Optimized allocation of power quality monitors in transmission systems: a multiobjective approach

Abstract

This paper proposes a methodology to solve the allocation problem of power quality monitors in transmission systems. The problem is formulated to minimize the total cost of the monitoring system and to maximize the redundancy of measurements. The proposed approach explicitly deals with both objectives to find a set of efficient solutions in the objective space. The Multiobjective Evolutionary Algorithm with Tables (MEAT) is the optimization method investigated due to its recent relevant results in the literature. The methodology proposed considers the electrical system topology, and it was applied to different IEEE-test systems for validation. The results show that the MEAT finds a set of efficient solutions that are diversified and well-distributed along the Pareto Front, indicating adequate exploration of the objective space and the search space. With the Pareto Front, the utility can choose a plan with relevant trade-off involving the total cost and the redundancy of measurements. The results show that the Pareto Front can be very useful when deciding the most proper monitoring plan according to available funds.