Optimal Placement of Distributed Generators with Regard to Reliability ‎Assessment using Virus Colony Search Algorithm

Sayed Jamal al-Din Hosseini, Mohammadreza Moradian, Hossein Shahinzadeh, Sima Ahmadi

Abstract


The integration of distributed generation (DG) resources is growing day by day in electricity grids. There are many reasons which persuade the operators to utilize DGs such as restrictions on the construction and development of transmission lines and distribution network, transition of traditional power systems to restructured electricity markets, the competitive conditions in wholesale and retail markets, the implication of economic and environmental issues in the production of electrical energy, increasing the system reliability and customer satisfactory level. The reliability improvement capability of power systems by utilization of these units has attracted the attention of many electrical engineering experts and power system planners and operators. Reliability plays a prominent role in the satisfaction of all power industry participants, especially the consumers of the electricity. In this paper, the effect of distributed generation units on the power system reliability has been investigated.  Therefore, the virus colony search (VCS) algorithm is employed to determine the optimal placement and size of distributed generators subject to improve the reliability indices. The simulation is carried out on a 34-bus IEEE test network. The optimization results are also compared with the results of both genetic algorithm (GA), particle swarm optimization (PSO) algorithm, differential evolution (DE) algorithm, multi-objective particle swarm optimization (MOPSO) algorithm, modified shuffled frog leaping algorithm (MSFLA), gravitational search algorithm (GSA), biogeography-based optimization (BBO) algorithm, hybrid big bang-big crunch (HBB-BC) algorithm and glowworm swarm optimization (GSO) algorithm.

Keywords


Distributed Generation, Virus Colony Algorithm, Optimal placement and sizing, Reliability, Distribution Network.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v8i2.7112.g7406

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