Results 101 to 110 of about 108,466 (288)

SHORT TERM LOAD FORECASTING UNTUK HARI LIBUR PADA KONDISI BEBAN ANOMALI MENGGUNAKAN ALGORITMA HYBRID BACK PROPAGATION-SWARM PARTICLE [PDF]

, 2015
Keakuratan prediksi beban listrik akan berdampak pada biaya pembangkitan yang lebih ekonomis. Penggunaan energi listrik pada hari libur nasional, menunjukkan pola beban yang cenderung tidak identik, pola ini berbeda dari pola beban pada hari normal.
Rasyid, Sopian Al
core  

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

, 2018
The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward ...
Chen, Qixin, Hong, Tao, Kang, Chongqing, Wang, Yi   +3 more
core   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Short-term power load forecasting in distribution networks considering human comfort level

Frontiers in Energy Research
The growth of power demand and the increase of new energy penetration have resulted in a heightened necessity for the precision of short-term power load forecasting in distribution networks. The majority of current research on short-term load forecasting
Yong Li, Hua Wang, Xianbin Huang, Juanyang Hao, Wenting Lei, Quanlin Wang   +5 more
doaj   +1 more source

Characterization of Nitinol Produced by Laser Powder Bed Fusion for Mechanical Metamaterial Applications

Advanced Engineering Materials, EarlyView.
Stabilization of L‐PBF Ni50.7Ti49.3 under low‐cycle loading was investigated. Recoverable strain after cycling was dependent on the amount of applied load. Recovery ratio was 53.4% and 35.1% at intermediate and high load, respectively. The maximum total strain reached 10.3% at a high load of 1200 MPa.
Ondřej Červinek, Jakub Hurník, Miroslav Šmíd, Ondřej Zobač, Melanie Todt, Daniel Koutný   +5 more
wiley   +1 more source

Research on Load Forecasting Based on Bayesian Optimized CNN-LSTM Neural Network

Energies
With the high penetration of renewable energy integration and massive user participation in electricity markets, traditional short-term load forecasting methods exhibit limitations in both adaptability and prediction accuracy.
Pengyang Duan, Huannian Jiao, Jianying Sun, Aiming Han, Zheng Dai, Liang Cheng, Xiaotao Chen   +6 more
doaj   +1 more source

Управление электрической нагрузкой с использованием прогнозной модели Хольта-Винтерса [PDF]

, 2016
У даній роботі розглянуто метод управління електричним навантаженням промислового підприємства з використанням прогнозних моделей Хольта-Вінтерса. Представлений аналіз наукових досліджень в галузі управління електричним навантаженням.
Khodakivskyi, I., Rozen, V., Розен, В. П., Розен, В. П., Ходаковский, И. Г., Ходаківський, І. Г.   +5 more
core  

Multi-time-horizon Solar Forecasting Using Recurrent Neural Network

, 2018
The non-stationarity characteristic of the solar power renders traditional point forecasting methods to be less useful due to large prediction errors.
Mishra, Sakshi, Palanisamy, Praveen
core   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Neural-Wavelet Based Hybrid Model for Short-Term Load Forecasting [PDF]

, 2013
Exactly power load forecasting especially the short term load forecasting is of important significance in the case of energy shortage today. Conventional ANN-based load forecasting methods deal with 24-hour-ahead load forecasting.
Chaturvedi, D. K., Premdayal, Sinha Anand   +1 more
core   +1 more source