Abstract
New York State (NYS) is shifting towards renewable energy, targeting 70 % renewable generation by 2030 and a net-zero carbon power grid by 2040. This transition necessitates the systematic retirement of fossil fuel generators (FFGs), which have long supported grid stability but contribute significantly to CO2 emissions. However, FFG retirement introduces chal-lenges related to grid reliability, energy curtailment, transmission congestion, and peak load management, given the intermittent nature of renewable energy sources (RES). This paper presents an optimization model designed to develop an effective FFG retirement schedule that considers these operational complexities alongside RES integration and transmission constraints. Utilizing historical data on demand and weather patterns, the model evaluates multiple scenarios to balance cost, emissions reduction, and grid stability. The findings indicate that strategic retire-ment of 22 GW generation capacity of high-emission inefficient FFGs, combined with targeted transmission upgrades and RES expansion, can support NYS's energy targets by 2030. This framework offers valuable insights for policymakers aiming to achieve decarbonization while preserving grid resilience.
Original language | English |
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Title of host publication | 2025 IEEE Texas Power and Energy Conference (TPEC) |
Place of Publication | Piscataway, US |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9798331541125 |
ISBN (Print) | 9798331541132 |
DOIs | |
Publication status | Published - 10 Feb 2025 |
Event | 2025 TEXAS POWER AND ENERGY CONFERENCE (TPEC) - Memorial Student Center at Texas A&M University, College Station, United States Duration: 10 Feb 2025 → 11 Feb 2025 https://tpec.engr.tamu.edu/ |
Conference
Conference | 2025 TEXAS POWER AND ENERGY CONFERENCE (TPEC) |
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Abbreviated title | TPEC 2025 |
Country/Territory | United States |
City | College Station |
Period | 10/02/25 → 11/02/25 |
Internet address |
Keywords
- Fossil Fuel Generator Retirement
- Renewable Energy Integration
- Grid Reliability Optimization