Results 11 to 20 of about 287,989 (277)
Journal of Power Sources, 2022 We report an improved and simple exponential model for the charging and discharging behavior of series- connected modules of supercapacitors under varying load conditions and over extended periods of time. In this work, only a single variable leakage resistance (VLR) with exponential current/voltage profile is used to model the effects of different ...
Pourkheirollah, Hamed +3 more
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Energy Conversion and Management, 2013 Abstract For an energy-limited economy system, it is crucial to forecast load demand accurately. This paper devotes to 1-week-ahead daily load forecasting approach in which load demand series are predicted by employing the information of days before being similar to that of the forecast day.
Jie Wu +4 more
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Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing) and Artificial Intelligence Models (ANN, SVM): The Case of Greek Electricity Market [PDF]
Energies, 2016 In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC) technique and the traditional multiple regression (PC-regression), for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity Market for the period 2004–2014.
George P. Papaioannou +3 more
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International Journal of Electrical Power & Energy Systems, 2016 Abstract In this paper an analytical design method is proposed for constant voltage controlled inverter based DG with frequency dependent ZIP–Exponential static load model to obtain proper inverter output control and successful islanding detection.
Ankita Samui, S.R. Samantaray
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IEEE Transactions on Neural Networks and Learning SystemsShort-term load forecasting (STLF) is challenging due to complex time series (TS) which express three seasonal patterns and a nonlinear trend. This paper proposes a novel hybrid hierarchical deep learning model that deals with multiple seasonality and produces both point forecasts and predictive intervals (PIs).
Slawek Smyl +2 more
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Dynein-Inspired Multilane Exclusion Process with Open Boundary Conditions
Entropy, 2021 Motivated by the sidewise motions of dynein motors shown in experiments, we use a variant of the exclusion process to model the multistep dynamics of dyneins on a cylinder with open ends.
Riya Nandi, Uwe C. Täuber, Priyanka
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Short-Term Load Forecasting Based on Multi-branch Residual Gated Convolution Neural Network
Zhongguo dianli, 2022 Short-term load forecasting is one of the important tasks for power utilities to formulate grid planning and scheduling plans. Considering the temporal characteristics of the load data, in order to improve the prediction accuracy of power load, a short ...
Jiangchuan FAN +4 more
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Regression Model-Based Short-Term Load Forecasting for Load Despatch Centre
Journal of Applied Engineering and Technological Science, 2023 Forecasting load is an integral part of the planning, operation, and control of power systems. This paper is part of a research effort aimed at developing better energy demand forecasting models for load dispatch centers (LDCs) in Indian states as part ...
Saikat Gochhait, Deepak Sharma
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COVID-19: a simple statistical model for predicting intensive care unit load in exponential phases of the disease [PDF]
Scientific Reports, 2021 AbstractOne major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an intensive care unit (ICU), the need for future intensive care can easily be underestimated.
Matthias Ritter +4 more
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Microgrid small‐signal stability analysis considering dynamic load model
IET Renewable Power Generation, 2021 Microgrids suitable operation depends on the system's proper design, based on accurate component models. A complete model considering entire system dynamics is a vital necessity for a successful design.
Aram Mahdavian +2 more
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