Economic-environmental-security transform curves of electric power system production schedules and simulations
A quasi-optimal technique ('quasi' in that the technique discards unreaonable optimums), realized by a dynamially evolving mixed integer program, is used to develop regional electric power maintenanee and production sample schedules, as well as unit commitment sample schedules. This sophisticated, yet omputationally feasible, method is used to develop the bulk dispatch schedules required to meet electric power demands at various preset reliability levels while oentrolling the associated dollar and environmental impact consequences. This report considers a hypothetical system of about twelve power plants situated close to one another on the same river system. The maintenance and unit commitment scheduling mechanisms are used to display the tradeoffs which exist between the economic costs, environmental consequences and reliability levels of all possible optimum schedules. These tradeoff, or transform, surfaces are generated from acoul schedules for system opertio. Also generated is a sample system imulation. Three possible generation expansion plans are compared and their potential operating performances are displayed. These specifically hypothesized expansion plans were tested os two different possible future load demand curves. The results show that there is great value in the use of an accurate dollar and environmental impact simulator. Hypothetical data has been used, but effort has been made to make this data as representl&tve as possible. The results of this project show that a great amount of flexibility is available to both the operations scheduler and the system expansion planner, and that the dollar costs, water and air pollution impacts cover a wide range of consequences. These results also show that S.'i.opkebably very wasteful to operate or plan a system using any simple, single- minded measure of desirability as a decision making strategy.
Prepared in association with Electric Power Systems Engineering Laboratory and Dept. of Civil Engineering, M.I.T
MIT Energy Lab
Production scheduling, Electric power-plants -- Environmental aspects, Electric power-plants -- Costs, Electric power production
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