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      An Effective Bi-Stage Method for Renewable Energy Sources Integration into Unbalanced Distribution Systems Considering Uncertainty

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      MDPI AG

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          Abstract

          The output generations of renewable energy sources (RES) depend basically on climatic conditions, which are the main reason for their uncertain nature. As a result, the performance and security of distribution systems can be significantly worsened with high RES penetration. To address these issues, an analytical study was carried out by considering different penetration strategies for RES in the radial distribution system. Moreover, a bi-stage procedure was proposed for optimal planning of RES penetration. The first stage was concerned with calculating the optimal RES locations and sites. This stage aimed to minimize the voltage variations in the distribution system. In turn, the second stage was concerned with obtaining the optimal setting of the voltage control devices to improve the voltage profile. The multi-objective cat swarm optimization (MO-CSO) algorithm was proposed to solve the bi-stages optimization problems for enhancing the distribution system performance. Furthermore, the impact of the RES penetration level and their uncertainty on a distribution system voltage were studied. The proposed method was tested on the IEEE 34-bus unbalanced distribution test system, which was analyzed using backward/forward sweep power flow for unbalanced radial distribution systems. The proposed method provided satisfactory results for increasing the penetration level of RES in unbalanced distribution networks.

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          Power flow analysis for radial distribution system using backward/forward sweep method

          Rupa (2014)
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            Author and article information

            Contributors
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            Journal
            PROCCO
            Processes
            Processes
            MDPI AG
            2227-9717
            March 2021
            March 06 2021
            : 9
            : 3
            : 471
            Article
            10.3390/pr9030471
            3593605a-513b-4a1a-b749-2ff258d15d87
            © 2021

            https://creativecommons.org/licenses/by/4.0/

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            Self URI (article page): https://www.mdpi.com/2227-9717/9/3/471

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