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Multi-Period Optimization Model for Electricity Generation Planning Considering Plug-in Hybrid Electric Vehicle Penetration
Ahmadi, Lena; Elkamel, Ali; Abdul-Wahab, Sabah A.; Pan, … - In: Energies 8 (2015) 5, pp. 3978-4002
One of the main challenges for widespread penetration of plug-in hybrid electric vehicles (PHEVs) is their impact on the electricity grid. The energy sector must anticipate and prepare for this extra demand and implement long-term planning for electricity production. In this paper, the...
Persistent link: https://www.econbiz.de/10011274570
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A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations
Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik - In: Energies 5 (2012) 3, pp. 621-657
Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes....
Persistent link: https://www.econbiz.de/10010668063
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Forecasting Monthly Electric Energy Consumption Using Feature Extraction
Meng, Ming; Niu, Dongxiao; Sun, Wei - In: Energies 4 (2011) 10, pp. 1495-1507
Monthly forecasting of electric energy consumption is important for planning the generation and distribution of power … waves were modeled separately by a grey model and radio basis function neural networks. Adding the forecasting values of … each model can yield the forecasting results for monthly electricity consumption. The grey model has a good capability for …
Persistent link: https://www.econbiz.de/10010668113
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Day-Ahead Electricity Price Forecasting Using a Hybrid Principal Component Analysis Network
Hong, Ying-Yi; Wu, Ching-Ping - In: Energies 5 (2012) 11, pp. 4711-4725
) network for forecasting LMPs in a day-ahead market. The PCA network extracts essential features from periodic information in … the market. These features serve as inputs to the MLF network for forecasting LMPs. The historical LMPs in the PJM market … are employed to test the proposed method. It is found that the proposed method is capable of forecasting day-ahead LMP …
Persistent link: https://www.econbiz.de/10010668182
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Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters
Wang, Fei; Mi, Zengqiang; Su, Shi; Zhao, Hongshan - In: Energies 5 (2012) 5, pp. 1355-1370
Short-term solar irradiance forecasting (STSIF) is of great significance for the optimal operation and power …
Persistent link: https://www.econbiz.de/10010676107
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A Bayesian Method for Short-Term Probabilistic Forecasting of Photovoltaic Generation in Smart Grid Operation and Control
Bracale, Antonio; Caramia, Pierluigi; Carpinelli, Guido; … - In: Energies 6 (2013) 2, pp. 733-747
A<b> </b>new short-term probabilistic forecasting method is proposed to predict the probability density function of the … effectiveness and advantages of the proposed forecasting method. …
Persistent link: https://www.econbiz.de/10011030942
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Circuit Simulation for Solar Power Maximum Power Point Tracking with Different Buck-Boost Converter Topologies
Shiau, Jaw-Kuen; Lee, Min-Yi; Wei, Yu-Chen; Chen, Bo-Chih - In: Energies 7 (2014) 8, pp. 5027-5046
The power converter is one of the essential elements for effective use of renewable power sources. This paper focuses on the development of a circuit simulation model for maximum power point tracking (MPPT) evaluation of solar power that involves using different buck-boost power converter...
Persistent link: https://www.econbiz.de/10010884951
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Geophysical Methods for Monitoring Temperature Changes in Shallow Low Enthalpy Geothermal Systems
Hermans, Thomas; Nguyen, Frédéric; Robert, Tanguy; … - In: Energies 7 (2014) 8, pp. 5083-5118
Low enthalpy geothermal systems exploited with ground source heat pumps or groundwater heat pumps present many advantages within the context of sustainable energy use. Designing, monitoring and controlling such systems requires the measurement of spatially distributed temperature fields and the...
Persistent link: https://www.econbiz.de/10010885348
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Shadow Replication: An Energy-Aware, Fault-Tolerant Computational Model for Green Cloud Computing
Cui, Xiaolong; Mills, Bryan; Znati, Taieb; Melhem, Rami - In: Energies 7 (2014) 8, pp. 5151-5176
As the demand for cloud computing continues to increase, cloud service providers face the daunting challenge to meet the negotiated SLA agreement, in terms of reliability and timely performance, while achieving cost-effectiveness. This challenge is increasingly compounded by the increasing...
Persistent link: https://www.econbiz.de/10010886252
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Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)
Giorgi, Maria Grazia De; Campilongo, Stefano; … - In: Energies 7 (2014) 8, pp. 5251-5272
forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and …
Persistent link: https://www.econbiz.de/10010886253