基于系统动力学和蒙特卡洛模拟的电动汽车日负荷远期预测

doi:10.11930/j.issn.1004-9649.201711126

中国电力 ›› 2018, Vol. 51 ›› Issue (9): 126-134.DOI: 10.11930/j.issn.1004-9649.201711126

基于系统动力学和蒙特卡洛模拟的电动汽车日负荷远期预测

陈蓉珺^1,2, 何永秀^1,2, 陈奋开^1,2, 董明宇^3,4, 李德智^3,4, 光峰涛^1,2

1. 华北电力大学经济与管理学院, 北京 102206;
2. 新能源电力与低碳发展研究北京市重点实验室(华北电力大学), 北京 102206;
3. 中国电力科学研究院有限公司, 北京 100192;
4. 需求侧多能互补优化与供需互动技术北京市重点实验室, 北京 100192

收稿日期:2017-11-19 修回日期:2018-03-21 出版日期:2018-09-05 发布日期:2018-09-20
作者简介:陈蓉珺(1994-),女,硕士,从事电力技术经济与管理、需求响应、负荷预测,E-mail:crj713@126.com
基金资助:
国家电网公司科技项目（广义负荷解析理论与数据分析研究，YDB17201700053）。

Long-term Daily Load Forecast of Electric Vehicle Based on System Dynamics and Monte Carlo Simulation

CHEN Rongjun^1,2, HE Yongxiu^1,2, CHEN Fenkai^1,2, DONG Mingyu^3,4, LI Dezhi^3,4, GUANG Fengtao^1,2

1. School of Economics and Management, North China Electric Power University, Beijing 102206, China;
2. Beijing Key Laboratory of New Energy and Low-Carbon Development(North China Electric Power University), Beijing 102206, China;
3. China Electric Power Research Institute, Beijing 100192, China;
4. Beijing Key Laboratory of Demand Side Multi-Energy Carriers Optimization and Interaction Technique, Beijing 100192, China

Received:2017-11-19 Revised:2018-03-21 Online:2018-09-05 Published:2018-09-20
Supported by:
This work is supported by Science and Technology Project of SGCC (Research on generalized load analytic theory and data analysis, No.YDB17201700053).

摘要/Abstract

摘要： 对电动汽车负荷进行预测，有助于电力系统规划管理与优化运行。首先从宏观、中观、微观角度，采用系统动力学模型构建电动私家汽车保有量预测模型，随后分析电动汽车充放电特性，采用蒙特卡洛方法模拟电动私家汽车充放电行为，最后利用实际数据，预测未来电动私家汽车大规模接入电网后电网负荷曲线的变化，发现在电动私家车无序充电的情景下，电动私家汽车体量越大，电网峰谷差越大，带来的不利影响也越大，通过进一步测算发现，电动私家汽车参与放电可以在一定程度上缓解电动汽车充电增加的电网负荷，具有一定削峰填谷效益。

关键词: 电动汽车, 负荷预测, 系统动力学, 蒙特卡洛模拟, 电动汽车保有量

Abstract: A private electric vehicle quantity forecasting model is established from macro, medium and micro perspective based on system dynamics model. Then the charging and discharging characteristics of electric vehicles are analyzed. Besides, the Monte Carlo method is used to simulate the charging and discharging behavior of private electric cars. Finally, the actual data is used to predict the change of grid load curve considering large-scale electric vehicles accessing to the grid in the future. The results show that, in the case of unregulated charging mode, the larger the quantity of electric private cars is, the greater the difference between the peak and the valley load and the adverse impact are. Moreover, it is found by further calculation that private electric cars participating in the discharge can, to some extent, cut down the grid peak load increased by EV charging and has a certain peak-load shifting benefits.

Key words: electric vehicles, load forecasting, system dynamics, Monte Carlo simulation, electric vehicle quantity

中图分类号:

陈蓉珺, 何永秀, 陈奋开, 董明宇, 李德智, 光峰涛. 基于系统动力学和蒙特卡洛模拟的电动汽车日负荷远期预测[J]. 中国电力, 2018, 51(9): 126-134.

CHEN Rongjun, HE Yongxiu, CHEN Fenkai, DONG Mingyu, LI Dezhi, GUANG Fengtao. Long-term Daily Load Forecast of Electric Vehicle Based on System Dynamics and Monte Carlo Simulation[J]. Electric Power, 2018, 51(9): 126-134.

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https://www.electricpower.com.cn/CN/Y2018/V51/I9/126

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基于系统动力学和蒙特卡洛模拟的电动汽车日负荷远期预测

Long-term Daily Load Forecast of Electric Vehicle Based on System Dynamics and Monte Carlo Simulation

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基于系统动力学和蒙特卡洛模拟的电动汽车日负荷远期预测

Long-term Daily Load Forecast of Electric Vehicle Based on System Dynamics and Monte Carlo Simulation

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