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Optimal Distributed Energy Resources Allocation for Enriching Reliability and Economic Benefits Using Sine-Cosine Algorithm

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This paper presents an optimization algorithm called sine-cosine algorithm (SCA) for optimal distributed energy resources (DERs) allocation in various configurations of radial distribution networks. This study is demonstrated in two… Click to show full abstract

This paper presents an optimization algorithm called sine-cosine algorithm (SCA) for optimal distributed energy resources (DERs) allocation in various configurations of radial distribution networks. This study is demonstrated in two statuses to find the optimal locations and sizes of DERs to be installed on the distribution system. First status; the most candidate locations for connecting DERs are suggested by using the loss sensitivity factor theory and the proposed SCA is applied to select the optimal capacities of DERs. Second status; the SCA is used to determine both the optimal locations and sizes of DERs. The positive impact of DERs on distribution systems reliability has been investigated in addition to the system power losses and bus voltages. The fitness function is to maximize the savings produced by not only power losses reduction but also reliability enhancement. The proposed algorithm is applied to IEEE 33 and 69-bus radial distribution networks with installing different number of DERs. The simulation results using Matlab programming environment show that the proposed methodology is viable, supporting reliability as well as fulfilling the conventional objectives such as cost minimization, voltage profile improvement, system losses reduction. A comparison between SCA and other methods is introduced to verify the superiority of SCA where SCA fulfils the maximum saving and maximum reduction of power losses equals to 61.3% and 69.2% for IEEE 33-bus and 69-bus networks, respectively.

Keywords: sine cosine; energy; cosine algorithm; optimal distributed; sca; reliability

Journal Title: Technology and Economics of Smart Grids and Sustainable Energy
Year Published: 2020

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