Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage

Nadia Ahmed, Marco Levorato, Roberto Valentini and Guann-Pyng Li
Additional contact information
Nadia Ahmed: Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USA
Marco Levorato: Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USA
Roberto Valentini: Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, 67100 L’Aquila, Italy
Guann-Pyng Li: Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USA

Energies, 2020, vol. 13, issue 9, 1-18

Abstract: This paper presents a battery-aware stochastic control framework for residential energy management systems (EMS) equipped with energy harvesting, that is, photovoltaic panels, and storage capabilities. The model and control rationale takes into account the dynamics of load, the weather, the weather forecast, the utility, and consumer preferences into a unified Markov decision process. The embedded optimization problem is formulated to determine the proportion of energy drawn from the battery and the grid to minimize a cost function capturing a user-defined tradeoff between battery degradation and financial expense by user preferences. Numerical results are based on real-world weather data for Golden, Colorado, and load traces. The results illustrate the ability of the system to limit battery degradation assessed using the Rain flow counting method for lithium ion batteries.

Keywords: residential demand response; energy management system; stochastic control; battery aging; markov decision processes (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/9/2201/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/9/2201/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:9:p:2201-:d:353294

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().