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Mohammad Hassan Moradi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 55951861000
HIndex:
Faculty: Faculty of Engineering
Address:
Phone: 09188131713

Research

Title
Optimal siting and sizing of renewable energy sources and charging stations simultaneously based on Differential Evolution algorithm
Type
JournalPaper
Keywords
Differential Evolution algorithm, Electric vehicle charging stations, Renewable energy sources, Autonomous microgrid
Year
2015
Journal INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
DOI
Researchers Mohammad Hassan Moradi ، ، Seyedmohammadreza Tousi ، ُS Mahdi Hosseinian Hosseinian

Abstract

Electric Vehicles (EVs) are seen to have some negative impacts on microgrid performance, such as diminishing power quality and efficiency and increasing power losses, voltage variations and even customer energy prices. This paper proposes a new method for evaluating the effect of integrating a large number of EVs on a power system and their impact on the network voltage profile via injecting reactive power into highly-loaded buses. A multi-objective optimization problem is developed to obtain the optimal siting and sizing of charging stations and renewable energy sources (RES). The optimization problem focuses on reducing power losses, improving voltage stability of the system and reducing charging costs of EVs. In order to increase the network load factor some coefficients are introduced. Such coefficients, which depend on wind speed, solar irradiance and hourly peak demand ratio in the load characteristic of day-ahead, help aggregators to charge their EVs in off-peak hours. Differential Evolution (DE) algorithm is used for solving the optimization problem. The performance of the proposed method is evaluated for 69-bus and 94-bus microgrids.