Adaptability Evaluation of Distributed Power Sources Connected to Distribution Network

Huang, Yuansheng; Jiang, Yuqing; Wang, Jing

doi:10.1109/access.2021.3066206

Cited by 11 publications

(4 citation statements)

References 28 publications

(23 reference statements)

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“…The purpose of the five-level risk classification is to better identify and assess risks, prioritize risk control, and adopt effective risk management measures. Therefore, according to the characteristics of the new power system and the grading standards of previous research studies, this paper uses the five-level method [19] to classify the research objects into "major risk", "large risk", "general risk", "low risk", and "no risk", and the corresponding value ranges are [0, 20), [20,40), [40, 60), [60, 80), [80, 100). The calculation formula of the evaluation level expressed by the three parameters of the cloud model is…”

Section: Integrated Cloud Computingmentioning

confidence: 99%

Research on New Electric Power System Risk Assessment Based on Cloud Model

Tang,

Li,

Zhang

et al. 2024

Sustainability

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A large number of new energy power electronic equipment is connected to the new power system, and the high proportion of new energy brings huge volatility and randomness, so it is necessary to establish a systematic risk assessment system to adapt to the new power system. This paper has improved the neglect of environmental benefits and supply and demand balance in the existing indicator system and established an indicator system for the risk of the new power system from the five perspectives of safety, supply and demand, sufficiency, cleanliness, and flexibility through the analysis of the evaluation indicator system of the large power grid and the influencing factors of the new power system. The index weight of a new power system is established by means of the entropy weight–critic combination weighting method, and the comprehensive evaluation is carried out by combining it with the cloud model. Finally, the specific data of the new power system in Fujian Province from 2020 to 2022 are taken as an example to verify the feasibility of combining the combined weighting method and the cloud model, and it is concluded that the new power system in Fujian Province has been in a “low risk” operation state for the recent three years.

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Section: Integrated Cloud Computingmentioning

confidence: 99%

Research on New Electric Power System Risk Assessment Based on Cloud Model

Tang,

Li,

Zhang

et al. 2024

Sustainability

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“…Although there is a lack of research related to effect evaluation on three-phase imbalance treatment, there are many mature evaluation theories and methods used in various fields of power systems, such as the comprehensive evaluation of power quality combined with subjectivity and objectivity, fuzzy mathematics evaluation methods, and radar chart methods. [12][13][14][15][16]. Reference [12] establishes a scientific and reasonable evaluation index system of distribution network adaptability and combines the analytic hierarchy process (AHP) and entropy weight method to determine the index weight.…”

Section: Introductionmentioning

confidence: 99%

“…[12][13][14][15][16]. Reference [12] establishes a scientific and reasonable evaluation index system of distribution network adaptability and combines the analytic hierarchy process (AHP) and entropy weight method to determine the index weight. Reference [13] combines AHP and the entropy weight method to comprehensively evaluate the reliability of the power consumption of a distribution network.…”

Section: Introductionmentioning

confidence: 99%

Evaluation Index and Evaluation Method of Three-Phase Imbalance Treatment Effect Based on Commutation

Chen

Zhou

et al. 2022

IEEE Access

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With the construction and development of the distribution Internet of things in China, the threephase imbalance treatment in the distribution area has gradually attracted attention as an optional function, and a large number of intelligent terminal manufacturers have begun to study this aspect. In this paper, research is carried out on the three-phase imbalance treatment function based on commutation control. The evaluation index system of imbalance treatment based on commutation is proposed in combination with the imbalance harm and the influence of treatment, and the three-phase imbalance treatment effect is evaluated by combining the analytic hierarchy process and improved entropy weight method. An example is given to verify the effectiveness of the evaluation method proposed in this paper.INDEX TERMS Three-phase load imbalance, intelligent terminal, index system, analytic hierarchy process, improved entropy weight method

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“…The AHP can refer to historical operating data to determine subjective and objective weights and select reasonable solutions. The problem of multi-objective comprehensive evaluation can be solved by the combination of the EWM and AHP (EWM-AHP) [14], and some relevant studies have been conducted in the fields of power quality assessment [15] and fault identification [16]. Existing EWM-AHP methods have studied voltage and reactive power evaluation, but there are still some problems.…”

Section: Introductionmentioning

confidence: 99%

Archives of Electrical Engineering

Ji,

Chen,

Xiao

et al. 2021

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The output of renewable energy is strongly uncertain and random, and the distribution of voltage and reactive power in regional power grids is changed with the access to large-scale renewable energy. In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a novel combinational evaluation method of voltage and reactive power in regional power grids containing renewable energy is proposed. Firstly, the actual operation data of renewable energy and load demand are clustered based on the K-means algorithm, and several typical scenarios are divided. Then, the entropy weight method (EWM) and the analytic hierarchy process (AHP) are combined to evaluate the voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve in typical scenarios. Besides, the evaluation results are used as the training samples for back-propagation (BP) neural networks. The proposed combinational evaluation method can calculate the weight coefficient of the indexes adaptively with the change of samples, which simplifies the calculation process of the indexes' weight. At last, the case simulation of an actual regional power grid is provided, and the historical data of one year is taken as the sample for training, evaluating and analyzing. And finally, the effectiveness of the proposed method is verified based on the comparison with the existing method. The evaluated results could provide reference and guidance to the operation analysis and planning of renewable energy.

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Adaptability Evaluation of Distributed Power Sources Connected to Distribution Network

Cited by 11 publications

References 28 publications

Research on New Electric Power System Risk Assessment Based on Cloud Model

Research on New Electric Power System Risk Assessment Based on Cloud Model

Evaluation Index and Evaluation Method of Three-Phase Imbalance Treatment Effect Based on Commutation

Archives of Electrical Engineering

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