考虑车网互动的园区电网动态双层能量管理策略

doi:10.16183/j.cnki.jsjtu.2022.524

摘要/Abstract

摘要：

为解决大量接入的清洁能源出力波动和充电场内汽车数量的随机变化给电网能量管理带来的困难,提出一种园区电网双层优化控制策略.上层基于模型预测控制技术建立风光储集成动态优化模型,综合应用园区电池储能系统和电动汽车(EV)电池储能系统参与电网能量平衡.下层则考虑同时满足EV车主对EV的充电需求和上层能量调度的车网互动管理需求,制定园区电网内停车场的EV有序充放电策略.仿真算例验证表明:所提策略能将分散园区各处的EV储能集成为统一虚拟储能,扩展园区电网储能系统,增加可再生分布式电源的消纳与园区电网的经济效益.

关键词: 园区电网, 电动汽车入网, 电动汽车虚拟储能, 模型预测控制, 混合储能系统

Abstract:

This paper proposes a two-layer optimal control strategy for the park power grid, aiming at addressing the energy management challenges arising from the fluctuations in the output of clean energy sources and the random changes in the number of electric vehicles (EV) at the charging station. The upper layer establishes a dynamic optimization model of landscape storage based on the model predictive control technology, which comprehensively incorporates both the battery energy storage system of the park and the battery energy storage system of EVs, enabling them to participate in balancing the energy demand of the power grid, while the lower layer considers meeting the charging demand of EV owners and the vehicle-to-grid management demand of upper layer for energy dispatching simultaneously, and formulates an orderly charging and discharging strategy for EVs in the parking lot of the power grid. The simulation results show that the proposed strategy effectively can integrate scattered EV storage in the park into a unified virtual energy storage system, expand the energy storage capacity of the grid, and increase the consumption of renewable distributed generation supply, ultimately improving economic benefits for the park grid.

Key words: park power grid, electric vehicle (EV) grid connection, electric vehicle virtual energy storage, model predictive control, hybrid energy storage system

中图分类号:

TM732

邱革非, 冯泽华, 沈赋, 何超, 何虹辉, 刘铠铭. 考虑车网互动的园区电网动态双层能量管理策略[J]. 上海交通大学学报, 2024, 58(6): 916-925.

QIU Gefei, FENG Zehua, SHEN Fu, HE Chao, HE Honghui, LIU Kaiming. Dynamic Double-Layer Energy Management Strategy for Park Power Grid Considering Vehicle-to-Grid[J]. Journal of Shanghai Jiao Tong University, 2024, 58(6): 916-925.

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参数	取值
参数	A类车	B类车	C类车
电池容量/(kW·h)	60	50	45
最低电池容量/(kW·h)	13	12	9
离网SOC/%	70	75	80
额定充/放电功率/kW	15/12	12/8	9/6
最小充电功率/kW	5	4	3
接入电网的汽车/辆	30	40	45
充/放电效率/%	95/95	95/95	95/95
入网时刻7:00,7:15,7:30的汽车/辆	0.5∶1∶1.5	1∶1.5∶2.5	1∶1∶1
离网时刻17:00,18:00,20:00,21:00的汽车/辆	1∶1.5∶1.5∶1	1∶2∶1∶1	2∶1∶1∶1

情况	γ_MRE/%	γ_MSE/%	R²	成本/元
1	4.399	5.962	0.852	1241.7
2	3.895	4.762	0.907	1137.9
3	3.692	4.432	0.932	1053.5