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Controllable Load Management Approaches in Smart Grids

Author

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  • Jingshuang Shen

    (Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

  • Chuanwen Jiang

    (Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

  • Bosong Li

    (Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

Abstract

With rapid smart grid technology development, the customer can actively participate in demand-side management (DSM) with the mutual information communication between the distributor operation company and the smart devices in real-time. Controllable load management not only has the advantage of peak shaving, load balance, frequency regulation, and voltage stability, but is also effective at providing fast balancing services to the renewable energy grid in the distributed power system. The load management faces an enormous challenge as the customer has a large number of both small residential loads and dispersed renewable sources. In this paper, various controllable load management approaches are discussed. The traditional controllable load approaches such as the end users’ controllable appliances, storage battery, Vehicle-to-Grid (V2G), and heat storage are reviewed. The “broad controllable loads” management, such as the microgrid, Virtual Power Plant (VPP), and the load aggregator are also presented. Furthermore, the load characteristics, control strategies, and control effectiveness are analyzed.

Suggested Citation

  • Jingshuang Shen & Chuanwen Jiang & Bosong Li, 2015. "Controllable Load Management Approaches in Smart Grids," Energies, MDPI, vol. 8(10), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:11187-11202:d:56842
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    References listed on IDEAS

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    Cited by:

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    14. Ricardo Faia & Pedro Faria & Zita Vale & João Spinola, 2019. "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, MDPI, vol. 12(9), pages 1-18, April.
    15. Alam, Khandoker Shahjahan & Kaif, A.M.A. Daiyan & Das, Sajal K., 2024. "A blockchain-based optimal peer-to-peer energy trading framework for decentralized energy management with in a virtual power plant: Lab scale studies and large scale proposal," Applied Energy, Elsevier, vol. 365(C).
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