This paper addresses the problem of optimal scheduling of an aggregated power profile (during a coordinated discharging or charging operation) by means of a heterogeneous fleet of storage devices subject to availability constraints. Devices have heterogeneous initial levels of energy, power ratings and efficiency; moreover, the fleet operates without cross-charging of the units. An explicit feedback policy is proposed to compute a feasible schedule whenever one exists and scalable design procedures to achieve maximum time to failure or minimal unserved energy in the case of unfeasible aggregated demand profiles. Finally, a time-domain characterization of the set of feasible demand profiles using aggregate constraints is proposed, suitable for optimization problems where the aggregate population behaviour is of interest.

On Optimal Coordinated Dispatch for Heterogeneous Storage Fleets With Partial Availability / David Angeli; Zihang Dong; Goran Strbac. - In: IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS. - ISSN 2325-5870. - ELETTRONICO. - 10:(2023), pp. 1137-1148. [10.1109/tcns.2022.3221472]

On Optimal Coordinated Dispatch for Heterogeneous Storage Fleets With Partial Availability

David Angeli;
2023

Abstract

This paper addresses the problem of optimal scheduling of an aggregated power profile (during a coordinated discharging or charging operation) by means of a heterogeneous fleet of storage devices subject to availability constraints. Devices have heterogeneous initial levels of energy, power ratings and efficiency; moreover, the fleet operates without cross-charging of the units. An explicit feedback policy is proposed to compute a feasible schedule whenever one exists and scalable design procedures to achieve maximum time to failure or minimal unserved energy in the case of unfeasible aggregated demand profiles. Finally, a time-domain characterization of the set of feasible demand profiles using aggregate constraints is proposed, suitable for optimization problems where the aggregate population behaviour is of interest.
2023
10
1137
1148
David Angeli; Zihang Dong; Goran Strbac
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1301540
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