Intelligent Multiobjective Optimization of Distribution System Operations

Robert J. Sarfi, Ashu M. G. Solo


A hybrid fuzzy knowledge-based system with crisp and fuzzy rules as well as numerical methods was developed for multiobjective optimization of power distribution system operation. The development process and knowledge-acquisition process for the fuzzy knowledge-based system are described in detail. Fuzzy sets are defined for recent temperature trend, line section loading, transformer aging, voltage-level guidelines, and the degree of desirability of a proposed switching combination. After a heuristic preprocessor proposes a list of switch openings that would seem to reduce system losses, network radiality rules consider whether to open a particular switch and find a corresponding switch that can be closed to maintain radiality. Network parameter rules determine whether the proposed switching combination will violate network integrity. Network performance rules find the degree of desirability of proposed switching combinations for enhancing multiple objectives. All operational aspects of power distribution systems are considered, and a solution is still found in real time.

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