Optimal Coordinated Charging and Routing Scheme of Electric Vehicles in Distribution Grids: Real Grid Cases. (October 2021)

• Record Type: Journal Article
• Authors: Kasani, Venkata Satish; Tiwari, Deepak; Khalghani, Mohammad Reza; Solanki, Sarika Khushalani; Solanki, Jignesh
• Is Part Of: Sustainable cities and society. Volume 73(2021)
• Publication Date: 2021-10
• Subjects: Electric vehicle coordinated charging -- Vehicular behavior model -- Demand response -- Optimal routing method; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2021.103081
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: This paper proposes an efficient coordinated charging method for plug-in hybrid electric vehicles to minimize the grid overloading and voltage issues. This paper develops an optimal routing technique for a real public transportation system to optimize energy consumption. Demand response methods are considered in the proposed methodology to smooth out the load profile. This paper uses real-world data and case studies to mimic actual conditions. Abstract: The government policies and benefits led to the surge in penetration of Plug-in Hybrid Electric Vehicles (PHEVs) and Battery Electric Vehicles (BEVs) into both public and private sectors. Power Grids are dynamic with load and generation varying, and wide spread adoption of PHEVs can jeopardize and endanger the operation and security of the distribution grids due to overloading and congestion. This paper develops two optimization models, one is for the routing algorithm of Battery Electric Vehicles (BEVs) to find the minimum energy consumption for Personal Rapid Transit (PRT) system in a collegiate environment. The other optimization model is for charging a maximum number of PHEVs interfaced with American Electric Power (AEP) utility system. Mixed Integer Linear Programming (MILP) is used to determine the charging schedules of PHEVs to minimize the power system overloading. MILP is also used to find the optimum charging schedule of BEVs to satisfy the passenger demand of the transit system. Different charging strategies have been developed, and their effects on distribution system voltage profile and losses have been illustrated. We used the real-time data for the PRT routing algorithm. PHEV customers are categorized into different real-world Demand Response (DR) participants capable of flattening the load curve. A time series simulation of a distribution feeder test system is performed to show the feasibility of the proposed methods. Case studies on AEP system and West Virginia University transportation system were carried out. The simulation results demonstrate the effectiveness of our proposed optimization framework in reducing system peak load and satisfying the demand while utilizing minimum number of BEVs.