Use of a model predictive control framework for optimal control of grid scale electrical energy storage in conjunction with a wind farm

Graduation date: 2012Over the last decade, wind penetration in the Pacific Northwest has increased rapidly. The variable nature of this massive new resource has increased stress on the hydropower resource to the point where system limits are currently being reached. In order to cultivate continued growth of the wind energy industry both in the Pacific Northwest and the rest of the world, something must be added to help mitigate the effects of the variability of wind power. This research aims to show what can be done by adding energy storage to a wind farm. A novel model predictive control structure has been created with the focus of increasing the dispatchability and reliability of wind farm power output along with allowing participation in frequency regulation. First, the effectiveness of the addition of energy storage with simple control is explored. This is followed by a study on the performance of the system when predictive control is added. Finally, a cost analysis is performed to assess the level of savings and potential profitability of the simulated system. Conclusions support the use of an energy storage resource for more reliable wind farm performance. However, storage technologies are still approaching the price point needed to ensure profitability