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Predictive Modelling for Energy Management and Power Systems Engineering

Predictive Modelling for Energy Management and Power Systems Engineering (Paperback)

Pijush Samui, Sanjiban Sekhar Roy, Ravinesh C. Deo (엮은이)
Elsevier
256,870원

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Predictive Modelling for Energy Management and Power Systems Engineering
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책 정보

· 제목 : Predictive Modelling for Energy Management and Power Systems Engineering (Paperback) 
· 분류 : 외국도서 > 과학/수학/생태 > 과학 > 에너지
· ISBN : 9780128177723
· 쪽수 : 552쪽
· 출판일 : 2020-09-30

목차

1. A Multi-Objective Optimal VAR Dispatch Using FACTS Devices Considering Voltage Stability and Contingency Analysis
2. PV panels lifespan increase by control
3. Community-scale rural energy systems: General planning algorithms and management methods in developing countries
4. Proven ESS Applications for Power System Stability and Transition Issues
5. Forecasting solar radiation with evolutionary polynomial regression, wavelet transform & ensemble empirical mode decomposition
6. Development and Comparison of Data-driven Models for Wind Speed Forecasting in Australia
7. Modelling Photosynthetic Active Radiation with a Hybrid Multilayer Perceptron-Firefly Optimizer Algorithm
8. Predictive Modeling of Oscillating Plasma Energy Release for Clean Combustion Engines
9. Nowcasting solar irradiance for effective solar power plants operation and smart grid management
10. Short-term energy demand modelling with hybrid emotional neural networks integrated with genetic algorithm
11. Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference System in energy modeling of agricultural products
12. Support Vector Machine Models for Multi-Step Wind Speed Forecasting
13. MARS Model for Prediction of Short and Long-term Global Solar Radiation
14. Wind Speed Forecasting in Nepal using Self Organizing Map-based Online Sequential Extreme Learning Machine (SOM-OSELM)
15. Potential growth in small-scale distributed generation systems in Brazilian capitals
16. The trend of Energy Consumption in Developing Nations for the last two decades: A case study from a statistical perspective

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