Browsing by Author "Cruz, Marco Rafael Meneses"
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- Stochastic management framework of distribution network systems featuring large-scale variable renewable energy sources and flexibility optionsPublication . Cruz, Marco Rafael Meneses; Catalão, João Paulo da Silva; Mariano, Sílvio José Pinto Simões; Fitiwi, Desta ZahlayThe concerns surrounding climate change, energy supply security and the growing demand are forcing changes in the way distribution network systems are planned and operated, especially considering the need to accommodate large-scale integration of variable renewable energy sources (vRESs). An increased level of vRESs creates technical challenges in the system, bringing a huge concern for distribution system operators who are given the mandate to keep the integrity and stability of the system, as well as the quality of power delivered to end-users. Hence, existing electric energy systems need to go through an eminent transformation process so that current limitations are significantly alleviated or even avoided, leading to the so-called smart grids paradigm. For distribution networks, new and emerging flexibility options pertaining to the generation, demand and network sides need to be deployed for these systems to accommodate large quantities of variable energy sources, ensuring an optimal operation. Therefore, the management of different flexibility options needs to be carefully handled, minimizing the sideeffects such as increasing costs, worsening voltage profile and overall system performance. From this perspective, it is necessary to understand how a distribution network can be optimally operated when featuring large-scale vRESs. Because of the variability and uncertainty pertinent to these technologies, new methodologies and computational tools need to be developed to deal with the ensuing challenges. To this end, it is necessary to explore emerging and existing flexibility options that need to be deployed in distribution networks so that the uncertainty and variability of vRESs are effectively managed, leading to the real-time balancing of demand and supply. This thesis presents an extensive analysis of the main technologies that can provide flexibility to the electric energy systems. Their individual or collective contributions to the optimal operation of distribution systems featuring large-scale vRESs are thoroughly investigated. This is accomplished by taking into account the stochastic nature of intermittent power sources and other sources of uncertainty. In addition, this work encompasses a detailed operational analysis of distribution systems from the context of creating a sustainable energy future. The roles of different flexibility options are analyzed in such a way that a major percentage of load is met by variable RESs, while maintaining the reliability, stability and efficiency of the system. Therefore, new methodologies and computational tools are developed in a stochastic programming framework so as to model the inherent variability and uncertainty of wind and solar power generation. The developed models are of integer-mixed linear programming type, ensuring tractability and optimality.