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In this paper, an expert system is designed to derive the rephasing strategy of laterals and distribution transformers to enhance three-phase balancing of distribution systems. The heuristic rules adopted by distribution engineers are incorporated in the knowledge base of the expert system in the problem-solving process. The neutral current reduction algorithm is developed to support the inference engine to derive the rephasing strategy to reduce the neutral current of distribution feeder so that the tripping of over-current relay can be prevented and the customer service interruption cost and labor cost to execute the rephasing strategy can be justified by the power loss reduction obtained. To demonstrate the effectiveness of the proposed expert system to enhance three-phase balance, a practical distribution feeder in Taiwan Power Company (Taipower) is selected for computer simulation. By minimizing the objective function subjected to the rephasing rules, the rephasing strategy has been derived to identify the laterals and distribution transformers for phasing adjustment. After executing the proposed rephasing strategy by Taipower engineers, the phase currents and neutral current of test feeder has been collected by the SCADA system to verify the reduction of neutral current. The power loss reduction obtained by three-phase balancing has been solved by three-phase load flow analysis, which is then used to justify the customer service interruption cost and labor cost for rephasing of test feeder. [ABSTRACT FROM AUTHOR]

This paper derives two fuzzy financial profitability models, namely, a least cost solution model and a cost-benefit analysis model, to evaluate the fuzzy financial profitability of load management alternatives. A straightforward vertex parameters' fuzzy mathematics operation using the function principle is derived as an alternative to the traditional extension principle and is applied to evaluate a number of different financial decision indexes. Compared to the extension principle, the function principle is simple to implement and is conceptually straightforward. The geometric moments of the fuzzy financial indexes are established in order to determine their relative ranking as part of a decision-making process. The performances of the proposed fuzzy financial models are verified by considering their application to two practical load management programs in Taiwan, namely, a cooling energy storage air conditioner and a cogeneration project. These investigations not only confirm that the results of the fuzzy financial models are consistent with those of the conventional crisp models but also demonstrate that the proposed models are more flexible, intelligent, and computationally efficient compared to the extension principle fuzzy mathematics approach. The developed models represent readily implemented possibility analysis tools for use in the arena of uncertain financial decision-making. [ABSTRACT FROM AUTHOR]