Wind power interval prediction based on hybrid semi-cloud model and nonparametric kernel density estimation

Zhang, Kai; Yu, Xiaodong; Liu, Shulin; Dong, Xia; Li, Daoqing; Zang, Hongzhi; Xu, Rui

doi:10.1016/j.egyr.2022.02.094

Cited by 27 publications

(10 citation statements)

References 1 publication

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“… The kernel density estimation method [24] is used to fit the historical data to obtain probability distribution models for WT and PV power. And the optimal Copula function is selected as the joint function for the combined WT and PV power model.…”

Section: Methods For Evaluating the Adequacy Of Power System On Multi...mentioning

confidence: 99%

Multi‐time scale adequacy evaluation of the power system with high penetration of renewable energy sources based on empirical mode decomposition

Zhang

Xing

Sun

et al. 2023

IET Generation Trans & Dist

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Adequacy, especially in the power system with high penetration of renewable energy sources, is a crucial consideration in power system planning and operational dispatching. A multi‐time scale adequacy evaluation method based on empirical mode decomposition (EMD) is proposed, taking into account the multi‐time scale characteristics of renewable energy sources and the response characteristics of flexible regulation resources. In this method, a net load curve is decomposed into several component curves by the EMD algorithm. Then, the adequacy demand on each time scale is obtained by waveform recognition. Furthermore, the available adequacy resources on different time scales are quantified according to the regulation models of flexible resources. By analysing the adequacy demand and available adequacy resources of the power system on the same time scale, the adequacy evaluation indices on each time scale can be calculated and weighted to form the comprehensive indices. Finally, the adequacy evaluation indices on each time scale with different capacities of renewable energy sources and energy storage systems are compared and analysed using a practical power system as a case. Simulation results show the validity of the multi‐time scale adequacy evaluation method.

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Section: Methods For Evaluating the Adequacy Of Power System On Multi...mentioning

confidence: 99%

Multi‐time scale adequacy evaluation of the power system with high penetration of renewable energy sources based on empirical mode decomposition

Zhang

Xing

Sun

et al. 2023

IET Generation Trans & Dist

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show abstract

“…The uncertainty of PV power under different weather conditions is firstly analyzed, then a generalized weather classification method based on solar irradiance reduction index K is performed. Aiming at the uncertainty of power and kernel density estimation, a power interval forecasting method based on hybrid semi-cloud model and non-parametric kernel density estimation is proposed [14]. To address the problem of low traditional power interval forecasting accuracy, a new interval method is proposed based on PSR-BLS-QR with adaptive rolling error correction [15].…”

Section: Erefmentioning

confidence: 99%

Bayesian Optimization - LSTM Modeling and Time Frequency Correlation Mapping Based Probabilistic Forecasting of Ultra-short-term Photovoltaic Power Outputs

Shi,

Wang,

Zhou

et al. 2024

IEEE Trans. on Ind. Applicat.

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“…. , x n }, the probability density function of the random variable at any point can be expressed as [28]:…”

Section: Distribution Characteristics Of Conversion Efficiencymentioning

confidence: 99%

A Novel Operating State Evaluation Method for Photovoltaic Strings Based on TOPSIS and Its Application

Wang

Liu

et al. 2023

Sustainability

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PV strings are essential for energy conversion in large-scale photovoltaic (PV) power plants. The operating state of PV strings directly affects the power generation efficiency and economic benefits of PV power plants. In the process of evaluating PV arrays, a reference array needs to be identified. By comparing PV arrays with the reference array, the operational status of the PV arrays can be evaluated. However, in the actual operation of PV power stations, it is difficult to directly determine the reference state of a PV array due to random fluctuations in the PV power output. In order to solve the problems mentioned above, this paper proposes a method to select the reference state and perform a grading evaluation of PV strings. Additionally, the proposed method is based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm, which is used to rank the performance of PV arrays to determine their status. In order to solve the problem of random fluctuations in PV power generation, a probability distribution model of the PV string conversion efficiency was built by using the kernel density estimation method. Then, the characteristic indicator of the PV string’s operating state was described by the output power of the PV string and its probability distribution model. Then, based on the operating characteristic indicator, the reference state of the PV string was determined using the TOPSIS method, and the grading evaluation of the operating state of the PV string was realized. Finally, the effectiveness of the proposed method was verified using the actual data of a PV power station.

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Wind power interval prediction based on hybrid semi-cloud model and nonparametric kernel density estimation

Cited by 27 publications

References 1 publication

Multi‐time scale adequacy evaluation of the power system with high penetration of renewable energy sources based on empirical mode decomposition

Multi‐time scale adequacy evaluation of the power system with high penetration of renewable energy sources based on empirical mode decomposition

Bayesian Optimization - LSTM Modeling and Time Frequency Correlation Mapping Based Probabilistic Forecasting of Ultra-short-term Photovoltaic Power Outputs

A Novel Operating State Evaluation Method for Photovoltaic Strings Based on TOPSIS and Its Application

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