Smoothing control strategy of wind and photovoltaic output power fluctuation by considering the state of health of battery energy storage system

• Published in: IET renewable power generation Vol. 13; no. 4; pp. 578 - 586
• Main Authors: Lamsal, Dipesh, Sreeram, Victor, Mishra, Yateendra, Kumar, Deepak
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 18.03.2019
• Subjects: battery energy storage system; battery health; battery power; battery storage plants; control strategy; fluctuated power; fuzzy set theory; fuzzy‐based discrete Kalman filter approach; intermittent nature; Kalman filters; output power fluctuations; photovoltaic output power fluctuation; photovoltaic power systems; photovoltaic systems; power fluctuation rates; power generation control; PV generation systems; Research Article; secondary cells; smooth output power; solar irradiance; wind power; wind speed; control strategy; battery power; battery health; fuzzy set theory; wind speed; power generation control; photovoltaic power systems; photovoltaic systems; power fluctuation rates; solar irradiance; PV generation systems; wind power; smooth output power; fuzzy-based discrete Kalman filter approach; secondary cells; battery storage plants; photovoltaic output power fluctuation; Kalman filters; output power fluctuations; fluctuated power; battery energy storage system; intermittent nature
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2018.5111

The output power of wind and photovoltaic (PV) systems contain fluctuations due to the intermittent nature of solar irradiance and wind speed. It is required to smooth the fluctuated power before supplying it to the grid. Here, a fuzzy-based discrete Kalman filter approach is proposed for smoothing output power fluctuations of the wind and PV generation systems using a battery energy storage system. The proposed approach incorporates the state of health of the battery as a feedback to not only obtain smooth output power but also improve the battery health by adaptively regulating the battery power. The effectiveness of the proposed approach is verified by evaluating the power fluctuation rates and performance indices.