﻿ 电动汽车典型快充站优化运行配置方法
 计算机系统应用  2020, Vol. 29 Issue (8): 242-248 PDF

1. 海南电网有限责任公司, 海口 570100;
2. 海南电网有限责任公司 海口供电局, 海口 570100;
3. 国电南瑞科技股份有限公司, 南京 211106

Optimal Operation and Configuration for Typical Fast-Charging Station of Electric Vehicle
ZHANG Lu-Lu1, ZHU Guang-Yun1, SHI Yin-Yue2, KE Hui-Min3
1. Hainan Power Grid Co. Ltd., Haikou 570100, China;
2. Haikou Power Supply Bureau, Hainan Power Grid Co. Ltd., Haikou 570102, China;
3. NARI Technology Development Co. Ltd., Nanjing 211106, China
Foundation item: Technical Project of China Southern Power Grid Corporation (070000KK52180020)
Abstract: In order to reduce the impact fluctuation of high power fast-charging pile on the power grid, and considering the advantages of Distributed Generation (DG) and energy storage of typical fast-charging stations, an optimal operation configuration method for typical fast-charging stations of Electric Vehicles (EVs) is proposed. By analyzing the power output characteristics of the DG in the station and the charging behavior law of EVs, the optimal operation configuration model of typical fast-charging station is established taking the minimum operation cost of the charging station as the optimization objective. The optimal solution of the model is solved by genetic optimization algorithm with the constraints of the power balance in the station and the power output of the distributed power supply. Finally, the feasibility of the proposed method is verified by different configuration examples to provide technical support for the optimal operation of a typical fast-charging station.
Key words: electric vehicles     typical fast-charging station     charging behavior law     optimal operation and configuration     genetic optimization algorithm

1 站内典型设备运行特性分析 1.1 电动汽车充电行为分析

 ${t_c} = \dfrac{{{C_b} \times (1 - SOC)}}{{{P_c}}}$ (1)

 ${P_s}(t) = \sum\limits_{k = 1}^{{m_c}} {{P_{c,k}}} (t)$ (2)

1.2 风力发电特性分析

 ${P_{WT}} = \left\{ \begin{array}{l} 0,\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;v < {v_{ci}}\\ a{v^2} + bv + c,{\kern 1pt} \;\;{v_{ci}} \le v < {v_r}\\ {P_{WTr}},{\kern 1pt} \;\;\;\;\;\;\;\;\;\;{v_r} \le v < {\kern 1pt} {v_{co}}{\kern 1pt} {\kern 1pt} \\ 0,\;\;\;\;\;\;\;\;\;\;\;\;\;\;v \ge {v_{co}}{\kern 1pt} {\kern 1pt} {\kern 1pt} \end{array} \right.$ (3)

 $v = - c{[\ln (1 - p)]^{\dfrac{1}{k}}}$ (4)

1.3 光伏太阳能

 ${P_{PV}}(t) = {P_{\max }}f\left( {G(t)} \right)\left( {1 + kT(t)} \right)$ (5)

 $f(G(t)) = \dfrac{{\Gamma (\alpha + \beta )}}{{\Gamma (\alpha )\Gamma (\beta )}} \cdot {\left( {\dfrac{{G(t)}}{{{G_{\max }}}}} \right)^{\alpha - 1}} \cdot {\left( {1 - \dfrac{{G(t)}}{{{G_{\max }}}}} \right)^\beta }$ (6)

 $\begin{split} & {P_{\max }} = {V_{\max }}{I_{\max }} =\\ & {V_{\max }}\left\{ {{I_{ph}} - {I_0}\left[ {\exp (\dfrac{{{V_{\max }} + {I_{\max }}{R_s}}}{{nk{T_{PV}}{N_s}/q}}) - 1} \right] - \dfrac{{{V_{\max }} + {I_{\max }}{R_s}}}{{{R_p}}}} \right\} \\ \end{split}$ (7)

2 优化配置建模 2.1 目标函数

 $NPV = \sum\limits_{h = 1}^n {\dfrac{{{C_h}}}{{{{(1 + i)}^h}}}} - I$ (8)
 ${C_h} = \sum\limits_{t = 1}^{8760} {(I{N_{ft}} - OU{T_{ft}})} - {C_m}$ (9)
 $I = {C_{st}} \cdot {Q_c} + \sum\limits_{k = 1}^m {({C_k} \cdot {Q_k} \cdot {y_k})} + {C_P} \cdot {S_p} + {C_s} \cdot {E_s}$ (10)

 $I{N_{ft}} = {P_{EV}} \cdot {C_{EV}} + {P_{S2G}} \cdot {C_G}$ (11)
 $OU{T_{ft}} = {P_{G2S}} \cdot {C_{B}}$ (12)
 ${C_m} = \dfrac{{\displaystyle\sum\limits_{t = 1}^{8760} {{P_s}(t)} }}{{{T_s}}} \cdot {C_s} \cdot {E_s} + {C_{mh}}$ (13)

2.2 约束条件

(1)充电站功率平衡

 ${P_{WT}} + {P_{PV}} + {P_{G2S}} + {P_{s{\text{放}}}} = {P_{EV}} + {P_{S2G}} + {P_{s{\text{充}}}}$ (14)

(2)储能能量平衡

 ${E_{{{st}}}} = {E_{{{st}} - 1}} + {E_{{{st{\text{充}}}}}}{{ - }}{E_{{{st{\text{放}}}}}}$ (15)

(3)风力发电机组供电功率约束

 ${P_{WT}} < {P_{WT{\text{额}}}}$ (16)

(4)光伏板功率约束

 ${P_{PV}} < {P_{PV{\text{额}}}}$ (17)

(5)储能系统充放电功率和电能约束

 ${P_{s{\text{充}}}} \le {P_{s{\text{额}}}}$ (18)
 ${P_{s{\text{放}}}} \le {P_{s{\text{额}}}}$ (19)

 ${E_{st{\text{放}}}} \le {E_{st - 1}}$ (20)
 ${E_{st{\text{充}}}} \le {E_s} - {E_{st - 1}}$ (21)

(6)接入点的电网供电和消耗功率约束

 ${P_{G2S}} \le {P_{G\max }}$ (22)
 ${P_{S2G}} \le {P_{G\max }}$ (23)

(7)充电站供电功率限制

 ${P_{EV}} \le {P_{EV{\text{额}}}}$ (24)

(8)电动汽车的等待时间限制

 ${t_{EVk}} \le {t_{EV\max }}$ (25)

3 优化算法

 图 1 遗传算法流程

3.1 染色体: 优化变量

3.2 交叉和变异算子

 $child = parent1 + Ratio \times (parent2 - parent1)$ (27)

3.3 适应度函数: 盈利能力

 图 2 适应度函数流程

4 算例分析 4.1 算例描述

4.2 仿真结果分析

4.3 算例比较分析

 图 3 每个算例每月使用的电能来源

 图 4 年度等值的比较

 图 5 3种模式下充电站内优化配置结果

5 结论

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