Multi-Stage Stochastic Model for Optimum Mix Selection of Distributed Renewable Generation Plants in Critical Electrical Systems
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Stochastic Dynamic Optimization, Distributed Generation, Operation Planning, Expansion Planning, Renewable Energy Uncertainties. (es)Descargas
The present paper develops a dynamic optimization mathematical model to obtain the optimum mix of generation plants with renewable energy resources (RER) necessary to provide reliability to a radial electrical system. This model takes as inputs the energy potential of water, wind and solar resources available and injectable in the area, capital cost of these plants and related infrastructure; as well as existing electrical grid and conventional generation plants parameters. The optimization process is performed for the 8760 hours of a typical year within which it is considered out of service states for existing transmission lines, bus bars and power plants. Within its stochastic approach it is contemplated a cost sensibility analysis. The real application case’s results evidence an improvement around 90% in the SAIFI and SAIDI performance indexes.
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Sayas, L., & Felix, R. (2017). Multi-Stage Stochastic Model for Optimum Mix Selection of Distributed Renewable Generation Plants in Critical Electrical Systems. Simposio Internacional Sobre La Calidad De La Energía Eléctrica - SICEL, 9. https://revistas.unal.edu.co/index.php/SICEL/article/view/64208
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Derechos de autor 2018 Simposio Internacional sobre la Calidad de la Energía Eléctrica - SICEL

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.