A novel real-time demand side management scheme for the addition of electrical vechicles to the future grid

Electric Vehicles (EVs) as the alternative to the current fossil fuel vehicles represent the most promising green approach to the electrification of a significant portion of the transportation sector. Taking the randomness of EVs’ charging/ discharging characteristics into consideration, a significant uncertainty will be added to the grid. Consequently, charging/discharging management of EVs in the presence of large scale intermittent Renewable Energy Resources is considered as the most significant challenge for the future smart grid. Tackling the challenges of stable operation, this thesis proposes a novel approach of micro-grid stability by exploiting the demand side management. In this context, a comprehensive interactive hierarchical based architecture for the electricity supply and demand interaction in a smart grid environment is proposed to encourage the high participation of residential customers in a new deregulated electricity market. A novel market-oriented energy imbalance management scheme is also proposed for the seamless integration of EVs to the grid in the presence of intermittent resources. The proposed scheme which, unlike previous works, utilizes the grid’s operating characteristics model within the signaling gametheoretic approach for the successful operation of electricity market. Optimal decision strategies for both EV owners and utility are devised by capturing the conflicting economic interests of players together under load/generation uncertainties. Thus, this thesis presents a planning tool for electric utilities that can provide an insight into the implementation of demand response at the end-user level in an automated way to bridge the gap between scheduling EVs and its benefits. The efficacy of the proposed approach in reducing peak loads while satisfying customers’ needs are demonstrated and compared with other schemes. Results show that the proposed methodology can successfully alleviate more than 53% of the peaks caused by the mass adoption of EVs with the better utilization of intermittent resources and substantial amount of profit

Stochastic management framework of distribution network systems featuring large-scale variable renewable energy sources and flexibility options

The 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.As mudanças climáticas, a crescente procura por energia e a segurança de abastecimento estão a modificar a operação e o planeamento das redes de distribuição, especialmente pela necessidade de integração em larga escala de fontes de energia renováveis. O aumento desses recursos energéticos sustentáveis gera enormes desafios a nível técnico no sistema, atendendo a que o operador do sistema de distribuição tem o dever de manter a integridade e a estabilidade da rede, bem como a qualidade de energia entregue aos consumidores. Portanto, os sistemas de energia elétrica existentes devem passar por um eminente processo de transformação para que as limitações atuais sejam devidamente atenuadas ou mesmo evitadas, esperando-se assim chegar ao paradigma das redes elétricas inteligentes. Para as redes de distribuição acomodarem fontes variáveis de energia renovável, novas e emergentes opções de flexibilidade, que dizem respeito à geração, carga e à própria rede, precisam de ser desenvolvidas e consideradas na operação ótima da rede de distribuição. Assim, a gestão das opções de flexibilidade deve ser cuidadosamente efetuada para minimizar os efeitos secundários como o aumento dos custos, agravamento do perfil de tensão e o desempenho geral do sistema. Desta perspetiva, é necessário entender como uma rede de distribuição pode operar de forma ótima quando se expõe a uma integração em larga escala de fontes variáveis de energia renovável. Devido à variabilidade e incerteza associadas a estas tecnologias, novas metodologias e ferramentas computacionais devem ser desenvolvidas para lidar com os desafios subsequentes. Desta forma, as opções de flexibilidade existentes e emergentes devem ser implantadas para gerir a incerteza e variabilidade das fontes de energia renovável, mantendo o necessário balanço entre carga e geração. Nesta tese é feita uma análise extensiva das principais tecnologias que podem providenciar flexibilidade aos sistemas de energia elétrica, e as suas contribuições para a operação ótima dos sistemas de distribuição, tendo em consideração a natureza estocástica dos recursos energéticos intermitentes e outras fontes de incerteza. Adicionalmente, este trabalho contém investigação detalhada sobre como o sistema pode ser otimamente gerido tendo em conta estas tecnologias de forma a que a uma maior percentagem de carga seja fornecida por fontes variáveis de energia renovável, mantendo a fiabilidade, estabilidade e eficiência do sistema. Por esse motivo, novas metodologias e ferramentas computacionais usando programação estocástica são desenvolvidas para modelizar a variabilidade e incerteza inerente à geração eólica e solar. A convergência para uma solução ótima é garantida usando programação linear inteira-mista para formular o problema

Demand Response in Smart Grids

The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer