Optimum placement of distributed generation considering economics as well as operational issues

Abstract

Summary Distributed generations (DGs) are in increased use because of numerous advantages. While determining the optimum DG placement in the network, issues related to optimum operation and controls have not been taken care of in earlier literatures. The determination of optimal DG locations in distribution network for optimum operation and control in respect of Generation and Load shedding cost (GLC), voltage, and frequency control taking into account of DG type, capacity, variation of DG output power, and load has been presented in this work. A comprehensive solution algorithm has been proposed to find out the optimum set of location of DG units that suit all probable variation of load and DG output power. Lightning search algorithm (LSA) is used to find optimal allocation of DG units in this work. For the multi‐objective function optimization, the weighting factors are optimized by using artificial bee colony (ABC) technique. A comparison study with the NSGA‐II optimization technique has also been reported in this work.

A new index‐based method for optimal DG placement in distribution networks

“…These techniques can be divided into two general categories. The first category is the optimization‐based methods 3‐21 . For example, Ant Lion Optimization Algorithm (ALOA) is proposed for optimal location and sizing of DG based renewable sources for various distribution systems in 4 .…”

“…Manna et al proposed multiple DG placements in the islanded microgrid system, with consideration of system voltage and frequency control simultaneously with load and DG output power variation. The lightning search algorithm (LSA) is used to find the optimal allocation of DG units in this work 13 . Kumar et al present a novel opposition‐based tuned‐chaotic differential evolution (OTCDE) technique for the optimal sizing and placement of multiple DG units 14 .…”

“…The first category is the optimization-based methods. [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] For example, Ant Lion Optimization Algorithm (ALOA) is proposed for optimal location and sizing of DG based renewable sources for various distribution systems in. 4 The backtracking search optimization algorithm (BSOA) is addressed to assign the distributed generators (DGs) along with radial distribution networks.…”

“…The lightning search algorithm (LSA) is used to find the optimal allocation of DG units in this work. 13 Kumar et al present a novel opposition-based tuned-chaotic differential evolution (OTCDE) technique for the optimal sizing and placement of multiple DG units. 14 Huy et al using a differential evolution algorithm to optimize the location, size, and power factor setting each distributed generation source to minimize network losses and maximize distributed generation integration.…”

Optimal allocation of biomass distributed generation in distribution systems using equilibrium algorithm

“…The integration of clean energy is accompanied in driving down the cost of these resources such as biomass distributed generation units (BDGs). There are various benefits of installing the distributed generations (DGs) with their several types and characteristics which can be categorized into economic, technical, and environmental benefits 1‐23 . Economically, DG avoids the costs of installing new transmission circuits and power generation plants.…”