicle charging service providers, power grid companies and users, and the second objective function is established with the goal of maximizing the utilization rate of charging facilities;

[0014] The third objective function is established with the goal of maximizing the local consumption rate of new energy, and the selection of charging facilities, the scale of charging facilities, and the spatial layout of charging facilities are used as decision variables;

[0015] Establishing constraint conditions, and constructing a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraint conditions;

[0016] The tea area charging pile layout optimization model is solved to obtain the optimal tea area charging pile layout optimization plan.

[0017] The beneficial effects of the present invention are as follows: objective functions are established respectively to minimize the comprehensive costs of multiple subjects including electric vehicle charging service providers, power grid companies and users, to maximize the utilization rate of charging facilities, and to maximize the local consumption rate of new energy, and the selection of charging facilities, the scale of charging facilities and the spatial layout of charging facilities are used as decision variables. A charging pile layout optimization model for the tea area is constructed according to multiple objective functions, decision variables and constraints, and the charging pile layout optimization model for the tea area is solved to obtain the optimal charging pile layout optimization plan for the tea area. The economy of multiple subjects is fully considered, and multi-objective optimization is achieved by establishing three objective functions, taking into account the development needs of safety, economy and greenness, so as to effectively solve the seasonal heavy overload problem in the tea area while fully meeting the local charging needs, and meet the needs of green tea making and local consumption of photovoltaic power. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of the steps of a charging pile layout optimization method for a tea area according to an embodiment of the present invention;

[0019] Figure 2 This is a structural schematic diagram of a charging pile layout optimization system for tea areas according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of optimization in the charging pile layout optimization method for tea areas according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0022] Please refer to Figure 1 , a charging pile layout optimization method for tea areas, comprising the steps of:

[0023] The first objective function is established with the goal of minimizing the comprehensive cost of multiple entities including electric vehicle charging service providers, power grid companies and users, and the second objective function is established with the goal of maximizing the utilization rate of charging facilities;

[0024] The third objective function is established with the goal of maximizing the local consumption rate of new energy, and the selection of charging facilities, the scale of charging facilities, and the spatial layout of charging facilities are used as decision variables;

[0025] Establishing constraint conditions, and constructing a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraint conditions;

[0026] The tea area charging pile layout optimization model is solved to obtain the optimal tea area charging pile layout optimization plan.

[0027] From the above description, it can be seen that the beneficial effects of the present invention are: to minimize the comprehensive costs of multiple subjects including electric vehicle charging service providers, power grid companies and users, to maximize the utilization rate of charging facilities, and to maximize the local consumption rate of new energy, respectively, to establish objective functions, and to use the selection of charging facilities, the scale of charging facilities and the spatial layout of charging facilities as decision variables, to construct a charging pile layout optimization model in the tea area according to multiple objective functions, decision variables and constraints, to solve the charging pile layout optimization model in the tea area, to obtain the optimal charging pile layout optimization plan in the tea area, to fully consider the economic efficiency of multiple subjects, to achieve multi-objective optimization by establishing three objective functions, to take into account the development needs of safety, economy and greenness, so as to fully meet the local charging needs, to effectively solve the seasonal heavy overload problem in the tea area, and to meet the needs of green tea making and local photovoltaic consumption.

[0028] Furthermore, the first objective function is established with the goal of minimizing the multi-agent comprehensive cost of electric vehicle charging service providers, power grid companies and users, including:

[0029] Calculate the construction and operation and maintenance comprehensive conversion costs of electric vehicle charging service providers based on the operation and maintenance costs of charging piles, and determine the user's charging power, the user's discharging power, the charging service fee, and the discharging service fee;

[0030] Calculate the comprehensive cost of the electric vehicle charging service provider based on the comprehensive converted cost of construction and operation and maintenance, the charging power of the user, the discharging power of the user, the charging service fee and the discharging service fee;

[0031] Calculate the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period according to the net load of the substation area, and calculate the V2G demand response fee that the power grid company needs to provide according to the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period;

[0032] Calculate the comprehensive cost of the grid company based on the V2G demand response fee that the grid company needs to provide and the charging power of the user;

[0033] Calculate the charging pile discharge compensation price during demand response according to the discharge service fee, and calculate the user's comprehensive cost according to the charging pile discharge compensation price during demand response, the user's charging power, the user's discharge power and the charging service fee;

[0034] Generate a multi-subject comprehensive cost of the electric vehicle charging service provider, the power grid company and the user according to the comprehensive cost of the electric vehicle charging service provider, the comprehensive cost of the power grid company and the comprehensive cost of the user;

[0035] The first objective function is generated by minimizing the multi-agent comprehensive cost of the electric vehicle charging service provider, the power grid company and the user.

[0036] From the above description, it can be seen that the generated first objective function can comprehensively consider the costs of electric vehicle charging service providers (virtual power plants), power grid companies, and users, and ensure the economic efficiency of charging pile layout optimization while meeting charging needs and safe operation of the power grid.

[0037] Furthermore, the comprehensive cost of the electric vehicle charging service provider is calculated based on the comprehensive converted cost of construction and operation and maintenance, the charging power of the user, the discharging power of the user, the charging service fee and the discharging service fee, specifically:

[0038]

[0039] In the formula, S fw represents the comprehensive cost of electric vehicle charging service providers, S T represents the comprehensive converted cost of construction and operation and maintenance of electric vehicle charging service providers during the T period, represents the charging power of the user at time t, represents the charging service fee at time t, represents the discharge power of the user at time t, Represents the discharge service fee at time t.

[0040] From the above description, it can be seen that for electric vehicle charging service providers, on the one hand, they provide charging pile installation and operation and maintenance services, and on the other hand, they obtain service fees by providing charging and discharging services. Therefore, the comprehensive cost of electric vehicle charging service providers needs to be calculated based on the comprehensive converted cost of construction and operation and maintenance, the user's charging power, the user's discharging power, the charging service fee and the discharging service fee.

[0041] Furthermore, the comprehensive cost of the grid company is calculated based on the V2G demand response fee that the grid company needs to provide and the charging power of the user, specifically:

[0042]

[0043] In the formula, S grid represents the comprehensive cost of the power grid company, S dr represents the V2G demand response fee that the power grid company needs to provide, T represents the time period, represents the charging power of the user at time t, Represents the charging price of the charging pile at time t.

[0044] From the above description, it can be seen that for the power grid company, it is necessary to ensure safe and stable power supply in the tea area and solve the problem of seasonal heavy overload in the substation. One way is to increase the carrying capacity by increasing the capacity of equipment, which requires expenditure on equipment capacity increase; another way is to use the demand response mechanism to guide electric vehicle users to charge when new energy is booming, and discharge to the grid through V2G (Vehicle-to-Grid) piles during the period of heavy overload in the substation to solve the problem of heavy overload in the substation. Since the tea area is seasonally heavily overloaded and there are fewer periods of heavy overload, the cost of equipment capacity increase is generally greater than the demand response cost (within the entire life cycle of the equipment), and the equipment utilization rate after capacity increase is low, so the demand response method will have better economic efficiency. Therefore, the comprehensive cost of the power grid company is calculated based on the V2G demand response fee that the power grid company needs to provide and the charging power of the user.

[0045] Furthermore, the comprehensive cost of the user is calculated according to the charging pile discharge compensation price during the demand response, the charging power of the user, the discharge power of the user and the charging service fee, specifically:

[0046]

[0047] In the formula, S yh represents the comprehensive cost of the user, T represents the time period, represents the charging power of the user at time t, represents the charging price of the charging pile at time t, represents the charging service fee at time t, represents the discharge power of the user at time t, Represents the charging pile discharge compensation price at time t of demand response.

[0048] From the above description, it can be seen that for users, they are both users of charging facilities and participants in demand response, so the user's comprehensive cost is calculated based on the charging pile discharge compensation price, the user's charging power, the user's discharge power and the charging service fee during demand response.

[0049] Furthermore, the second objective function is established with the goal of maximizing the utilization rate of charging facilities, specifically:

[0050]

[0051] In the formula, r represents the utilization rate of charging facilities, represents the charging power of the user at time t, Q ch represents the total capacity of the charging facilities in the tea area, T represents the time period, w1 represents the charging cost coefficient, w2 represents the charging convenience coefficient, Indicates the average charging service fee in the tea area, K max represents the maximum charging facility service fee that users can choose in the surrounding area, T' avg represents the average single charging time of the charging facilities in the tea area, T' max Indicates the maximum average single charging time of the charging facilities that users can choose in the area.

[0052] From the above description, it can be seen that the utilization rate of charging facilities is affected by many factors such as charging service radius, service fees, travel habits, and charging pile location. Therefore, the utilization rate of charging facilities is equivalent to the product of the charging cost coefficient and the charging convenience coefficient. The second objective function can ensure that the charging facility utilization rate of the final charging pile layout optimization plan is as large as possible.

[0053] Furthermore, the third objective function is established with the goal of maximizing the local consumption rate of new energy, specifically:

[0054]

[0055] In the formula, C pv (%) represents the local photovoltaic consumption rate, T represents the time period, represents the scale of local consumption of photovoltaic power generation at time t, represents the photovoltaic power generation at time t.

[0056] From the above description, it can be seen that combining photovoltaic output forecasts, considering demand response measures, and establishing a third objective function with the goal of maximizing the local consumption rate of new energy can improve power supply reliability and resilience and reduce power supply costs.

[0057] Furthermore, the establishing constraint condition includes:

[0058] Establish constraints on charging facility configuration capacity, economic constraints, grid operation constraints, electric vehicle charging and discharging constraints, and distributed power generation output constraints;

[0059] The charging facility configuration capacity constraint is specifically:

[0060]

[0061] In the formula, Q ch Indicates the total capacity of the charging facilities in the tea area. Indicates the charging power of the user at time t;

[0062] The economic constraints are specifically:

[0063] S dr,total zr ;

[0064] In the formula, S dr,total represents the lifetime demand response cost, S zr It represents the cost of capacity expansion and transformation of power grid equipment;

[0065] The power grid operation constraints are specifically:

[0066]

[0067]

[0068] In the formula, represents the total load demand at time t, represents the photovoltaic power generation at time t, Q n Indicates the rated capacity of the distribution transformer or line;

[0069] The electric vehicle charging and discharging constraints are specifically:

[0070]

[0071]

[0072] In the formula, Indicates the rated charging power of electric vehicles. Indicates the rated discharge power of electric vehicles, Indicates the maximum charging power of electric vehicles, ​represents the maximum discharge power of electric vehicles, i represents the tea area's own vehicles, transport vehicles and external vehicles;

[0073] The output constraints of the distributed power sources are specifically:

[0074]

[0075] Where P pv0 Indicates the maximum photovoltaic power generation power.

[0076] From the above description, it can be seen that establishing charging facility configuration capacity constraints, economic constraints, power grid operation constraints, electric vehicle charging and discharging constraints and distributed power output constraints can guide the generation of a practical optimal layout plan for charging piles. The charging facility configuration capacity constraints ensure that the formed optimized configuration plan can meet the maximum charging demand of the tea area. The economic constraints ensure that the demand response method is more economical than the equipment capacity expansion and transformation, so as to be more in line with the actual energy consumption of the tea area and ensure that the formed plan is more feasible. The power grid operation constraints ensure that the formed optimized plan can meet the basic requirements of power grid operation, that is, no overload in operation and no overload in the reverse transmission of new energy. The electric vehicle charging and discharging constraints ensure that the formed optimized plan can meet the capacity limitations of electric vehicle charging and discharging equipment. In addition, the distributed power output constraints ensure that the formed optimized plan can meet the capacity limitations of distributed power generation equipment.

[0077] Furthermore, the tea area charging pile layout optimization model is solved to obtain the optimal tea area charging pile layout optimization solution, which includes:

[0078] Using a multi-objective optimization algorithm to solve the tea area charging pile layout optimization model according to the first objective function and the second objective function in the tea area charging pile layout optimization model, a plurality of tea area charging pile layout optimization schemes are obtained;

[0079] According to the third objective function in the tea area charging pile layout optimization model, the optimal tea area charging pile layout optimization scheme is determined from the multiple tea area charging pile layout optimization schemes.

[0080] From the above description, it can be seen that the idea of ​​double-layer optimization is adopted when solving the model, and the optimal layout optimization plan of charging piles in the tea area is more scientific and effective.

[0081] Please refer to Figure 2 Another embodiment of the present invention provides a charging pile layout optimization system for tea areas, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step in the above-mentioned charging pile layout optimization method for tea areas is implemented.

[0082] The above-mentioned charging pile layout optimization method and system for tea areas of the present invention can be applied to tea areas, and the following is an explanation through specific implementation methods:

[0083] Please refer to Figure 1 and Figure 3 , Embodiment 1 of the present invention is:

[0084] A charging pile layout optimization method for tea areas, comprising the steps of:

[0085] S1. The first objective function is established with the goal of minimizing the comprehensive cost of multiple entities including electric vehicle charging service providers, power grid companies and users, and the second objective function is established with the goal of maximizing the utilization rate of charging facilities, specifically including S11-S18:

[0086] In an optional embodiment, if Figure 3 As shown, before S1, it also includes:

[0087] S0. Analyze the development status of the tea-growing area to obtain current status data, and conduct supply and demand forecast analysis based on the current status data to obtain the total charging demand of the tea-growing area and the net load of the substation considering the local consumption of photovoltaic power generation.

[0088] Specifically, analyze the distribution transformer and line operation conditions in the tea-growing area, with a focus on analyzing the seasonal heavy overload periods and load amounts of power supply equipment; analyze the charging demand for electric vehicles in the tea-growing area, including electric vehicles for self-use in the tea-growing area, electric transport logistics vehicles, and electric vehicles for external tea purchases, and analyze the charging demand characteristics and scale of different types of vehicles; analyze the current scale of distributed photovoltaic development, access conditions, output characteristics, and consumption conditions in the tea-growing area; combine the current status analysis results to form current status data; based on the current status data, consider the influence of local new factor development strategies, tea supply and demand, time-of-use electricity prices, user travel habits and other factors, carry out charging demand forecasts and new energy output forecasts, and obtain the overall load of the tea-growing area, electric vehicle charging demand, photovoltaic output, etc., to provide data support for the optimization of charging pile layout.

[0089] The total charging demand of the tea area is specifically:

[0090]

[0091] In the formula, represents the total charging demand of the tea area at time t, that is, the charging power of users at time t, It represents the charging demand of the tea area's own vehicles at time t, represents the charging demand of tea transport vehicles at time t, Indicates the charging demand of external vehicles in the tea area at time t.

[0092] The net load of the area considering the local consumption of photovoltaic power generation is specifically:

[0093]

[0094] In the formula, represents the net load of the substation at time t, represents the total load demand at time t, Represents the photovoltaic power generation at time t. When the area is overloaded, When the area is overloaded, When the photovoltaic transmission causes reverse overload in the area, Q n Indicates the rated capacity of the distribution transformer or line.

[0095] Users charge and discharge through electric vehicle charging service providers (virtual power plants). Users charge through charging piles under normal circumstances, participate in demand response through V2G piles during demand response periods, discharge to the grid during peak loads, and charge when new energy is generated. The charging and discharging fees are settled with the service providers. Therefore, the economic boundaries are analyzed around the three entities of electric vehicle charging service providers, power grid companies, and users, as follows:

[0096] S11. Calculate the comprehensive construction and operation and maintenance costs of the electric vehicle charging service provider based on the operation and maintenance costs of the charging piles, and determine the user's charging power, the user's discharging power, the charging service fee, and the discharging service fee.

[0097] The construction and operation and maintenance comprehensive conversion costs of electric vehicle charging service providers are calculated based on the operation and maintenance costs of charging piles, specifically:

[0098]

[0099] In the formula, S T represents the comprehensive converted cost of construction and operation and maintenance of electric vehicle charging service providers during the T period, n represents the number of charging piles configured, Z represents the comprehensive unit price of charging pile installation, m represents the cost conversion coefficient, Indicates the operation and maintenance cost of the charging pile.

[0100] S12. Calculate the comprehensive cost of the electric vehicle charging service provider based on the comprehensive converted cost of construction and operation and maintenance, the charging power of the user, the discharging power of the user, the charging service fee and the discharging service fee, specifically:

[0101]

[0102] In the formula, S fw represents the comprehensive cost of electric vehicle charging service providers, represents the charging service fee at time t, represents the discharge power of the user at time t, Represents the discharge service fee at time t.

[0103] S13. Calculate the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period according to the net load of the substation area, and calculate the V2G demand response fee that the power grid company needs to provide according to the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period, specifically:

[0104]

[0105]

[0106] In the formula, It represents the discharge demand of V2G issued by the power grid company to users during heavy overload period, S dr Indicates the V2G demand response fee that the grid company needs to provide, represents the V2G demand response compensation price at time t.

[0107] S14. Calculate the comprehensive cost of the grid company according to the V2G demand response fee that the grid company needs to provide and the charging power of the user, specifically:

[0108]

[0109] In the formula, S grid represents the comprehensive cost of the power grid company, T represents the time period, Indicates the charging price (electricity price part) of the charging pile at time t.

[0110] S15, calculating the charging pile discharge compensation price during demand response according to the discharge service fee, and calculating the user's comprehensive cost according to the charging pile discharge compensation price during demand response, the user's charging power, the user's discharge power and the charging service fee, specifically:

[0111]

[0112] In the formula, S yh Represents the comprehensive cost of the user, Represents the charging pile discharge compensation price at time t of demand response.

[0113] S16. Generate a multi-subject comprehensive cost of the electric vehicle charging service provider, the power grid company and the user according to the comprehensive cost of the electric vehicle charging service provider, the comprehensive cost of the power grid company and the comprehensive cost of the user.

[0114] S17, generating a first objective function by minimizing the multi-agent comprehensive cost of the electric vehicle charging service provider, the power grid company and the user, specifically:

[0115]

[0116] Where S represents the comprehensive cost of electric vehicle charging service providers, power grid companies and users.

[0117] S18. Establish a second objective function with the goal of maximizing the utilization rate of charging facilities, specifically:

[0118]

[0119]

[0120] In the formula, r represents the utilization rate of charging facilities, Q ch represents the total capacity of charging facilities in the tea area, w1 represents the charging cost coefficient, w2 represents the charging convenience coefficient, Indicates the average charging service fee in the tea area, K max represents the maximum charging facility service fee that users can choose in the surrounding area, T' avg represents the average single charging time of the charging facilities in the tea area. The charging time here includes the time it takes for the vehicle to drive to the charging pile. T' max Indicates the maximum average single charging time of the charging facilities that users can choose in the area.

[0121] Among them, the value of w1 is determined by the charging service fee; the value of w2 is determined by the charging service radius, travel habits and the location of the charging pile; the value range of w1 and w2 is [0,1].

[0122] S2. Establish the third objective function with the goal of maximizing the local consumption rate of new energy, and take the selection of charging facilities, the scale of charging facilities and the spatial layout of charging facilities as decision variables.

[0123] Among them, the third objective function is established with the goal of maximizing the local consumption rate of new energy, specifically:

[0124]

[0125] In the formula, C pv (%) represents the local photovoltaic consumption rate, It represents the scale of local consumption of photovoltaic power generation at time t.

[0126] The charging facility selection refers to the ratio and power selection of V2G piles and charging piles; the charging facility scale refers to the number of V2G piles and charging piles built; and the charging facility spatial layout refers to the geographical location of the charging facility construction.

[0127] S3, establishing constraints, and constructing a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraints, specifically including S31-S32:

[0128] S31. Establish constraints on charging facility configuration capacity, economic constraints, grid operation constraints, electric vehicle charging and discharging constraints, and distributed power generation output constraints.

[0129] Among them, the charging facility configuration capacity constraint, that is, the total capacity of the charging facilities in the tea area should meet the maximum charging demand of the tea area, is specifically:

[0130]

[0131] The economic constraints mentioned above, in order to solve the seasonal overload problem in tea-growing areas, the demand response method should be more economical than carrying out equipment capacity expansion and transformation (within the entire life cycle of the equipment), specifically:

[0132] S dr,total zr ;

[0133] In the formula, S dr,total represents the lifetime demand response cost, S zr It represents the cost of capacity expansion and transformation of power grid equipment;

[0134] The grid operation constraints include that the grid operation in the substation area is not overloaded and that new energy generation does not cause reverse power flow overload in the substation area, specifically:

[0135]

[0136]

[0137] In the formula, represents the total load demand at time t;

[0138] The electric vehicle charging and discharging constraints are specifically:

[0139]

[0140] In the formula, Indicates the rated charging power of electric vehicles. Indicates the rated discharge power of electric vehicles, Indicates the maximum charging power of electric vehicles, represents the maximum discharge power of electric vehicles, i represents the tea area's own vehicles, transport vehicles and external vehicles;

[0141] The output constraint of the distributed power source, i.e. the photovoltaic output is less than the rated power, is specifically:

[0142]

[0143] Where P pv0 Indicates the maximum photovoltaic power generation power. ​

[0144] S32. Construct a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraint conditions.

[0145] S4. Solve the tea area charging pile layout optimization model to obtain the optimal tea area charging pile layout optimization solution, such as Figure 3 As shown, specifically including S41-S42:

[0146] S41. Use a multi-objective optimization algorithm to solve the tea area charging pile layout optimization model according to the first objective function and the second objective function in the tea area charging pile layout optimization model to obtain multiple tea area charging pile layout optimization solutions.

[0147] In an optional implementation, the multi-objective optimization algorithm is a particle swarm algorithm.

[0148] S42. Determine the optimal tea area charging pile layout optimization scheme from the multiple tea area charging pile layout optimization schemes according to the third objective function in the tea area charging pile layout optimization model.

[0149] Specifically, the new energy local consumption level of each tea area charging pile layout optimization plan is calculated, and the tea area charging pile layout optimization plan with the maximum new energy local consumption level is selected from the multiple tea area charging pile layout optimization plans as the optimal tea area charging pile layout optimization plan.

[0150] The optimization plan for the layout of charging piles in the tea area includes the selection of charging facilities, the scale of charging facilities and the spatial layout of charging facilities, that is, the ratio and power selection of V2G piles and charging piles, the number of piles to be built and the geographical location of the piles to be built.

[0151] The present invention is oriented to the energy consumption characteristics of the tea-growing area, solves the seasonal heavy overload problem in the area by optimizing the layout of charging piles, takes into account the lowest comprehensive cost of multiple subjects, the maximum utilization rate of charging facilities and the maximum local consumption of new energy, and fills the gap in the optimization layout method of charging piles in the tea-growing area; and, comprehensively considers relevant subjects such as electric vehicle charging service providers (virtual power plants), power grid companies, and users, comprehensively analyzes the economic boundaries of each subject, takes the lowest comprehensive cost as an objective function, and ensures that the optimization layout plan of charging piles has good feasibility; at the same time, comprehensively analyzes the charging service radius, service fees, travel habits, charging The factors that affect the utilization rate of charging facilities, such as the location of charging piles, are taken into account. The charging cost coefficient and charging convenience coefficient are innovatively proposed, and the impact of various influencing factors on the utilization rate of charging facilities is clarified. In addition, according to the idea of ​​double-layer optimization, the multi-subject comprehensive cost is minimized and the utilization rate of charging facilities is maximized. The multi-objective optimization algorithm is used to perform multi-objective optimization and solve the problem, and multiple optimization schemes for the layout of charging piles in the tea area are obtained. Furthermore, the local consumption level of new energy of each scheme is calculated with the goal of maximizing the local consumption rate of new energy. The scheme with the largest local consumption degree is selected as the optimal scheme, and the optimal layout scheme of charging piles in the tea area is obtained.

[0152] Please refer to Figure 2 , Embodiment 2 of the present invention is:

[0153] A charging pile layout optimization system for tea-growing areas, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the charging pile layout optimization method for tea-growing areas in Embodiment 1 is implemented.

[0154] In summary, the present invention provides a charging pile layout optimization method and system for tea-growing areas, which respectively establish objective functions to minimize the comprehensive costs of multiple subjects of electric vehicle charging service providers, power grid companies and users, to maximize the utilization rate of charging facilities, and to maximize the local consumption rate of new energy, and use the selection of charging facilities, the scale of charging facilities and the spatial layout of charging facilities as decision variables, and construct a charging pile layout optimization model for tea-growing areas according to multiple objective functions, decision variables and constraints. The charging pile layout optimization model for tea-growing areas is solved to obtain the optimal charging pile layout optimization scheme for tea-growing areas, which fully considers the economy of multiple subjects, realizes multi-objective optimization, and takes into account the development needs of safety, economy and greenness, so as to effectively solve the seasonal heavy overload problem in tea-growing areas while fully meeting the local charging needs, and meet the local consumption needs of green tea making and photovoltaics; in addition, the charging facility configuration capacity constraints, economic constraints, power grid operation constraints, electric vehicle charging and discharging constraints and distributed power supply output constraints are established, which can guide the generation of an optimal layout scheme of charging piles that conforms to reality; and, when solving the model, a double-layer optimization idea is adopted, and the optimal layout optimization scheme of charging piles in tea-growing areas is obtained, which is more scientific and effective.

[0155] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A charging pile layout optimization method for tea areas, characterized in that: Includes steps: The first objective function is established with the goal of minimizing the comprehensive cost of multiple entities including electric vehicle charging service providers, power grid companies and users, and the second objective function is established with the goal of maximizing the utilization rate of charging facilities; The third objective function is established with the goal of maximizing the local consumption rate of new energy, and the selection of charging facilities, the scale of charging facilities, and the spatial layout of charging facilities are used as decision variables; Establishing constraint conditions, and constructing a tea area charging pile layout optimization model according to the first objective function, the second objective function, the third objective function, the decision variables and the constraint conditions; The tea area charging pile layout optimization model is solved to obtain the optimal tea area charging pile layout optimization plan.

2. The method for optimizing the layout of charging piles for tea-growing areas according to claim 1, characterized in that: The first objective function is established with the goal of minimizing the multi-agent comprehensive cost of electric vehicle charging service providers, power grid companies and users, including: Calculate the construction and operation and maintenance comprehensive conversion costs of electric vehicle charging service providers based on the operation and maintenance costs of charging piles, and determine the user's charging power, the user's discharging power, the charging service fee, and the discharging service fee; Calculate the comprehensive cost of the electric vehicle charging service provider based on the comprehensive converted cost of construction and operation and maintenance, the charging power of the user, the discharging power of the user, the charging service fee and the discharging service fee; Calculate the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period according to the net load of the substation area, and calculate the V2G demand response fee that the power grid company needs to provide according to the discharge demand for V2G by the power grid company in response to the demand issued by the user during the heavy overload period; Calculate the comprehensive cost of the grid company based on the V2G demand response fee that the grid company needs to provide and the charging power of the user; Calculate the charging pile discharge compensation price during demand response according to the discharge service fee, and calculate the user's comprehensive cost according to the charging pile discharge compensation price during demand response, the user's charging power, the user's discharge power and the charging service fee; Generate a multi-subject comprehensive cost of the electric vehicle charging service provider, the power grid company and the user according to the comprehensive cost of the electric vehicle charging service provider, the comprehensive cost of the power grid company and the comprehensive cost of the user; The first objective function is generated by minimizing the multi-agent comprehensive cost of the electric vehicle charging service provider, the power grid company and the user.

3. The method for optimizing the layout of charging piles for tea-growing areas according to claim 2, characterized in that: The comprehensive cost of the electric vehicle charging service provider is calculated based on the comprehensive converted cost of construction and operation and maintenance, the charging power of the user, the discharging power of the user, the charging service fee and the discharging service fee, specifically: In the formula, S fw represents the comprehensive cost of electric vehicle charging service providers, S T represents the comprehensive converted cost of construction and operation and maintenance of electric vehicle charging service providers during the T period, represents the charging power of the user at time t, represents the charging service fee at time t, represents the discharge power of the user at time t, Represents the discharge service fee at time t.

4. The method for optimizing the layout of charging piles for tea-growing areas according to claim 2, characterized in that: The comprehensive cost of the grid company is calculated based on the V2G demand response fee that the grid company needs to provide and the charging power of the user, specifically: In the formula, S grid represents the comprehensive cost of the power grid company, S dr represents the V2G demand response fee that the power grid company needs to provide, T represents the time period, represents the charging power of the user at time t, Represents the charging price of the charging pile at time t.

5. The method for optimizing the layout of charging piles for tea-growing areas according to claim 2, characterized in that: The comprehensive cost of the user is calculated according to the charging pile discharge compensation price during the demand response, the charging power of the user, the discharge power of the user and the charging service fee, specifically: In the formula, S yh represents the comprehensive cost of the user, T represents the time period, represents the charging power of the user at time t, represents the charging price of the charging pile at time t, represents the charging service fee at time t, represents the discharge power of the user at time t, Represents the charging pile discharge compensation price at time t of demand response.

6. The method for optimizing the layout of charging piles for tea-growing areas according to claim 1, characterized in that: The second objective function is established with the goal of maximizing the utilization rate of charging facilities, specifically: In the formula, r represents the utilization rate of charging facilities, represents the charging power of the user at time t, Q ch represents the total capacity of the charging facilities in the tea area, T represents the time period, w1 represents the charging cost coefficient, w2 represents the charging convenience coefficient, Indicates the average charging service fee in the tea area, K max represents the maximum charging facility service fee that users can choose in the surrounding area, T' avg represents the average single charging time of the charging facilities in the tea area, T' max Indicates the maximum average single charging time of the charging facilities that users can choose in the area.

7. The method for optimizing the layout of charging piles for tea-growing areas according to claim 1, characterized in that: The third objective function is established with the goal of maximizing the local consumption rate of new energy, specifically: In the formula, C pv (%) represents the local photovoltaic consumption rate, T represents the time period, represents the scale of local consumption of photovoltaic power generation at time t, represents the photovoltaic power generation at time t.

8. The method for optimizing the layout of charging piles for tea-growing areas according to claim 1, characterized in that: The establishment of constraint conditions includes: Establish constraints on charging facility configuration capacity, economic constraints, grid operation constraints, electric vehicle charging and discharging constraints, and distributed power generation output constraints; The charging facility configuration capacity constraint is specifically: In the formula, Q ch Indicates the total capacity of the charging facilities in the tea area. Indicates the charging power of the user at time t; The economic constraints are specifically: S dr,total <S zr ; In the formula, S dr,total represents the lifetime demand response cost, S zr It represents the cost of capacity expansion and transformation of power grid equipment; The power grid operation constraints are specifically: In the formula, represents the total load demand at time t, represents the photovoltaic power generation at time t, Q n Indicates the rated capacity of the distribution transformer or line; The electric vehicle charging and discharging constraints are specifically: In the formula, Indicates the rated charging power of electric vehicles. Indicates the rated discharge power of electric vehicles, Indicates the maximum charging power of electric vehicles, represents the maximum discharge power of electric vehicles, i represents the tea area's own vehicles, transport vehicles and external vehicles; The output constraints of the distributed power sources are specifically: Where P pv0 Indicates the maximum photovoltaic power generation power.

9. The method for optimizing the layout of charging piles for tea-growing areas according to claim 1, characterized in that: The method of solving the tea area charging pile layout optimization model to obtain the optimal tea area charging pile layout optimization solution includes: Using a multi-objective optimization algorithm to solve the tea area charging pile layout optimization model according to the first objective function and the second objective function in the tea area charging pile layout optimization model, to obtain multiple tea area charging pile layout optimization solutions; According to the third objective function in the tea area charging pile layout optimization model, the optimal tea area charging pile layout optimization scheme is determined from the multiple tea area charging pile layout optimization schemes.

10. A charging pile layout optimization system for tea areas, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, each step of the method for optimizing the layout of charging piles for a tea area according to any one of claims 1 to 9 is implemented.

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