Design and control of smart local energy systems considering multi-phase optimal power flow

Distributed energy system optimisation is complex, especially when considering the intermittency of renewable energy and demand, combined with the large-scale non-convex optimal power flow problem. To respond to these challenges, we propose to use new theoretical advances in optimisation under uncertainty, control theory, and distributed optimisation in combination with machine learning techniques, to decompose the large-scale problem into a tractable problem that may be solved for real-time optimisation and control considering demand response to build a next generation energy system management tool.