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

分布式能源系统的优化是复杂的，特别是在考虑可再生能源和需求的间歇性的情况下，结合大规模的非凸最优潮流问题。为了应对这些挑战，我们建议使用不确定性优化、控制理论和分布式优化方面的新理论进展，并结合机器学习技术，将大规模问题分解为一个可处理的问题，可以考虑需求响应进行实时优化和控制，以构建下一代能源系统管理工具。

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.