Ranking Index in the Pareto Optimal Front Based Evolutionary Programming Technique for Best Selection of Several Optimal Multi-Objective Capacity Benefit Margins

Abstract:

The amount of power transfer between areas is purporting as imperative information required by the utility so that this will assist them towards an effective operation of electricity market performed in a deregulated power system. CBM is defined as the amount of the transfer capability reserved by the load-serving entities which will be used during the case of generation deficiency. This paper presents a new approach used to perform simultaneous determination of capacity benefit margin (CBM) for all areas by using the evolutionary programming (EP) technique. Ranking index in the Pareto optimal front cluster of total loss-of-load expectation (LOLE) and total LOLE difference will be used for selecting several best solutions of multi-objective CBMs. Eventually, performance of the proposed method is investigated thoroughly via a test system of modified IEEE-RTS79. Utilization of the proposed technique is superior in terms of offering flexibility to the utility in selecting several best solutions of multi-objective CBMs.

• Periodical: Applied Mechanics and Materials (Volume 785)
• Pages: 506-510
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.785.506
• Online since: August 2015
• Authors: Muhammad Murtadha Othman*, Nurulazmi Abd Rahman, Ismail Musirin
• Keywords: Capacity Benefit Margin (CBM), Evolutionary Programming (EP), Ranking Index in Pareto Optimal Front Cluster

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