To meet the needs of the increasing number and importance of energy interchanges in new competitive power system environments, a method for multi-objective optimization is proposed which uses a goal decision network (GDN) to model the knowledge used to analyze interchange contracts. A new search algorithm, guided by negotiation operators and the knowledge in the GDN, is developed to identify optimal solutions and the tradeoffs between problem objectives. The algorithm is used to optimize an energy-purchase contract with respect to the objectives of reliability, cost savings, and the survival rate of fish migrating through a hydro-electric system.
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