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Information Journal Paper

Title

OPTIMAL AND ROBUST DISTRIBUTION SYSTEM PLANNING TO LOAD FORECASTING UNCERTAINTY

Pages

  323-332

Keywords

OPTIMAL DISTRIBUTION SYSTEM PLANNING (ODSP)Q2
IMPERIALIST COMPETITIVE ALGORITHM (ICA)Q2

Abstract

 This paper presents a new method for distribution system planning considering load UNCERTAINTY that the obtained network is robust to the load forecasting UNCERTAINTY. At first a method for optimal network planning ignoring load UNCERTAINTY has been presented and then by mixing this method with Monte Carlo Method, a novel method has been presented for planning distribution system considering load UNCERTAINTY. Supposing that the location and size of HV substations are obtained in another work, the optimal route of MV feeders are obtained through the new Imperialist Competitive Algorithm (ICA) developed for the optimal expansion planning of distribution network. In order to check the radial structure of the network obtained in any iteration of ICA, a novel mathematical algorithm is employed. For the scenario with considering load UNCERTAINTY, optimal network and the histogram figures for some electrical parameters of the optimal network are obtained. According to the results, the obtained optimal network is robust to the load UNCERTAINTY.

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    APA: Copy

    NAJAFI RAVADANEGH, S., & KHATAMI, HAMED. (2016). OPTIMAL AND ROBUST DISTRIBUTION SYSTEM PLANNING TO LOAD FORECASTING UNCERTAINTY. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 46(2 (76)), 323-332. SID. https://sid.ir/paper/256429/en

    Vancouver: Copy

    NAJAFI RAVADANEGH S., KHATAMI HAMED. OPTIMAL AND ROBUST DISTRIBUTION SYSTEM PLANNING TO LOAD FORECASTING UNCERTAINTY. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2016;46(2 (76)):323-332. Available from: https://sid.ir/paper/256429/en

    IEEE: Copy

    S. NAJAFI RAVADANEGH, and HAMED KHATAMI, “OPTIMAL AND ROBUST DISTRIBUTION SYSTEM PLANNING TO LOAD FORECASTING UNCERTAINTY,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 46, no. 2 (76), pp. 323–332, 2016, [Online]. Available: https://sid.ir/paper/256429/en

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