Dynamic Economic Load Dispatch of CHP Microgrid Using Improved Particle Swarm Optimization
Surmadhur Pant1, Vishal Gupta2

1Surmadhur Pant, Department of Electrical and Electronics, Shivalik College of Engineering Dehradun (Uttarakhand), India.

2Dr. Vishal Gupta, ICFAI University Dehradun (Uttarakhand), India.

Manuscript received on 09 January 2020 | Revised Manuscript received on 05 February 2020 | Manuscript Published on 20 February 2020 | PP: 51-57 | Volume-9 Issue-3S January 2020 | Retrieval Number: C10100193S20/2020©BEIESP | DOI: 10.35940/ijitee.C1010.0193S20

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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: For the sustainable development and various industrial applications, Combined Heat – Power system offers advantages such as saving of energy, economic as well as environment protection benefits. Paper deal with dynamic economic load dispatch of C-H-P, Micro-Grid (Wind- Energy Conversion system, P-V array), Fuel Cell, Boiler(Waste- Heat), thermal and electrical loads. For this purpose, a nonlinear optimal CHP micro grid model has been built and simulated for the economic function of present power generating resources and to generate the twenty four(24) work schedule with forecasted condition of wind, solar, heat and electrical demand for next 24 hours. The methodology used for finding the solution of model is improved particle swarm optimization. Model has been tested with and without peak valley pricing. Results indicate that cost of the system is effectively reduced with peak valley pricing. The simulated results of the system with improved particle swarm optimization (IPSO) and PSO techniques have been shown and compared. The simulation results indicate that the improved PSO providesimprovised solution as compared to PSO.

Keywords: Microgrid Combine CHP-Heat and Power), Dynamic Economic Dispatch, PSO=particle Swarm Optimization.
Scope of the Article: Swarm Intelligence