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Forecasting tools and probabilistic scheduling approach incorporatins renewables uncertainty for the insular power systems industry

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Bibliographic Details
Summary:Nowadays, the paradigm shift in the electricity sector and the advent of the smart grid, along with the growing impositions of a gradual reduction of greenhouse gas emissions, pose numerous challenges related with the sustainable management of power systems. The insular power systems industry is heavily dependent on imported energy, namely fossil fuels, and also on seasonal tourism behavior, which strongly influences the local economy. In comparison with the mainland power system, the behavior of insular power systems is highly influenced by the stochastic nature of the renewable energy sources available. The insular electricity grid is particularly sensitive to power quality parameters, mainly to frequency and voltage deviations, and a greater integration of endogenous renewables potential in the power system may affect the overall reliability and security of energy supply, so singular care should be placed in all forecasting and system operation procedures. The goals of this thesis are focused on the development of new decision support tools, for the reliable forecasting of market prices and wind power, for the optimal economic dispatch and unit commitment considering renewable generation, and for the smart control of energy storage systems. The new methodologies developed are tested in real case studies, demonstrating their computational proficiency comparatively to the current state-of-the-art.
Main Authors:Silva, Gerardo José Osório da
Subject:Indústria de energia eléctrica - Gestão sustentável Indústria de energia eléctrica - Despacho económico Indústria de energia eléctrica - Energias renováveis Indústria de energia eléctrica - Armazenamento de energia
Year:2015
Country:Portugal
Document type:doctoral thesis
Access type:open access
Associated institution:Universidade da Beira Interior
Language:English
Origin:uBibliorum
Description
Summary:Nowadays, the paradigm shift in the electricity sector and the advent of the smart grid, along with the growing impositions of a gradual reduction of greenhouse gas emissions, pose numerous challenges related with the sustainable management of power systems. The insular power systems industry is heavily dependent on imported energy, namely fossil fuels, and also on seasonal tourism behavior, which strongly influences the local economy. In comparison with the mainland power system, the behavior of insular power systems is highly influenced by the stochastic nature of the renewable energy sources available. The insular electricity grid is particularly sensitive to power quality parameters, mainly to frequency and voltage deviations, and a greater integration of endogenous renewables potential in the power system may affect the overall reliability and security of energy supply, so singular care should be placed in all forecasting and system operation procedures. The goals of this thesis are focused on the development of new decision support tools, for the reliable forecasting of market prices and wind power, for the optimal economic dispatch and unit commitment considering renewable generation, and for the smart control of energy storage systems. The new methodologies developed are tested in real case studies, demonstrating their computational proficiency comparatively to the current state-of-the-art.

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