Abstract
This paper presents a comparison of optimization methods applied to islanded micro-grids including renewable energy sources, diesel generators and battery energy storage systems. In particular, a comparative analysis between an optimization model based on linear programming and a model based on mixed integer programming has been carried out. The general formulation of these models has been presented and applied to a real case study micro-grid installed in Somalia. The case study is an islanded micro-grid supplying the city of Garowe by means of a hybrid power plant, consisting of diesel generators, photovoltaic systems and batteries. In both models the optimization is based on load demand and renewable energy production forecast. The optimized control of the battery state of charge, of the spinning reserve and diesel generators allows harvesting as much renewable power as possible or to minimize the use of fossil fuels in energy production.
Highlights
Islanded micro-grids are commonly settled in remote rural areas, which have a small population size and do not have large industrial plants
The micro-grid spinning reserve, PSR_TOT, is calculated as maximum the between a fixed term SRload and a variable one, PPV, that corresponds to the photovoltaic power produced; SRload is estimated as the maximum load variation observed in the historical data available, corresponding to 250 kW
Mixed Integer Programming (MIP) will be used in order to overcome the limitations of the Linear Programming (LP), since the model requires the use of discrete variables (e.g., diesel generators (DGs) start/stop)
Summary
Islanded micro-grids are commonly settled in remote rural areas, which have a small population size and do not have large industrial plants. Some research works employed nonlinearity in optimization models to attempt applying Mixed Integer Non Linear Programming (MINLP) for energy mix They approach the MINLP making use of the Benders decomposition [13]. The second one aims to minimize the operating costs, and it is based on Mixed Integer Programming (MIP) Both models have been applied, as a case study, to an islanded micro-grid composed of DGs, photovoltaic (PV) systems and a Battery Energy Storage System (BESS) operating in Somalia since. Forecasting are intrinsically affected by errors, using measurements allowed validating the models in a real case study Results show that both the optimization methods led to some improvements with respect to the present and non-optimized control logics. The paper compares and discusses the outcomes of the LP model and of the MIP model
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