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Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array

Lookup NU author(s): Professor Volker Pickert



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Energy management strategies are instrumental in the performance and economy of smart homesintegrating renewable energy and energy storage. This article focuses on stochastic energy managementof a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It ismotivated by the challenges associated with sustainable energy supplies and the local energy storageopportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energycharges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements,and accommodating the variability of solar power. First, the random-variable models are developed,including Markov Chain model of PEV mobility, as well as predictive models of home power demand andPV power supply. Second, a stochastic optimal control problem is mathematically formulated for managingthe power flow among energy sources in the smart home. Finally, based on time-varying electricityprice, we systematically examine the performance of the proposed control strategy. As a result, theelectric cost is 493.6% less for a Tesla Model S with optimal stochastic dynamic programming (SDP)control relative to the no optimal control case, and it is by 175.89% for a Nissan Leaf.

Publication metadata

Author(s): Wu X, Hu X, Moura S, Yin X, Pickert V

Publication type: Article

Publication status: Published

Journal: Journal of Power Sources

Year: 2016

Volume: 333

Pages: 203-212

Print publication date: 30/11/2016

Online publication date: 05/10/2016

Acceptance date: 27/09/2016

Date deposited: 01/12/2016

ISSN (print): 0378-7753

ISSN (electronic): 1873-2755

Publisher: Elsevier


DOI: 10.1016/j.jpowsour.2016.09.157


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Funder referenceFunder name
0903005203398Fundamental Research Funds for the Central Universities
51375402NSF of China
2013JY0088Science and Technology Department of Sichuan Province
2015TD0021Science and Technology Department of Sichuan Province
2016HH0010Science and Technology Department of Sichuan Province
z1220315Xihua University Fund
szjj2012-012Xihua University Fund