In this paper, we study the problem of managing an energy community hosting a fleet of electric vehicles for rent. On the day-ahead, service requests of electric vehicles are submitted to the community. Then, the optimal request-to-vehicle assignment has to be found, as well as the optimal charging schedule of vehicle batteries. A suitable model is presented and included in an existing energy community architecture. The overall community management problem is formulated as a bilevel model, featuring two nested optimization problems. The optimal request-to-vehicle assignment requires the solution of a mixed-integer linear program. To reduce the computational complexity, a heuristic solution to the assignment problem is presented. Numerical results show that the participation in the community grants a remarkable reduction of the electric vehicle charging cost. The adoption of the heuristic assignment solution provides a dramatic reduction of the computation time required to solve the bilevel model. At the same time, the level of suboptimality introduced appears to be negligible, being less than 1% in most of the considered cases.
Zanvettor, G.G., Casini, M., Giannitrapani, A., Paoletti, S., Vicino, A. (2022). Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles. ENERGIES, 15(22), 1-16 [10.3390/en15228697].
Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles
G. G. Zanvettor;M. Casini
;A. Giannitrapani;S. Paoletti;A. Vicino
2022-01-01
Abstract
In this paper, we study the problem of managing an energy community hosting a fleet of electric vehicles for rent. On the day-ahead, service requests of electric vehicles are submitted to the community. Then, the optimal request-to-vehicle assignment has to be found, as well as the optimal charging schedule of vehicle batteries. A suitable model is presented and included in an existing energy community architecture. The overall community management problem is formulated as a bilevel model, featuring two nested optimization problems. The optimal request-to-vehicle assignment requires the solution of a mixed-integer linear program. To reduce the computational complexity, a heuristic solution to the assignment problem is presented. Numerical results show that the participation in the community grants a remarkable reduction of the electric vehicle charging cost. The adoption of the heuristic assignment solution provides a dramatic reduction of the computation time required to solve the bilevel model. At the same time, the level of suboptimality introduced appears to be negligible, being less than 1% in most of the considered cases.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1220055