State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems

Abdul Latif, S. M.Suhail Hussain, Dulal Chandra Das, Taha Selim Ustun

    Research output: Contribution to journalReview articlepeer-review

    154 Scopus citations

    Abstract

    Load frequency management (LFM) has become more significant in modern power systems due to variation demand and generation profiles. Further, integration of renewable energy resources (RSs) into the power systems makes LFM job more challenging. To this end, the concept of secondary frequency control, or LFM, objective is introduced to single and multi-area power systems to manage the power mismatch of the particular power system. This helps regulate the system frequency for single/multi area systems and schedule tie-line power exchange for multi area systems. To control and reduce the system frequency deviation, load frequency controllers are introduced. However, to achieve optimal power management, intelligent soft computing techniques that take different controllers into account are utilized. This paper aims to provide a review of different controllers utilized in traditional as well as renewable energy-based power system for LFM such as; classical controllers, fractional order controllers, cascaded controllers, sliding mode controller (SMC), tilt-integral-derivative controllers, H-infinity controller and other recently developed controllers. Some popular and recently adopted soft-computing tools for power management such as; genetic algorithm, particle swarm optimization, firefly, cuckoo search techniques, fuzzy tuning tool, model predictive technique and other newer once have been explored. Finally, the paper concludes by highlighting some future scope in the field of LFM.

    Original languageBritish English
    Article number114858
    JournalApplied Energy
    Volume266
    DOIs
    StatePublished - 15 May 2020

    Keywords

    • Automatic generation control (AGC)
    • Intelligent controller
    • Interconnected renewable microgrid power system
    • Load frequency management (LFM)
    • Single/multi area electric power network
    • Soft computing techniques

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