Placement of Public Fast-Charging Station and Solar Distributed Generation with Battery Energy Storage in Distribution Network Considering Uncertainties and Traffic Congestion. (September 2021)

• Record Type: Journal Article
• Authors: Pal, Arnab; Bhattacharya, Aniruddha; Chakraborty, Ajoy Kumar
• Is Part Of: Journal of energy storage. Volume 41(2021)
• Publication Date: 2021-09
• Subjects: Battery energy storage -- distributed generation -- EV charging station -- optimal allocation -- uncertainty; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2021.102939
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Placement of EV fast charging station in distribution network with road network. Simultaneous allocation of DG and scheduling of BES. Consideration of EVs' travel distances with traffic congestions on roads. The uncertainties of EV, PV and traffic flow are taken and tackled with 2m PEM. 2-stage optimization is applied to solve the problem. Abstract: In this paper, a sustainable solution for the allocation of Public Fast-Charging Stations (PFCSs) and Solar Distributed Generations (SDGs) along with Battery Energy Storages (BESs) and its scheduling is proposed. The solution is obtained with minimization of Energy loss, voltage deviation index, and investment as well as operation maintenance costs of PFCS, SDG, BES, considering battery degradation. Moreover, the associate relevant factors such as; number of charging ports, capacities of the PFCS and EV flow captured by the PFCS are evaluated. Two-stage optimization is employed to getting the solutions. The first stage of optimization deals with PFCS's location, SDG's locations with sizes and BES scheduling. On the other hand, second stage looks after the assignment of EVs to the apt PFCSs considering the shortest distances with traffic congestions in view of reducing energy consumption of the EVs. As a test case, a 33 node radial distribution network is chosen with the corresponding traffic network. The allocation problem is solved by using Harris Hawks Optimization (HHO) and Grey Wolf Optimizer (GWO). Four other established optimization techniques are used to authenticate the solutions. The EV assignment problem is tackled by Integer Linear Programming (ILP). 2m Point Estimation Method (2m PEM) is applied to deal with the uncertainties associated with EVs, traffic flow and SDG.