Title :
Novel approach to generation Portfolio Optimization by using genetic algorithms and stochastic methods
Author :
Di Giorgio, Alessandro ; Mercurio, Andrea ; Pimpinella, Laura
Author_Institution :
Dept. of Comput. & Syst. Sci., Univ. of Rome Sapienza, Rome, Italy
Abstract :
In this paper we present the Portfolio Optimization Problem in the electricity generation framework. We consider traditional and fully controllable energy sources together with wind source, strongly supported by economical benefits but exposed to intermittent generation volatility. Due to the statistical uncertainty about parameters, we formalize the optimization problem in a probabilistic sense and solve it by using Genetic Algorithms.
Keywords :
genetic algorithms; investment; power generation economics; probability; stochastic processes; wind power plants; electricity generation portfolio optimization problem; energy sources; genetic algorithms; intermittent generation volatility; statistical uncertainty; stochastic methods; wind source; Coal; Genetic algorithms; Green products; Investment; Optimization; Portfolios; Power generation; Generation Company; Genetic Algorithms; Monte Carlo method; Net Present Value; Portfolio;
Conference_Titel :
Control Conference (ECC), 2009 European
Conference_Location :
Budapest
Print_ISBN :
978-3-9524173-9-3
