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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.
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
URL: http://dx.doi.org/10.1016/j.jpowsour.2016.09.157
DOI: 10.1016/j.jpowsour.2016.09.157
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