Comprehensive benefit evaluation method for orderly charging of three-phase power distribution network electric vehicle

Abstract

The invention discloses a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase power distribution network. The method comprises the following steps: acquiring basic charging parameters of the electric vehicles; establishing a constraint condition of charging of an electric vehicle aggregator, a constraint condition of power flow of a distribution network, a constraint condition of standby supply and constraint conditions of new energy output, outsourcing power and node load of the distribution network; establishing a distribution network operation objective function, and obtaining an optimal operation model of the distribution network; the electric vehicle charging basic parameters are substituted into the distribution network optimal operation model, and an electric vehicle disordered charging operation result and an electric vehicle ordered charging operation result are obtained respectively; and according to the disordered charging operation result of the electric vehicle and the ordered charging operation result of the electric vehicle, the ordered charging comprehensive benefit of the electric vehicle is determined. According to the invention, the accuracy of comprehensive benefit evaluation of ordered charging of the three-phase power distribution network electric vehicle can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of distribution network analysis, and in particular to a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network. Background Art

[0002] Nowadays, the electrification process in the transportation sector is accelerating, and the number of electric vehicles is showing a rapid growth trend. However, the access of a large number of electric vehicles to the distribution network will lead to a significant increase in electricity demand, especially during peak charging periods, which may cause the power grid in some areas to overload, causing a series of problems such as voltage limit violations and network congestion, affecting the safe and stable operation of the distribution network.

[0003] As an emerging business model, electric vehicle aggregators have received great attention. They can aggregate a large number of electric vehicle users and use intelligent control technology to adjust the charging time and power of the electric vehicles they manage according to the actual needs of the power grid to achieve orderly charging of electric vehicles. In the prior art, a multi-stage random architecture is used to cope with the uncertainty of renewable energy generation and study the orderly charging and discharging method of large-scale electric vehicles. In the prior art, based on the constructed steady-state voltage safety zone, the overall voltage safety margin of the system is improved by optimizing the charging and discharging decision. In addition, through the intelligent management of electric vehicle charging loads by aggregators, the power quality can also be optimized, the three-phase imbalance of the distribution network can be alleviated, and the network loss can be reduced. In the prior art, a non-cooperative game framework is proposed to study the charging behavior of electric vehicle aggregators under the guidance of the three-phase balance compensation mechanism. Furthermore, aggregators can use the rapid response capability of the electric vehicles they manage to provide auxiliary services to the power grid, thereby meeting the flexibility requirements of the power grid. In the prior art, the optimal allocation of electric vehicle energy and regulation resources is achieved in the best way while considering the limitations of the power network.

[0004] However, the widespread promotion of the EV aggregator business model depends on a comprehensive analysis of the benefits of orderly EV charging. Therefore, it is of great significance to study an effective comprehensive benefit evaluation method for orderly EV charging in three-phase distribution networks.

[0005] In the prior art, an economic evaluation framework is proposed to study the benefits of electric vehicles in balancing load fluctuations and alternative energy storage investments. In the prior art, a coordinated charging framework for electric vehicles is formulated based on market mechanisms, so as to achieve dynamic adjustment of electric vehicle charging strategies to maximize market benefits. In the prior art, the benefits of electric vehicle aggregators are considered to be maximized in terms of energy and backup provision. However, most of the above studies focus on one or some specific aspects, such as peak shaving and valley filling, power quality improvement, and auxiliary service support, but lack a comprehensive evaluation of the benefits of orderly access to electric vehicles. In particular, the orderly management of electric vehicles can effectively improve the utilization rate of equipment, reduce the operating pressure of equipment, thereby delaying equipment investment and saving investment costs. Such benefits are rarely included in the benefits of orderly access to electric vehicles. To this end, it is necessary to establish a complete benefit evaluation framework to achieve an accurate evaluation of the comprehensive benefits.

[0006] At the same time, the accurate evaluation of the benefits of orderly access to electric vehicles depends on a systematic quantitative method. Most existing studies use a distribution network operation model based on single-phase distribution network trends with the goal of economic optimization to evaluate the impact of electric vehicle access, ignoring the benefits of electric vehicles on improving three-phase imbalance. However, under the framework of comprehensive benefit evaluation, in order to accurately obtain indicators that support various types of benefit evaluation, it relies on the construction of a more refined three-phase distribution network model, and the comprehensive impact of electric vehicles in various aspects needs to be considered during operation. For this reason, it is necessary to establish a refined evaluation method that fits the comprehensive benefit evaluation framework. Summary of the invention

[0007] In view of the above-mentioned deficiencies in the prior art, the present invention provides a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network, which solves the problem of inaccurate comprehensive benefit evaluation of orderly charging of electric vehicles in a three-phase distribution network in the prior art.

[0008] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network, comprising the following steps:

[0009] S1. Obtaining basic parameters for electric vehicle charging; wherein the basic parameters include electric vehicle parameters, new energy installed capacity and output parameters, and distribution network parameters;

[0010] S2. Establish constraints on charging of electric vehicle aggregators, constraints on distribution network flow, constraints on backup provision, and constraints on distribution network new energy output, purchased electricity, and node load;

[0011] S3. Establish the distribution network operation objective function, and use the constraints of electric vehicle aggregator charging, distribution network flow, backup provision, and distribution network new energy output, purchased electricity, and node load to constrain the distribution network operation objective function, and obtain the distribution network optimal operation model;

[0012] S4. Substituting the basic charging parameters of electric vehicles into the optimal operation model of the distribution network, and obtaining the disorderly charging operation results of electric vehicles and the orderly charging operation results of electric vehicles respectively;

[0013] S5. Determine the comprehensive benefits of orderly charging of electric vehicles based on the results of disorderly charging of electric vehicles and orderly charging of electric vehicles; the comprehensive operation benefits include investment substitution benefits, cost savings benefits, renewable energy consumption benefits, emission reduction benefits, three-phase imbalance improvement benefits, network loss reduction benefits and ancillary service benefits.

[0014] The beneficial effects of the above scheme are:

[0015] (1) Based on the qualitative analysis of the impact of the change in electric vehicle access mode on the distribution network, the present invention systematically proposes the definition of various benefits and the corresponding quantification methods. Among them, various benefits from investment and operation are included in the benefit evaluation framework and can be accurately quantified based on the operation indicators of the distribution network.

[0016] (2) The present invention proposes a multi-objective optimization model for distribution networks taking into account electric vehicle access to achieve the optimal trade-off among transaction costs, power quality, and backup provision. Specifically, a refined network flow model taking into account three-phase imbalance and network loss and a backup provision model for electric vehicle aggregators are designed to achieve a refined evaluation of distribution network operation indicators and accurate quantification of related benefits.

[0017] Furthermore, in S2, the constraints for charging by electric vehicle aggregators are:

[0018]

[0019] in, represents the aggregate maximum charging power of aggregator n at time t, represents the aggregate minimum cumulative charging energy of aggregator n at time t, represents the aggregate maximum accumulated charging energy of aggregator n at time t, represents the charging power of aggregator n at time t, represents the set of single electric vehicles managed by aggregator n, η represents the charging efficiency, Δt represents the duration of each period, represents the maximum charging power of individual electric vehicles managed by aggregator n, represents the minimum cumulative charging energy of individual electric vehicles managed by aggregator n, It represents the maximum accumulated charging energy of individual electric vehicles managed by aggregator n.

[0020] The beneficial effect of the above further scheme is that by accurately calculating the upper and lower limits of the charging power and storage capacity of electric vehicle aggregators, the charging behavior of aggregators can be effectively constrained, thereby improving the overall practicality and accuracy of the evaluation method.

[0021] Furthermore, in S2, the constraints of the distribution network flow are:

[0022]

[0023] in,

[0024] symbol represents conjugation, represents a set of solutions for the exact power flow, H represents the conversion matrix between phase-to-ground connection and phase-to-phase connection, Represents the active power injected into the node by the new energy or load connected in Y / Delta at all three-phase nodes, Represents the reactive power injected into the node by new energy or load connected in Y / Delta at all three-phase nodes, represents the system three-phase admittance matrix, represents the complex power injected into the node by the Y-connected new energy or load at all three-phase nodes, represents the complex power injected into the node by the new energy or load connected in delta at all three-phase nodes, represents the phase-to-ground voltage phasors at all three-phase nodes,

[0025] The beneficial effect of the above further solution is that it accurately describes the impact of electric vehicle access on system node voltage.

[0026] Furthermore, in S2, the constraints provided by the backup are:

[0027]

[0028] Among them, σ represents the proportion of the available standby adjustable power to the total adjustable power; τ SR ,τ RU and τ RD They respectively represent the duration that electric vehicle aggregators need to continue providing corresponding spinning reserve and up and down reserve services.

[0029] The above further scheme has the beneficial effect of accurately reflecting the limitations imposed by the capacity and energy of the electric vehicle aggregator in the process of providing spare capacity.

[0030] Furthermore, in S2, the constraints on the distribution network's renewable energy output, purchased power, and node load are:

[0031]

[0032]

[0033] in, represents the output of renewable energy at node m in period t; represents the installed capacity of new energy at node m; δ t It represents the ratio of the maximum output of renewable energy in period t to the installed capacity; They represent the total active load and reactive load of the node at node m and phase k in time period t respectively; They represent the node basic active load and reactive load of node m at phase k in time period t respectively; represents the correlation coefficient, which is equal to 1 when the aggregator n is located at node m and phase k, and is equal to 0 otherwise; ξ represents a constant related to the EV power factor.

[0034] The beneficial effects of the above further scheme are: establishing an accurate distribution network operation model and ensuring that the output of new energy, purchased electricity and node loads meet certain constraints, which can not only improve the stability, reliability and efficiency of the power system, but also optimize resource allocation, reduce losses, and improve service quality, and is of great significance to environmental protection and sustainable development.

[0035] Furthermore, in S3, the distribution network operation objective function is:

[0036] minC DSO =C buy +C loss +C dalance +C carbon -P res -P reserve (5-1)

[0037]

[0038] C balance =λ balance d (5-4)

[0039]

[0040] Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, Cbalance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

[0041] Furthermore, after S2, the method further includes:

[0042] S1A, calculate the injected power at the balance node through the power calculation formula;

[0043] The power calculation formula is:

[0044]

[0045] in, represents the injected power at the equilibrium node;

[0046] S1B, according to the injected power, the linear expression of the system line loss is calculated;

[0047] The linear expression for the system line loss is calculated using the following formula:

[0048]

[0049] in,

[0050] S1C, expand the constraints of distribution network flow and the linear expression of system line loss in the time dimension, and establish the voltage security constraints of the distribution network;

[0051] The expansion results of the constraints of the distribution network flow and the linear expression of the system line loss in the time dimension are:

[0052]

[0053] in,

[0054] The voltage safety constraint of the distribution network is:

[0055]

[0056] Among them, v min and v max They are the minimum and maximum limit values ​​of the distribution network node voltage respectively.

[0057] Further, after S1C, the method further includes:

[0058] Calculate the maximum node voltage deviation of the distribution network system;

[0059] The formula used to calculate the maximum node voltage deviation of the distribution network system is:

[0060]

[0061] in, represents the voltage amplitude of node m at phase k during time period t; are the voltage amplitudes of node m in phases A, B, and C at time period t respectively.

[0062] Furthermore, in S3, the optimal operation model of the distribution network is:

[0063] minC DSO =C buy +C loss +C balance +C carbon -P res -P reserve

[0064] st(1-1)-(7-1)

[0065] Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, C balance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

[0066] The beneficial effects of the above further scheme are: considering various factors affecting the operation of the distribution network, it can not only improve the reliability, resource utilization efficiency and service quality of the power system, but also promote environmental protection and sustainable development, bringing significant economic and social benefits. From disorderly access to orderly access under unified management by aggregators, it can not only improve the system operation efficiency and reduce the system operation cost, but also improve the system operation safety and reliability, reduce the equipment investment for improving power quality and distribution network operation performance, and thus generate many benefits in investment and operation.

[0067] Furthermore, in S5, the calculation formula for investment substitution benefit is:

[0068]

[0069] Among them, B IS represents the investment substitution benefit; Inv It represents the daily investment cost required to increase the unit peak load in the system (that is, the comprehensive cost including the dynamic capacity increase of transformers and the investment and construction of distributed power sources); and They represent the power purchased by the distribution network from the upper power grid during time period t when electric vehicles are charged in an unordered and orderly manner;

[0070] The cost saving benefit is calculated as:

[0071]

[0072] Among them, B CS Indicates cost saving benefits; It represents the price of electricity purchased by the distribution network from the upper power grid in time period t;

[0073] The calculation formula for the benefit of renewable energy consumption is:

[0074]

[0075] Among them, B RI represents the efficiency of renewable energy consumption; RES Represents the renewable energy feed-in tariff, which is used to quantify the positive impact of increasing renewable energy consumption; and They represent the grid-connected power of renewable energy in time period t when electric vehicles are charged in an unordered and orderly manner, respectively;

[0076] The calculation formula for emission reduction benefits is:

[0077]

[0078] Among them, B CR represents the emission reduction benefit; CA represents the price of carbon allowances; Indicates the carbon emission intensity of electricity supplied by the upstream power grid;

[0079] The calculation formula for the three-phase unbalance improvement benefit is:

[0080] B UM =λ balance (d w / o -d)

[0081] Among them, B UM represents the emission reduction benefit; balance represents the unit three-phase unbalanced governance cost; d w / o and d represent the maximum node voltage deviation of the system when the electric vehicles are charged in an unordered and orderly manner, respectively, and are used to measure the maximum three-phase voltage imbalance of the system;

[0082] The calculation formula for network loss reduction benefits is:

[0083]

[0084] Among them, B NL Indicates the network loss reduction benefit; loss represents the unit loss cost; and They represent the network loss of the system in time period t when electric vehicles are charged in an unordered and orderly manner, respectively;

[0085] The calculation formula for ancillary service benefits is:

[0086]

[0087] Among them, B AS Indicates the ancillary services benefits; and They represent the spinning reserve and up / down regulation reserve provided by the aggregator in period n and t respectively; and They represent the compensation prices when the aggregator provides the corresponding spinning reserve and up / down regulation reserve capacity in time period t respectively.

[0088] The beneficial effects of the above further scheme are: the definition of various benefits and the corresponding quantification methods are established, among which various benefits from investment and operation are covered in the benefit evaluation framework and can be accurately quantified based on the operating indicators of the distribution network, and based on various benefits, it can help the power grid balance the load and provide strong support for system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] Figure 1 The figure is a flow chart of a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network. DETAILED DESCRIPTION

[0090] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0091] like Figure 1 As shown, a comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network includes the following steps:

[0092] S1. Obtain basic parameters for electric vehicle charging; wherein the basic parameters include electric vehicle parameters, new energy installed capacity and output parameters, and distribution network parameters.

[0093] S2. Establish constraints on charging of electric vehicle aggregators, constraints on distribution network flow, constraints on backup provision, and constraints on distribution network new energy output, purchased electricity, and node load.

[0094] In this embodiment, in S2, the constraints for charging by the electric vehicle aggregator are:

[0095]

[0096]

[0097] in, represents the aggregate maximum charging power of aggregator n at time t, represents the aggregate minimum cumulative charging energy of aggregator n at time t, represents the aggregate maximum accumulated charging energy of aggregator n at time t, represents the charging power of aggregator n at time t, represents the set of single electric vehicles managed by aggregator n, η represents the charging efficiency, Δt represents the duration of each period, represents the maximum charging power of individual electric vehicles managed by aggregator n, represents the minimum cumulative charging energy of individual electric vehicles managed by aggregator n, It represents the maximum accumulated charging energy of individual electric vehicles managed by aggregator n.

[0098] In practical applications, a large number of electric vehicles are usually aggregated by aggregators at the station level before participating in the optimization and regulation of the distribution network level. This is because individual electric vehicles have little impact on the power market and distribution network trends, and regulating large numbers of individuals will cause a large computational burden and communication burden. Therefore, an electric vehicle aggregator model can be established to obtain the constraints that the electric vehicle aggregator should meet when charging. And in (1-1)-(1-5), the minimum / maximum energy boundaries of electric vehicles correspond to the electric vehicle not starting to charge at maximum power until it leaves, and the electric vehicle starting to charge at maximum power immediately after connecting to the power grid. When electric vehicles charge out of order, their actual accumulated energy overlaps with the upper bound of the accumulated energy. In contrast, when electric vehicles charge in an orderly manner, they will adjust their charging power within the cumulative energy-power feasible domain to achieve the optimal given optimization goal.

[0099] In this embodiment, in S2, the constraints of the distribution network flow are:

[0100]

[0101] in,

[0102] symbol represents conjugation, represents a set of solutions for the exact power flow, H represents the conversion matrix between phase-to-ground connection and phase-to-phase connection, Represents the active power injected into the node by the new energy or load connected in Y / Delta at all three-phase nodes, Represents the reactive power injected into the node by new energy or load connected in Y / Delta at all three-phase nodes, represents the system three-phase admittance matrix, represents the complex power injected into the node by the Y-connected new energy or load at all three-phase nodes, represents the complex power injected into the node by the new energy or load connected in delta at all three-phase nodes, represents the phase-to-ground voltage phasors at all three-phase nodes,

[0103] In a specific embodiment, a distribution system with 1 balancing node and M three-phase PQ nodes is considered. Definition and The complex power and phase-to-ground voltage phasor are injected at the balance node respectively. And when the Y-connected and delta-connected loads at the three-phase node inject complex power, The power flow direction is from k ′ phase is injected into the k phase.

[0104] In this embodiment, in S2, the constraint conditions provided by the standby are:

[0105]

[0106] Among them, σ represents the proportion of the available standby adjustable power to the total adjustable power; τ SR ,τ RU and τ RD They respectively represent the duration that electric vehicle aggregators need to continue providing corresponding spinning reserve and up and down reserve services.

[0107] In this embodiment, (3-1) and (3-2) restrict the available spare capacity to its charging level, and (3-3) and (3-4) restrict the EV aggregator to reserve sufficient energy to ensure continuous service within a given time period.

[0108] In this embodiment, in S2, the constraints of the distribution network's new energy output, purchased power, and node load are:

[0109]

[0110] in, represents the output of renewable energy at node m in period t; represents the installed capacity of new energy at node m; δ t It represents the ratio of the maximum output of renewable energy in period t to the installed capacity; They represent the total active load and reactive load of the node at node m and phase k in time period t respectively; They represent the node basic active load and reactive load of node m at phase k in time period t respectively; represents the correlation coefficient, which is equal to 1 when the aggregator n is located at node m and phase k, and is equal to 0 otherwise; ξ represents a constant related to the EV power factor.

[0111] In this embodiment, (4-1) indicates that the output of new energy in time period t is equal to the sum of the output of new energy at each node, (4-2) limits the output range of new energy, (4-3) gives the calculation method of purchased electricity, (4-4) and (4-5) give the relationship between node load and node basic load, electric vehicle aggregator load and new energy output.

[0112] S3. Establish the distribution network operation objective function, and use the constraints of electric vehicle aggregator charging, distribution network flow, backup provision, distribution network new energy output, purchased electricity and node load to constrain the distribution network operation objective function, and obtain the optimal operation model of the distribution network.

[0113] In this embodiment, in S3, the distribution network operation objective function is:

[0114] minC DSO =C buy +C loss +C dalance +C carbon -P res -P reserve (5-1)

[0115]

[0116]

[0117] C balance =λ balance d (5-4)

[0118]

[0119] Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, C balance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

[0120] Optionally, after S2, the method further includes:

[0121] S1A, calculate the injected power at the balance node through the power calculation formula;

[0122] The power calculation formula is:

[0123]

[0124] in, represents the injected power at the equilibrium node;

[0125] S1B, according to the injected power, the linear expression of the system line loss is calculated;

[0126] The linear expression for the system line loss is calculated using the following formula:

[0127]

[0128] in,

[0129] S1C, expand the constraints of distribution network flow and the linear expression of system line loss in the time dimension, and establish the voltage security constraints of the distribution network;

[0130] The expansion results of the constraints of the distribution network flow and the linear expression of the system line loss in the time dimension are:

[0131]

[0132] in,

[0133] The voltage safety constraint of the distribution network is:

[0134]

[0135] Among them, v min and v max They are the minimum and maximum limit values ​​of the distribution network node voltage respectively.

[0136] Optionally, after S1C, the method further includes:

[0137] Calculate the maximum node voltage deviation of the distribution network system;

[0138] The formula used to calculate the maximum node voltage deviation of the distribution network system is:

[0139]

[0140] in, represents the voltage amplitude of node m at phase k during time period t; are the voltage amplitudes of node m in phases A, B, and C at time period t respectively.

[0141] In this embodiment, in S3, the optimal operation model of the distribution network is:

[0142] minC DSO =C buy +C loss +C balance +C carbon -P res -P reserve

[0143] st(1-1)-(7-1)

[0144] Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, C balance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

[0145] S4. Substitute the basic charging parameters of electric vehicles into the optimal operation model of the distribution network to obtain the disorderly charging operation results of electric vehicles and the orderly charging operation results of electric vehicles respectively.

[0146] S5. Determine the comprehensive benefits of orderly charging of electric vehicles based on the results of disorderly charging of electric vehicles and orderly charging of electric vehicles; the comprehensive operation benefits include investment substitution benefits, cost savings benefits, renewable energy consumption benefits, emission reduction benefits, three-phase imbalance improvement benefits, network loss reduction benefits and ancillary service benefits.

[0147] In this embodiment, in S5, the calculation formula of investment substitution benefit is:

[0148]

[0149] Among them, B IS represents the investment substitution benefit; Inv It represents the daily investment cost required to increase the unit peak load in the system (that is, the comprehensive cost including the dynamic capacity increase of transformers and the investment and construction of distributed power sources); and They represent the power purchased by the distribution network from the upper-level power grid during time period t when electric vehicles are charged in an disorderly and orderly manner.

[0150] The orderly access of EV aggregators reduces the peak load demand on the grid by optimizing charging management and filling valleys with peak loads. This optimization reduces the need for infrastructure investment that the grid must make to cope with load peaks, such as building additional power plants, substations or energy storage facilities.

[0151] The cost saving benefit is calculated as:

[0152]

[0153] Among them, B CS Indicates cost saving benefits; It represents the price at which the distribution network purchases electricity from the upper power grid during time period t.

[0154] By optimizing charging management, electric vehicle aggregators can enhance the use of low-priced electricity from the upstream power grid and local renewable energy, reducing the need to purchase electricity from the upstream power grid during high-priced periods. This optimization reduces the cost of purchasing electricity from the distribution network and becomes a direct cost saving benefit brought by the orderly access of electric vehicles.

[0155] The calculation formula for the benefit of renewable energy consumption is:

[0156]

[0157] Among them, B RI represents the efficiency of renewable energy consumption; RES Represents the renewable energy feed-in tariff, which is used to quantify the positive impact of increasing renewable energy consumption; and They represent the grid-connected power of renewable energy in period t when electric vehicles are charged in an disorderly and orderly manner, respectively.

[0158] Electric vehicle aggregators optimize charging time to match charging demand with the peak hours of local renewable energy generation, thereby improving the absorption capacity of renewable energy. By reducing dependence on fossil fuel power generation, the orderly access of electric vehicles increases the proportion of green electricity in the overall power system and brings benefits to the absorption of renewable energy.

[0159] The calculation formula for emission reduction benefits is:

[0160]

[0161] Among them, B CR represents the emission reduction benefit; CA represents the price of carbon allowances; Indicates the carbon emission intensity of electricity supplied by the upstream power grid.

[0162] Orderly access reduces the use of fossil energy by increasing the use of renewable energy, thereby reducing greenhouse gas and pollutant emissions.

[0163] The calculation formula for the three-phase unbalance improvement benefit is:

[0164] B UM =λ balance (d w / o -d)

[0165] Among them, B UM represents the emission reduction benefit; balance represents the unit three-phase unbalanced governance cost; d w / o and d represent the maximum node voltage deviation of the system when the electric vehicles are charged in an unordered and orderly manner, respectively, and are used to measure the maximum three-phase voltage imbalance of the system.

[0166] Orderly access optimizes load distribution, making electric vehicle charging more evenly distributed among the three phases, reducing the three-phase imbalance of the power grid, thereby reducing the wear and failure rate of power equipment and improving power supply reliability.

[0167] The calculation formula for network loss reduction benefits is:

[0168]

[0169] Among them, B NL Indicates the network loss reduction benefit; loss represents the unit loss cost; and They represent the network loss of the system in time period t when electric vehicles are charged in an disorderly and orderly manner.

[0170] Orderly access optimizes the charging time and load distribution of electric vehicles, reduces the energy loss caused by long-distance transmission and load concentration during power transmission, and brings the benefit of reducing network losses.

[0171] The calculation formula for ancillary service benefits is:

[0172]

[0173] Among them, B AS Indicates the ancillary services benefits; and They represent the spinning reserve and up / down regulation reserve provided by the aggregator in period n and t respectively; and They represent the compensation prices when the aggregator provides the corresponding spinning reserve and up / down regulation reserve capacity in time period t respectively.

[0174] As virtual energy storage, electric vehicle aggregators provide auxiliary services such as frequency regulation and backup to the power grid through their rapid response capabilities, thereby obtaining corresponding market benefits.

[0175] In this embodiment, the access mode of electric vehicles is changed from disorderly access to orderly access managed by aggregators, which can not only improve the system operation efficiency and reduce the system operation cost, but also improve the system operation safety and reliability, reduce the equipment investment for improving the power quality and distribution network operation performance, thereby generating many benefits in investment and operation.

[0176] In terms of investment substitution, when there is disorderly access, electric vehicle users tend to charge during peak hours, which leads to local grid overload, especially in high-load areas, and the system requires additional capacity expansion and infrastructure maintenance investment. Orderly access, through regulation by aggregators, disperses charging time, reduces load concentration during peak hours, and cuts load peaks. This load smoothing reduces the pressure on grid equipment, extends the service life of equipment, and reduces the investment demand for capacity expansion and equipment replacement.

[0177] In terms of improving operating economy, disorderly access means centralized charging when connected to the distribution network. At this time, there may be 1) high electricity prices and expensive system energy costs, and 2) renewable energy generation output is at a low point, and wind power or solar power cannot be effectively utilized. Through the optimized management of aggregators, orderly access allocates the charging needs of electric vehicles to periods with low electricity prices or peak renewable energy generation. This flexible scheduling can not only reduce operating costs and maximize the utilization of renewable energy, but also reduce dependence on upstream and local high-carbon emission intensity energy, improving the system's environmental performance.

[0178] In terms of improving power quality, the concentrated load caused by disorderly charging not only increases the loss of distribution lines, but also aggravates the three-phase imbalance problem in the power grid. The charging of electric vehicles is often concentrated on a single phase, resulting in asymmetric three-phase voltage in the power system, further increasing the risk of grid losses and equipment damage. Orderly access managed by aggregators can reduce the problem of three-phase imbalance by optimizing charging plans and balancing the phase distribution of electric vehicle charging. By evenly distributing the load, the charging behavior of electric vehicles can reduce the loss of distribution lines (i.e., network losses are reduced). The alleviation of three-phase voltage imbalance not only improves the power supply quality, but also reduces grid losses and equipment damage, reducing grid operating costs.

[0179] In terms of the provision of ancillary services, disorderly charging behavior makes its charging demand inflexible and unable to be quickly adjusted based on the needs of the power grid. In the case of orderly access, aggregators can use their rapid response capabilities to provide backup and regulation services to the power grid by treating electric vehicles as virtual energy storage. In particular, when the power grid needs peak load regulation or emergency response, electric vehicles can quickly adjust their charging or discharging behavior to help the power grid balance the load and obtain economic benefits from backup services.

[0180] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the invention.

Claims

1. A comprehensive benefit evaluation method for orderly charging of electric vehicles in a three-phase distribution network, characterized in that: The method comprises: S1. Obtain basic parameters for electric vehicle charging; The basic parameters include electric vehicle parameters, new energy installed capacity and output parameters, and distribution network parameters; S2. Establish constraints on charging of electric vehicle aggregators, constraints on distribution network flow, constraints on backup provision, and constraints on distribution network new energy output, purchased electricity, and node load; S3, establish a distribution network operation objective function, and use the constraints of the electric vehicle aggregator charging, the distribution network flow, the backup supply, and the distribution network new energy output, purchased power, and node load to constrain the distribution network operation objective function, and obtain the distribution network optimal operation model; S4, substituting the basic charging parameters of the electric vehicle into the optimal operation model of the distribution network to obtain the disorderly charging operation results of the electric vehicle and the orderly charging operation results of the electric vehicle respectively; S5. Determine the comprehensive benefit of orderly charging of the electric vehicle according to the disorderly charging operation result of the electric vehicle and the orderly charging operation result of the electric vehicle; The comprehensive operating benefits include investment substitution benefits, cost savings benefits, renewable energy consumption benefits, emission reduction benefits, three-phase imbalance improvement benefits, network loss reduction benefits and ancillary service benefits.

2. The method according to claim 1, characterized in that In S2, the constraints for charging by the electric vehicle aggregator are: in, represents the aggregate maximum charging power of aggregator n at time t, represents the aggregate minimum cumulative charging energy of aggregator n at time t, represents the aggregate maximum accumulated charging energy of aggregator n at time t, represents the charging power of aggregator n at time t, represents the set of single electric vehicles managed by aggregator n, η represents the charging efficiency, Δt represents the duration of each period, represents the maximum charging power of individual electric vehicles managed by aggregator n, represents the minimum cumulative charging energy of individual electric vehicles managed by aggregator n, It represents the maximum accumulated charging energy of individual electric vehicles managed by aggregator n.

3. The method according to claim 2, characterized in that In S2, the constraints of the distribution network flow are: in, symbol represents conjugation, represents a set of solutions for the exact power flow, H represents the conversion matrix between phase-to-ground connection and phase-to-phase connection, Represents the active power injected into the node by the new energy or load connected in Y / Delta at all three-phase nodes, Represents the reactive power injected into the node by new energy or load connected in Y / Delta at all three-phase nodes, represents the system three-phase admittance matrix, represents the complex power injected into the node by the Y-connected new energy or load at all three-phase nodes, represents the complex power injected into the node by the new energy or load connected in delta at all three-phase nodes, represents the phase-to-ground voltage phasors at all three-phase nodes, 4. The method according to claim 3, characterized in that In S2, the constraint conditions provided by the standby are: Where, σ represents the proportion of available standby adjustable power to the total adjustable power; τ SR ,τ RU and τ RD They respectively represent the duration that electric vehicle aggregators need to continue providing corresponding spinning reserve and up and down reserve services.

5. The method according to claim 4, characterized in that In S2, the constraints of the distribution network's new energy output, purchased power, and node load are: in, represents the output of renewable energy at node m in period t; represents the installed capacity of new energy at node m; δ t It represents the ratio of the maximum output of renewable energy in period t to the installed capacity; They represent the total active load and reactive load of the node at node m and phase k in time period t respectively; They represent the node basic active load and reactive load of node m at phase k in time period t respectively; represents the correlation coefficient, which is equal to 1 when the aggregator n is located at node m and phase k, and is equal to 0 otherwise; ξ represents a constant related to the EV power factor.

6. The method according to claim 5, characterized in that In S3, the distribution network operation objective function is: min C DSO =C buy +C loss +C balance +C carbon -P res -P reserve (5-1) C balance =λ balance d (5-4) Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, C balance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

7. The method according to claim 6, characterized in that After S2, the method further includes: S1A, calculate the injected power at the balance node through the power calculation formula; The power calculation formula is: in, represents the injected power at the equilibrium node; S1B, calculating a linear expression of system line loss according to the injected power; The calculation formula used to calculate the linear expression of the system line loss is: in, S1C, expanding the constraint conditions of the distribution network power flow and the linear expression of the system line loss in the time dimension, and establishing the voltage safety constraint of the distribution network; The expansion result of the constraint condition of the distribution network flow and the linear expression of the system line loss in the time dimension is: in, The voltage safety constraint of the distribution network is: Among them, v min and v max They are the minimum and maximum limit values ​​of the distribution network node voltage respectively.

8. The method according to claim 7, characterized in that After S1C, the method further includes: Calculate the maximum node voltage deviation of the distribution network system; The formula used to calculate the maximum node voltage deviation of the distribution network system is: in, represents the voltage amplitude of node m at phase k during time period t; are the voltage amplitudes of node m in phases A, B, and C at time period t respectively.

9. The method according to claim 8, characterized in that In S3, the optimal operation model of the distribution network is: minC DSO =C buy +C loss +C balance +C carbon -P tes -P reserve st(1-1)-(7-1) Among them, C buy represents the power purchase cost of the upper power grid, C loss represents the network loss cost, C balance represents the three-phase unbalanced cost, C carbon represents the carbon emission cost, P res Represents the benefits brought by the output of new energy, P reserve Represents the revenue earned by EV aggregators from providing backup.

10. The method according to claim 9, characterized in that In S5, the calculation formula of the investment substitution benefit is: Among them, B IS represents the investment substitution benefit; Inv It represents the daily investment cost required to increase the unit peak load in the system (that is, the comprehensive cost including the dynamic capacity increase of transformers and the investment and construction of distributed power sources); and They represent the power purchased by the distribution network from the upper power grid during time period t when electric vehicles are charged in an unordered and orderly manner; The cost saving benefit is calculated as follows: Among them, B CS Indicates cost saving benefits; It represents the price of electricity purchased by the distribution network from the upper power grid in time period t; The calculation formula for the renewable energy consumption benefit is: Among them, B RI represents the efficiency of renewable energy consumption; RES Represents the renewable energy feed-in tariff, which is used to quantify the positive impact of increasing renewable energy consumption; and They represent the grid-connected power of renewable energy in time period t when electric vehicles are charged in an unordered and orderly manner, respectively; The calculation formula for the emission reduction benefit is: Among them, B CR represents the emission reduction benefit; CA represents the price of carbon allowances; Indicates the carbon emission intensity of electricity supplied by the upstream power grid; The calculation formula for the three-phase unbalance improvement benefit is: B UM =λ balance (d w / o -d) Among them, B UM represents the emission reduction benefit; balance represents the unit three-phase unbalanced governance cost; d w / o and d represent the maximum node voltage deviation of the system when the electric vehicles are charged in an unordered and orderly manner, respectively, and are used to measure the maximum three-phase voltage imbalance of the system; The calculation formula for the network loss reduction benefit is: Among them, B NL Indicates the network loss reduction benefit; loss represents the unit loss cost; and They represent the network loss of the system in time period t when electric vehicles are charged in an unordered and orderly manner, respectively; The calculation formula of the ancillary service benefit is: Among them, B AS Indicates the ancillary services benefits; and They represent the spinning reserve and up / down regulation reserve provided by the aggregator in period n and t respectively; and They represent the compensation prices when the aggregator provides the corresponding spinning reserve and up / down regulation reserve capacity in time period t respectively.

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