Nature Inspired Optimization for Electrical Power System

Prof. Manjaree Pandit received her M.Tech. degree in Electrical Engineering from Maulana Azad College of Technology, Bhopal, India, in 1989 and her Ph.D. degree from Jiwaji University Gwalior, India, in 2001. She is currently working as a Professor and Dean of Academics at the Department of Electrical Engineering, M.I.T.S., Gwalior, India. She is a senior member of the IEEE, a reviewer for several journals, and has published more than 60 papers in respected international journals. Her research interests include the integration of hybrid renewable energy sources with power grids, nature inspired algorithms, ANN and fuzzy neural network applications to electrical power systems. Dr. Hari Mohan Dubey is an Associate Professor at Madhav Institute of Technology & Science, Gwalior, India. Dr. Dubey received his Ph.D. degree in Electrical Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India. He is associated with various SCI journals asreviewer, and has published more than 70 research papers in various international journals/conference proceedings. His main research interests are in bio-inspired algorithms and their applications to electrical engineering, particularly, power system planning and operation with the integration of renewable energy sources. Dr. Jagdish Chand Bansal is an Associate Professor at South Asian University New Delhi and Visiting Faculty at the Department of Maths and Computer Science, Liverpool Hope University, UK. Dr. Bansal received his Ph.D. in Mathematics from the IIT Roorkee. Before joining SAU New Delhi, he worked as an Assistant Professor at ABV-Indian Institute of Information Technology and Management, Gwalior, and at BITS Pilani. He is the series editor of Algorithms for Intelligent Systems (AIS), published by Springer; the Editor-in-Chief of International Journal of Swarm Intelligence (IJSI), published by Inderscience; and an Associate Editor of IEEE ACCESS, published by the IEEE. He is the general secretary of the Soft Computing Research Society (SCRS). His main research interests are in swarm intelligence and nature inspired optimization techniques. Recently, he proposed a fission–fusion social structure-based optimization algorithm, Spider Monkey Optimization (SMO), which is currently being applied to various problems in the engineering domain. He has published more than 60 research papers in various international journals/conference proceedings.  

Teaching Learning Based Optimization for Static and Dynamic Load Dispatch.- Application of Elitist Teacher Learner Based Optimization Algorithm for Congestion Management.- PSO Based Optimization of Levelized Cost of Energy for Hybrid Renewable Energy System.- PSO Based PID Controller Designing for LFC of Single Area Electrical Power Network.- Combined Economic Emission Dispatch of Hybrid Thermal-PV System Using Artificial Bee Colony Optimization.- Dynamic Scheduling of Energy Resources in Microgrid Using Grey Wolf Optimization.- Short-Term Hydrothermal Scheduling Using Bio- Inspired Computing: A Review.