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Distributed Optimisation Algorithm for Demand Side Management in a Grid-Connected Smart Microgrid

Author

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  • Omowunmi Mary Longe

    (Department of Electrical & Electronics Engineering Science, University of Johannesburg, 2092 Johannesburg, South Africa)

  • Khmaies Ouahada

    (Department of Electrical & Electronics Engineering Science, University of Johannesburg, 2092 Johannesburg, South Africa)

  • Suvendi Rimer

    (Department of Electrical & Electronics Engineering Science, University of Johannesburg, 2092 Johannesburg, South Africa)

  • Hendrik C. Ferreira

    (Department of Electrical & Electronics Engineering Science, University of Johannesburg, 2092 Johannesburg, South Africa)

  • A. J. Han Vinck

    (Institute of Digital Signal Processing, University of Duisburg-Essen, 47057 Duisburg, Germany)

Abstract

The contributions of Distributed Energy Generation (DEG) and Distributed Energy Storage (DES) for Demand Side Management (DSM) purposes in a smart macrogrid or microgrid cannot be over-emphasised. However, standalone DEG and DES can lead to under-utilisation of energy generation by consumers and financial investments; in grid-connection mode, though, DEG and DES can offer arbitrage opportunities for consumers and utility provider(s). A grid-connected smart microgrid comprising heterogeneous (active and passive) smart consumers, electric vehicles and a large-scale centralised energy storage is considered in this paper. Efficient energy management by each smart entity is carried out by the proposed Microgrid Energy Management Distributed Optimisation Algorithm (MEM-DOA) installed distributively within the network according to consumer type. Each smart consumer optimises its energy consumption and trading for comfort (demand satisfaction) and profit. The proposed model was observed to yield better consumer satisfaction, higher financial savings, and reduced Peak-to-Average-Ratio (PAR) demand on the utility grid. Other associated benefits of the model include reduced investment on peaker plants, grid reliability and environmental benefits. The MEM-DOA also offered participating smart consumers energy and tariff incentives so that passive smart consumers do not benefit more than active smart consumers, as was the case with some previous energy management algorithms.

Suggested Citation

  • Omowunmi Mary Longe & Khmaies Ouahada & Suvendi Rimer & Hendrik C. Ferreira & A. J. Han Vinck, 2017. "Distributed Optimisation Algorithm for Demand Side Management in a Grid-Connected Smart Microgrid," Sustainability, MDPI, vol. 9(7), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1088-:d:102333
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    References listed on IDEAS

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    Citations

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    Cited by:

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    4. Jicheng Liu & Dandan He, 2018. "Profit Allocation of Hybrid Power System Planning in Energy Internet: A Cooperative Game Study," Sustainability, MDPI, vol. 10(2), pages 1-19, February.
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