User-centric Demand Side Energy Management Techniques with Mobile Battery Energy Storage System Integration and Socialization Modelling

Abstract

Smart grids enable two-way communication between power generation and demand sides, allowing efficient operation of the energy system by power generators, grid operators, end users, and market stakeholders. Demand Side Management (DSM) in smart grids helps users adjust their energy usage, providing energy, environmental, and economic benefits.

User engagement is crucial for DSM performance, but current DSM designs focus mainly on economic and energy factors, ignoring user participation drivers. Integrating large-scale renewable energy poses challenges in maintaining power system flexibility. Therefore, more user-centric DSM studies are needed, especially with distributed renewable energy.

This thesis first proposes a community-level user-centric DSM model for energy trading in a Peer-to-Peer (P2P) market. By considering social factors like social networks and socio-demographic characteristics, user engagement can be greatly improved.

The second research introduces a DSM model addressing renewable penetration using Mobile Battery Energy Storage Systems (MBESS) due to their low cost and ease of deployment. MBESS enhances distribution system reliability and integrates distributed energy without causing grid fluctuations. This research designs two comprehensive decision-making frameworks for MBESS service providers to generate MBESS-based energy backup plans for energy users under planned outage events and two decoupled solving approaches are also proposed correspondingly to solve these two problems.

The third research focuses on household appliance usage, proposing a local-level DSM model to create intelligent usage plans under real-time electricity pricing. It considers economic factors, user satisfaction, and thermal comfort, formulating a multi-objective problem with a corresponding solving approach.

Finally, comprehensive simulations and case studies validate the effectiveness of these DSM models.