Affiliations: [a] Department of Electrical Engineering, Jaipur Engineering College and Research Centre, Jaipur, India
| [b] Department of Electronics and Telecommunication Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India
| [c] Department of Electrical Engineering, Swami Keshwanand Institute of Technology, Jaipur, India
Correspondence:
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Corresponding author. Rahul kumar Malee, Department of Electrical Engineering, Jaipur Engineering College and Research Centre, Jaipur, India. E-mail: [email protected].
Abstract: Expansion planning of distribution system is the most significant tool which deal with the continuous increasing load demand. The main motive of the expansion planning is the minimization of the investment and operation cost of distribution network equipment which consider the installation/reinforcement cost of substation, feeders and Distribution Generation. In this paper, price and load uncertainties are taken in to expansion planning which gives the robust and reliable expansion planning. These uncertainties are molded as Normal Probability Distribution Function. By using Monte Carlo Simulation uncertainties are added in to planning. A 72 bus (Kian-pars Ahvaz 11 KV a practical distribution network in Iran) distribution network is used for case study of expansion planning. This multistage dynamic expansion planning problem is resolved by the Quantum Particle Swarm Optimization. The proposed algorithm is compared with the standard Particle Swarm Optimization and results shows the superiority of proposed algorithm over PSO.
Keywords: Probability distribution function, distributed generation, quantum PSO, monte-carlo simulation
