Cost recovery and investment barriers for renewables under market manipulation of thermal collusion. (1st March 2021)

• Record Type: Journal Article
• Authors: Fang, Xichen; Guo, Hongye; Zhang, Da; Chen, Qixin
• Is Part Of: Applied energy. Volume 285(2021)
• Publication Date: 2021-03-01
• Subjects: Electricity market -- Price manipulation -- Cross-product arbitrage -- Renewable cost recovery -- Renewable investment -- MPEC; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2021.116487
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A novel price manipulation of colluded thermals with long-term contracts is studied. A bi-level model is formulated and recast as a mixed integer linear program. We study the impact of manipulation on renewable cost recovery and investment. A case study is conducted using data from California independent system operator. Abstract: Last decade has witnessed a booming development in renewables and significant changes in the generation mix around the world. Given their relatively low variable costs, renewables are expected to be cleared first in the electricity market and earn profit margins under a marginal pricing mechanism to recover their fixed costs. However, some strategic price manipulation behaviors may distort the spot price and cause market failure. In this article, we show that thermals could exploit cross-product arbitrage possibilities through long-term contracts under high renewable penetration, and thereby lower spot prices and squeeze renewable profit margins, discouraging future renewable investments. We build a bi-level model to study strategic behaviors of thermals discussed above and their impacts on the market equilibrium. The model can be recast as a mathematical problem with equilibrium constraints (MPEC) and further formulated as a mixed integer linear programming (MILP) after proper linearization. We then use internal rates of return (IRR) and minimal acceptable rates of return (MARR) to evaluate impacts of thermal arbitrage on renewable investments. A case study is performed to validate the model using the CAISO data. Finally, we provide policy recommendations to regulate this specific type of strategic behaviors.