Risk-Averse Model Predictive Operation Control of Islanded Microgrids

Abstract

In this paper we present a risk-averse model predictive control (MPC) scheme\nfor the operation of islanded microgrids with very high share of renewable\nenergy sources. The proposed scheme mitigates the effect of errors in the\ndetermination of the probability distribution of renewable infeed and load.\nThis allows to use less complex and less accurate forecasting methods and to\nformulate low-dimensional scenario-based optimisation problems which are\nsuitable for control applications. Additionally, the designer may trade\nperformance for safety by interpolating between the conventional stochastic and\nworst-case MPC formulations. The presented risk-averse MPC problem is\nformulated as a mixed-integer quadratically-constrained quadratic problem and\nits favourable characteristics are demonstrated in a case study. This includes\na sensitivity analysis that illustrates the robustness to load and renewable\npower prediction errors.\n