A charging pile classification planning method considering coordination of terminal air conditioning load and electric vehicle

Abstract

The application discloses a charging pile classification planning method considering terminal air conditioner load and electric vehicle cooperation, and belongs to the technical field of power system planning and operation. The application firstly constructs a two-stage stochastic programming framework: the first stage decides the differentiated investment and construction scheme of bidirectional / one-way charging piles; the second stage optimizes the cooperative operation strategy of electric vehicle charging and discharging and terminal air conditioner load under the given construction scheme, and innovatively introduces the income brought by cooperative regulation to represent the income of two kinds of flexible resources participating in power distribution network auxiliary service, and quantifies the flexibility value of the power distribution network. The value is fed back to the first stage through the daily operation cost, forming a closed-loop optimization model. The model of the application finally solves the optimal bidirectional / one-way charging pile classification layout and quantity, can effectively reduce the total investment and operation cost, relieve the power distribution network congestion, improve the accommodation capacity of high proportion of renewable energy, and is especially suitable for weak power grid areas with limited power supply capacity.

Description

Technical Field

[0001] This invention belongs to the field of power system planning and operation technology, specifically a charging pile classification planning method that considers the coordination between terminal air conditioning load and electric vehicle. Background Technology

[0002] With the advancement of "dual-carbon" goals and the explosive growth of the new energy vehicle industry, my country's electric vehicle (EV) ownership has exceeded 60 million. As a core infrastructure, the rationality of charging pile planning directly determines the safety, stability, and operational efficiency of the terminal distribution network. However, the current large-scale, disorderly charging behavior of EVs is posing a severe challenge to the terminal distribution network, easily causing issues such as exceeding safety thresholds for transformer line load rates and transformer overcapacity tripping. Meanwhile, EVs, as flexible resources with mobile energy storage characteristics, have proven their vehicle-to-grid (V2G) discharge capacity to effectively mitigate load fluctuations and improve renewable energy absorption rates. However, this potential has not been fully utilized in the existing charging pile planning system, and the existing charging pile planning schemes have multiple shortcomings that urgently need optimization.

[0003] First, existing planning schemes generally adopt a "typical day snapshot" model, which selects load and distribution network parameters on a representative date as the basis for planning. This static planning fundamentally contradicts the dynamic characteristics of actual distribution network operation. On the one hand, end-user load and renewable energy output exhibit significant temporal fluctuations, with distributed photovoltaic output fluctuating by more than 80% within a single day. Static planning cannot cover the differences in distribution network constraints at different times. On the other hand, electric vehicle charging behavior is random and uncertain. The start time and duration of charging are affected by factors such as user travel habits and range requirements. Relying solely on typical day data will lead to a disconnect between planning results and actual demand.

[0004] Secondly, current planning schemes often assume that all charging piles have bidirectional charging and discharging capabilities. However, there are fundamental differences between unidirectional and bidirectional charging piles in terms of technical costs, functional positioning, and applicable scenarios. From a cost perspective, the construction cost of bidirectional charging piles is higher than that of unidirectional piles because activating their V2G function requires additional equipment such as a battery management system and communication modules. Uniformly planning based on bidirectional piles would lead to a waste of resources characterized by "high cost and low utilization." Furthermore, this "one-size-fits-all" planning model cannot match the load characteristics of different areas.

[0005] Furthermore, existing planning often treats EVs as independent loads within the distribution network constraints, failing to achieve synergy with other adjustable loads in the region, especially end-user air conditioning loads (ACLs), and neglecting the value of aggregating multiple flexible resources. In the end-user distribution network, ACLs account for as much as 30%-40%, possessing short-term power regulation capabilities, and their peak loads significantly overlap with EV charging peaks. However, existing planning schemes lack this cross-resource coordination mechanism, resulting in various flexible resources failing to form a combined force to cope with distribution network pressure, and even leading to the negative effect of load superposition and amplification.

[0006] Finally, electric vehicle discharge and load regulation have significant "positive contributions" to the power distribution network, such as peak shaving and valley filling, and congestion relief. However, existing planning models do not quantify and evaluate these values ​​and feed them back into decision-making. This leads to planning decisions often focusing too much on the direct costs of charging pile construction and ignoring its long-term regulation benefits, resulting in poor economic efficiency in planning outcomes.

[0007] Therefore, there is an urgent need for a more refined, dynamic, and collaborative planning method to cost-effectively unlock the flexibility value of EVs and ACLs and solve the congestion problem in the terminal distribution network. Summary of the Invention

[0008] This invention addresses the problems of existing charging pile classification and planning methods, such as static and singular planning, lack of differentiation between charging and discharging functions, lack of multi-resource coordination, and neglect of adjustment value. It provides a method that considers the interaction between terminal air conditioning load and electric vehicle (EV) coordination. This method comprehensively considers the V2G capability of EVs and the coordinated interaction of terminal air conditioning load, classifies and plans unidirectional and bidirectional charging piles, and quantifies the adjustment contribution of flexibility resources to ultimately improve the operational safety, economy, and equipment utilization efficiency of the power distribution network.

[0009] This invention is achieved using the following technical solution: a charging pile classification and planning method considering the coordination between terminal air conditioning load and electric vehicles, comprising the following steps:

[0010] Step 1: Construct a multi-timescale optimization model: Construct a one-stage planning model and a two-stage optimization operation model and establish their coupling relationship; obtain the construction scheme of bidirectional / unidirectional charging piles by solving the one-stage planning model, including the construction sites selected from candidate sites, the number of installations, and the installation type; obtain the daily operating cost of the construction scheme under the one-stage output construction scheme from the two-stage optimization operation model. This is reflected in the first-stage planning model, forming a closed loop;

[0011] Step 2: Define the objective function: The objective function of the one-stage planning model is the average daily investment cost. Minimum and average daily operating costs Minimum daily investment cost This includes daily construction costs, daily maintenance costs, and daily operating costs. Including daily operating costs on a typical day , Obtained from a two-stage optimized operation model;

[0012] Step 3: Model Solving and Solution Output: By solving the first-stage planning model and the second-stage optimization operation model, the construction locations, installation quantities, and installation types of bidirectional / unidirectional charging piles, as well as the average daily operating costs, are obtained. ;

[0013] Step 4: Determining the optimal construction plan among multiple construction options: The first-stage planning model uses the average daily investment cost. Minimum and average daily operating costs With the goal of minimizing, a non-dominated sorting genetic algorithm is used to obtain the optimal solution of the objective function under multiple construction schemes, and a fuzzy membership function is used to determine the optimal construction scheme.

[0014] The above-mentioned charging pile classification and planning method, which considers the coordination between terminal air conditioning load and electric vehicle, uses a one-stage planning model to calculate the average daily investment cost. Minimize and reduce daily operating costs minimize, In the formula, This refers to the service life of the charging station. This represents the number of candidate locations for bidirectional / unidirectional charging stations. and The unit construction costs are for unidirectional and bidirectional charging piles, respectively. and For the first Installation type variable for each candidate point This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. and The first The number of unidirectional and bidirectional charging piles installed at each candidate site. and The annual maintenance costs are for a single unidirectional charging station and a single bidirectional charging station, respectively. For the first Daily operating cost for a typical day For the first The probability of occurrence on a typical day This represents the number of typical days;

[0015] Daily operating cost of the two-stage optimized operation model Daily operating costs of EVs Daily operating costs of ACL Benefits from coordinated regulation of EV and ACL Daily operating costs as follows: In the formula, This represents the number of typical days. For the first Daily operating cost for a typical day For the first The total number of time intervals included in a typical intraday optimization cycle. The construction plan is derived from the first-stage planning model. For construction site Total number of terminal air conditioning loads at the location and for Construction location at all times The total charging power and total discharging power of all EVs are as follows: and These are the unit prices for charging and discharging EVs, respectively. The unit price of the EV to be dispatched for Construction location at all times The total power of the terminal air conditioning load, For construction site The baseline power of the terminal air conditioning load. The unit price of electricity This is the temperature deviation coefficient. for Construction location at all times First The indoor temperature where the air conditioning load of the terminal unit is located. for Construction location at all times First The expected temperature of the terminal air conditioning load in Taiwan. For comfort cost coefficient, The unit price for distribution network ancillary services. For value coefficient, For time intervals.

[0016] The above-mentioned charging pile classification and planning method, which considers the coordination between terminal air conditioning load and electric vehicles, has the following constraints in its first-stage planning model:

[0017] In the formula, and These are the operating power of a single unidirectional charging pile and a bidirectional charging pile, respectively. This indicates the maximum number of construction sites; Indicates the first The remaining capacity of each candidate point.

[0018] The above-mentioned charging pile classification and planning method that considers the coordination between terminal air conditioning load and electric vehicles includes a two-stage optimized operation model that includes power balance constraints, electric vehicle charging and discharging constraints, and terminal air conditioning load constraints.

[0019] Among them, power balance constraints: In the formula, for Construction location at all times Demand response of the distribution network;

[0020] Constraints on a single electric vehicle within the charging and discharging constraints of electric vehicles: In the formula: For electric vehicles exist State of charge at time t, For electric vehicles exist The state of charge at any given moment; and These refer to the charging efficiency and discharging efficiency of electric vehicles, respectively. For electric vehicles Battery capacity; For time intervals; and These are the upper and lower limits of the state of charge for electric vehicles, respectively. and These are the charging and discharging symbols for electric vehicles. For electric vehicles exist The charging power at any given moment; For electric vehicles exist Discharge power at any given moment; This is the upper limit of charging power; This is the upper limit of discharge power;

[0021] Based on the charging and discharging status of the individual electric vehicle, the following can be obtained: Construction location at all times The total charging and discharging power and constraints of all electric vehicles are shown below. , In the formula, and Construction sites The number of one-way and two-way charging piles built at the location. and For construction site The installation type variable at that location, This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. Construction site The number of electric vehicles at the location;

[0022] The individual terminal air conditioning load constraints are as follows: In the formula: and They are respectively Time and Time of the first The indoor temperature where the air conditioning load of the terminal unit is located; for The outdoor temperature at any given time; The equivalent heat capacity of the room; The equivalent thermal resistance of the terminal air conditioning load; For the first Taiwan terminal air conditioning load Operating power at any given time; The energy efficiency ratio of the terminal air conditioning load; and These represent the lower and upper limits of user-acceptable comfort, respectively. This indicates the operating status of the terminal air conditioning load; a value of 1 indicates that it is working, and a value of 0 indicates that it is not working. The width of the temperature dead zone of the terminal air conditioning load. For the first Taiwan terminal air conditioning load The set temperature at any given time;

[0023] Start-up cycle of terminal air conditioning load and downtime They are respectively: In the formula, for The outdoor temperature at any given time;

[0024] For a single terminal air conditioner load, the operating power during the operating cycle In the formula, The rated power of a single terminal air conditioner load;

[0025] Based on the operating status of the single terminal air conditioner load, the following is obtained: Location of power distribution network construction The total power of all terminal air conditioning loads is: In the formula, for Construction location at all times The total power of the terminal air conditioning load, Construction site Number of terminal air conditioning loads at the location.

[0026] The above-mentioned charging pile classification and planning method, which considers the coordination between terminal air conditioning load and electric vehicle, has the following fuzzy membership function: In the formula, For the first The first construction plan Optimize the solution of the objective function; For the first Pareto frontier The maximum value of the objective function; For the first Pareto frontier Find the minimum value of the objective function; for Corresponding membership function value; This is the optimal construction plan.

[0027] Compared with the prior art, the advantages of the present invention are as follows:

[0028] Precise planning by category: By distinguishing between bidirectional and unidirectional charging piles, we avoid equipping all vehicles with expensive and underutilized bidirectional charging piles, thereby reducing investment costs and avoiding resource waste.

[0029] Deep resource synergy: By optimizing the model, the two loads EV and ACL, which are highly overlapping in time, are coordinated and optimized simultaneously, achieving a regulation effect of "1+1>2", which greatly improves the absorption capacity and operational safety of the distribution network.

[0030] Quantifying the value of regulation: The innovative introduction of the benefits brought by the coordinated regulation of EV and ACL quantifies the positive impact of flexible resources on the distribution network, connects the planning results with the operational results, and ensures the economic efficiency of the planning results.

[0031] Enhancing the resilience of the distribution network: By coordinating the charging and discharging needs of EVs and the ACL (Active Control List), the problems of distribution network congestion and over-limit issues can be effectively alleviated. Attached Figure Description

[0032] Figure 1 This is a flowchart of the two-stage model solution process of this invention.

[0033] Figure 2 This is a diagram showing the operating status of the terminal air conditioning load. Detailed Implementation

[0034] A charging pile classification and planning method that considers the coordination between terminal air conditioning load and electric vehicles includes the following steps:

[0035] Step 1: Construct a multi-timescale optimization model

[0036] This invention employs a two-stage stochastic programming framework to establish the coupling relationship between the one-stage planning model and the two-stage optimization operation model. The second stage constructs an optimization operation model on a daily basis and embeds it into the one-stage planning model. The first stage is the planning stage, where the planning model decides the construction location, installation type, and number of bidirectional / unidirectional charging piles. The second stage is the optimization operation stage, where the daily operating cost under the construction plan output from the first stage is obtained and reflected in the planning stage, forming a closed loop.

[0037] Step 2: Define the objective function and constraints

[0038] The objective function of the one-stage planning model is as follows:

[0039] (1);

[0040] In the formula, The average daily investment cost, Daily operating cost, This refers to the service life of the charging station. This represents the number of candidate locations for bidirectional / unidirectional charging stations. and The unit construction costs are for unidirectional and bidirectional charging piles, respectively. and For the first Installation type variable for each candidate point This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. and The first The number of unidirectional and bidirectional charging piles installed at each candidate site. and These are the annual maintenance costs for a single unidirectional charging station and a bidirectional charging station, respectively. For the first Daily operating costs for a typical day; For the first The probability of occurrence on a typical day This represents the number of typical days.

[0041] The constraints of the first-stage planning model are as follows:

[0042] (2);

[0043] In the formula, and These are the operating power of a single unidirectional charging pile and a single bidirectional charging pile, respectively. This indicates the maximum number of construction sites; Indicates the first The remaining capacity of each candidate point.

[0044] The constraints stipulate that unidirectional and bidirectional charging piles cannot be built simultaneously at the same candidate site; and due to limited budget or available land area, the number of unidirectional and bidirectional charging pile sites cannot exceed the maximum value. ;No. The total power capacity of the charging piles connected to each candidate charging station must not exceed the remaining capacity of the candidate charging station. .

[0045] The construction schemes for bidirectional / unidirectional charging piles can be obtained by solving the one-stage planning model. This includes the construction locations, installation types, and quantities of bidirectional / unidirectional charging piles selected from the candidate sites, and the construction plan. By inputting the two-stage optimization operation model, the daily operating cost under this construction scheme can be obtained. .

[0046] This invention assumes that EV and ACL are controlled by a single aggregator, and the daily operating cost of the two-stage optimization model is... Daily operating costs of EVs Daily operating costs of ACL Benefits from coordinated regulation of EV and ACL Daily operating costs as follows:

[0047] (3);

[0048] In the formula, For the first Daily operating cost for a typical day For the first The total number of time intervals included in a typical intraday optimization cycle. The construction plan is derived from the first-stage planning model. For construction site Total number of terminal air conditioning loads at the location and for Construction location at all times The total charging power and total discharging power of all EVs are as follows: and These are the unit prices for charging and discharging EVs, respectively. The unit price of the EV to be dispatched for Construction location at all times The total power of the terminal air conditioning load, For construction site The baseline power of the terminal air conditioning load. The unit price of electricity. This is the temperature deviation coefficient. for Construction location at all times First The indoor temperature where the air conditioning load of the terminal unit is located. for Construction location at all times First The expected temperature of the terminal air conditioning load in Taiwan. For comfort cost coefficient, The unit price for distribution network ancillary services. For value coefficient, For time intervals.

[0049] The optimized operation model includes power balance constraints, electric vehicle charging and discharging constraints, and air conditioning load constraints. The specific mathematical model is as follows:

[0050] Power balance constraints:

[0051] (4);

[0052] In the formula, for Construction location at all times Demand response of the distribution network.

[0053] Constraints for a single electric vehicle:

[0054] (5);

[0055] In the formula: For electric vehicles exist State of charge at time t, For electric vehicles exist The state of charge at any given moment; and These refer to the charging efficiency and discharging efficiency of electric vehicles, respectively. For electric vehicles Battery capacity; For time intervals; and These are the upper and lower limits of the state of charge for electric vehicles, respectively. and These are the charging and discharging symbols for electric vehicles. For electric vehicles exist The charging power at any given moment; For electric vehicles exist Discharge power at any given moment; This is the upper limit of charging power; This represents the upper limit of the discharge power.

[0056] Based on the charging and discharging status of the individual electric vehicle, the following can be obtained: Construction location at all times The total charging and discharging power and constraints of all electric vehicles are shown below, where equation (7) represents the coupling relationship between the first stage and the second stage.

[0057] (6);

[0058] (7);

[0059] In the formula, and Construction sites The number of one-way and two-way charging piles installed at the location. and For construction site The installation type variable at that location, This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. Construction site The number of electric vehicles at the location.

[0060] For ACL, when the temperature setpoint is constant, there are only two states: on and off. When on, the terminal air conditioning load operates at a constant power. When the lower limit of the temperature dead zone is reached, it switches from on to off until the indoor temperature reaches the upper limit of the temperature dead zone, at which point the terminal air conditioning load switches back to on. A schematic diagram of its room temperature and power operation is shown below. Figure 2 As shown. Therefore, the air conditioning load constraint for a single terminal is as follows:

[0061] (8);

[0062] In the formula: and They are respectively Time and Time of the first The indoor temperature where the air conditioning load of the terminal unit is located; for The outdoor temperature at any given time; The equivalent heat capacity of the room; The equivalent thermal resistance of the terminal air conditioning load; For the first Taiwan terminal air conditioning load Cooling power at any given time; The energy efficiency ratio of the terminal air conditioning load represents the cooling capacity that the terminal air conditioning load can provide for each unit of electricity consumed. and These represent the lower and upper limits of user-acceptable comfort, respectively. This indicates the operating status of the terminal air conditioning load; a value of 1 indicates that it is working, and a value of 0 indicates that it is not working. The width of the temperature dead zone of the terminal air conditioning load. For the first Taiwan terminal air conditioning load The set temperature at any given time.

[0063] By solving equation (9), the start-up cycle of the terminal air conditioning load can be obtained. and downtime They are respectively:

[0064] (9);

[0065] In the formula, for The outdoor temperature at any given time;

[0066] For a single terminal air conditioner load, the operating power during the operating cycle can be expressed by the following formula:

[0067] (10);

[0068] In the formula, This refers to the rated power of a single terminal air conditioner load.

[0069] Based on the operating status of the single terminal air conditioner load, the following is obtained: Construction location at all times The total power of all terminal air conditioning loads is:

[0070] (11);

[0071] In the formula, for Construction location at all times The total power of the terminal air conditioning load, Construction site Number of terminal air conditioning loads at the location.

[0072] Step 3: Model Solving and Solution Output

[0073] By solving the first-stage planning model and the second-stage optimized operation model, the construction locations, installation quantities, and installation types of bidirectional / unidirectional charging piles, as well as the daily operating costs, are obtained. .

[0074] Step 4: Determine the optimal solution under multiple construction options

[0075] The first-phase planning model uses the average daily investment cost Minimum and average daily operating costs With the goal of minimizing the objective, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to obtain the objective function evaluation value under multiple construction schemes. The solution process is as follows: Figure 1 As shown, the optimal solution is determined by using the fuzzy membership function shown in equation (12).

[0076] (12);

[0077] In the formula, For the first The first construction plan Optimize the solution of the objective function; For the first Pareto frontier The maximum value of the objective function; For the first Pareto frontier Find the minimum value of the objective function; for Corresponding membership function value; This is the optimal construction plan.

Claims

1. A charging pile classification and planning method considering the coordination between terminal air conditioning load and electric vehicle, characterized in that: Includes the following steps: Step 1: Construct a multi-timescale optimization model: Construct a one-stage planning model and a two-stage optimization operation model and establish their coupling relationship; obtain the construction scheme of bidirectional / unidirectional charging piles by solving the one-stage planning model, including the construction sites selected from candidate sites, the number of installations, and the installation type; obtain the daily operating cost of the construction scheme under the one-stage output construction scheme from the two-stage optimization operation model. This is reflected in the first-stage planning model, forming a closed loop; Step 2: Define the objective function: The objective function of the one-stage planning model is the average daily investment cost. Minimum and average daily operating costs Minimum daily investment cost This includes daily construction costs, daily maintenance costs, and daily operating costs. Including daily operating costs on a typical day , Obtained from a two-stage optimized operation model; Step 3: Model Solving and Solution Output: By solving the first-stage planning model and the second-stage optimization operation model, the construction locations, installation quantities, and installation types of bidirectional / unidirectional charging piles, as well as the daily operating costs, are obtained. ; Step 4: Determining the optimal construction plan among multiple construction options: The first-stage planning model uses the average daily investment cost. Minimum and average daily operating costs With the goal of minimizing, a non-dominated sorting genetic algorithm is used to obtain the optimal solution of the objective function under multiple construction schemes, and a fuzzy membership function is used to determine the optimal construction scheme. The phase one planning model will include the average daily investment cost. Minimize and reduce daily operating costs minimize, In the formula, This refers to the service life of the charging station. This represents the number of candidate locations for bidirectional / unidirectional charging stations. and The unit construction costs are for unidirectional and bidirectional charging piles, respectively. and For the first Installation type variables for each candidate point This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. and The first The number of unidirectional and bidirectional charging piles installed at each candidate site. and The annual maintenance costs are for a single unidirectional charging station and a single bidirectional charging station, respectively. For the first Daily operating costs for a typical day; For the first The probability of occurrence on a typical day This represents the number of typical days; Daily operating cost of the two-stage optimized operation model Daily operating costs of EVs Daily operating costs of ACL Benefits from coordinated regulation of EV and ACL Daily operating costs as follows: In the formula, For the first Daily operating cost for a typical day For the first The total number of time intervals included in a typical intraday optimization cycle. The construction plan is derived from the first-stage planning model. For construction site Total number of terminal air conditioning loads at the location and for Construction location at all times The total charging power and total discharging power of all EVs are as follows: and These are the unit prices for charging and discharging EVs, respectively. The unit price of the EV to be dispatched for Construction location at all times The total power of the terminal air conditioning load, For construction site The baseline power of the terminal air conditioning load. The unit price of electricity This is the temperature deviation coefficient. for Construction location at all times First Indoor temperature of the terminal air conditioning load in Taiwan for Construction location at all times First The expected temperature of the terminal air conditioning load in Taiwan. For comfort cost coefficient, The unit price for distribution network ancillary services. For value coefficient, For time intervals.

2. The charging pile classification and planning method considering the coordination of terminal air conditioning load and electric vehicle as described in claim 1, characterized in that: The constraints of the first-stage planning model are as follows: In the formula, and These are the operating power of a single unidirectional charging pile and a bidirectional charging pile, respectively. This indicates the maximum number of construction sites; Indicates the first The remaining capacity of each candidate point.

3. The charging pile classification and planning method considering the coordination between terminal air conditioning load and electric vehicle as described in claim 2, characterized in that: The two-stage optimized operation model includes power balance constraints, electric vehicle charging and discharging constraints, and terminal air conditioning load constraints. Among them, power balance constraints: In the formula, for Construction location at all times Demand response of the distribution network; Constraints on a single electric vehicle within the charging and discharging constraints of electric vehicles: In the formula: For electric vehicles exist State of charge at time t, For electric vehicles exist The state of charge at any given moment; and These refer to the charging efficiency and discharging efficiency of electric vehicles, respectively. For electric vehicles Battery capacity; For time intervals; and These are the upper and lower limits of the state of charge for electric vehicles, respectively. and These are the charging and discharging symbols for electric vehicles. For electric vehicles exist The charging power at any given moment; For electric vehicles exist Discharge power at any given moment; This is the upper limit of charging power; This is the upper limit of discharge power; Based on the charging and discharging status of the individual electric vehicle, the following can be obtained: Construction location at all times The total charging and discharging power and constraints of all electric vehicles are shown below. , In the formula, and Construction sites The number of one-way and two-way charging piles built at the location. and For construction site The installation type variable at that location, This indicates the installation of a one-way charging station. This indicates that a one-way charging station will not be installed. This indicates the installation of a two-way charging station. This indicates that a two-way charging station will not be installed. Construction site The number of electric vehicles at the location; The individual terminal air conditioning load constraints are as follows: In the formula: and They are respectively Time and Time of the first The indoor temperature where the air conditioning load of the terminal unit is located; for The outdoor temperature at any given time; The equivalent heat capacity of the room; The equivalent thermal resistance of the terminal air conditioning load; For the first Taiwan terminal air conditioning load Operating power at any given time; The energy efficiency ratio of the terminal air conditioning load; and These represent the lower and upper limits of user-acceptable comfort, respectively. This indicates the operating status of the terminal air conditioning load; a value of 1 indicates that it is working, and a value of 0 indicates that it is not working. The width of the temperature dead zone of the terminal air conditioning load. For the first Taiwan terminal air conditioning load The set temperature at any given time; Start-up cycle of terminal air conditioning load and downtime They are respectively: In the formula, for The outdoor temperature at any given time; For a single terminal air conditioner load, the operating power during the operating cycle In the formula, The rated power of a single terminal air conditioner load; Based on the operating status of the single terminal air conditioner load, the following is obtained: Location of power distribution network construction The total power of all terminal air conditioning loads is: In the formula, for Construction location at all times The total power of the terminal air conditioning load, Construction site Number of terminal air conditioning loads at the location.

4. The charging pile classification and planning method considering the coordination between terminal air conditioning load and electric vehicles according to claim 3, characterized in that: The fuzzy membership function is: In the formula, For the first The first construction plan Optimize the solution of the objective function; For the first Pareto frontier The maximum value of the objective function; For the first Pareto frontier Find the minimum value of the objective function; for Corresponding membership function value; This is the optimal construction plan.

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