Robust Micro-Grid Energy Management System Through a Scenario Approach

The growing adoption of distributed Renewable Energy Sources and Battery Energy Storage in micro-grids requires robust Energy Management Systems (EMS) to handle power generation and consumption uncertainties. In this paper, we propose a hierarchical EMS architecture comprised of two controllers operating at different time scales: a supervisory Model Predictive Controller, which optimises the micro-grid costs, and a low-level Model Predictive Controller, which manages micro-grid uncertainties, ensuring smooth operations. The proposed EMS decouples economic objectives from robustness concerns, reducing operation costs, grid intervention, and operational constraint violations. The computational complexity is kept low by relying on a data-driven scenario approach to solve the resulting stochastic optimisation problem. The architecture is tested using data from a Japanese micro-grid in Tsukuba to prove its effectiveness during daily operations.