Over the years, different energy systems have often been planned and managed independently and not always efficient and optimised. A paradigm shift towards a holistic, multi-generation approach can achieve more significant benefits by integrating the energy infrastructure for electricity, natural gas and district heating networks and creating energy hubs in the urban districts of future smart cities. In such systems, different energy carriers interact collaboratively. The number of uncertainties in multi-energy hubs requires developing optimisation planning methodologies capable of keeping the risk below acceptable values. In this context, the paper proposes a robust linear programming optimisation algorithm to solve the energy hub planning problem under uncertainty. The optimisation algorithm allows the identification of the optimal energy carriers to meet energy demands and minimise energy costs keeping the risk of failure below the allowable level. Simulation results highlight the benefits of applying the proposed approach considering a multi-energy hub structure in an urban district of the city of Cagliari (Italy).
Multi-Energy Smart City Urban District Planning with Robust Optimisation
Marco GaliciSoftware
;Gianni CelliWriting – Review & Editing
;Emilio Ghiani
Writing – Review & Editing
;Simona RuggeriWriting – Review & Editing
;Giuditta PisanoWriting – Review & Editing
;Fabrizio PiloWriting – Review & Editing
2022-01-01
Abstract
Over the years, different energy systems have often been planned and managed independently and not always efficient and optimised. A paradigm shift towards a holistic, multi-generation approach can achieve more significant benefits by integrating the energy infrastructure for electricity, natural gas and district heating networks and creating energy hubs in the urban districts of future smart cities. In such systems, different energy carriers interact collaboratively. The number of uncertainties in multi-energy hubs requires developing optimisation planning methodologies capable of keeping the risk below acceptable values. In this context, the paper proposes a robust linear programming optimisation algorithm to solve the energy hub planning problem under uncertainty. The optimisation algorithm allows the identification of the optimal energy carriers to meet energy demands and minimise energy costs keeping the risk of failure below the allowable level. Simulation results highlight the benefits of applying the proposed approach considering a multi-energy hub structure in an urban district of the city of Cagliari (Italy).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.