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Multiobjective TOU Pricing Optimization Based on NSGA2

Author

Listed:
  • Huilan Jiang
  • Bingqi Liu
  • Yawei Wang
  • Shuangqi Zheng

Abstract

Fast and elitist nondominated sorting generic algorithm (NSGA2) is an improved multiobjective genetic algorithm with good convergence and robustness. The Pareto optimal solution set using NSGA2 has the character of uniform distribution. This paper builds a time-of-use (TOU) pricing mathematical model considering actual constraint conditions and puts forward a new method which realizes multiobjective TOU pricing optimization using NSGA2. A variety of objective TOU pricing schemes can be provided for decision makers compared with traditional method. Furthermore, the multiple attribute decision making theory is applied in processing the Pareto optimal solution set to calculate the optimal compromise price scheme. The simulation results have shown that the TOU pricing scheme determined by the method proposed above can achieve a better effect of clipping the peak load to fill the valley load. Consequently, the study in this paper is innovative and is a successful exploration of coordinating the relation of various objective functions concerned in TOU pricing optimization problem.

Suggested Citation

  • Huilan Jiang & Bingqi Liu & Yawei Wang & Shuangqi Zheng, 2014. "Multiobjective TOU Pricing Optimization Based on NSGA2," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-8, July.
    • Handle: RePEc:hin:jnljam:104518
    DOI: 10.1155/2014/104518
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    Cited by:

    1. Xiaoqing Zeng & Zilin He & Yali Wang & Yongfei Wu & Ao Liu, 2024. "An Effective Method of Equivalent Load-Based Time of Use Electricity Pricing to Promote Renewable Energy Consumption," Mathematics, MDPI, vol. 12(9), pages 1-27, May.
    2. Wu, Xiaodan & Li, Juan & Chu, Chao-Hsien, 2019. "Modeling multi-stage healthcare systems with service interactions under blocking for bed allocation," European Journal of Operational Research, Elsevier, vol. 278(3), pages 927-941.
    3. Esmeralda Mukoni & Karen S. Garner, 2022. "Multi-Objective Non-Dominated Sorting Genetic Algorithm Optimization for Optimal Hybrid (Wind and Grid)-Hydrogen Energy System Modelling," Energies, MDPI, vol. 15(19), pages 1-18, September.
    4. Wanlei Xue & Xin Zhao & Yan Li & Ying Mu & Haisheng Tan & Yixin Jia & Xuejie Wang & Huiru Zhao & Yihang Zhao, 2023. "Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand," Energies, MDPI, vol. 16(4), pages 1-17, February.

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