Slide 1.pngSlide 2.pngSlide 3.pngSlide 4.pngSlide 5.pngSlide 6.png

Pr. Kartik Pandya

Charotar University of Science & Technology (CHARUSAT)-Changa, India


Talk Title
 Renewable Energy Optimization Using Levy Differential Evolutionary Particle Swarm Optimization (Levy-DEEPSO)

Talk Abstract

The ever increasing use of Renewable Energy Sources (RES) in electrical power systems have created many challenges regarding their optimum economic operation and control beause RES are highly uncertain and intermittent. As a result RES have created highly non-linear, discontinuous and multi-model “complex” optimization problems in electrical power systems. “Optimization” is a mathematical tool which could be used to achieve sub-optimal solutions of highly complex power systems in the presence of  RES. So, in this context, there is a need to develop the robust optimization algorithm to find near global optimum solutions that guarantee efficient and economical operation of the grid.  An IEEE PES Optimization Competition-2017 USA, 3rd rank winner Levy Differential Evolutionary Particle Swarm Optimization (LEVY DEEPSO) algorithm has been discussed to solve optimal power flow problem consisting of active and reactive power dispatch in the presence of  Wind, Solar and Small-hydro. The objective is to minimize the total fuel cost of traditional generators plus the expected cost of the uncertainty cost function for renewable generators subject to operational constraints for N-1 contingency. In the basic DEEPSO, the velocity of each particle is adjusted using self-adaptive mutated inertia weights, sampling and recombination of current generation and individual past best particle and probabilistically controlled communication between the particles. To further enhance the global search ability of DEEPSO, the velocity of each particle has been also updated using Levy flight, which is a random walk whose step length is drawn from the Levy distribution. It has been successfully tested on IEEE 57-bus test system and its performance has been compared with other meta-heuristic methods. 

Short Biography

Dr.  Kartik S. Pandya is working as a full Professor at the Dept. of Electrical Engineering at CSPIT, Charotar University of Science & Technology-Changa, INDIA. He perused his Bachelors and Masters degree from L.D. College of Engineering and Ph.D from M.S. University of  Baroda, INDIA. He has more than 18 years of teaching experience. His team had successfully executed unique consultancy project of ABB entitled: “Prototype Development of Switch-Sync Simulator Demo Kit”. His proposed algorithms entitled “Levy-DEEPSO’ and “CHAOS-DEEPSO” secured 3rd and 4th ranks respectively in the IEEE PES competition on “Evaluating the Performance of Modern Heuristic Optimizers on Smart Grid Operation Problems” at IEEE PES general meeting-2017 at Chicago, USA. Recently, his proposed algorithm entitled, “Entropy Enhanced Covariance Matrix Adaptation Evolution Strategy” has secured a rank in top two algorithms in IEEE PES 2018 competition entitled, “Operational planning of sustainable power systems”. It will be presented at 2018 IEEE PES general meeting at Portland, Oregon, USA from 5-9 August, 2018.

Talk Keywords
Levy-DEEPSO, Optimization, Renewable Energy Sources.
Target Audience
Under graduate, graduate and reseach students, Professors and working professionals
Speaker-intro video

The International Conference on Innovative Applied Energy (IAPE’18)