A Simultaneous Biogeography based Optimal Placement of DG Units and Capacitor Banks in Distribution Systems with Nonlinear Loads

Abstract

This paper uses a new algorithm namely biogeography based optimization (BBO) intended for the simultaneous placement of the distributed generation (DG) units and the capacitor banks in the distribution network. The procedure of optimization has been conducted in the presence of nonlinear loads (a cause of harmonic injection). The purpose of simultaneous optimal placement of the DG and the capacitor is the reduction of active and reactive losses. The difference in the values of loss reduction at different levels of the load have been included in the objective function and the considered objective function includes the constraints of voltage, size and the number of DG units and capacitor banks and the allowable range of the total harmonic distortion (THD) of the total voltage in accordance with the IEEE 519 standards. In this paper the placement has been performed on two load types ie constant and mixed power, moreover the effects of load models on the results and the effects of optimal placement on reduction of the THD levels have also been analyzed. The mentioned cases have been studied on a 33 bus radial distribution system.

Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems

“…The algorithm is found based on the observation of species emergence and migration from one island to the other. Based on that natural phenomenon, the mathematical model of biogeography is described [24,25].…”

Optimal Location and Sizing of Distributed Generators Based on Renewable Energy Sources Using Modified Moth Flame Optimization Technique

“…A hybrid fuzzy logic controller technique and ant-lion optimization algorithmŠs with particle swarm optimization based combination is proposed in [24] to solve the optimal allocation of distributed generations in a radial distribution network to minimize the total cost of operation and deviation of voltage indexes. In [25] at different load levels, the objective function to find optimal location and sizing of DGs is reducing real and reactive power losses which solved by using biogeography-based optimization (BBO) algorithm. An efficient optimization algorithm to optimally allocate the multiple DG units in distribution systems based on sine cosine algorithm (SCA) and chaos map theory is proposed in [26] using three objective functions.…”

“…The parameter ε is a very important parameter in (25) where it controls the flying direction of the moth around the flame. Equation (25) permits a moth to navigate around a flame and not essentially within the space between them.…”

Inbreeded GA for optimal distributed resource allocation in distribution systems

“…DGs can provide more reliable, secured, and self‐sustainable operation of distribution systems with lesser carbon footprints, and can deliver quality power to customers. The optimal placement of DG reduces active and reactive losses, improves voltage profile, increases reliability and network security and helps in lowering the harmonics and its adverse effects [1]. However, most of the DG units are operated at unity power factor so that their penetration level may be improved by adequate reactive power support, which can be provided by installing shunt capacitors (SCs) in distribution systems.…”

“…Very few attempts [1, 3–8] have been made for optimally placing SCs and DGs simultaneously using several powerful metaheuristics such as particle swarm optimisation (PSO) [3, 4], artificial bee‐colony [5], memetic algorithm [7], combined imperialist competitive algorithm‐genetic algorithm [8], etc. These problems involve the determination of their optimal number, size and sites in distribution network while satisfying several network and operational constraints.…”