Exploring Innovative Design Principles using Innovization in Multi- Objective Optimal Reactive Power Dispatch Problem
Devnath Shah1, Saibal Chatterjee2

1Devnath Shah, Department of Electrical Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli, Arunachal Pradesh India.
2Saibal Chatterjee, Department of Electrical and Electronics Engineering, NIT, Mizoram Aizawl, Mizoram, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2711-2719 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9751109119/2019©BEIESP | DOI: 10.35940/ijeat.A9751.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Recently, researchers in the field of Evolutionary Multi-Objective Optimization give a systematic approach for exploring innovative design principles in a conflicting multi-objective optimization problem by analyzing pareto optimal solution using either manual or automated approach. They call it “Innovization” and defined as: “innovation through optimization”. This paper applies manual innovization to multi-objective Optimal Reactive Power Dispatch Problem using Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) as multi-objective optimization algorithm and manually searches for all possible innovative design principles by analyzing multiple pareto optimal solutions. Standard IEEE 30 bus test system is considered for the current work. Simulation results reveal number of innovative design principles. Innovative design principles includes function approximation of relationship between conflicting objectives, characteristics of decision variable with respect to different objectives and actual range of decision variables. Simulation results clearly show much faster convergence when decision variables were obtained using innovative design principles for specified desired objectives as compared to normal case. Results also show some decision variables can be eliminated by setting it to a fixed value, which leads to simplification of optimization problem as the values of these variables remains constant with respect to the values of objective function.
Keywords: Power System, Reactive Power Dispatch, Evolutionary Algorithm, Innovization, Multi-Objective Optimization.