文章摘要
詹祥澎,杨军,吴赋章,等.基于去中心化交易模式的充电站日前购电策略[J].电力系统自动化. DOI: 10.7500/AEPS20190510002.
ZHAN Xiangpeng,YANG Jun,WU Fuzhang, et al.Day-ahead Electricity Purchase Strategy of Charging Station Based on Decentralized Trading Mode[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20190510002.
基于去中心化交易模式的充电站日前购电策略
Day-ahead Electricity Purchase Strategy of Charging Station Based on Decentralized Trading Mode
DOI:10.7500/AEPS20190510002
关键词: 电动汽车、电力市场、智能合约、节点边际电价、阻塞管理、充电站调度
KeyWords: electric vehicle (EV)  electric power market  intelligent contract  distribution locational marginal price (DLMP)  congestion management  charging station scheduling
上网日期:2019-09-06
基金项目:国家重点研发计划项目(2017YFB0902900);教育部人文社会科学研究项目(17YJCZH212);国家自然科学基金面上项目(51977154)。
作者单位E-mail
詹祥澎 武汉大学电气与自动化学院 xiangpengzhan@whu.edu.cn 
杨军 武汉大学电气与自动化学院 Jyang@whu.edu.cn 
吴赋章 武汉大学电气与自动化学院 wufuzhangwfz@163.com 
韩思宁 武汉大学电气与自动化学院 2018202070019@whu.edu.cn 
徐箭 武汉大学电气与自动化学院 xujian@whu.edu.cn 
胡文平 国网河北省电力科学研究院 hwp8@163.com 
摘要:
      电动汽车充电站大规模建设下协调充电站的充电功率对配电网的安全经济运行具有十分重要的意义。受制于不同充电站之间的利益冲突以及实时控制技术的瓶颈,电网公司难以对充电站实行集中管理。文中基于去中心化交易模式,提出了充电站参与日前电力市场的购电策略。首先,借助区块链存储技术,设计了适用于充电站日前购电协议的智能合约;其次,采用二阶锥规划求解交流最优潮流模型得到不同时间配电网各节点用电的边际成本,并以此为潮流运行点构建线性化阻塞管理模型,从而得到配电网节点边际电价;最后,考虑电动汽车的停泊特性,以购电成本最小为目标建立了充电站分散式优化调度模型并根据价格信号分散求解。在IEEE 33节点配电网系统中进行了充电站购电策略仿真,仿真结果表明所提出的充电站日前购电策略能实现分散式调度,改善了配电网的潮流分布;同时,节点边际电价能够作为公平的价格信号引导充电站有序充电,在保证配电网安全经济运行的同时降低充电站的购电成本,提高充电机的利用率。
Abstract:
      It is very important to coordinate charging power of charging station (CS) for safe and economic operation of distribution network with a large number of CSs construction. Restricted by the conflict of interests between different CSs and the bottleneck of real-time control technology, it is difficult for distribution system operator (DSO) to centralize the management of CSs. In this paper, we proposed a strategy for charging stations to participate in the electricity market, based on the decentralized trading mode. Firstly, according to the block chain storage technology, an intelligent contract was designed for pre-purchase protocol of charging stations. Secondly, the AC optimal power flow model was solved by second-order conic programming to obtain the marginal cost of power consumption at each bus of distribution network at different time. Based on the solution, a linearized congestion management model was established to calculate the distribution locational marginal prices (DLMPs). Finally, in order to minimize the cost of electricity purchase, we proposed a decentralized optimal dispatching model of CS and solved it according to the price signal. The simulation of charging station power purchase strategy on IEEE 33-bus distribution network system showed that the proposed strategy could achieve decentralized dispatch and optimize the power flow of a distribution network. Meanwhile, as a fair price signal, DLMPs could provide guidance for CSs to charge orderly, which was able to reduce the cost of CSs and improve the utilization rate of chargers under conditions of safety and economy.
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