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Economic Load Dispatch with PEV Using Evolutionary Techniques

Tejaswita Khobaragade, K. T. Chaturvedi


In this paper, the Economic Load Dispatch (ELD) problem is solved by using four different evolutionary techniques Social Spider Algorithm (SSA), Particle Swarm Optimization (PSO), and Teaching Learning Based Optimization (TLBO) with PEV on 20-unit thermal generation station. The most recent Self-Learning Teaching Learning Based Optimization (SL-TLBO) is introduced, including a weighting factor w for adjusting the learning range. A comprehensive study demonstrates that the unique algorithm has the potential to give significant economic and environmental benefits to power system operators while also providing competitive charging strategies for policymakers and PEV aggregators. In this paper, a 15-unit thermal system is addressed, and PEVs are studied along with several evolutionary strategies that meet the restrictions. Various techniques, such as the use of Plug-in Electric Vehicles (PEVs) and Renewable Energy Resources (RERs), have already been recommended to limit the exponential increase in these GHG emissions. The performance of each technique has been evaluated and different results obtained. The performance analysis has been studied with load demand among all the 20-unit thermal generation stations at minimum generation cost and attain the system constraints.


Economic Load Dispatch (ELD), SSA, PSO, TLBO and PEV

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Abdullah Kavousi-Fard, Alireza Abbasi, Mohammad-Amin Rostami, Abbas Khosravi, Optimal distribution feeder reconfiguration for increasing the penetration of plug-in electric vehicles and minimizing network costs, Energy, Volume 93, Part 2, 2015, Pages 1693-1703, ISSN 0360-5442,

Zhile Yang, Kang Li, Qun Niu, Yusheng Xue, A comprehensive study of economic unit commitment of power systems integrating various renewable generations and plug-in electric vehicles, Energy Conversion and Management, Volume 132, 2017, Pages 460-481, ISSN 0196-8904.

Alberto Luque-Chang, Erik Cuevas, Fernando Fausto, Daniel Zaldívar, Marco Pérez, "Social Spider Optimization Algorithm: Modifications, Applications, and Perspectives", Mathematical Problems in Engineering, vol. 2018, Article ID 6843923, 29 pages, 2018.

R.V. Rao, V.J. Savsani, D.P. Vakharia, Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems, Computer-Aided Design, Volume 43, Issue 3, 2011, Pages 303-315, ISSN 0010-4485,

Baş, E., Ülker, E. Improved social spider algorithm for large scale optimization. Artif Intell Rev 54, 3539–3574 (2021).

W.T. Elsayed, Y.G. Hegazy, F.M. Bendary, M.S. El-bages, Modified social spider algorithm for solving the economic dispatch problem, Engineering Science and Technology, an International Journal, Volume 19, Issue 4, 2016, Pages 1672-1681, ISSN 2215-0986,

An efficient binary social spider algorithm for feature selection problem, Expert Systems with Applications, Volume 146, 2020, 113185, ISSN 0957-4174,

F. Baccino, S. Grillo, S. Massucco and F. Silvestro, "Optimal charging strategy algorithm for PEVs: A Monte Carlo validation," 2014 IEEE International Electric Vehicle Conference (IEVC), 2014, pp. 1-7, doi: 10.1109/IEVC.2014.7056188.

S. Behera, S. Behera and A. K. Barisal, "Dynamic Economic Load Dispatch with Plug-in Electric Vehicles using Social Spider Algorithm," 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), 2019, pp. 489-494, doi: 10.1109/ICCMC.2019.8819640.

Turker, Harun & Seddik, Bacha. (2014). Smart Charging of Plug-in Electric Vehicles (PEVs) in Residential Areas: Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G) concepts. International Journal of Renewable Energy Technology. 4. 859-871.

MathWorks, MATLAB, and Simulink for Electric Vehicle Development (2024)

Behera, S., Behera, S., Kumar Barisal, A., & Pradhan, S. (2020). Economic Load Dispatch with Renewable Energy Resources and Plug-in Electric Vehicles. 2020 International Conference on Renewable Energy Integration into Smart Grids: A Multidisciplinary Approach to Technology Modelling and Simulation (ICREISG). doi:10.1109/icreisg49226.2020.9174543

S. Behera, S. Behera and A. K. Barisal, "Dynamic Economic Load Dispatch with Plug-in Electric Vehicles using Social Spider Algorithm," 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2019, pp. 489-494.

In the year 2010 S. Mirjalili proposed Hybrid Algorithm (PSOGSA). The basic need for the following hybridization is to merge the ability of social thinking (gbest) in PSO with the local search means of GSA.

Mohammad Hanif Nur Mohammad “Artificial Bee Colony and Genetic Algorithm for Optimization of Non-smooth Economic Load Dispatch with Transmission Loss” Proceedings of the International Conference on Big Data, IoT, and Machine Learning pp 271-287 04 December 2021.

Pandian Vasant Fahad Parvez Mahdi, Seri Iskandar Jose Antonio Marmolejo-Saucedo, Junzo Watada “Quantum-Behaved Bat Algorithm for Solving the Economic Load Dispatch Problem Considering a Valve-Point Effect” Research Anthology on Advancements in Quantum Technology © 2021,10.4018/978-1-7998-8593-1.ch004

Kunaldeep Kalita; Ashwani Kumar Rai; Kunal Pandey; Rachana Garg “Comparative Analysis of different Variants of Particle Swarm Optimization for Economic Load Dispatch Problem” 2020 International Conference on Computational Performance Evaluation (ComPE) DOI: 10.1109/ComPE49325.2020 2-4 July 2020

Rasool Ghanizadeh; Seyed Majid Hojber Kalali; Hatef Farshi “Teaching–learning-based optimization for economic load dispatch 2019 5th Conference on Knowledge-Based Engineering and Innovation (KBEI),10.1109/KBEI46916.2019

Yu Zhai; Nankun Mu; Xiaofeng Liao; Junqing Le; Tingwen Huang “Unit Commitment Problem Using An Efficient PSO Based Algorithm” 2019 Eleventh International Conference on Advanced Computational Intelligence (ICACI) DOI: 10.1109/ICACI45541.2019 7-9 June 2019

Power N. Karthik A. K. Parvathy R. Arul K. Padmanathan “A New Heuristic Algorithm for Economic Load Dispatch Incorporating Wind” Artificial Intelligence and Evolutionary Computations in Engineering Systems pp 47-65| 19 August 2021 Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1361)

Fukui Li, Jingyuan He, Mingliang Zhou, and Bin Fang “VLSs: A Local Search Algorithm for Distributed Constraint” International Journal of Pattern Recognition and Artificial Intelligence 24 Jan 2022 s

Wu Denga, Xiaoxiao Zhanga, Yongquan Zhouc, Yi Liud, Xiangbing Zhoub, Huiling Chene, Huimin Zhaoa “An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems” Information Sciences Volume 585, March 2022.

BorcePostolovAtanasIliev “New metaheuristic methodology for solving security constrained hydrothermal unit commitment based on adaptive genetic algorithm” International Journal of Electrical Power & Energy Systems Volume 134, January 2022, 107163

D. Santra (RCC Institute of Information Technology, India), A. Mukherjee (RCC Institute of Information Technology, India), K. Sarker (Budge Budge Institute of Technology, India) and S. Mondal (Jadavpur University, India) “ Hybrid Genetic Algorithm-Gravitational Search Algorithm to optimize Multi-Scale Load Dispatch” International Journal of Applied Metaheuristic Computing (IJAMC) 12(3) © 2021 10.4018/IJAMC.2021070102

Siddhartha Tiwari, Prof. Dr. Dwarka Prasad “A Genetic Algorithm Approach for the Solution of Economic Load Dispatch Problem” International Journal of Scientific Research & Engineering Trends Volume 7, Issue 1, Jan-Feb-2021, ISSN

Vimal Singh Bisht, Navneet Joshi, Govind Singh Jethi Abhijit Singh Bhakuni, “A Review on Genetic Algorithm and Its Application in Power System Engineering” Metaheuristic and Evolutionary Computation: Algorithms and Applications pp 107-130| 09 October 2020 Part of the Studies in Computational Intelligence book series (SCI, volume 916)

Borče Postolov, Atanas Iliev “SECURITY CONSTRAINED HYDROTHERMAL UNIT COMMITMENT FOR DIFFERENT HYDROLOGICAL SCENARIOS USING GENETIC ALGORITHM” Journal of Electrical Engineering and Information Technologies, Vol. 6, No. 1, pp. 15–28 (2021).

K. Rajesh N. Visali N. Sreenivasulu “Optimal Load Scheduling of Thermal Power Plants by Genetic Algorithm” Emerging Trends in Electrical, Communications, and Information Technologies pp 397-409, 25 September 2019

Behera, Soudamini & Behera, Sasmita & Barisal, Ajit & Pradhan, Sonam. (2020). Economic Load Dispatch with Renewable Energy Resources and Plug-in Electric Vehicles. 22-26. 10.1109/ICREISG49226.2020.9174543.

H. Chen, Z. Hu, H. Luo, J. Qin, R. Rajagopal, and H. Zhang, "Design and Planning of a Multiple-Charger Multiple-Port Charging System for PEV Charging Station," in IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 173-183, Jan. 2019, doi: 10.1109/TSG.2017.2735636


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