Myopic real-time decentralized charging management of plug-in hybrid electric vehicles
•A distributed cooperative control-based algorithm is presented for charging management of plug-in hybrid electric vehicles (PHEVs).•The proposed algorithm is decentralized, myopic, and techno-economical.•The proposed algorithm safeguards the electrical constraints of the power network against viola...
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Veröffentlicht in: | Electric power systems research 2017-02, Vol.143, p.522-532 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A distributed cooperative control-based algorithm is presented for charging management of plug-in hybrid electric vehicles (PHEVs).•The proposed algorithm is decentralized, myopic, and techno-economical.•The proposed algorithm safeguards the electrical constraints of the power network against violation.•It also reduces the individual PHEV charging costs only based on the exiting situation without any load or electricity price forecast.
This paper proposes a decentralized control algorithm for charging management of Plug-in Hybrid Electric Vehicles (PHEVs) in distribution networks. The objectives of the proposed control algorithm are to mitigate PHEV integration challenges (e.g., over-currents and under-voltages in distribution networks) and to reduce the charging costs of PHEVs. The proposed algorithm adjusts the charging rates of PHEV chargers utilizing distributed cooperative control to prevent the network constraints (i.e., voltage and current limits) from being violated. It also determines the operating modes of the chargers (i.e., charging, discharging, or idle) using a decision making algorithm to increase the State Of Charges (SOCs) and decrease the charging costs only based on the current conditions of the distribution network. The proposed algorithm is evaluated on a modified IEEE 37-Node Test Feeder and the simulation studies are carried out using OpenDSS and MATLAB. The advantages and disadvantages of the proposed algorithm are discussed and compared with the exiting methods according to the simulation results. |
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ISSN: | 0378-7796 1873-2046 |
DOI: | 10.1016/j.epsr.2016.11.002 |