Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/24549
Título : Simulation of the optimal programing strategy between different markets of a pure pumping storage plant
Autor : Zumalave Freire, Ignacio
Bohnen, Daan
García Ruiz, David
Universidad Pontificia Comillas, Escuela Técnica Superior de Ingeniería (ICAI)
Palabras clave : 33 Ciencias tecnológicas;3322 Tecnología energética;332205 Fuentes no convencionales de energía;53 Ciencias económicas;5312 Economía sectorial;531205 Energía
Fecha de publicación : 2017
Resumen : The increasing incorporation of renewable energies in the electrical system needs more and more energy storage systems due to their intermittent associated production. Currently, the industry's state of the art technology is pumping hydropower, that can be seen as giant batteries, being able to store the excess of energy in the system when there is not enough demand and act as regulators balancing the system when needed. For this reason, it is essential to manage this type of facilities in an optimal way. This project seeks to obtain, through the formulation of optimization models, the optimum scheduling of a pumping plant not only for a single market, but for several electricity markets. The models developed try to replicate the behavior of these markets as detailed as possible and, as a result, obtain a tool that maximizes the usage of the plant. Due to the wide options of market participation that this kind of plant offers, only the daily and intraday markets have been studied considering all possible options for the management of the energy reserves that are stored through pumping and turbining. The results obtained by the developed models have been satisfactory, fulfilling the proposed objectives. These results show that the optimal management of the plant depends on several factors, such as taxes, initial and final level of the upper reservoir, time horizon, market prices, competition in the market, and pump storage plant characteristics.
Descripción : Master in the Electric Power Industry
URI : http://hdl.handle.net/11531/24549
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