Frequency Control of a Wind-diesel-generator Hybrid System with Squirrel Search Algorithm Tuned Robust Cascade Fractional Order Controller Having Disturbance Observer Integrated

Abstract

This paper proposes an optimal cascaded fractional order controller (CC-FOC) having disturbance observer (DOB) to minimize the frequency deviation of an autonomous wind-diesel-generator (WDG) system in the wake of load variation and random wind power output. The model of WDG consists of a variable-speed wind turbine (VSWT) and a diesel engine generator to match the ever-rising load demand. To regulate the frequency of the WDG system, fractional-order proportional-integral-derivative (FOPID) and tilt-integral-derivative (TID) controllers are simultaneously used as master and slave controllers, respectively, for developing the CC-FOC. An improved squirrel search algorithm (SSA) with quasi-oppositional-based learning (QOSSA) is applied to explore the optimum gains of the proposed non-integer controller. The performance of the developed controller is compared with the outputs of FOPID, TID, and PID controllers. The result demonstrates the mastery and effectiveness of the proposed controller against random load and wind power fluctuations. Finally, Kharitonov’s stability theorem is applied to ensure the robustness margin of the studied WDG plant for a wide range of system parameters variation.

Keywords:

• load frequency control
• nonlinear control
• robust control
• optimization algorithms
• wind-diesel hybrid power system

Additional information

Notes on contributors

Dipayan Guha

Dipayan Guha received the Ph.D. degree in Electrical Engineering from the National Institute of Technology Durgapur, India, in 2017. He is presently associated with the Electrical Engineering Department of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. He has seven years of teaching experience. He has published around 60 research papers in International Journals and conference records. He was awarded Gold Medal in 2013 for ranking in M.Tech degree and acknowledged with the best journal paper award from Taylor and Francis in 2020. He has supervised eight M.Tech students, and four are perusing their thesis work. He has reviewed many research works submitted to National/International Journals. He has conducted several short term courses/faculty development programmes. He also has records of Govt. funded Consultancy Project. He has also contributed to International Conferences like INDICON 2021, UPCON 2020, etc. He has been listed in the “World Ranking of top 2% Scientists” released by Stanford University for the year 2021. His research interest includes load frequency control, distributed generations, model order reduction, intelligent control, fractional-order systems/controllers, optimization techniques, estimation, etc.

Provas Kumar Roy

Provas Kumar Roy obtained PhD degree in Electrical Engineering from National Institute of Technology Durgapur in 2011. He received his Master degree in Electrical Machine in 2001 from Jadavpur University, Kolkata. He finished his Engineering studies in Electrical Engineering from Regional Engineering College (Presently Known as National Institute of Technology) Durgapur. Presently, he is working as a Professor in Electrical Engineering Department at Kalyani Government Engineering College, West Bengal, India. He was the recipient of the Outstanding Reviewer Award for International Journal of Electrical Power and Energy Systems (Elsevier) in 2018, Engineering Application of Artificial Intelligence (Elsevier) in 2017, Renewable Energy Focus (Elsevier) in 2018, Ain Shams Engineering Journal (Elsevier) in 2017. He has published more than 180 research papers in National/International Journals and conferences. He has more than 100 Journals published in reputed SCI and Scopus indexed Journals. Moreover, he has more than 12 book chapters and one international standard book. Eight research scholars have obtained their Ph.D. degree under his guidance and 8 students are pursuing their Ph.D. degree. The total citation count of his papers is 3750. His name has been included in the “World Ranking of top 2% Scientists” list by Stanford University scientists for two consecutive years, i.e. for the years 2019 and 2020. His research interest includes economic load dispatch, optimal power flow, FACTS, automatic generation control, radial distribution network, power system stabilizer, image processing, machine learning, evolutionary computing techniques, etc.

Subrata Banerjee

Subrata Banerjee has received his PhD degree from IIT Kharagpur, India in 2005. He is working as a Professor with the Department of Electrical Engineering, NIT, Durgapur, India. He has successfully completed a few research and consultancy projects. He has authored about 200 research papers in national/international journals and conference records; 07 book chapters. He has guided eleven (11) Ph.D. and twenty-three (23) M. Tech students and many are pursuing their degree under his guidance. He has filed three Indian patents out of which one has been granted. Prof. Banerjee is the recipient of several academic awards, including 10 nos. Best Paper Awards and TATA RAO Prize etc. He is a Fellow of the IE (India), the IETE (India), and the IET (UK). He is serving as Associate Editor in IET Power Electronics (UK). His research interest includes modeling & control of switch-mode converters and inverters, multilevel inverters, different modulation techniques, electromagnetic levitation, control system design, load frequency control, etc.