2338. Assessing Renewable Energy Curtailment: Metrics, Impacts, and Mitigation Strategies
Invited abstract in session WD-44: Advanced methods for designing and operating energy systems under uncertainty, stream Energy Economics & Management.
Wednesday, 14:30-16:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Seyed Ehsan Ahmadi
|
| Marketing Operations and Systems, Northumbria University | |
| 2. | Mohammad Fattahi
|
| Marketing, Operations, and Systems, Northumbria University, Newcastle Business School |
Abstract
As renewable energy sources (RES) expand, curtailment becomes a major issue, impacting grid reliability and investment feasibility. This study quantifies curtailment’s effects on congestion, infrastructure risk, and energy transition decisions. By incorporating uncertainty in both load and RES generation, we introduce key metrics, including annual curtailed energy, peak curtailment levels, curtailment as a percentage of total RES generation, financial cost of curtailment, and revenue loss due to curtailed energy. Using a sample average approximation approach and historical load and weather data from 1980 to 2019 in New York State, we examine curtailment’s relationship with RES expansion. Our findings show that a 20% increase in RES leads to a 5.52-fold rise in curtailment, exposing grid limitations. While energy storage is often proposed as a solution, our results reveal that adding 3,000 MW of storage only reduces curtailment by 1.28%, proving its limited effectiveness under high-curtailment conditions. These findings highlight the need for alternatives beyond grid-based strategies. Power-to-X (P2X) technologies, which convert surplus RES into hydrogen, synthetic fuels, or heat, provide a more effective option for minimizing curtailment and optimizing energy use. This research presents a structured framework for assessing curtailment risks and investment opportunities, supporting a more resilient and adaptive energy transition.
Keywords
- Energy Policy and Planning
- OR in Energy
- Optimization Modeling
Status: accepted
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