### Optimal Thermal Generating Unit Commitment via Evolutionary Algorithms: A Review

#### Abstract

This paper presents a literature survey of economic load dispatch problem. The economic load dispatch (ELD) is one of the most important optimization problems of electrical power system. The aim of the ELD problem is to determine the power productions of total generating units from a system in order to have minimum fuel cost, and to meet the all constrains. Solving ELD involves conveying a precise model of optimization and then selecting an appropriate optimization technique. The simplest model for the ELD problem is one in which the fuel cost of the generating units is quadratic in nature, and with two constraints only: the equality and inequality constraints, respectively; the generators operate between the minimum and maximum limits of power. However, the more practical features of the operational units, the precise model is improved by considering the valve-point effects and by presenting the constraints like ramp rate limits, prohibited zones, the transmission losses; it introduces a non-linear, non-smooth and non-continuous accurate model of optimization. To solve the ELD problem, several methods, classic or based on artificial intelligence, have been used over time. Several soft computing methods like particle swarm optimization (PSO), artificial bee colony (ABC), ant colony optimization (ACO), simulated annealing (SA), genetic algorithm (GA), etc. are now being applied to find even better solution to the ELD problem. An interesting trend in this area is application of hybrid approaches like GA-PSO, ABC-PSO, CSA-SA, etc. and the results are found to be highly competitive.

**Cite this Article**

Nitin Tyagi, Tushar Tyagi. Optimal Thermal Generating Unit Commitment via Evolutionary Algorithms: A Review. Journal of Artificial Intelligence Research & Advances. 2016; 3(2): 26–32p.

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Dinu Calin Secui. A New Modified Artificial Bee Colony Algorithm for the Economic Dispatch Problem. Energ Convers Manage. 2015; 89: 43–62p.

Nasimul Nomana, Hitoshi Iba. Differential Evolution for Economic Load Dispatch Problems. Electr Pow Syst Res. 2008; 78: 1322–1331p.

Leandro dos Santos Coelho, Rodrigo Clemente Thom Souza, Viviana Cocco Mariani. Improved Differential Evolution Approach Based on Cultural Algorithm and Diversity Measure Applied to Solve Economic Load Dispatch Problems. Math Comput Simul. 2009; 79: 3136–3147p.

Samir Sayah, Abdellatif Hamouda. A Hybrid Differential Evolution Algorithm Based on Particle Swarm Optimization for Non-Convex Economic Dispatch Problems. Appl Soft Comput. 2013; 13: 1608–1619p.

Nima Amjady, Hossein Sharifzadeh. Solution of Non-Convex Economic Dispatch Problem Considering Valve Loading Effect by a New Modified Differential Evolution Algorithm. Int J Elect Power Energy Systems. 2010; 32: 893–903p.

Qun Niu, Hongyun Zhang, Xiaohai Wanga, et al. A Hybrid Harmony Search with Arithmetic Crossover Operation for Economic Dispatch. Int J Electrical Power and Energy Systems. 2014; 62: 237–257p.

Ling Wang, Ling-po Li. An Effective Differential Harmony Search Algorithm for the Solving Non-Convex Economic Load Dispatch Problems. Int J Elect Power Energy Systems. 2013; 44: 832–843p.

Ranjit Roy, Ghoshal SP. A Novel Crazy Swarm Optimized Economic Load Dispatch for Various Types of Cost Functions. Int J Elect Power Energy Systems. 2008; 30: 242–253p.

Phan Tu Vu, Dinh Luong Le, Ngoc Dieu Vo, et al. A Novel Weight-Improved Particle Swarm Optimization Algorithm for Optimal Power Flow and Economic Load Dispatch Problems. IEEE. 2010.

-1-4244-6547-7.

Yong Zhang, Dun-wei Gong, Na Geng, et al. Hybrid Bare-Bones PSO for Dynamic Economic Dispatch with Valve-Point Effects. Appl Soft Comput. 2014; 18: 248–260p.

Qun Niu, Xiaohai Wang, Zhuo Zhoua. An Efficient Cultural Particle Swarm Optimization for Economic Load Dispatch with Valve-point Effect. Procedia Eng. 2011; 23: 828–834p.

Safari A, Shayeghi H. Iteration Particle Swarm Optimization Procedure for Economic Load Dispatch with Generator Constraints. Expert Syst Appl. 2011; 38: 6043–6048p.

Basu M. Modified Particle Swarm Optimization for Non-Convex Economic Dispatch Problems. Int J Elect Power Energy Systems. 2015; 69: 304–312p.

Vahid Hosseinnezhad, Mansour Rafiee, Mohammad Ahmadian, et al. Species-based Quantum Particle Swarm Optimization for Economic Load Dispatch. Int J Elect Power Energy Systems. 2014; 63: 311–322p.

Serhat Duman, Nuran Yorukeren, Altas Ismail H. A Novel Modified Hybrid PSOGSA Based on Fuzzy Logic for Non-Convex Economic Dispatch Problem with Valve-Point Effect. Int J Elect Power Energy Systems. 2015; 64: 121–135p.

Vahid Hosseinnezhad, Ebrahim Babaei. Economic Load Dispatch Using θ-PSO. Int J Elect Power Energy Systems. 2013; 49: 160–169p.

Sumit Banerjee, Deblina Maity, Chandan Kumar Chanda. Teaching Learning Based Optimization for Economic Load Dispatch Problem Considering Valve Point Loading Effect. Int J Elect Power Energy Syst. 2015; 73: 456–464p.

Orero SO, Irving MR. Large Scale Unit Commitment Using a Hybrid Genetic Algorithm. Int J Elect Power Energy Syst. 1997; 19(1): 45–55p.

Pothiya S, Ngamroo I, Kongprawechnon W. Ant Colony Optimization for Economic Load Dispatch with Non-Smooth Cost Function. Int J Elect Power Energy Systems. 2010; 32: 478–487p.

Elattar Ehab E. A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Dynamic Economic Dispatch Problem. Int J Elect Power Energy Systems. 2015; 69: 18–26p.

Aniruddha Bhattacharya, Chattopadhyay PK. Solving Complex Economic Load Dispatch Problems Using Biogeography-Based Optimization. Expert Syst Appl. 2010; 37: 3605–3615p.

Provas Kumar Roy, Sudipta Bhui, Chandan Paul Department. Solution of Economic Load Dispatch Using Hybrid

Chemical Reaction Optimization Approach. 2014; Appl Soft Comput. 24: 109–125p.

DOI: http://dx.doi.org/10.37591%2Fjoaira.v3i2.770

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