The Utilization of Shared Energy Storage in Energy Systems: Design, Modeling and Optimization

Energy storage (ES) plays a significant role in modern smart grids and energy systems. With the advances of ES technologies, efficiently applying ES to energy systems has become the bottleneck for achieving the benefits of ES. The traditional approach of utilizing ES is the so-called distributed framework in which there is a separate ES for each individual user. Due to the inherent limits in the distributed framework such as cost inefficiency and space limitations, many studies have promoted to utilize a shared ES in energy systems to further exploit the potentials of ES. However, current studies always focus on maximizing the benefits of utilizing the shared ES and neglect the importance of fairness in ES sharing. To build a successful ES sharing system, the challenge is to balance the conflict between efficiency and fairness in ES sharing. The efficiency means maximizing the overall economic benefits from ES sharing. The fairness is the regulation to ensure the fair energy exchange between the participants in ES sharing and fair distribution of benefits from ES sharing. To bridge this gap, this thesis addresses the challenge of utilizing the shared ES in energy systems in terms of system design, operational strategy, and optimization algorithms. To the best of our knowledge, the first literature review for ES sharing has been completed in this thesis. This review determines the scope of ES sharing, classifies the architectures of ES sharing systems, and validates the research gaps for ES sharing. This thesis proposes a balanced sharing strategy to achieve the tradeoff between efficiency and fairness in ES sharing. The strategy is developed based on multi-objective optimization to manage the ES sharing system with two users; It is extended to handle energy price uncertainty through robust optimization and operate the ES sharing system with multiple users by applying Game Theory concepts. The algorithm development work in this thesis aims to advance the solutions to the balanced sharing strategy. It includes the improvement of the algorithms for multi-objective optimization, bi-linear optimization, and Game Theory. Overall, this thesis presents an integral intellectual framework for ES sharing to address the key challenge of applying shared ES in energy systems