Shanmukha Sundar

Work place: Dayananda Sagar College of Engineering, Bangalore, India

E-mail: hod_eee@dayanandasagar.edu

Website:

Research Interests: Engineering, Computational Engineering, Computational Science and Engineering

Biography

Dr. Shanmukha Sundar has completed Ph. D in optimal Power flow control with from Visvesvaraya Technological University, Karnataka, India in 2010. His areas of interests are Electrical power system, Power Electronics and FACTS controller. He has published several papers in reputed journals and conferences. Currently he is working as Professor and Head of the Electrical Engineering Department, Dayananda Sagar college of Engineering, Bangalore, India.

Author Articles
Optimized Controller Design Using an Adaptive Bacterial Foraging Algorithm for Voltage Control and Reactive Power Management in Off-Grid Hybrid Power System

By Harsha Anantwar B.R. Lakshmikantha Shanmukha Sundar

DOI: https://doi.org/10.5815/ijigsp.2019.01.04, Pub. Date: 8 Jan. 2019

This paper investigates the application of adaptive Bacteria Forging Algorithm (BFA) to design optimal controllers for voltage stability of off-grid hybrid power system (OGHPS).Voltage fluctuations will have great impact on the quality of power supply. Voltage rise/drop depends on the surplus / shortage of reactive power in the system, hence it has become extremely important to manage the reactive power balance for voltage control in the off-grid hybrid power system. The off -grid hybrid power system considered in this work as a test system, consist of an Induction generator (IG) for wind power systems, Photo-Voltaic (PV) system with inverter, Synchronous generator (SG) for diesel  power generation and composite load. The Over-rated PV inverter has ample amount of reactive power capacity while sourcing PV real power. Two control structures are incorporated, to regulate system voltage. The first  control structure is for the reactive power compensation  of the system by inverter, by controlling the magnitude of inverter output voltage and the second control structure is for  controlling the SG excitation by an automatic voltage regulator (AVR) and hence the load voltage. Both control structures have proportional-integral (PI) controller. Both control loops are coordinated by tuning their parameters optimally and simultaneously using an adaptive Bacterial forging optimization algorithm. Small signal model of all components of OGHPS is simulated in SIMULINK, tested for reactive load disturbance and /or wind power input disturbance of different magnitudes to investigate voltage stability. 

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