ADMM-Based Multiperiod Optimal Power Flow Considering Plug-In Electric Vehicles Charging

Fan, Hua, Duan, Chao, Zhang, Chuan-Ke, Jiang, Lin ORCID: 0000-0001-6531-2791, Mao, Chengxiong and Wang, Dan (2018) ADMM-Based Multiperiod Optimal Power Flow Considering Plug-In Electric Vehicles Charging IEEE TRANSACTIONS ON POWER SYSTEMS, 33 (4). pp. 3886-3897. ISSN 0885-8950, 1558-0679

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Abstract

When plug-in electric vehicles (PEVs) participate in grid operation, the intertemporal feature of PEVs charging transforms the traditional optimal power flow (OPF) problem into multiperiod OPF (MOPF) problem. In the case that the population of PEVs is huge, the large number of variables and constraints renders the centralized solution technique unsuitable to solve the MOPF problem. Therefore, a distributed algorithm based on alternating direction method of multipliers is developed to decompose the MOPF into two update steps that are solved in an alternating and iterative style. To improve the solution efficiency, the second update step is transformed into a Euclidean projection problem by approximating the original objective with a surrogate function. Then, a projection algorithm is utilized to solve the approximate problem. Numerical results show that this reformulated model obtains suboptimal solutions with small relative error, but gains considerable speed-up. Furthermore, its scalability and effectiveness are tested in the 119-bus and 906-bus distribution networks.

Item Type:	Article
Uncontrolled Keywords:	Plug-in electric vehicles, multiperiod optimal power flow, alternating direction method of multipliers (ADMM), projection algorithm
Depositing User:	Symplectic Admin
Date Deposited:	24 Jan 2018 07:59
Last Modified:	16 Jun 2026 13:52
DOI:	10.1109/TPWRS.2017.2784564
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3016713
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