Zobrazeno 1 - 10
of 369
pro vyhledávání: '"Weihao Hu"'
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 20, Pp 3221-3233 (2024)
Abstract The variability of renewable energy within microgrids (MGs) necessitates the smoothing of power fluctuations through the effective scheduling of internal power equipment. Otherwise, significant power variations on the tie‐line connecting t
Externí odkaz:
https://doaj.org/article/39aa1e3fb5b64753819007e9f0cfe0ce
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 160, Iss , Pp 110074- (2024)
Short-term residential load forecasting (STRLF) holds great significance for the stable and economic operation of distributed power systems. Different households in the same region may exhibit similar consumption patterns owing to the analogous envir
Externí odkaz:
https://doaj.org/article/9f67da44d67c4cb48f167ff963f585e7
Publikováno v:
CSEE Journal of Power and Energy Systems, Vol 10, Iss 3, Pp 1119-1130 (2024)
Electricity prices have complex features, such as high frequency, multiple seasonality, and nonlinearity. These factors will make the prediction of electricity prices difficult. However, accurate electricity price prediction is important for energy p
Externí odkaz:
https://doaj.org/article/64ec89feeb5b4ebfbe70d498103387d8
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 12, Iss 1, Pp 213-224 (2024)
With the development of advanced metering infrastructure (AMI), large amounts of electricity consumption data can be collected for electricity theft detection. However, the imbalance of electricity consumption data is violent, which makes the trainin
Externí odkaz:
https://doaj.org/article/dfdaa0150b7d49abb235e2cd7a5ebeac
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 1061-1068 (2023)
With the rapid development of artificial intelligence, the rack load power is constantly increasing. The 48 V/12 V converter which is suitable for the two-stage step-down structure of 48 V distribution system has received much attention. In this pape
Externí odkaz:
https://doaj.org/article/5023f93eb9d544248b08723f0145034b
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 894-903 (2023)
Effective economic dispatch for the integrated energy system (IES) can improve energy efficiency and promote renewable energy accommodation. Tradition IES economic dispatch are based on model-based methods that rely on accurate system parameters and
Externí odkaz:
https://doaj.org/article/937f6e1a7b0845bfadb257a71bb3f46b
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 522-531 (2023)
Bearing fault diagnosis is very important for the security and efficiency of electric machines. In recent years, the newly emerging deep learning methods have risen bearing fault diagnosis as a research hotspot again. To achieve better performance an
Externí odkaz:
https://doaj.org/article/d76d5454f3374a258448110d946542bb
Autor:
Hongbin Zhang, Weihao Hu
Publikováno v:
Buildings, Vol 14, Iss 6, p 1723 (2024)
Conventional methods for calculating tension currently suffer from an excessive simplification of boundary conditions and a vague definition of effective cable length, both of which cause inaccurate cable tension calculations. Therefore, this study u
Externí odkaz:
https://doaj.org/article/bc0170c2d3364484bcf6eb448b30f2d4
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 1-10 (2023)
The accurate estimation of lithium battery state of health (SOH) is very important for the safe and stable operation of the battery. Since the user’s charging process is random, it is difficult for the user to know the battery SOH through the charg
Externí odkaz:
https://doaj.org/article/5fa9250924ce404e8e01c23d7d56711d
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 11, Iss 6, Pp 1770-1783 (2023)
This paper proposes a robust and computationally efficient control method for damping ultra-low frequency oscillations (ULFOs) in hydropower-dominated systems. Unlike the existing robust optimization based control formulation that can only deal with
Externí odkaz:
https://doaj.org/article/0a443606f46b484ebfb40dfb3a172d1d