Foundations and Trends® in Technology, Information and Operations Management > Vol 16 > Issue 3–4

Corporate Renewable Procurement Analytics

By Selvaprabu Nadarajah, Information and Decision Sciences, University of Illinois at Chicago, USA, selvan@uic.edu

 
Suggested Citation
Selvaprabu Nadarajah (2023), "Corporate Renewable Procurement Analytics", Foundations and Trends® in Technology, Information and Operations Management: Vol. 16: No. 3–4, pp 250-266. http://dx.doi.org/10.1561/0200000106-5

Publication Date: 10 Jul 2023
© 2023 S. Nadarajah
 
Subjects
Renewable energy technologies,  Integration of renewable energy sources,  Optimization,  Reinforcement learning,  Markov decision processes
 

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In this article:
1. Introduction
2. Renewable Power Procurement
3. Data and Decisions
4. Rolling Power Purchases and Reoptimization
5. Conclusions
References

Abstract

Corporate decarbonization goals have increased rapidly in the last few years. The procurement of renewable power is a core strategy used by companies to meet these goals, increasingly in a dynamic manner that addresses the risks associated with uncertain prices and supply intermittency, among others. This section discusses the interplay between data and decision analytics in this rapidly evolving area by considering the construction of a dynamic portfolio of power purchase agreements, which are popular long-term contracts signed by corporations, to meet a future renewable procurement target. It analyzes a stylized setting to provide insight into the effect on decisions of the joint evolution of uncertainties. It also discusses how forecasts, stochastic processes, and deterministic models can be used to obtain procurement policies in practical settings. These elements have a rich history in operations management but have received limited attention for renewable power procurement. Emphasis is placed on how a traditional rolling planning model based on forecasts can be adapted to this procurement setting, as well as where a recent rolling planning technique based on information relaxations can add value.

DOI:10.1561/0200000106-5
ISBN: 978-1-63828-248-8
176 pp. $99.00
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ISBN: 978-1-63828-249-5
176 pp. $300.00
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Table of contents:
1. Disruption Mitigation and Pricing Flexibility
2. Optimal Newsvendor IRM with Downside Risk
3. Competitive Forward and Spot Trading Under Yield Uncertainty
4. The Impact of Commodity Price Uncertainty on the Economic Value of Waste-to-Energy Conversion in Agricultural Processing
5. Corporate Renewable Procurement
6. Blockchain-Based Digital Payment Obligations for Trade Finance
7. Long-term Service Agreement in Power Systems
8. The Bullwhip Effect in Servicized Manufacturers

Frontiers in Supply Chain Finance and Risk Management

This monograph contains eight thought-leading contributions on various topics related to supply chain finance and risk management: “Disruption Mitigation and Pricing Flexibility” by Oben Ceryan and Florian Lücker. “Optimal Newsvendor IRM with Downside Risk” by Paolo Guiotto and Andrea Roncoroni. “Competitive Forward and Spot Trading Under Yield Uncertainty” by Lusheng Shao, Derui Wang, and Xiaole Wu. “The Impact of Commodity Price Uncertainty on the Economic Value of Waste-to-Energy Conversion in Agricultural Processing” by Bin Li, Onur Boyabatlı, and Buket Avcı. “Corporate Renewable Procurement” by Selvaprabu Nadarajah. “Blockchain-Based Digital Payment Obligations for Trade Finance” by Jing Hou, Burak Kazaz, and Fasheng Xu. “Long-term Service Agreement in Power Systems” by Panos Kouvelis, Hirofumi Matsuo, Yixuan Xiao, and Quan Yuan. “The Bullwhip Effect in Servicized Manufacturers” by Jiang Shenyang, Jiang Zhibin, Niu Yimeng, and Wu Jing.

 
TOM-106-5

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Foundations and Trends® in Technology, Information and Operations Management, Volume 16, Issue 3-4 Special Issue: Frontiers in Supply Chain Finance and Risk Management
See the other articles that are also part of this special issue.