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Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

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  • Ashok Krishnan
  • L. P. M. I. Sampath
  • Y. S. Foo Eddy
  • H. B. Gooi

Abstract

This paper proposes an efficient energy management system (EMS) for industrial microgrids (MGs). Many industries deploy large pumps for their processes. Oftentimes, such pumps are operated during hours of peak electricity prices. A lot of industries use a mix of captive generation and imported utility electricity to meet their energy requirements. The MG considered in this paper includes diesel generators, battery energy storage systems, renewable energy sources, flexible loads, and interruptible loads. Pump loads found in shipyard dry docks are modelled as exemplar flexible industrial loads. The proposed EMS has a two-stage architecture. An optimal MG scheduling problem including pump scheduling and curtailment of interruptible loads (ILs) is formulated and solved in the first stage. An optimal power flow problem is solved in the second stage to verify the feasibility of the MG schedule with the network constraints. An iterative procedure is used to coordinate the two EMS stages. Multiple case studies are used to demonstrate the utility of the proposed EMS. The case studies highlight the efficacy of load management strategies such as pump scheduling and curtailment of ILs in reducing the total electricity cost of the MG.

Suggested Citation

  • Ashok Krishnan & L. P. M. I. Sampath & Y. S. Foo Eddy & H. B. Gooi, 2018. "Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints," Complexity, Hindawi, vol. 2018, pages 1-20, July.
    • Handle: RePEc:hin:complx:9842025
    DOI: 10.1155/2018/9842025
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    2. Li, Zhengmao & Xu, Yan, 2018. "Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes," Applied Energy, Elsevier, vol. 210(C), pages 974-986.
    3. Parisio, Alessandra & Rikos, Evangelos & Tzamalis, George & Glielmo, Luigi, 2014. "Use of model predictive control for experimental microgrid optimization," Applied Energy, Elsevier, vol. 115(C), pages 37-46.
    4. Zhang, Xinan & Bao, Jie & Wang, Ruigang & Zheng, Chaoxu & Skyllas-Kazacos, Maria, 2017. "Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage," Renewable Energy, Elsevier, vol. 100(C), pages 18-34.
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    1. Hafiz Abdul Muqeet & Hafiz Mudassir Munir & Haseeb Javed & Muhammad Shahzad & Mohsin Jamil & Josep M. Guerrero, 2021. "An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges," Energies, MDPI, vol. 14(20), pages 1-34, October.

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