The integration of all sectors of energy production, distribution and consumption in multi-source energy networks has lately gained attention as an attractive strategy to deal with the challenges raised by decarbonization roadmaps. For such a network to become a smart energy system, however, it needs to be managed and controlled in a smart way. While existing techniques mainly focus either on short-term unit commitment or on yearly scheduling separately, this work presents an original combined optimization algorithm which merges the two methods, in order to enhance system real-time control with long-term evaluations (e.g. incentives and yearly constraints). The control architecture comprises three coordinated optimization levels, each periodically updated through the receding time horizon strategy. A long-term supervisory module performs whole-year optimal scheduling accounting for long-term factors and determines the constraints for a short-term supervisory module which, in turn, optimizes the control action for the energy production system in real-time. In parallel, energy distribution modules minimize energy supply to the different portions of the distribution network downstream. Simulation results on a hospital case study demonstrate a 9.7% reduction in total operating cost over the whole year, as well as an increase in revenues deriving from incentives for high efficiency cogeneration.
Smart management of integrated energy systems through co-optimization with long and short horizons / Saletti, Costanza; Morini, Mirko; Gambarotta, Agostino. - In: ENERGY. - ISSN 0360-5442. - 250:(2022), p. 123748.123748. [10.1016/j.energy.2022.123748]
Smart management of integrated energy systems through co-optimization with long and short horizons
Saletti Costanza
;Morini Mirko;Gambarotta Agostino
2022-01-01
Abstract
The integration of all sectors of energy production, distribution and consumption in multi-source energy networks has lately gained attention as an attractive strategy to deal with the challenges raised by decarbonization roadmaps. For such a network to become a smart energy system, however, it needs to be managed and controlled in a smart way. While existing techniques mainly focus either on short-term unit commitment or on yearly scheduling separately, this work presents an original combined optimization algorithm which merges the two methods, in order to enhance system real-time control with long-term evaluations (e.g. incentives and yearly constraints). The control architecture comprises three coordinated optimization levels, each periodically updated through the receding time horizon strategy. A long-term supervisory module performs whole-year optimal scheduling accounting for long-term factors and determines the constraints for a short-term supervisory module which, in turn, optimizes the control action for the energy production system in real-time. In parallel, energy distribution modules minimize energy supply to the different portions of the distribution network downstream. Simulation results on a hospital case study demonstrate a 9.7% reduction in total operating cost over the whole year, as well as an increase in revenues deriving from incentives for high efficiency cogeneration.File | Dimensione | Formato | |
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