This paper is published in Volume-6, Issue-4, 2020
Area
Electrical Engineering
Author
Jaspreet Singh
Co-authors
Puneet Jain
Org/Univ
Adesh Institute of Engineering and Technology, Faridkot, Punjab, India
Pub. Date
29 July, 2020
Paper ID
V6I4-1286
Publisher
Keywords
Particle Swarm Optimization, Flower Pollination Algorithm, Combined Economic Emission Load Dispatch, Modified Random Search Particle Swarm Optimization, MRSPSO, FPA, Economic Load Dispatch

Citationsacebook

IEEE
Jaspreet Singh, Puneet Jain. Combined emission economic load dispatch problem using hybrid combination of flower pollination algorithm and moderate random search particle swarm optimization, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Jaspreet Singh, Puneet Jain (2020). Combined emission economic load dispatch problem using hybrid combination of flower pollination algorithm and moderate random search particle swarm optimization. International Journal of Advance Research, Ideas and Innovations in Technology, 6(4) www.IJARIIT.com.

MLA
Jaspreet Singh, Puneet Jain. "Combined emission economic load dispatch problem using hybrid combination of flower pollination algorithm and moderate random search particle swarm optimization." International Journal of Advance Research, Ideas and Innovations in Technology 6.4 (2020). www.IJARIIT.com.

Abstract

The total cost of electricity generation is minimized while fulfilling the total load demand and considering all constraints in the Combined Economic Emission Dispatch (CEELD) problem. Electricity generation from fossil fuel negatively impacts the environment. Therefore, various optimization techniques have been deployed for the CEELD problem. In the literature, the Modified Random Search Particle Swarm Optimization (MRSPSO) and Flower pollination algorithm (FPA) are used as a solution for CEELD known as Combined Economic Emission Load dispatch problem. However, MRSPSO is easy to settle into local optima in high-dimensional space and delivers a low convergence rate in the iterative process, whereas in the FPA, the diverse population make it prone to being limited to the local optima. Thus, in order to overcome these limitations, in this paper, we have hybrid the FPA and MRSPSO algorithm that improves the convergence rate to meet the optimal solution. Initially, we have implemented MRSPSO and FPA algorithm; after that, combined it for CEELD. The experimental results were performed in MATLAB. The experimental results show that the hybrid approach gives better results as compared to the MRSPSO and FPA. Thus, the proposed technique is efficient and can be deployed for real-time CEELD problem.
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