Distributed Solution for Pareto Front Based Multi-objective OPF

Pareto front (PF) based multi-objective OPF (MO-OPF) is an effective tool in power system operation and an efficient multi-objective algorithm is necessary to tackle it. In addition, under some scenarios this algorithm needs to have distributed solution capability to cope with some difficulties in operation. Most of the existing distributed MO-OPF approaches are based on mathematical programming techniques by which a multi-objective problem needs to be converted into multiple single-objective problems (SOP). The tedious repetition of algorithmic executions is inevitable. In this study, coevolutionary algorithm (CA) is applied to solve the distributed MO-OPF. The problem is decomposed based on decision variables. After segmenting by the geographical division, multiple subpopulations are coevolved among areas and a distributed power flow calculation method is embedded to support the distributed fitness evaluation. The experimental results demonstrate the effectiveness of the distributed approach and the advantages of the second decomposition.