微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

赵琦玮; 王昕; 王鑫; 郎永波; 贾立凯

微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

1.
上海电力学院电气工程学院,上海 200090;
2.
上海交通大学电工与电子技术中心,上海 200240;
3.
国网吉林省电力有限公司延边供电公司,吉林延边 133001

基金项目: 国家自然科学基金项目(61673268)

详细信息

作者简介:
赵琦玮(1993—),男,硕士研究生,从事计及电动汽车的微电网优化调度策略研究,E-mail:530648436@qq.com;王昕(1972—),男,博士,副教授,从事可再生能源的分布式发电、功率预测和稳定接入技术等的研究,E-mail:wangxin26@sjtu.edu.cn;王鑫(1982—),男,工程师,从事配电网运维与检修、配电自动化工作;郎永波(1981—),男,高级工程师,从事配电网变电工作;贾立凯(1987—),男,工程师,从事配电网运维与检修、配电自动化工作。

中图分类号: TM734

Multi-time Scale Optimal Scheduling Model for Electric Vehicles Charging Considering Forecast Error in Micro-grid

1.
School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2.
Center of Electrical & Electronic Technology, Shanghai Jiao Tong University, Shanghai 200240, China;
3.
Yanbian Power Supply Company, Jilin Electric Power Co., Ltd., State Grid Corporation of China, Yanbian 133001, China

摘要: 针对微电网中电动汽车充放电及风光荷预测误差带来的问题,提出一种在微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型,由日前调度计划和日内短期滚动优化调度构成。日前调度模型兼顾微电网与电动汽车车主双方利益,以微电网运行成本最低、所有电动汽车车主充电总成本最低为目标;滚动调度模型以实际等效负荷与日前调度计划中等效负荷匹配程度最大为目标,将实际车主充电总成本不大于日前计划车主充电总成本作为约束条件考虑。最后使用适用于电动汽车充电优化问题的灰狼优化算法求解,优化结果表明,微电网通过多时间尺度优化调度可以有效降低运行成本,并减小预测误差带来的影响,同时电动汽车车主也可以获得一定的经济利益。
- 微电网 /
- 电动汽车 /
- 预测误差 /
- 优化调度 /
- 灰狼优化算法
Abstract: Aiming at the problems caused by electric vehicles charging and discharging and wind power, photovoltaic and load forecasting errors in the microgrid, a multi-time scale optimal scheduling model for electric vehicles charging considering day-ahead prediction errors is proposed. The model consists of day-ahead scheduling plan and day-in short term rolling optimal scheduling. The day-ahead scheduling model takes into account the interests of both the microgrid operator and the electric vehicle owners, with the lowest microgrid operating cost and the lowest total charging cost for all the electric vehicle owners. The rolling scheduling model aims at maximizing the matching degree between the actual equivalent load and the predicted one in the day-ahead dispatching plan with the prerequisite that the actual total charging cost of vehicle owners is not greater than the planned cost.Finally, the gray wolf optimization algorithm is applied to solve the model. The optimization results show that the microgrid operating cost and the prediction error‘s impact on scheduling can be effectively reduced through the proposed model, which also benefits electric vehicle owners economically.
- microgrid /
- electric vehicle /
- forecast error /
- optimal scheduling /
- grey wolf optimization

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微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

Multi-time Scale Optimal Scheduling Model for Electric Vehicles Charging Considering Forecast Error in Micro-grid

计量

微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

1. 上海电力学院电气工程学院,上海 200090;

2. 上海交通大学电工与电子技术中心,上海 200240;

3. 国网吉林省电力有限公司延边供电公司,吉林延边 133001

English Abstract

Multi-time Scale Optimal Scheduling Model for Electric Vehicles Charging Considering Forecast Error in Micro-grid

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留言板

微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

Multi-time Scale Optimal Scheduling Model for Electric Vehicles Charging Considering Forecast Error in Micro-grid

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出版历程

微电网环境下考虑日前预测误差的电动汽车多时间尺度优化调度模型

1. 上海电力学院电气工程学院,上海 200090; 2. 上海交通大学电工与电子技术中心,上海 200240; 3. 国网吉林省电力有限公司延边供电公司,吉林延边 133001

English Abstract

Multi-time Scale Optimal Scheduling Model for Electric Vehicles Charging Considering Forecast Error in Micro-grid

全文HTML

目录

1. 上海电力学院电气工程学院,上海 200090;

2. 上海交通大学电工与电子技术中心,上海 200240;

3. 国网吉林省电力有限公司延边供电公司,吉林延边 133001