Meter placement in active distribution system using objective discretization and indicator-based multi-objective evolutionary algorithm with adaptive reference point method
- Vol.103(3), June
- New York Springer 2022
- 887-901p.
A new indicator-based multi-objective evolutionary algorithm (MOEA) using the objective discretization method is proposed for the meter placement problem (MPP) in active distribution system. Because MPP is a combinatorial optimization, a combination of measurement sets produces a discrete objective space. Therefore, the objective discretization method has been adopted to enhance the performance of MOEA. The proposed MOEA is an indicator-based method using an inverted generational distance indicator with noncontributing solution detection (IGD-NS) and with an adaptive reference point method (IB-MOEA-AR). The advantage of the IGD-NS indicator is that it measures the diversity and convergence of the solution set as well as identifies the solutions, which does not contribute to the indicator. As the performance of MOEA mostly depends on the Pareto front shape, the proposed method employs an adaptive reference point approach to follow the shape of the Pareto front. Moreover, the effect of distributed generation is investigated on distribution system state estimation performance for different measurement uncertainties as well as for various distributed renewable generations. The MPP is modeled as a multi-objective problem with the objectives consisting of minimization of total meter cost and state estimation errors. The versatility of the proposed method is demonstrated on Indian Practical 85-bus distribution system and UKGDS 95-bus distribution system. The results obtained are compared to existing MOEAs in the literature, to demonstrate the superiority of the proposed method over other methods.