TY - JOUR
T1 - Robust Energy Management for a Corporate Energy System with Shift-Working V2G
AU - Dai, Shihao
AU - Gao, Feng
AU - Guan, Xiaohong
AU - Yan, Chao Bo
AU - Liu, Kun
AU - Dong, Jiaojiao
AU - Yang, Lei
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Corporate energy system (CES)
KW - plug-in electric vehicle (PEV)
KW - robust optimization (RO)
KW - shift-work
KW - vehicle-To-grid (V2G)
UR - https://www.scopus.com/pages/publications/85083453109
U2 - 10.1109/TASE.2020.2980356
DO - 10.1109/TASE.2020.2980356
M3 - 文章
AN - SCOPUS:85083453109
SN - 1545-5955
VL - 18
SP - 650
EP - 667
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 2
M1 - 9058769
ER -