Abstract
Small-scale hybrid energy systems are often composed by different power production technologies and adopted in mini-grids. In this work, a Mixed Integer Linear Programming optimization algorithm has been developed to compute the optimal scheduling of a micro-grid constituted by Internal Combustion Generators (ICGs) and a Storage System that can be either a conventional battery storage system or a Pumping Hydro energy Storage (PHES) based on Pump-as-Turbines. The algorithm computes the optimal energy generation scheduling of the micro-grid, minimizing a multi-objective fitness function constituted by the total costs of the energy system and the total CO2 and NOx emissions. In particular, the emissions are modelled with varying trends depending on the ICG load and not with constant values, which represents a simplification that is often adopted but that can induce misleading results. Furthermore, the algorithm takes into account all the physical constraints related to the generators and the storage system, such as maximum and minimum power generation, ramp-up and ramp-down limits and minimum up and down-time. The two energy storage technologies are compared and results show that a management strategy based on this algorithm can reduce significantly the total emissions of the system.
Highlights
In a scenario where the effects of climate change are no longer negligible, human activities are responsible of global warming with consequences that will become soon irreversible
A Mixed Integer Linear Programming optimization algorithm has been developed to compute the optimal scheduling of a micro-grid constituted by Internal Combustion Generators (ICGs) and a Storage System that can be either a conventional battery storage system or a Pumping Hydro energy Storage (PHES) based on Pump-as-Turbines
A mixed integer linear programming (MILP) algorithm has been developed to compute the optimal unit commitment that minimizes the total costs and greenhouse gases emissions of a hybrid energy system composed by four Internal Combustion Generators (ICGs) and a storage system that can be constituted either by conventional batteries or a Pumping Hydro Energy Storage System (PHES)
Summary
In a scenario where the effects of climate change are no longer negligible, human activities are responsible of global warming with consequences that will become soon irreversible. A field of intervention to reduce greenhouse gases emissions is related to energy systems and hybrid renewable energy systems efficiency, which has to be necessarily improved To this purpose, it is fundamental to investigate and develop optimization methods during the operating phase of complex energy systems and energy hubs [1]. A MILP algorithm has been developed to compute the optimal unit commitment that minimizes the total costs and greenhouse gases emissions of a hybrid energy system composed by four Internal Combustion Generators (ICGs) and a storage system that can be constituted either by conventional batteries or a Pumping Hydro Energy Storage System (PHES). The novelty of this investigation work regards the use of greenhouse gases emissions trends of the ICG, which are usually considered as constant in literature when ICGs are operating at partial load. It constitutes a promising technology that has still to be fully investigated and that can turn to be a feasible alternative to conventional batteries in many cases
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