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Optimal Load Dispatch in Competitive Electricity Market by Using Different Models of Hopfield Lagrange Network

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  • Thanh Long Duong

    (Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam)

  • Phuong Duy Nguyen

    (Faculty of Electronics-Telecommunications, Saigon University, Ho Chi Minh City 700000, Vietnam)

  • Van-Duc Phan

    (Center of Excellence for Automation and Precision Mechanical Engineering, Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam)

  • Dieu Ngoc Vo

    (Department of Power Systems, Ho Chi Minh City University of Technology, VNU-HCM, Ho Chi Minh City 700000, Vietnam)

  • Thang Trung Nguyen

    (Power System Optimization Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

Abstract

In this paper, a Hopfield Lagrange network (HLN) method is applied to solve the optimal load dispatch (OLD) problem under the concern of the competitive electric market. The duty of the HLN is to determine optimal active power output of thermal generating units in the aim of maximizing the benefit of electricity generation from all available units. In addition, the performance of the HLN is also tested by using five different functions consisting of the logistic, hyperbolic tangent, Gompertz, error, and Gudermanian functions for updating outputs of continuous neurons. The five functions are tested on two systems with three units and 10 units considering two revenue models in which the first model considers payment for power delivered and the second model concerns payment for reserve allocated. In order to evaluate the real effectiveness and robustness of the HLN, comparisons with other methods such as particle swarm optimization (PSO), the cuckoo search algorithm (CSA) and differential evolution (DE) are also implemented on the same systems. High benefits and fast execution time from the HLN lead to a conclusion that the HLN should be applied for solving the OLD problem in a competitive electric market. Among the five applied functions, error function is considered to be the most effective one because it can support the HLN to find the highest benefit and reach the fastest convergence with the smallest number of iterations. Thus, it is suggested that error function should be used for updating outputs for continuous neurons of the HLN.

Suggested Citation

  • Thanh Long Duong & Phuong Duy Nguyen & Van-Duc Phan & Dieu Ngoc Vo & Thang Trung Nguyen, 2019. "Optimal Load Dispatch in Competitive Electricity Market by Using Different Models of Hopfield Lagrange Network," Energies, MDPI, vol. 12(15), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2932-:d:253142
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    References listed on IDEAS

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    Cited by:

    1. Le Chi Kien & Thanh Long Duong & Van-Duc Phan & Thang Trung Nguyen, 2020. "Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization," Sustainability, MDPI, vol. 12(3), pages 1-35, February.
    2. Dotzauer, Martin & Oehmichen, Katja & Thrän, Daniela & Weber, Christoph, 2022. "Empirical greenhouse gas assessment for flexible bioenergy in interaction with the German power sector," Renewable Energy, Elsevier, vol. 181(C), pages 1100-1109.

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