Power distribution network old transformer area transformation method and system considering intelligent charging pile replacement

Abstract

The invention discloses a power distribution network old transformer area transformation method and system considering intelligent charging pile replacement, and the method comprises the steps: considering the capacity expansion of a power distribution transformer and the intelligent charging pile replacement of an old transformer area, taking the minimization of the comprehensive transformation cost of the old transformer area as a target, and constructing a transformation optimization model of the old transformer area; and solving the transformation optimization model of the old transformer area to obtain a distribution transformer capacity expansion and intelligent charging pile substitution scheme for old transformer area transformation. In order to meet the ever-increasing charging requirement, the capacity expansion of the distribution transformer and the replacement of the intelligent charging pile are promoted at the same time, the advantage that the intelligent charging pile can redistribute the charging period is fully utilized, the charging load characteristic is optimized, the power supply capacity of the distribution transformer is utilized to the maximum extent, and the overall cost of old transformer area transformation is reduced; the charging demands of different types of electric vehicles and the increment of the vehicle load in the planning period are considered at the same time, and the comprehensive cost of transformation of the old transformer area of the power distribution network is minimized while the charging demands of electric vehicle users are ensured.

Description

Technical Field

[0001] The present invention belongs to the field of optimization of distribution networks and electric vehicle charging facilities, and specifically relates to a method and system for renovating old distribution network areas taking into account the replacement of smart charging piles. Background Art

[0002] The rapid popularization of electric vehicles has brought unprecedented challenges to traditional power infrastructure, especially in some old substations, where the construction of charging facilities can hardly keep up with the pace of electric vehicle growth. Most of the charging facilities in the old substations were built in the early stage of distribution network construction. At that time, the charging needs of a large number of electric vehicles were not taken into account. Therefore, the charging facilities in the old substations are seriously lagging in layout and capacity, and many charging piles in the old substations are non-intelligent. These non-intelligent charging piles can only charge according to user needs, do not have the function of load optimization and regulation, and lack effective management of charging sequence, which makes the power load concentrated in the peak hours of electricity consumption in the morning and evening, aggravating the power supply pressure in the substations, especially with the increasing number of electric vehicles. This load sequence problem will cause frequent overload of the distribution network, increase the operating risk of the power system, and reduce the power supply reliability of the power grid. In addition, the capacity of distribution transformers in old substations is generally small, which is difficult to adapt to the growing demand for electric vehicle charging. As the charging load continues to increase, the load rate of distribution transformers rises rapidly, and overload is prone to occur, affecting the power supply reliability of the distribution system.

[0003] Therefore, in order to meet the increasing charging demand of electric vehicles, power companies must increase the capacity of charging facilities in old substations, but this process requires a lot of investment, the construction is difficult, and it will also affect the surrounding electricity consumption. How to efficiently improve the charging capacity of old substations with limited resources has become an urgent problem to be solved in power system planning. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for renovating old distribution network areas taking into account the replacement of smart charging piles in order to solve the above-mentioned problems existing in the prior art.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] In the first aspect, the present invention proposes a method for transforming old distribution network areas by replacing smart charging piles, including:

[0007] S1. Considering the expansion of distribution transformers and the replacement of smart charging piles in old substations, with the goal of minimizing the comprehensive renovation cost of old substations, a renovation optimization model for old substations is constructed. The constraints of the renovation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time increment constraints within the planning cycle;

[0008] S2. Solve the optimization model for the renovation of old substations and obtain the capacity expansion of distribution transformers and smart charging pile replacement solutions for the renovation of old substations.

[0009] In S1, the objective function of the optimization model for the transformation of old substations includes:

[0010]

[0011]

[0012]

[0013]

[0014] In the above formula, C T is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the e area, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased during period t.

[0015] In S1, the multiple charging demand constraints of electric vehicles in the area include:

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] In the above formula, is the emergency charging load of the substation e in the period t in the year y, T U is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, is the flexible charging load of the substation e in period t in year y, P CH is the maximum charging power of a single electric vehicle, is the charging load of electric vehicles connected to the substation e in the period t in the year y, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y.

[0022] In S1, the timing increment constraints within the planning cycle include:

[0023]

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] In the above formula, is the base load of the substation e in period t in year y, μBL is the annual growth rate of the base load in the planning period, is the emergency charging demand of the substation e in time period t in year y, μ C is the annual growth rate of charging demand during the planning period, is the number of electric vehicles with flexible charging and discharging time in area e in year y, is the total demand for off-site electric vehicle charging in period t in year y, FB y，t，l is the basic traffic flow on road l in period t in year y, μ T is the annual growth rate of traffic demand during the planning period, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in substation e in year y, and μPV is the annual growth rate of distributed photovoltaic installation capacity during the planning period.

[0031] In S1, the constraints of the transformation optimization model also include the power balance constraint of the substation, the capacity constraint of the distribution transformer in the substation, the charging and discharging power constraint of electric vehicles in the substation, the charging pile constraint in the substation, the road traffic capacity constraint, the actual output constraint of distributed photovoltaics in the substation, the capacity constraint of the distribution transformer in the substation, the power balance constraint of the distribution network lines, and the voltage constraint of the distribution network nodes.

[0032] In the second aspect, the present invention proposes a system for transforming old distribution network areas considering the replacement of smart charging piles, including a model building module and a model solving module;

[0033] The model building module is used to consider the expansion of distribution transformers and the replacement of smart charging piles in old substations, and to build a transformation optimization model for old substations with the goal of minimizing the comprehensive transformation cost of old substations. The constraints of the transformation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time sequence increment constraints within the planning cycle;

[0034] The model solving module is used to solve the transformation optimization model of the old substation area, and obtain the distribution transformer expansion and smart charging pile replacement solutions for the transformation of the old substation area.

[0035] The model building module includes an objective function building unit;

[0036] The objective function construction unit is used to construct the objective function of the transformation optimization model of the following old transformer area:

[0037]

[0038]

[0039]

[0040]

[0041] In the above formula, CT is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the e area, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased during period t.

[0042] The model building module also includes multiple types of charging demand constraint building units;

[0043] The multiple charging demand constraint construction unit is used to construct multiple charging demand constraints for electric vehicles in the following area:

[0044]

[0045]

[0046]

[0047]

[0048]

[0049] In the above formula, is the emergency charging load of the substation e in the period t in year y, T U is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, is the flexible charging load of the substation e in period t in year y, P CH is the maximum charging power of a single electric vehicle, is the charging load of electric vehicles connected to the substation e in the period t in the year y, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y.

[0050] The model building model also includes a timing increment constraint building unit;

[0051] The timing increment constraint construction unit is used to construct the timing increment constraints within the following planning cycle:

[0052]

[0053]

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] In the above formula, is the base load of the substation e in period t in year y, μ BL is the annual growth rate of the basic load during the planning period, is the emergency charging demand of the substation e in time period t in year y, μ C is the annual growth rate of charging demand during the planning period, is the number of electric vehicles with flexible charging and discharging time in area e in year y, is the total demand for off-site electric vehicle charging in period t in year y, FB y，t，l is the basic traffic flow on road l in period t in year y, μ T is the annual growth rate of traffic demand during the planning period, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in substation e in year y, and μPV is the annual growth rate of distributed photovoltaic installation capacity during the planning period.

[0060] In the model building module, the constraints of the transformation and optimization model also include power balance constraints of the substation, capacity constraints of the distribution transformer in the substation, charging and discharging power constraints of electric vehicles in the substation, charging pile constraints in the substation, road traffic capacity constraints, actual output constraints of distributed photovoltaics in the substation, capacity constraints of the distribution transformer in the substation, power balance constraints of the distribution network lines, and voltage constraints of the distribution network nodes.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] The present invention proposes a method and system for renovating old distribution network substations considering replacement with smart charging piles. The method considers the expansion of distribution transformers and the replacement of smart charging piles in old substations, and aims to minimize the comprehensive renovation cost of old substations. A renovation optimization model for old substations is constructed. The constraints of the renovation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time sequence increment constraints within a planning cycle. By solving the renovation optimization model of old substations, distribution transformer expansion and smart charging pile replacement solutions for the renovation of old substations are obtained. On the one hand, in order to meet the growing charging demand and reduce the renovation cost of old distribution network substations, this method simultaneously promotes the expansion of distribution transformers and the replacement of smart charging piles, fully utilizing the advantage of smart charging piles in reallocating charging time periods, optimizing charging load characteristics, reducing the peak-to-valley difference in substation loads, and maximizing the use of distribution transformer power supply capacity to reduce the overall cost of renovation of old substations. On the other hand, this method takes into account the charging needs of different types of electric vehicles and the increase in vehicle load during the planning period, and proactively plans the expansion of distribution transformers and the configuration scale of electric vehicle charging piles, minimizing the comprehensive cost of renovation of old distribution network substations while ensuring the charging needs of electric vehicle users. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a topological structure diagram of the example described in Example 1.

[0064] Figure 2 This is the time-of-use electricity price diagram of the example described in Example 1.

[0065] Figure 3 This is a photovoltaic output characteristic diagram of the example described in Example 1.

[0066] Figure 4 This is a local emergency charging demand diagram for the example described in Example 1.

[0067] Figure 5 The figure is an overall flow chart of the method of the present invention.

[0068] Figure 6 This is a structural diagram of an old area with multiple types of charging demands according to the method described in Example 1.

[0069] Figure 7 The structure diagram of the system of the present invention is shown in FIG. DETAILED DESCRIPTION

[0070] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0071] The present invention proposes a method and system for renovating old distribution network substations taking into account the replacement of smart charging piles. In order to meet the growing charging demand and reduce the renovation cost of old distribution network substations, the capacity expansion of distribution transformers and the replacement of smart charging piles are promoted simultaneously. With the goal of minimizing the comprehensive renovation cost of old substations, a renovation optimization model for old substations is constructed. The charging demand of different types of electric vehicles and the increase in vehicle load within the planning period are considered in the renovation optimization model. The capacity expansion of distribution transformers and the configuration scale of electric vehicle charging piles are planned in a forward-looking manner. While ensuring the charging needs of electric vehicle users, the comprehensive cost of renovation of old distribution network substations is minimized.

[0072] Embodiment 1:

[0073] This embodiment takes a 14-node distribution network-16-node transportation network as the research object, and its topology is as follows: Figure 1 As shown in the figure, the parameter settings for the area transformation of this example include: the unit price of the distribution transformer is 1 million yuan, the capacity of a single new distribution transformer is 1 MW, the unit price of the smart charging pile is 30,000 yuan, the typical number of days in a year is 365 days, the investment cycle is 5 years, the discount rate is 0.05, the maximum load rate of the distribution transformer is 80%, the maximum charging and V2G discharge power of a single electric vehicle are both 80 kW, the unit time is 1 hour, the charging energy demand of a single electric vehicle is 40 kWh, the annual growth rates of basic load, charging demand, traffic demand, and distributed photovoltaic installation capacity during the planning period are 0.1, 0.2, 0.1, and 0.1 respectively, the rated voltage of the distribution network node is 10 kV, and the lower and upper limits of the distribution network node voltage are 9.5 kV and 10.5 kV respectively; the time-of-use electricity price used in the example is as follows Figure 2 As shown in Figure 2, the photovoltaic output characteristics are as follows: Figure 3 As shown, local emergency charging demand is Figure 4 shown.

[0074] like Figure 5 As shown in the figure, the reconstruction method of old distribution network area considering the replacement of smart charging piles is carried out in the following steps:

[0075] 1. Considering the expansion of distribution transformers and the replacement of smart charging piles in old substations, with the goal of minimizing the comprehensive renovation cost of old substations, a renovation optimization model for old substations is constructed;

[0076] The objective functions of the optimization model for the transformation of old substations include:

[0077]

[0078]

[0079]

[0080]

[0081] In the above formula, C T is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the e area, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased in time period t;

[0082] Considering the basic load, electric vehicle charging piles and distributed photovoltaics in the old distribution network, the constraints of the renovation optimization model of the old distribution network include the operation constraints within the distribution network and the operation constraints of the distribution network. Among them, the operation constraints within the distribution network include the power balance constraints of the distribution network, the capacity constraints of the distribution transformers in the distribution network, the charging and discharging power constraints of electric vehicles in the distribution network, the multiple charging demand constraints of electric vehicles in the distribution network, the charging pile constraints in the distribution network, the road traffic capacity constraints, the actual output constraints of distributed photovoltaics in the distribution network, the capacity constraints of the distribution transformers in the distribution network, and the timing increment constraints within the planning period; the distribution network operation constraints include the power balance constraints of the distribution network lines and the voltage constraints of the distribution network nodes; while ensuring the charging needs of electric vehicle users, the comprehensive cost of the renovation of the old distribution network distribution network is minimized.

[0083] The power balance constraint of the substation is:

[0084]

[0085] The capacity constraint of the distribution transformer in the substation is:

[0086]

[0087] The charging and discharging power constraints of electric vehicles in the area are:

[0088]

[0089] The structure of old substations with multiple charging needs is as follows: Figure 6As shown in the figure, three types of charging demands are considered: local emergency charging, local flexible charging and discharging, and remote charging. Among them, local emergency charging is limited to fixed areas and fixed time periods; local flexible charging can meet the charging demand within a typical day in a fixed area, with time flexibility, and it is allowed to use the V2G model as a temporary power source for reverse power supply; electric vehicles for remote charging can choose to charge in any nearby area, with spatial flexibility, but the charging demand needs to be met within a specified time period; therefore, the multiple charging demand constraints of electric vehicles in the area are:

[0090]

[0091]

[0092]

[0093]

[0094]

[0095] For the charging piles in the area, the number of electric vehicles connected to the charging piles in any period cannot exceed the number of charging piles, and the number of electric vehicles connected for flexible charging cannot exceed the number of smart charging piles. Therefore, the constraints on the charging piles in the area are:

[0096]

[0097]

[0098]

[0099] The road traffic capacity constraint is:

[0100]

[0101]

[0102] The actual output constraints of distributed photovoltaics in the area are:

[0103]

[0104] The capacity constraint of the distribution transformer in the substation area is:

[0105]

[0106] The timing increment constraint within the planning cycle is:

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114] In the above formula, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the electric vehicle charging load in the e-station in the period t in the year y, is the actual output of distributed photovoltaic power generation in area e during period t in year y, is the capacity of the distribution transformer in area e, φ L is the maximum load factor of the distribution transformer, is the emergency charging load of the substation e in the period t in the year y, is the flexible charging load of the substation e in period t in year y, is the charging load of electric vehicles connected to the substation e in the period t in the yth year, TU is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, P CH is the maximum charging power of a single electric vehicle, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y, is the number of old charging piles in area e, is the number of smart charging piles converted in area e, P CH is the maximum charging power of a single electric vehicle, is the upper limit of the total number of charging piles in the area e, F y，t，l is the traffic flow generated by off-site charging of electric vehicles on road l in year y during period t, ε e，g，l The correlation coefficient between the travel distance of electric vehicles charged in other places and the road ise，g，l = 1, an electric vehicle from traffic node g that is charged remotely in area e passes through road l, FB y，t，l is the basic traffic flow on road l in period t in year y, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in the area e in year y, λ t is the power generation efficiency of distributed photovoltaic in time period t; is the capacity of the distribution transformer in area e in year y, is the initial capacity of the original distribution transformer in the substation e, is the number of distribution transformers expanded in area e in year y, PC U The capacity of a single new distribution transformer, μ BL is the annual growth rate of the basic load during the planning period, μ C is the annual growth rate of charging demand during the planning period, μ T is the annual growth rate of traffic demand during the planning period, μ PV The annual growth rate of distributed photovoltaic installation capacity during the planning period;

[0115] At the distribution network operation level, the main considerations are the distribution network line flow and the distribution network node voltage. In order to reduce the operating pressure of the distribution network, the distributed photovoltaic power stations and electric vehicle charging stations in the old substation areas all use local reactive power compensation;

[0116] The power balance constraint of the distribution network line is:

[0117]

[0118]

[0119]

[0120] The voltage constraint of the distribution network node is:

[0121]

[0122]

[0123]

[0124] In the above formula, are the active power and reactive power on the distribution network line w in the yth year and in the period t, τ w，e is the correlation coefficient between the distribution line w and the substation e, when τ w，e =1, the distribution network line w is connected to the substation e, when τ w，e= 0, the distribution network line w is not connected to the substation e. is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the basic reactive load connected to the substation e in period t in year y, LC w is the capacity of distribution line w, ΔU y，t，w is the voltage drop on the distribution network line w in the yth year and the period t, are the resistance and reactance of the distribution network line w, U N is the rated voltage of the distribution network node, U y，t，a , U y，t，b are the voltages of the distribution network nodes a and b in the yth year and time period t. Nodes a and b are the two endpoints of the distribution network line w. U y，t，e is the node voltage of the station area e in the period t in the year y, U m , U M They are the lower and upper limits of the node voltage in the distribution network respectively.

[0125] 2. Solve the optimization model for the transformation of old substations, and obtain the capacity expansion of distribution transformers and smart charging pile replacement solutions for the transformation of old substations;

[0126] In order to verify the effectiveness of the present invention, the method for transforming old distribution network substations considering the replacement of smart charging piles (method 1) proposed in the present invention and the method for transforming old distribution network substations using traditional charging piles (method 2) are applied to a 14-node distribution network-16-node transportation network example for comparison. In particular, method 2 does not replace traditional charging piles with smart charging piles with orderly charging functions, but only expands the capacity of distribution transformers in distribution network substations to meet the growing load demand. The comparison of the economic indicators of the two transformation methods is shown in Table 1.

[0127] Table 1 Comparison of economic indicators of two transformation methods

[0128]

[0129] Table 1 lists the cost of expanding the capacity of the distribution transformer, upgrading and transforming the charging pile, purchasing electricity cost and comprehensive cost when the two methods are adopted. Comparing Method 1 with Method 2, it can be seen that although the cost of upgrading and transforming the charging pile is increased when Method 1 is adopted, the cost of expanding the capacity of the distribution transformer is reduced by 41.27% compared with that when Method 2 is adopted, the cost of purchasing electricity is reduced by 12.40%, and the comprehensive cost is reduced by 14.59%;

[0130] The above results show that the method for renovating old distribution network areas considering the replacement of smart charging piles proposed in the present invention achieves the effect of minimizing the comprehensive cost of renovating old distribution network areas while ensuring the charging needs of electric vehicle users.

[0131] Embodiment 2:

[0132] like Figure 7 As shown, the old distribution network area reconstruction system considering the replacement of smart charging piles includes a model building module and a model solving module;

[0133] The model building module is used to consider the expansion of distribution transformers and the replacement of smart charging piles in old substations, and to build a transformation optimization model for old substations with the goal of minimizing the comprehensive transformation cost of old substations. The constraints of the transformation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time sequence increment constraints within the planning cycle;

[0134] The model solving module is used to solve the transformation optimization model of the old substation area, and obtain the distribution transformer expansion and smart charging pile replacement solutions for the transformation of the old substation area.

[0135] The model building module includes an objective function building unit;

[0136] The objective function construction unit is used to construct the objective function of the transformation optimization model of the following old transformer area:

[0137]

[0138]

[0139]

[0140]

[0141] In the above formula, C T is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the e area, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased during period t.

[0142] The model building module also includes multiple types of charging demand constraint building units;

[0143] The multiple charging demand constraint construction unit is used to construct multiple charging demand constraints for electric vehicles in the following area:

[0144]

[0145]

[0146]

[0147]

[0148]

[0149] In the above formula, is the emergency charging load of the substation e in the period t in the year y, T U is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, is the flexible charging load of the substation e in period t in year y, P CH is the maximum charging power of a single electric vehicle, is the charging load of electric vehicles connected to the substation e in the period t in the year y, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y.

[0150] The model building model also includes a timing increment constraint building unit;

[0151] The timing increment constraint construction unit is used to construct the timing increment constraints within the following planning cycle:

[0152]

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159] In the above formula, is the base load of the substation e in period t in year y, μBL is the annual growth rate of the base load in the planning period, is the emergency charging demand of the substation e in time period t in year y, μ C is the annual growth rate of charging demand during the planning period, is the number of electric vehicles with flexible charging and discharging time in area e in year y, is the total demand for off-site electric vehicle charging in period t in year y, FB y，t，l is the basic traffic flow on road l in period t in year y, μ T is the annual growth rate of traffic demand during the planning period, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in substation e in year y, and μPV is the annual growth rate of distributed photovoltaic installation capacity during the planning period.

[0160] In the model building module, the constraints of the transformation and optimization model also include power balance constraints of the substation, capacity constraints of the distribution transformer in the substation, charging and discharging power constraints of electric vehicles in the substation, charging pile constraints in the substation, road traffic capacity constraints, actual output constraints of distributed photovoltaics in the substation, capacity constraints of the distribution transformer in the substation, power balance constraints of the distribution network lines, and voltage constraints of the distribution network nodes.

Claims

1. A method for transforming old distribution network areas by replacing smart charging piles, characterized in that: The method comprises: S1. Considering the expansion of distribution transformers and the replacement of smart charging piles in old substations, with the goal of minimizing the comprehensive renovation cost of old substations, a renovation optimization model for old substations is constructed. The constraints of the renovation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time increment constraints within the planning cycle; S2. Solve the optimization model for the renovation of old substations and obtain the capacity expansion of distribution transformers and smart charging pile replacement solutions for the renovation of old substations.

2. The method for transforming old distribution network areas considering the replacement of smart charging piles according to claim 1 is characterized in that: In S1, the objective function of the optimization model for the transformation of old substations includes: In the above formula, C T is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the area e, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased during period t.

3. The method for transforming old distribution network areas considering the replacement of smart charging piles according to claim 1 is characterized in that: In S1, the multiple charging demand constraints of electric vehicles in the area include: In the above formula, is the emergency charging load of the substation e in the period t in year y, T U is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, is the flexible charging load of the substation e in period t in year y, P CH is the maximum charging power of a single electric vehicle, is the charging load of electric vehicles connected to the substation e in the period t in the year y, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y.

4. The method for transforming old distribution network areas considering the replacement of smart charging piles according to claim 1 is characterized in that: In S1, the timing increment constraints within the planning cycle include: In the above formula, is the base load of the substation e in period t in year y, μ BL is the annual growth rate of the basic load during the planning period, is the emergency charging demand of the substation e in time period t in year y, μ C is the annual growth rate of charging demand during the planning period, is the number of electric vehicles with flexible charging and discharging time in area e in year y, is the total demand for off-site electric vehicle charging in period t in year y, FB y，t，l is the basic traffic flow on road l in period t in year y, μ T is the annual growth rate of traffic demand during the planning period, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in the substation e in year y, μ PV It is the annual growth rate of distributed photovoltaic installation capacity during the planning period.

5. The method for transforming old distribution network areas considering the replacement of smart charging piles according to claim 1 is characterized in that: In S1, the constraints of the transformation optimization model also include the power balance constraint of the substation, the capacity constraint of the distribution transformer in the substation, the charging and discharging power constraint of electric vehicles in the substation, the charging pile constraint in the substation, the road traffic capacity constraint, the actual output constraint of distributed photovoltaics in the substation, the capacity constraint of the distribution transformer in the substation, the power balance constraint of the distribution network lines, and the voltage constraint of the distribution network nodes.

6. Considering the replacement of smart charging piles for old distribution network area transformation system, the characteristics are: The system includes a model building module and a model solving module; The model building module is used to consider the expansion of distribution transformers and the replacement of smart charging piles in old substations, and to build a transformation optimization model for old substations with the goal of minimizing the comprehensive transformation cost of old substations. The constraints of the transformation optimization model include multiple types of charging demand constraints for electric vehicles in the substation and time sequence increment constraints within the planning cycle; The model solving module is used to solve the transformation optimization model of the old substation area, and obtain the distribution transformer expansion and smart charging pile replacement solutions for the transformation of the old substation area.

7. The system for transforming old distribution network areas considering the replacement of smart charging piles according to claim 6 is characterized in that: The model building module includes an objective function building unit; The objective function construction unit is used to construct the objective function of the transformation optimization model of the following old transformer area: In the above formula, C T is the cost of expanding the capacity of the distribution transformer, C P is the replacement cost of smart charging piles, yn is the last year of the planning period, α is the discount rate, γ is the planning period, C E The cost of purchasing electricity; is the number of distribution transformers expanded in area e in year y, PR T is the unit price of distribution transformer, is the number of smart charging piles replaced in the area e, PR P is the unit price of smart charging piles, d is the typical daily quantity in a year, is the power transmitted from the upper power grid to the substation e in the yth year during the period t, is the base load of the substation e in period t in year y, is the unit price of electricity purchased during period t.

8. The system for transforming old distribution network areas considering the replacement of smart charging piles according to claim 6 is characterized in that: The model building module also includes multiple types of charging demand constraint building units; The multiple charging demand constraint construction unit is used to construct multiple charging demand constraints for electric vehicles in the following area: In the above formula, is the emergency charging load of the substation e in the period t in year y, T U is the unit time, is the emergency charging demand of the substation e in time period t in year y, E U The charging energy requirement for a single electric vehicle is is the number of electric vehicles with flexible charging and discharging time in area e in year y, P DI is the V2G discharge power of a single electric vehicle, is the flexible charging load of the substation e in period t in year y, P CH is the maximum charging power of a single electric vehicle, is the charging load of electric vehicles connected to the substation e in the period t in the year y, is the number of off-site electric vehicle charging demands received by area e from traffic node g in period t in year y, is the total demand for off-site electric vehicle charging in period t in year y.

9. The system for transforming old distribution network areas considering the replacement of smart charging piles according to claim 6 is characterized in that: The model building model also includes a timing increment constraint building unit; The timing increment constraint construction unit is used to construct the timing increment constraints within the following planning cycle: In the above formula, is the base load of the substation e in period t in year y, μ BL is the annual growth rate of the basic load during the planning period, is the emergency charging demand of the substation e in time period t in year y, μ C is the annual growth rate of charging demand during the planning period, is the number of electric vehicles with flexible charging and discharging time in area e in year y, is the total demand for off-site electric vehicle charging in period t in year y, FB y，t，l is the basic traffic flow on road l in period t in year y, μ T is the annual growth rate of traffic demand during the planning period, CF y，l is the upper limit of traffic capacity on road l in year y, is the distributed photovoltaic capacity configured in the substation e in year y, μ PV It is the annual growth rate of distributed photovoltaic installation capacity during the planning period.

10. The system for transforming old distribution network areas considering the replacement of smart charging piles according to claim 6 is characterized in that: In the model building module, the constraints of the transformation and optimization model also include power balance constraints of the substation, capacity constraints of the distribution transformer in the substation, charging and discharging power constraints of electric vehicles in the substation, charging pile constraints in the substation, road traffic capacity constraints, actual output constraints of distributed photovoltaics in the substation, capacity constraints of the distribution transformer in the substation, power balance constraints of the distribution network lines, and voltage constraints of the distribution network nodes.

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