Abstract
Unit commitment (UC) is a major problem in power system operation which determines the operation schedule of the generating units by minimizing system operation cost. Because of the uncertainty of wind power, the UC problem needs to solve as a multi-period stochastic optimization. In this stochastic problem, scenarios tree is generated and may be too large to be solved when time horizon is longer. This paper presents an approach based on Maximum Entropy principle to generate and reduce scenarios by transforming a stochastic process to a finite-state Markov chain process and finding transition probability matrix. This approach is applied to transform a wind power process modeled by ARMA(1,1) model with Stochastic Volatility. A simple stochastic unit commitment is solved in this article. Because of power system security, reserve constraints also considered.
| Original language | English |
|---|---|
| Title of host publication | 2017 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 348-353 |
| Number of pages | 6 |
| Volume | 2017-January |
| ISBN (Electronic) | 9781538620953 |
| DOIs | |
| Publication status | Published - 2017 Dec 12 |
| Event | 6th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2017 - San Diego, United States Duration: 2017 Nov 5 → 2017 Nov 8 |
Other
| Other | 6th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2017 |
|---|---|
| Country/Territory | United States |
| City | San Diego |
| Period | 17/11/5 → 17/11/8 |
Keywords
- ARMA
- Markov chain
- Renewable energy
- Stochastic unit commitment
- Stochastic volatility
- Wind power
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
