Optimal Control of Plug-In Electric Vehicles Charging for Composition of Frequency Regulation Services

Roberto Germanà, Francesco Liberati, Emanuele De Santis, Alessandro Giuseppi, Francesco Delli Priscoli and Alessandro Di Giorgio
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Roberto Germanà: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy
Francesco Liberati: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy
Emanuele De Santis: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy
Alessandro Giuseppi: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy
Francesco Delli Priscoli: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy
Alessandro Di Giorgio: Department of Computer, Control and Management Engineering (DIAG), University of Rome “La Sapienza”, 00185 Rome, Italy

Energies, 2021, vol. 14, issue 23, 1-17

Abstract: This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution.

Keywords: ancillary services; frequency regulation; plug-in electric vehicles (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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