电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2014年
1期
13-20
,共8页
张洪财%胡泽春%宋永华%徐智威%贾龙
張洪財%鬍澤春%宋永華%徐智威%賈龍
장홍재%호택춘%송영화%서지위%가룡
电动汽车%停车生成率模型%蒙特卡洛模拟%充电负荷%时空分布
電動汽車%停車生成率模型%矇特卡洛模擬%充電負荷%時空分佈
전동기차%정차생성솔모형%몽특잡락모의%충전부하%시공분포
electric vehicle(EV)%parking generation rate model%Monte Carlo simulation%charging load%spatial and temporal distribution
提出了一种基于电动汽车驾驶、停放特性的考虑时空分布的电动汽车充电负荷预测方法。采用停车生成率模型预测停车需求,结合不同类型汽车、不同停放目的地的停车特性,建立电动汽车停车需求时空分布模型。从电动汽车日行驶里程、日停放需求时空分布特性入手,分析充电需求。采用蒙特卡洛模拟方法,仿真大规模电动汽车不同时间、不同空间的停放、驾驶以及充电行为,预测电动汽车充电负荷的时空分布特性。以深圳市为例,预测结果表明:电动汽车用户充电行为选择以及公共停车场充电设施配建比例不同,充电负荷也将有不同的分布;居民区、工作单位配建充电设施可满足大部分电动汽车的充电需求;同一城市不同区域建设用地类型不同,充电负荷具有明显差异。
提齣瞭一種基于電動汽車駕駛、停放特性的攷慮時空分佈的電動汽車充電負荷預測方法。採用停車生成率模型預測停車需求,結閤不同類型汽車、不同停放目的地的停車特性,建立電動汽車停車需求時空分佈模型。從電動汽車日行駛裏程、日停放需求時空分佈特性入手,分析充電需求。採用矇特卡洛模擬方法,倣真大規模電動汽車不同時間、不同空間的停放、駕駛以及充電行為,預測電動汽車充電負荷的時空分佈特性。以深圳市為例,預測結果錶明:電動汽車用戶充電行為選擇以及公共停車場充電設施配建比例不同,充電負荷也將有不同的分佈;居民區、工作單位配建充電設施可滿足大部分電動汽車的充電需求;同一城市不同區域建設用地類型不同,充電負荷具有明顯差異。
제출료일충기우전동기차가사、정방특성적고필시공분포적전동기차충전부하예측방법。채용정차생성솔모형예측정차수구,결합불동류형기차、불동정방목적지적정차특성,건립전동기차정차수구시공분포모형。종전동기차일행사리정、일정방수구시공분포특성입수,분석충전수구。채용몽특잡락모의방법,방진대규모전동기차불동시간、불동공간적정방、가사이급충전행위,예측전동기차충전부하적시공분포특성。이심수시위례,예측결과표명:전동기차용호충전행위선택이급공공정차장충전설시배건비례불동,충전부하야장유불동적분포;거민구、공작단위배건충전설시가만족대부분전동기차적충전수구;동일성시불동구역건설용지류형불동,충전부하구유명현차이。
A new method of predicting the electric vehicle(EV) charging load considering the spatial and temporal distribution is proposed based on driving and parking characteristics of private cars.The parking demand is predicted with the parking generation rate model and the spatial and temporal distribution model of EV parking demand is developed by integrating various parking demands and characteristics in different types of areas.Then,EV charging demands are analyzed based on the daily driving mileages and the spatial and temporal distribution characteristics of daily parking demands.The Monte Carlo simulation method is adopted to simulate EV parking,driving and charging behavior sat different time and different places for the prediction of the spatial and temporal distribution characteristics of EV charging load.The predicted outcomes of Shenzhen in 2020 show that EV charging load changes with different charging behaviors and charging facilities available;charging demands can be mostly satisfied with charging facilities at residential quarters and workplaces;charging loads in different parts of a city with different pieces of land for construction are markedly different.