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Alexandre Alonso Travesset
2019
Gestió òptima de l'energia en microxarxes amb incertesa a la producció i a la demanda.
Jordi De la Hoz Casas, F-Javier Heredia Cervera
Faculty iof Mathematics and Statistics.
09/2019
teaching
microgrids
electricity market
MSc Thesis
The following Master Thesis involves the construction of a mathematical model aimed at evaluating the economic feasibility of microgrids, which are powered by renewable energy sources. These sources are characterized by their spatial and temporal variability, thus the need to use a statistical approach to forecast these variables becomes apparent. Furthermore, other uncertain variables such as the electrical demand and the market pool price contribute to the formulation of the program. State-of-the-art time-series based models are fitted in order to forecast the behaviour of the uncertain variables. Synthetic data arisen from simulations is drawn from these models in order to generate scenarios of probability. The scenarios are then reduced by means of the backward reduction algorithm in order to increase computational performance, and subsequently introduced in a two-stage stochastic program coded in AIMMS interface. Results show significant details about energy management and prove the suitability of using a stochastic approach rather than a deterministic one to perform the optimisation.