Fuzzy Optimization for Power System Scheduling and Transaction Problems

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9420972 Luh Scheduling power systems and determining inter-utility power transactions are important activities faced by electric utilities. These two activities form an integrated problem since they are coupled through system demand and reserve requirements. The objective is to supply reliable, economic and clean power. This problem is becoming very important because of the deregulation trend making the power market more competitive, and because of the Clean Air Act making utility operating conditions more stringent. The University of Connecticut, with support from Northeast Utilities Service Company, proposes to explore three vital and closely linked areas: (l) a Lagrangian relaxation based fuzzy optimization approach for short-term scheduling and transaction to handle uncertainties such as transaction and fuel prices and system demand; (2) transaction and scheduling for a long time horizon up to one year with the consideration of emission constraints and transmission line capacity constraints by using the time aggregation idea; and (3) a new class of algorithms to optimize the concave, piecewise smooth, and non- differentiable Lagrangian dual functions by exploring their geometric characteristics for improved performance. These areas form a synergistic research program, with one area leading to the next and supporting the others. Our aim is to help utility engineers make effective scheduling and transaction decisions based on sound mathematical principles, and to advance the state- of-the-art and practice of optimization techniques for systems characterized by uncertainties in general and power systems in particular. ***