期刊
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
卷 18, 期 2, 页码 650-667出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASE.2020.2980356
关键词
Vehicle-to-grid; Uncertainty; Robustness; Batteries; Logic gates; Microgrids; Power generation; Corporate energy system (CES); plug-in electric vehicle (PEV); robust optimization (RO); shift-work; vehicle-to-grid (V2G)
资金
- National Key Research and Development Program of China [2016YFB0901900]
- National Natural Science Foundation of China [61473218, U1766205]
This study investigates the integration of plug-in electric vehicles (PEVs) into a corporate energy system using V2G technology. A robust optimization model is developed to address uncertainties and a shift-working V2G model is proposed, enhancing system efficiency and reducing energy costs.
The penetration of plug-in electric vehicles (PEVs) has greatly increased over the past few years. By using vehicle-to-grid (V2G) technology, PEVs can be used as mobile batteries in a microgrid. Here, we aim to coordinate the V2G dispatch with traditional energy management in a corporate energy system (CES). To do so, a two-stage robust optimization (RO) model is built with respect to uncertainties in the CES, e.g., photovoltaic (PV) power. Particularly, relationships between the working time schedule and PEVs are investigated and analyzed for the first time, and a novel PEV aggregator model, i.e., shift-working V2G, is presented. The shift-working V2G model provides beneficial characteristics, like weakened randomness and stable storage capacity. A quantitative method to evaluate the V2G capacity is then presented. An analytical solution methodology is also proposed, which can equivalently convert the robust min-max-min model to a single-level mixed-integer linear programming (MILP) model. Case studies are conducted for an iron and steel company in Shanghai, China, with almost 40 000 PEVs. The results show that V2G integration can significantly improve the load-tracking ability of CES and help reduce the energy cost, although the V2G cost is considered. The computational efficiency is also improved compared with the existing methods. Note to Practitioners-This article is motivated by the problem of using the battery storage capacities of plug-in electric vehicles (PEVs) in a corporate energy system (CES) such as an iron and steel plant, aiming at minimizing the energy cost. In existing studies, behaviors of PEVs (e.g., arriving or leaving time) have usually been elusive since they are directly decided by drivers, and thus, it is difficult to determine how much storage capacity PEVs can provide. However, in a CES where a shift-work regulation is implemented, employees should arrive or leave punctually during each shift, and the same is true of their PEVs. Based on this fact, PEVs within one shift could show weakened randomness and stable storage capacities. In this article, the influences of the shift-work regulation on the PEVs are fully analyzed, and the shift-working V2G provides an easy way to integrate PEVs into the CES. In practice, the shift-working V2G model can be applied to any energy system that also implements a shift-work regulation, such as a fire station.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据