Affiliation:
1. University of Padova, Padova, Italy
Abstract
The development of proper tools for power plants production planning is becoming crucial to profitably compete in a deregulated market scenario. Two numerical techniques, the former based on the dynamic programming, the latter on an original real-coded genetic algorithm, are suggested in this paper to optimize the management of cogeneration power plants with thermal storage. Detailed mathematical models are required to simulate plant part-load performance in order to evaluate possible operation plans profitability. Electricity price trends, forecasted from market analyses, are used as input data. Technical constrains and those derived from the market characteristics are included in the optimization problem. The suggested approaches are applied to some possible market situations, typical of different seasons and competition intensities. Results obtained are compared in terms of accuracy and resolution time. Iterative analyses are also performed to assess possible management flexibility improvements resulting from different design choices of the cogeneration system.
Cited by
3 articles.
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