Monireh Ahmadi; Seyed Hossein Hosseini; Murteza Farsadi
Abstract
This study investigated the effect of distributed generation resources and demand-response program on the placement of charging/discharging stations and optimal exploitation programming of electric vehicles in a distribution network. Effective factors in the sitting of stations and optimal charge/discharge ...
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This study investigated the effect of distributed generation resources and demand-response program on the placement of charging/discharging stations and optimal exploitation programming of electric vehicles in a distribution network. Effective factors in the sitting of stations and optimal charge/discharge power in stations are a combination of technical and economic parameters. Minimization of network losses, minimization of voltage loss in feeders, smoothing network load curve, and THD reduction were assumed as technical parameters. As to the economic scope, the placement of stations and charge/discharge power were considered the most effective parameters. In other words, the costs of charging/discharging operations needed to be minimized in the stations to reach the lowest costs spent on purchasing power. A price-based demand-response program was incorporated into the simulations to manage loads on the customer side and smooth the load curve. We implemented genetic, particle swarm optimization, and imperialist competitive hybrid meta-heuristic algorithms to find the optimum operating point. We performed simulations in an IEEE standard 69-bus network. The problem was solved using the former hybrid algorithm, and optimal sites of stations and exploitation program of charge/discharge were specified. This study evaluated the effects of renewable energy resources and price-based demand-response program on the optimal placement of stations and optimal exploitation program of stations. Furthermore, it addressed the effects of an increase in the number of stations and a rise in charge/discharge capacity.
javad nikoukar; Majid Khalili
Volume 08, Issue 03 , September 2019, , Pages 93-98
Abstract
Due to the ever-growing load, especially peak load, the increase in the capacity of plants is inevitable for the response to this growth. Peak load causes increases in customer costs and vast investments in generating and transmission parts. Therefore, restructuring in the electrical industry, competition ...
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Due to the ever-growing load, especially peak load, the increase in the capacity of plants is inevitable for the response to this growth. Peak load causes increases in customer costs and vast investments in generating and transmission parts. Therefore, restructuring in the electrical industry, competition in the electrical market and Demand Response Programs (DRPs) are of special importance in power systems. In DRPs, customers in certain periods, such as peak or times when the price is high, decrease self-consumption. It means profit for costumers and prevention of expensive production in peak time for a genera-tion source. Moreover, to decrease the operation cost of network and ever-growing technology significantly, the power sys-tems operators have employed new sources of energy production as well as thermal units, and it has led to the emergence of Electric Vehicles (EVs) technology as a new source of energy production. This paper studies the simultaneous presence of DRPs and EVs to minimize the total operation cost of a network from one hand and from the other to improve the level of system reserve in Unit Commitment (UC) problem with considering the security constraint. Here, the proposed framework is structured as a Mixed Integer Programming (MIP) and solved using CPLEX solver.
