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Maximum Loading Enhancement by Differential Evolution Particle Swarm Optimization Based Optimal Power Flow Solution

M. Sai Veerraju*, Sanker Ram**, K. Vaisakh***

* Associate Professor, Department of Electrical and Electronics Engineering, S.R.K.R. Engineering College, Bhimavaram, India.

** Professor, Department of Electrical and Electronics Engineering, JNTU College of Engineering, JNT University, Hyderabad, AP, India.

*** Professor, Department of Electrical Engineering, AU College of Engineering, Andhra University, Visakhapatnam, AP, India.

Periodicity:October - December'2009
DOI : https://doi.org/10.26634/jee.3.2.1043

Abstract

Maximum Loadability Limit (MLL) is the margin between the operating point of the system and the maximum loading point. The enhancement of maximum loadability limit of power system can be formulated as an optimization problem, which consists of two steps namely computing MLL and the optimum cost of generation for MLL. This paper proposes a differential evolution particle swarm optimization (DEPSO) algorithm for solving the optimal power flow problem for MLL enhancement with voltage stability constraint. The DEPSO employs features of both differential evolution (DE) and particle swarm optimization (PSO) for the development of hybrid algorithm. The feasibility of the proposed approach was tested on IEEE 30-, 57-bus test systems. Case studies were investigated to test and validate the robustness of the proposed method in finding optimal solution. Simulation results demonstrate that the DEPSO provides very remarkable results compared to original DE, PSO and other methods reported in the literature recently.

Keywords

Differential Evolution, Optimal Power Flow, Particle Swarm Optimization, Generation Cost, Voltage Stability Index.

How to Cite this Article?

M. Saiveerraju, B.V. Sankar Ram and K. Vaisakh (2009). Maximum Loading Enhancement By Differential Evolution Particle Swarm Optimization Based Optimal Power Flow Solution. i-manager’s Journal on Electrical Engineering, 3(2), Oct-Dec 2009, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 1-10. https://doi.org/10.26634/jee.3.2.1043

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