  To coordinate the economy, security and environment protection in the power
system operation, a two-step many-objective optimal power flow (MaOPF) solution
method is proposed. In step 1, it is the first time that knee point-driven
evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and
thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated
decision analysis technique is utilized to provide decision makers with
decision supports by combining fuzzy c-means (FCM) clustering and grey
relational projection (GRP) method together. In this way, the best compromise
solutions (BCSs) that represent decision makers' different, even conflicting,
preferences can be automatically determined from the set of Pareto-optimal
solutions. The primary contribution of the proposal is the innovative
application of many-objective optimization together with decision analysis for
addressing MaOPF problems. Through examining the two-step method via the IEEE
118-bus system and the real-world Hebei provincial power system, it is verified
that our approach is suitable for addressing the MaOPF problem of power
systems.
