Zobrazeno 1 - 10
of 956
pro vyhledávání: '"interval prediction"'
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 7, Pp 3142-3156 (2024)
Abstract The accurate prediction of photovoltaic (PV) power is crucial for planning, constructing, and scheduling high‐penetration distributed PV power systems. Traditional point prediction methods suffer from instability and lack reliability, whic
Externí odkaz:
https://doaj.org/article/0fd95a198a4b46dcb235b2fd4ad38124
Autor:
Jiaxi Li, Ming Wen, Zhuomin Zhou, Bo Wen, Zongchao Yu, Haiwei Liang, Xinyang Zhang, Yue Qin, Chufan Xu, Hongyi Huang
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 161, Iss , Pp 110204- (2024)
The large amount of source and load uncertainty in new power systems poses challenges to the optimization of power supply and demand balance. The traditional optimization methods have not fully considered the uncertainty characteristics of different
Externí odkaz:
https://doaj.org/article/e0af352428bc46b6adbe5d3c155a654a
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 6, Pp 806-818 (2024)
Aimed at the intermittency and fluctuation of photovoltaic output power, a short-term interval prediction model of photovoltaic power is proposed. First, the model uses the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) to
Externí odkaz:
https://doaj.org/article/6bc936023e594892888cd4b0317dd702
Publikováno v:
工程科学学报, Vol 46, Iss 4, Pp 723-734 (2024)
Deep learning has been extensively employed for predicting the remaining useful life (RUL) of equipment owing to the powerful feature extraction ability of deep learning. However, the deep learning prediction results are often affected by random nois
Externí odkaz:
https://doaj.org/article/5953262340144cb0938b90af02008265
Publikováno v:
Heliyon, Vol 10, Iss 14, Pp e33945- (2024)
Wind energy is becoming increasingly competitive, Accurate and reliable multi-engine wind power forecasts can reduce power system operating costs and improve wind power consumption capacity. Existing research on wind power forecasting has neglected t
Externí odkaz:
https://doaj.org/article/ee17fb39ca1c48c296aa00f90718369e
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 3, Pp 285-294 (2024)
This paper proposes an interval prediction technology of photovoltaic (PV) power based on parameter optimization of extreme learning machine (ELM) model. First, the weighted Euclidean distance is proposed as the evaluation index of PV power predictio
Externí odkaz:
https://doaj.org/article/b7834ea674834f079b958564f1b8c06d
Publikováno v:
IEEE Access, Vol 12, Pp 64069-64078 (2024)
The distribution network with high penetration of renewable energy such as wind and photovoltaic power has higher flexibility and power supply efficiency, but it also faces more faults and uncertainties. Traditional dynamic reconfiguration under faul
Externí odkaz:
https://doaj.org/article/9060a0e9d7e141898185c7a9d67b2a67
Publikováno v:
IEEE Access, Vol 12, Pp 39717-39727 (2024)
This paper presents an efficient motion planning framework for a perturbed linear system using a minimax objective function while ensuring the safety of the system. Specifically, the proposed approach is naturally deployed to handle model uncertainti
Externí odkaz:
https://doaj.org/article/f1ecae9045e44315949511fa43f522f3
Autor:
Zahra Jamshidzadeh, Sarmad Dashti Latif, Mohammad Ehteram, Zohreh Sheikh Khozani, Ali Najah Ahmed, Mohsen Sherif, Ahmed El-Shafie
Publikováno v:
Environmental Sciences Europe, Vol 36, Iss 1, Pp 1-19 (2024)
Abstract For more than one billion people living in coastal regions, coastal aquifers provide a water resource. In coastal regions, monitoring water quality is an important issue for policymakers. Many studies mentioned that most of the conventional
Externí odkaz:
https://doaj.org/article/dd263713e1b0400a8fc7dc83d479fb26
Publikováno v:
Agronomy, Vol 14, Iss 11, p 2678 (2024)
Key soil properties play pivotal roles in shaping crop growth and yield outcomes. Accurate point prediction and interval prediction of soil properties serve as crucial references for making informed decisions regarding fertilizer applications. Tradit
Externí odkaz:
https://doaj.org/article/20321c360ce846d78fd9d5dd60a38555