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A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program

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  • Safamehr, Hossein
  • Rahimi-Kian, Ashkan

Abstract

Providing a cost-efficient and reliable energy is one of the main issues in human societies of the 21st century. In response to this demand, new features of micro grid technology have provided huge potentials, specifically by the capability of having an interactive coordination between energy suppliers and consumers. Accordingly, this paper offers an improved model for achieving an optimal Demand Response programing. To solve the proposed multi-objective optimization problem, Artificial Bee Colony algorithm and quasi-static technique are utilized. The considered objectives in this paper are minimizing the overall cost of energy consumption and also improving the technical parameters of micro grid over a time horizon. This optimization is subject to several constraints such as satisfying the energy balance and the operating constraints of each energy supply sources. Manageable load or load as source is another enabling feature existing in smart energy networks, which is considered in this paper and its effect on cost reduction and reliability improvement is studied. Trying to examine the performance of the proposed Demand Response Programing in real conditions, the uncertainties are also analyzed by stochastic methods. The results show significant improvements which are obtained by applying just intelligent programming and management.

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  • Safamehr, Hossein & Rahimi-Kian, Ashkan, 2015. "A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program," Energy, Elsevier, vol. 91(C), pages 283-293.
    • Handle: RePEc:eee:energy:v:91:y:2015:i:c:p:283-293
    DOI: 10.1016/j.energy.2015.08.051
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    9. Kaygusuz, Asim, 2019. "Closed loop elastic demand control by dynamic energy pricing in smart grids," Energy, Elsevier, vol. 176(C), pages 596-603.
    10. Wu, Xiaomin & Cao, Weihua & Wang, Dianhong & Ding, Min & Yu, Liangjun & Nakanishi, Yosuke, 2021. "Demand response model based on improved Pareto optimum considering seasonal electricity prices for Dongfushan Island," Renewable Energy, Elsevier, vol. 164(C), pages 926-936.
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    13. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    14. Tri-Hai Nguyen & Luong Vuong Nguyen & Jason J. Jung & Israel Edem Agbehadji & Samuel Ofori Frimpong & Richard C. Millham, 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
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    17. Seyedeh Narjes Fallah & Ravinesh Chand Deo & Mohammad Shojafar & Mauro Conti & Shahaboddin Shamshirband, 2018. "Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions," Energies, MDPI, vol. 11(3), pages 1-31, March.
    18. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    19. Phani Raghav, L. & Seshu Kumar, R. & Koteswara Raju, D. & Singh, Arvind R., 2022. "Analytic Hierarchy Process (AHP) – Swarm intelligence based flexible demand response management of grid-connected microgrid," Applied Energy, Elsevier, vol. 306(PB).
    20. Luis Alejandro Arias & Edwin Rivas & Francisco Santamaria & Victor Hernandez, 2018. "A Review and Analysis of Trends Related to Demand Response," Energies, MDPI, vol. 11(7), pages 1-24, June.
    21. Wang, Luhao & Li, Qiqiang & Ding, Ran & Sun, Mingshun & Wang, Guirong, 2017. "Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach," Energy, Elsevier, vol. 130(C), pages 1-14.
    22. Qian Liu & Rui Wang & Yan Zhang & Guohua Wu & Jianmai Shi, 2018. "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, MDPI, vol. 11(1), pages 1-16, January.

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