Economic optimization of operations for hybrid energy systems under variable markets
Jun Chen and
Humberto E. Garcia
Applied Energy, 2016, vol. 177, issue C, 24 pages
Abstract:
Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper proposes a methodology for operations optimization to maximize their economic value based on predicted renewable generation and market information. A multi-environment computational platform for performing such operations optimization is also developed. To compensate for prediction error, a control strategy is accordingly designed to operate a standby energy storage element (ESE) to avoid energy imbalance within HES. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value. Simulation results of two specific HES configurations illustrate the proposed methodology and computational capability. Economic advantages of such operations optimizer and associated flexible operations are demonstrated by comparing the economic performance of flexible operations with that of constant operations. Sensitivity analysis with respect to market variability and prediction error are also performed.
Keywords: Hybrid energy systems; Renewable; Operations optimization; Economic analysis; Power market (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916306535
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:177:y:2016:i:c:p:11-24
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.2016.05.056
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 ().