Abstract
Capacity market is a long-term clearing model to coordinate the traditional thermal generation and the renewable energy generation, which minimizes the total capacity cost of traditional generation, while satisfying the operational constraints and reliability requirement. Furthermore, to address the uncertainties in the long-term optimal decision, min-max regret is employed to find the optimal solution under the worst regret, generating several representable scenarios that can help generation companies to understand how these scenarios would impact on the future generation planning. Finally, a decomposition method is proposed to solve this reliability based min-max regret stochastic optimization model by bisection. The test results on one regional grid in China show the effectiveness of the proposed model. © 2018 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 2065-2074 |
| Journal | IEEE Transactions on Sustainable Energy |
| Volume | 10 |
| Issue number | 4 |
| Online published | 26 Oct 2018 |
| DOIs | |
| Publication status | Published - Oct 2019 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
-
SDG 10 Reduced Inequalities
Research Keywords
- Capacity market
- min-max regret
- reliability evaluation
- renewable energy
- stochastic programming
Fingerprint
Dive into the research topics of 'Reliability Based Min-Max Regret Stochastic Optimization Model for Capacity Market with Renewable Energy and Practice in China'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver