Optimal Planning of a Microgrid using Electric Vehicles and Distributed Energy Resources under Grid's Blackouts

Abstract

Renewable energy sources have developed as a substitute to supply the increasing energy demand, replace finite energy resources such as fossil fuels, mitigate climate change, and play a major role in sustainable development. Lebanon has been experiencing for decades an intermittent and unreliable power supply. Thus, the overall purpose of this paper is to reshape the power supply system of the American University of Beirut (AUB) campus - currently characterized by consistent daily grid blackout hours - by shifting the electricity deficit to renewable distributed energy resources rather than the heavy reliance on on-site diesel generators. The concept of combining PV systems and battery storage systems (BSS) represents a promising solution to grid outages. This study also considers the use of electric vehicles (EVs) as a substitute to conventional fuel-based vehicles used for work-related trips. Additionally, to help AUB community commute easily on campus, the feasibility of integrating an e-scooter sharing system has been investigated in this work. Due to the limited space available on campus to install large BSS and despite the preliminary function that both transportation systems play, they can aid in supplying load demand by acting as a virtual battery storage system in absence of a large transportation demand. To achieve those targets, two main optimization stages were implemented. The first is a multi-objective optimization problem formulated to converge to an optimal PV and BSS capacity and to an optimal charge rate to be imposed on using e-scooter service (in $/km). This has been fulfilled by optimizing a rule-based energy management system (EMS) with the aid of one of the following nonlinear optimization techniques: Particle Swarm Optimization (PSO) and FMINCON solver via YALMIP parser. Whereas the second optimization level operates the optimally configured MG under an optimal EMS which finds the optimal performance of such MG using convex optimization technique. Results showed that the proposed system was able to minimize campus daily operational costs, contribute to a better adoption of clean energy resources, reduce diesel dependency during outages, and decrease power purchased at peak-tariff hours. Such findings suggest that the proposed system is a successful model that can help Lebanese community resolve the grid’s blackout issues and reduce diesel dependency in meeting load demand.