In large-scale photovoltaic (PV) power plants, the integration of a battery energy storage system (BESS) permits a more flexible operation, allowing the plant to support grid stability. In hybrid PV+BESS plants, the storage system can be integrated by using different power conversion system (PCS) layouts and different charge–discharge strategies. In the AC-coupling layout, the BESS is connected to the ac-side of the system through an additional inverter. In the DC-coupling layout, the BESS is connected to the dc-side, with or without a dedicated dc–dc converter, and no additional inverter is needed. Referring to a 288 MWp PV plant with a 275 MWh BESS, this paper compares the PCS efficiency between AC- and DC-coupling solutions. The power injected into the grid is obtained considering providing primary power-frequency regulation services. A charging and discharging strategy of the BESS is proposed to ensure cyclic battery energy shifting. The power flows in the different components of the system that are obtained under realistic operating conditions, and total energy losses and annual average efficiency are calculated accordingly. Finally, results show a higher efficiency of DC-coupling compared to the AC-coupling layout.

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.

This study proposes a novel Mixed Integer Linear Programming (MILP) model for optimal management of Battery Energy Storage System (BESS) plants integrated with a real-time cycle counting algorithm exploiting an innovative logarithmic formulation for battery degradation. By incorporating this logarithmic approach, the model effectively includes various stress factors like State of Energy, C-Rate, Depth of Discharge, and Temperature, along with Solid Electrolyte Interphase film formation, into a tractable linear model. Moreover, the limits of the Rainflow Counting Algorithm (RCA) are overcome. The comparison with the results obtained by applying the RCA method to the full physical model are positive: the count faithfully reflects that obtained through RCA, and degradation estimation is close to the real value, with relative error below 0.1%.

This paper presents the dynamic response of a DC - micro-grid (DC-MG) controlled in master-slave mode. The benefits of the micro-grids (MGs) are the low cost in terms of power electronics converters and the high reliability and quality, even in case of loss connection to the transmission system. A DC-MG in fact can survive in standalone mode if properly managed. The considered system is made by a photovoltaic array (PV), a wind turbine (WT), a gas engine (GE) and an energy storage system (ESS). The DC-MG behavior is analyzed in different scenarios to demonstrate the efficacy of the control for all the units, especially in case of variable weather conditions with different DC loads. Thus the voltage level of the system and the power flow are shown, out of a detailed description of the power electronic interfaces featuring the distributed generators (DGs).