Strategic Production and Trading in Renewable Energy Certificate Markets: Existence, Uniqueness, and Efficiency of Market Equilibria

• Published in: IEEE transactions on network science and engineering Vol. 11; no. 6; pp. 5538 - 5548
• Main Authors: Huang, Qisheng, Xu, Yunjian, Courcoubetis, Costas A.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Behavioral sciences; Companies; Costs; Electricity supply industry; Finance; Game theory; Lower bounds; Nash equilibrium; Portfolios; Power markets; Power supplies; Production; Public utilities; Renewable energy; renewable energy certificate trading; renewable generation; Renewable portfolio standard; Renewable resources
• ISSN: 2327-4697; 2334-329X
• DOI: 10.1109/TNSE.2023.3270632

As an incentive policy to promote renewable generation, the renewable standard portfolio (RPS) scheme has been widely adopted to enforce utility companies to procure a certain fraction of their energy supply from renewable sources. We construct a non-cooperative game theoretic model to study the strategic behavior of utility companies in a renewable energy certificate (REC) market, where utility companies purchase REC from renewable producers to meet their RPS obligation. In the constructed game, each utility company makes the renewable production decisions so as to minimize its total cost (the sum of renewable production and RPS penalty costs). We establish mild conditions that guarantee the existence of a Nash equilibrium. We further prove that if a Nash equilibrium exists, it must be unique and minimize the system cost. When symmetric utility companies' energy loads are independent and identical Gaussian distributed, as the number of utility companies increases to infinity, we show that the expected cost (of a utility company) converges to a lower bound, the product of the levelized cost of electricity (LCOE) of renewable generation and its expected RPS obligation. Numerical studies on real-world (load, RPS requirement, penalty, and LCOE) data show that the REC trading can reduce 5%-10% of the system cost.