Article ID Journal Published Year Pages File Type
400438 International Journal of Electrical Power & Energy Systems 2013 11 Pages PDF
Abstract

•This paper focuses on optimal location of multitypes DG as private sector.•optimization is done under pool and hybrid based electricity market.•Combination of genetic algorithm and Tabu Search approach is used for optimization.

The new idea of this paper is investigation the effect of bilateral contract between Disco and upstream network and between Disco-Customers in supplying demand power of customers based on hybrid power market rules. In this paper, an optimal location of multi types of distributed generation as independent private sector in a distribution system under pool and hybrid based electricity market in order to cover a constant demand power using bilateral contract for selling fixed value power with certain price value during every condition of market by upstream network to is presented and discussed. The hybrid market considered in this paper consists of four independent sectors and participants, as (1) DG owners, (2) distribution company known as Disco, (3) Independent Supervisor Operator (ISO) in order to superintend on market situation and finally (4) Customers. Based on hybrid electricity operation, in this study it is supposed that in every condition Disco using bilateral contract with 63/20 substation, purchase constant power with certain price and sell it to customers with another contract. Of course due to this bilateral contract, the operation cost of Disco increases and on the other hand the reliability of system increases and the revenue obtained from decreasing energy not supplied load is the important subject that is considered and analyzed in this research.In this research, GA-based Tabu Search method (GATS) is investigated and analyzed in order to optimal location of DG units with certain capacity but with multi types for optimizing net present worth subject to economical, technical, and market constraints. The costs include capital cost, replacement cost, operation and maintenance cost, fuel cost, production cost, and reliability improvement cost.

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Physical Sciences and Engineering Computer Science Artificial Intelligence
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