Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2016 - zeszyt 8

Distributed Generation Allocation Using the Genetic Algorithm of Chu-Beasley and Sensitivity

10.15199/48.2016.08.53

nr katalogowy: 100014
10.15199/48.2016.08.53

This paper presents a methodology for the allocation of distributed generation (DG) units to minimize active power losses in distribution networks. This methodology is based on the genetic algorithm of Chu-Beasley (GACB) and first-order sensitivity (FOS). To evaluate the different proposals of solution, instead of using Load Flow (LF), a FOS technique was used in order to directly estimate the solution of the LF. The proposed methodology was applied to three distribution systems, containing 34, 70 and 126 buses, respectively. Results obtained for the 34 bus system using GACB and FOS technique were compared with that obtained using GACB but solving the LF via Newton-Raphson (NR) method, showing the computational time gain when the FOS technique is used. For the three systems, the best locations for allocation two DG units are shown and the technical impacts in the network, i.e., active power losses and voltage profiles, are verified. Streszczenie. W artykule opisano metodologię lokalizacji rozproszonych źródeł energii przy kryterium minimalizacji strat mocy czynnej. Metoda bazuje na algorytmie genetycznym Chu-Beasley i czułości pierwszego rzędu. Metodę sprawdzono na przykładzie trzech różnych sieci dystrybucyjnych. Analiza lokalizacji rozproszonych generatorów przy wykorzystaniu algorytmu generycznego Chu-Beasley Keywords: Distributed generation; Sensitivity analysis; Genetic algorithm of Chu-Beasley. Słowa kluczowe: generacja rozproszona, algorytm genmetyczny Chu-Beasley. 1. Introduction The efforts towards the expansion of the participation of alternative energy in the electricity generation are growing in the world. Diversifying the energy matrix by implementing new sources of electric generation is the object and desire of many countries. These new forms of power generation may be connected to distribution and transmission networks. The renewable resources [1], e.g., wind, solar, biomass, among others, are classified as environmental[...]

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