A data-driven analytical approach to enable optimal emerging technologies integration in the co-optimized electricity and ancillary service markets

Yang Chen, Mengqi Hu and Zhi Zhou

Energy, 2017, vol. 122, issue C, 613-626

Abstract: The three emerging technologies (renewable energy, energy storage and demand response) play important roles in the co-optimized electricity and ancillary service (EAS) markets where electricity and ancillary service are simultaneously dispatched. While promising, we notice that most literature focuses on either technology integration or operation in the EAS markets. In this research, we develop a three-stage data-driven multi-criteria analytical framework to enable the optimal integration of emerging technologies and operation decisions in an EAS market context under various conditions. We propose multiple performance metrics to evaluate the EAS markets and use a Latin hypercube sampling approach to generate training data for these metrics based on a mixed integer quadratic programming model. Various data-driven models are developed for the performance metrics using the training data and two multi-criteria decision models based on the data-driven models are developed to select optimal technologies based on various criteria. To demonstrate the effectiveness of the proposed framework, we study a revised IEEE 118-bus system. It is demonstrated that our proposed approach can: 1) characterize the relations between each performance metric and technology parameters, 2) determine the significant impact technologies for each performance metric, and 3) recommend optimal emerging technologies integration for market/system operators.

Keywords: Data-driven modeling; Multi-criteria decision; Electricity and ancillary service market; Energy storage system; Demand response; Co-optimization (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544217301093
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:energy:v:122:y:2017:i:c:p:613-626

DOI: 10.1016/j.energy.2017.01.102

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().