Supply Chain Coordination for Renewable Energy Development
Because large-scale renewable energy sources, particularly wind energy, are often located in remote, sparsely-populated areas, they cannot be integrated into the existing grid without significant investment in dedicated and costly transmission capacity. Meeting society’s goals of rapidly reducing carbon emissions by increasing renewable energy generation therefore requires coordinating investments from both a power generation company and transmission company. The resulting decentralized supply chain faces incentive conflicts. In this paper, we formulate and analyze a continuous-time model of such a decentralized renewable supply chain, characterize the resulting equilibrium, and establish its uniqueness. We prove that both companies under-invest in their respective capacities compared to a centralized supply chain. In a number of settings, the transmission company does not invest at all due to the insufficient resulting marginal profit. To address the challenge of coordinating decentralized and costly investments in renewable generation and transmission capacities, we introduce a coordination scheme in which each company pays a specific portion of the other company’s total investment costs. We establish that there exists a unique investment cost-sharing scheme that perfectly coordinates this renewable energy supply chain and provides incentives for the transmission company to invest for all (practical) ranges of model parameters. We show that this coordination scheme is Pareto optimal, as it raises optimal profits for both companies across all practical ranges of model parameters. The resulting increases in total supply chain profits average 250% in our numerical studies.
About Alexander Angelus:
Alexander Angelus is an Assistant Professor of Operations Management at Mays Business School at Texas A&M University. He received his Ph.D. in Operations, Information and Technology from the Graduate School of Business at Stanford University, and B.S. in Mathematics from MIT. Previously, he was a faculty member at University of Texas at Dallas, Singapore Management University, and the University of California, Berkeley.
His research focus is on improving decision making for complex systems under uncertainty, including inventory planning for multi-stage supply chains, investment decisions for renewable energy generation, and capacity decisions for manufacturing firms such as vaccine producers and semiconductor manufacturers. His research has been published in Management Science; Operations Research; Manufacturing, Service & Operations Management; and Production and Operations Management.
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Supported by the Luxembourg National Research Fund (FNR) 17931929