Multi-objective building energy system optimization considering EV infrastructure
Musik Park,
Zhiyuan Wang,
Lanyu Li and
Xiaonan Wang
Applied Energy, 2023, vol. 332, issue C, No S0306261922017615
Abstract:
With increasing concerns over carbon dioxide emissions, the concept of Zero Energy Building (ZEB) has emerged. Electric Vehicles (EVs) are also considered environmentally friendly since they reduce greenhouse gas emissions, with a rapidly growing market. With these global trends of increasing EV amount and infrastructure, building energy systems should incorporate the ZEB concept and the increasing electricity requirements for EV charging. However, it is unclear how EV charging demand can affect building energy system design while aligning with ZEB requirements. Therefore, this paper develops a new framework to find the optimal energy system design that meets EV charging demand and ZEB requirements. The charging demand for EVs is predicted by the machine learning model, which combines the building energy demand from EnergyPlus. Ultimately, the Genetic Algorithm and PROBID method are applied to optimize the Total Annual Cost (TAC) and Self-Energy Sufficiency Ratio. EV charging demand has been found to affect energy system design, especially in small-size buildings. Using the proposed method, the building owner can determine the optimal capacity of an energy system based on economic and ZEB conditions, contributing to the future net ZEB and transportation systems.
Keywords: Renewable energy; Energy system optimization; Zero Energy Building; Electric vehicle; EnergyPlus (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261922017615
Full text for ScienceDirect subscribers only
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:eee:appene:v:332:y:2023:i:c:s0306261922017615
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2022.120504
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().