Hierarchical energy management system based on fuzzy prediction intervals for operation and coordination of microgrids

Abstract

The integration of large numbers of Distributed Energy Resources (DERs) into the distribution system could take place either by reinforcement of the existing network assets, or the incorporation of active management of flexible resources into different sections of the distribution network. For active management of a distribution network, the design of control strategies is necessary for an efficient and reliable large-scale integration of DERs. Besides the benefit of supporting the use of renewable energy sources, DERs play an important role in improving the resilience and sustainability of the electricity distribution system and also in the generation of new market opportunities. In this thesis, the active management of DERs is proposed using a hierarchical energy management system (EMS) applied to "Energy Communities". Energy communities are a concept which allows different end users to cooperate in their energy interactions with the aim of maximising their self-consumption, minimising energy costs, reducing peak power levels or a combination of these and other beneficial goals as well. The hierarchical EMS proposed allows incorporating mechanisms to ensure both the realisation of short-term power balancing objectives and long-term energy management, benefiting the microgrid owner and the distribution network operator. The hierarchical EMS is designed in two levels: main grid level and microgrid level. At the microgrid level, a real-time local rule-based controller is proposed and at the higher level, a Robust model predictive control (MPC) is used to manage the uncertainty associated with renewable distributed generation and electricity demand. The uncertainty is incorporated into the Robust MPC controller based on fuzzy prediction interval models in order to help the system to be prepared for errors in the predictions that might yield sub-optimal decisions. Several case studies are used to test the performance of the hierarchical EMS for the operation and coordination of microgrids. Robust EMS based on fuzzy prediction interval models is compared to the deterministic EMS and with a basic EMS without energy storage system (ESS). The results show that the deterministic and Robust EMSs provide improvements over the case without ESS, as they offer mechanisms for efficient energy management. The incorporation of an ESS into the energy community benefits both the end user, by reducing energy cost, and the distribution network operator, by limiting the peak power levels and enabling increased penetration of distributed generation (DG). Additionally, the hierarchical EMS is able to keep the community power flow close to the reference power defined by the higher level controller with minimum energy cost, among other benefits. Finally, end users operating as Energy Communities can optimise the use of DG and the size of the ESS required.