Research on Dedicated Network of Distribution Electric Power IoT Based on LoRa Technology and Multi-fork tree Model

Jin-hu, Wang; Guan, Guofei; Wang, Cheng-Liang; Wang, Xiaohua; He, Zhaoshui

doi:10.1088/1755-1315/358/3/032057

Cited by 1 publication

(1 citation statement)

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“…The comprehensive assessment of power quality reflects the overall level of quality of electrical energy provided by the grid and essentially represents the level of operation of the entire grid structure as well as the power supply capacity of the power system [19][20][21]. Determining the market price of electric energy according to the quality of electric energy is an important trend in the current power supply market, so the quality of electric energy will be an important factor affecting the feed-in tariff [22][23]. In addition, the comprehensive quantitative results obtained after the assessment are an important reference for power companies to maintain and improve the quality of electric energy.…”

Section: Introductionmentioning

confidence: 99%

Research on power quality assessment based on ubiquitous power IoT

Zhang¹,

Zhi²,

Zhao³

et al. 2023

Applied Mathematics and Nonlinear Sciences

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With the rapid development of the Internet in this era, the traditional power grid is no longer able to meet the growing demand of the people for electricity. In order to realize a new generation of power system with comprehensive sensing, reliable transmission, intelligent processing and interconnection, the State Grid proposes the strategic goal of developing ubiquitous power IoT. Firstly, the concept and basic architecture of ubiquitous power IoT are elaborated, and then the main key technologies of the architecture of power energy consumption monitoring and management system are explained. The power quality parameters are measured and calculated, and the G1 method, which is computationally small and does not require consistency testing, is used to determine the subjective weights in the power quality evaluation process, which can truly reflect the power quality level of power grids in different regions. The information entropy method is used to determine the objective weights in the process of power quality evaluation to solve the error of artificially determined weights, and the combination of subjective weights and objective weights can more truly reflect the influence of each index on the comprehensive level of power quality. The results of the study show that PV is rated between 2 and 3 good when grid-connected and off-grid, and wind turbines are rated between 3 and 4 medium when grid-connected and off-grid. The results of the integrated assessment levels are in line with the actual situation and can meet the growing demand for electricity.

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