Research on Marine Photovoltaic Power Forecasting Based on Wavelet Transform and Echo State Network

Du, Xiaomeng; Wang, Shuai; Zhang, Juan

doi:10.1515/pomr-2017-0064

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…To ensure the confidentiality and integrity of database data through data storage encryption, integrity verification and access control, and to achieve secure access to database data. In short, the security technology of network information is especially important for maintaining the true security of network information, so the work in this area needs to be strengthened [4].…”

Section: Strengthening the Security Management Of Power Network Informentioning

confidence: 99%

Analysis of Power Network Behavior Security Analysis Technology

Fan

Yang²,

Xu³

2018

MATEC Web Conf.

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Nowadays, with the rapid development of science and technology, network information technology is widely applied to various enterprise departments. In order to meet the increasing social needs, power companies have also built power network information systems. The establishment of the network information system has been put into use, which has greatly improved the efficiency of the power enterprise. However, the security risks of network information systems have followed. Once the network is damaged by the attack, it will cause the power system to fail to operate normally, which will inevitably cause significant losses. Power system information security issues threaten the security of the power system and the entire power industry. Studying the information security of power systems, how to protect the power information network from threats, how to ensure the safe and stable supply of electricity to the whole society, and striving to develop a safe and effective power network information system is an important issue facing the development of information technology.

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Section: Strengthening the Security Management Of Power Network Informentioning

confidence: 99%

Analysis of Power Network Behavior Security Analysis Technology

Fan

Yang²,

Xu³

2018

MATEC Web Conf.

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“…In ref. [28], Xinhui et al proposed a prediction model of an ESN based on wavelet theory (WT + ESN) for PV power prediction. This study used three error indicators to compare three traditional models of the WT + ESN model and proved the superiority of the WT + ESN model.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Photovoltaic Power Prediction Using Nonlinear Spiking Neural P Systems

Gao,

Wang,

Guo

et al. 2024

Sustainability

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To ensure high-quality electricity, improve the dependability of power systems, reduce carbon emissions, and promote the sustainable development of clean energy, short-term photovoltaic (PV) power prediction is crucial. However, PV power is highly stochastic and volatile, making accurate predictions of PV power very difficult. To address this challenging prediction problem, in this paper, a novel method to predict the short-term PV power using a nonlinear spiking neural P system-based ESN model has been proposed. First, we combine a nonlinear spiking neural P (NSNP) system with a neural-like computational model, enabling it to effectively capture the complex nonlinear trends in PV sequences. Furthermore, an NSNP system featuring a layer is designed. Input weights and NSNP reservoir weights are randomly initialized in the proposed model, while the output weights are trained by the Ridge Regression algorithm, which is motivated by the learning mechanism of echo state networks (ESNs), providing the model with an adaptability to complex nonlinear trends in PV sequences and granting it greater flexibility. Three case studies are conducted on real datasets from Alice Springs, Australia, comparing the proposed model with 11 baseline models. The outcomes of the experiments exhibit that the model performs well in tasks of PV power prediction.

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“…To denoise the ambient noise in the ocean, many scholars have proposed many denoising methods (Du et al , 2017; Gao et al , 2017). The traditional signal denoising methods are finite impulse response (FIR) filters (Johansson, 2012) and infinite impulse response (IIR) filters (Al-Alaoui, 2007).…”

Section: Introductionmentioning

confidence: 99%

Improved DOA estimation of MEMS vector hydrophone combined with CEEMDAN and wavelet transform for noise reduction

Chang,

Zhang,

Zhang

et al. 2024

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Purpose Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed. Design/methodology/approach Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference. Findings The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized. Originality/value This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

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Research on Marine Photovoltaic Power Forecasting Based on Wavelet Transform and Echo State Network

Cited by 4 publications

References 12 publications

Analysis of Power Network Behavior Security Analysis Technology

Analysis of Power Network Behavior Security Analysis Technology

Short-Term Photovoltaic Power Prediction Using Nonlinear Spiking Neural P Systems

Improved DOA estimation of MEMS vector hydrophone combined with CEEMDAN and wavelet transform for noise reduction

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