Wake management based life enhancement of battery energy storage system for hybrid wind farms. (September 2020)

• Record Type: Journal Article
• Authors: Dhiman, Harsh S.; Deb, Dipankar
• Is Part Of: Renewable & sustainable energy reviews. Volume 130(2020)
• Publication Date: 2020-09
• Subjects: Wind forecasting -- State-of-charge (SoC) -- Battery energy storage system (BESS) -- Energy reservoir model -- Wake management -- Yaw angle; BESS Battery energy storage system -- ERM Energy reservoir model -- EKF Extended Kalman filter -- KKT Karush-Kuhn-Tucker -- KF Kalman filter -- LSSVR Least square support vector regression -- MAE Mean absolute error -- MAPE Mean absolute percentage error -- NMSE Normalized mean squared error -- OCV Open-circuit voltage -- R2 Coefficient of determination -- RMSE Root mean squared error -- SVR Support vector regression -- SoC State of charge -- UKF Unscented Kalman filter -- WFLOP Wind farm layout optimization; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2020.109912
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: One way of setting up hybrid wind farms is through augmentation of turbines with battery energy storage systems (BESS). Due to variation in wind speed in such wind farms, the cost of BESS increases and reduction in battery life takes place. This paper proposes a wake management technique to reduce the operational cost of a hybrid wind farm equipped with BESS. The battery charging and discharging powers are ascertained considering error in the wind speed prediction. This investigation considers three different conditions for a wind farm, namely, (i) without wake (ii) without wake management and (iii) with wake management. An ageing model is utilized for the lead-acid battery while accounting for temperature and depth of discharge changes to assess the battery operational cost and lifecycle count. Simulation analysis for a two-turbine layout with the upstream turbine yawed from 0 ∘ to 5 ∘, presents a 44.37% savings in operational cost and 79.74% increase in battery life evaluated for a dataset obtained from Challicum hills in Australia. Additionally, the battery operational cost is minimized at a yaw angle of 15°. Uncertainty analysis is done to study the effect of prediction technique on the lifecycle count. The proposed methodology is extended to a 5-turbine layout where along with lifecycle count and operational cost, the horizontal shear on the turbine blades is also analyzed.