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Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using A search

Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using A search
Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using A search

The increasing integration of Electric vehicles (EVs) and renewable generators (RGs) is an inevitable trend of power grid concerning the global control of greenhouse gas release. This will challenge constrained distribution networks due to the intrinsic intermittency of renewable power and additional charging load demand of EVs. However, appropriate dispatch of EVs via vehicle-to-grid (V2G) operation in coordination with RGs can solve the stability issues, provide operational support for the power grid, reduce the reliance on fossil fuels and benefit both the environment and EV users. This paper develops a novel algorithm to solve the optimal decentralized coordinated dispatch problem of RGs and EVs based on multi-agent and the A search procedure. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem using the Analytic Hierarchy Process taking into account both power grid and EV users’ concerns and priorities. The inherent uncertainty of EV driving activities and RG output power are considered in this work, of which the stochastic modelling is established using copulas. The proposed algorithm is tested on a radial distribution network, a modified UK generic distribution system. The simulation results demonstrate the feasibility and stability of the proposed A-based optimal coordinated dispatch strategy.

A search, Decentralized dispatch, Renewable energy, Vehicle-to-grid
0142-0615
474-487
Wang, Lu
a67c8d01-75e7-45f9-84a6-b879eafbf4f8
Sharkh, Suleiman
c8445516-dafe-41c2-b7e8-c21e295e56b9
Chipperfield, Andy
524269cd-5f30-4356-92d4-891c14c09340
Wang, Lu
a67c8d01-75e7-45f9-84a6-b879eafbf4f8
Sharkh, Suleiman
c8445516-dafe-41c2-b7e8-c21e295e56b9
Chipperfield, Andy
524269cd-5f30-4356-92d4-891c14c09340

Wang, Lu, Sharkh, Suleiman and Chipperfield, Andy (2018) Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using A search. International Journal of Electrical Power and Energy Systems, 98, 474-487. (doi:10.1016/j.ijepes.2017.11.036).

Record type: Article

Abstract

The increasing integration of Electric vehicles (EVs) and renewable generators (RGs) is an inevitable trend of power grid concerning the global control of greenhouse gas release. This will challenge constrained distribution networks due to the intrinsic intermittency of renewable power and additional charging load demand of EVs. However, appropriate dispatch of EVs via vehicle-to-grid (V2G) operation in coordination with RGs can solve the stability issues, provide operational support for the power grid, reduce the reliance on fossil fuels and benefit both the environment and EV users. This paper develops a novel algorithm to solve the optimal decentralized coordinated dispatch problem of RGs and EVs based on multi-agent and the A search procedure. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem using the Analytic Hierarchy Process taking into account both power grid and EV users’ concerns and priorities. The inherent uncertainty of EV driving activities and RG output power are considered in this work, of which the stochastic modelling is established using copulas. The proposed algorithm is tested on a radial distribution network, a modified UK generic distribution system. The simulation results demonstrate the feasibility and stability of the proposed A-based optimal coordinated dispatch strategy.

Full text not available from this repository.

More information

Accepted/In Press date: 28 November 2017
e-pub ahead of print date: 4 January 2018
Published date: 1 June 2018
Keywords: A search, Decentralized dispatch, Renewable energy, Vehicle-to-grid

Identifiers

Local EPrints ID: 419188
URI: http://eprints.soton.ac.uk/id/eprint/419188
ISSN: 0142-0615
PURE UUID: 7c8cf3bb-117b-4aad-bd9c-37db6ef0f9ca
ORCID for Andy Chipperfield: ORCID iD orcid.org/0000-0002-3026-9890

Catalogue record

Date deposited: 06 Apr 2018 16:30
Last modified: 07 Oct 2020 01:48

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