Microgrids represent a flexible way to integrate renewable energy sources with programmable generators and storage systems. In this regard, a synergic integration of those sources is crucial to minimize the operating cost of the microgrid by efficient storage management and generation scheduling. The forecasts of renewable generation can be used to attain optimal management of the controllable units by predictive optimization algorithms. This paper introduces the implementation of a two-layer hierarchical energy management system for islanded photovoltaic microgrids. The first layer evaluates the optimal unit commitment, according to the photovoltaic forecasts, while the second layer deals with the power-sharing in real time, following as close as possible the daily schedule provided by the upper layer while balancing the forecast errors. The energy management system is experimentally tested at the Multi-Good MicroGrid Laboratory under three different photovoltaic forecast models: (i) day-ahead model, (ii) intraday corrections and (iii) nowcasting technique. The experimental study demonstrates the capability of the proposed management system to operate an islanded microgrid in safe conditions, even with inaccurate day-ahead photovoltaic forecasts.

This paper presents the Multi-Good MicroGrid (MGMG) experimental facility that has been built at the Department of Energy of Politecnico di Milano to test and develop new innovative predictive optimization Energy Management System (EMS) for MGMG operation. After an introduction on the current literature status about EMS and microgrid (MG) test facilities, this work describes in detail this new experimental setup. The MGMG integrates different goods, generators, renewable energy sources, various types of loads and energy storage systems. A case study is discussed in the second part of the paper: a grid connected MG that manages a photovoltaic field, a Li-ion storage and an aggregated residential load is analyzed. A comparison between a heuristic control strategy and the two-layer mixed integer linear programming predictive EMS we developed is performed. Both simulation and experimental results confirm that the optimized EMS ensures superior economical performances.

This paper aims to present an analysis performed on real operation data of an islanded microgrid, located in Somalia. The study is carried out from the first months of deployment, in November 2015, up to October 2018, emphasizing relevant events occurred and the effects on the overall system. The investigation focuses on load demand increase, induced by the electrification of the area, and consequent installation of new generators. Moreover, real data about lead-acid battery ageing are presented, with the implication on diesel generators operation.