Abstract
Due to the flexible charging and discharging capability, energy storage system (ESS) is thought of as a promising complement to wind farms (WF) in participating into electricity markets. This paper proposes a reserve-based real-time operation strategy of ESS to make arbitrage and to alleviate the wind power deviation from day-ahead contracts. Taking into account the operation strategy as well as two-price balancing market rules, a day-ahead bidding strategy of WF-ESS system is put forward and formulated. A modified gradient descent algorithm is described to solve the formulations. In the case studies, the computational efficiency of the algorithm is validated firstly. Moreover, a number of scenarios with/without considering the temporal dependence of wind power forecast error are designed and employed to compare the proposed strategy with other common ones in terms of profit.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2015 IEEE Eindhoven PowerTech |
| Publisher | IEEE |
| Publication date | 2015 |
| Pages | 1-6 |
| ISBN (Print) | 9781479976935 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | 2015 IEEE Eindhoven PowerTech - Eindhoven, Netherlands Duration: 29 Jun 2015 → 2 Jul 2015 https://powertech2015-eindhoven.tue.nl/ https://ieeexplore.ieee.org/xpl/conhome/7210291/proceeding |
Conference
| Conference | 2015 IEEE Eindhoven PowerTech |
|---|---|
| Country/Territory | Netherlands |
| City | Eindhoven |
| Period | 29/06/2015 → 02/07/2015 |
| Internet address |
Keywords
- energy storage
- gradient methods
- power markets
- wind power plants
- Power, Energy and Industry Applications
- Artificial intelligence
- Bidding strategy
- day-ahead bidding strategy
- day-ahead contracts
- electricity markets
- energy storage system
- ESS
- gradient descent algorithm
- operation strategy
- real-time operation
- storage capability
- two-price balancing market rules
- wind farm
- wind farms
- wind power deviation
- wind power forecast error