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Toward smart distributed renewable generation via multi-uncertainty featured non-intrusive interactive energy monitoring

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  • Liu, Yu
  • Liu, Congxiao
  • Ling, Qicheng
  • Zhao, Xin
  • Gao, Shan
  • Huang, Xueliang

Abstract

Quantities of advanced technologies have been utilized to realize the carbon neutrality, among which the smart implementations at energy user side are highlighted due to the extensive coverage. Supported by multiple energy management technologies, the integration of distributed renewable energy is prominent, but the compatibility problem of diverse technologies still exists especially considering the newly-developed features. In this paper, an interactive energy monitoring via non-intrusive way is allocated to analyze the roof-top photovoltaic generation and individual appliance consumption from integral energy measurements, and a complete solution is proposed to tackle the distributed generation intelligence with smart voltage maintenance. At first stage, aiming at the domestic reactive power management of photovoltaic inverters, the framework and strategy of coordination between smart meter and intelligent photovoltaic generation are proposed, and then the unified energy signature formulation of photovoltaic generation is presented. Afterwards, the energy disaggregation model is formularized by modified dictionary learning scheme with hybrid validation strategy. Lastly, a sparse coding and auxiliary optimization-based solution is proposed to solve the problem, achieving the robustness under real time architecture. Both the specific low voltage network simulator platform and the practical field measurement scenarios are utilized to verify the effectiveness of the proposed study, and results demonstrate that the proposed study provides an efficient monitoring solution to the intelligent photovoltaic generation, which helps to move toward the smart energy user implementation.

Suggested Citation

  • Liu, Yu & Liu, Congxiao & Ling, Qicheng & Zhao, Xin & Gao, Shan & Huang, Xueliang, 2021. "Toward smart distributed renewable generation via multi-uncertainty featured non-intrusive interactive energy monitoring," Applied Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921010497
    DOI: 10.1016/j.apenergy.2021.117689
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    References listed on IDEAS

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    2. Yini Ni & Yanghong Xia & Zichen Li & Qifan Feng, 2023. "A Non-Intrusive Identification Approach for Residential Photovoltaic Systems Using Transient Features and TCN with Attention Mechanisms," Sustainability, MDPI, vol. 15(20), pages 1-22, October.

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