Title :
Optimal operation strategy of energy storage unit in wind power integration based on stochastic programming
Author :
Yuan, Yuan ; Li, Qifeng ; Wang, W.
Author_Institution :
Sch. of Electr. Eng., Hohai Univ., Nanjing, China
fDate :
3/1/2011 12:00:00 AM
Abstract :
In order to obtain maximum profits in trading of wind power for large-scale wind farms, energy storage unit (ESU) can be introduced to decrease the bid imbalance and to shift energy from the cheapest to the most expensive, so that the penalty can be reduced and energy can be traded with higher price for wind farm. As the forecast error of wind power output is a stochastic variable, stochastic programming is adopted to determine the optimal operation strategies of ESU. Mathematical model for seeking the maximum benefits of wind farm and ESU is also developed based on stochastic programming. Hybrid genetic algorithm and neural network methods are employed to solve the optimisation problem. Economic analysis is also included to illustrate the feasibility of the hybrid system. Results indicate that ESU can improve the profits of wind farm by decreasing the bid imbalance and shifting wind energy from low-price intervals to higher ones.
Keywords :
energy storage; genetic algorithms; neural nets; stochastic programming; wind power; economic analysis; energy storage unit; hybrid genetic algorithm; large-scale wind farms; neural network methods; optimal operation strategy; stochastic programming; stochastic variable; wind power integration;
Journal_Title :
Renewable Power Generation, IET
DOI :
10.1049/iet-rpg.2009.0107