Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"power forecasting"”.
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Solar power forecasting using Gaussian process regression
Solar power forecasting has become an important aspect affecting crucial day-to-day activities in people's lives. Many African countries are now facing blackouts due to a shortage of energy. This has caused the urge to encourage people to use other energy sources to rise, resulting in different …
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Short-term wind power forecasting using artificial neural networks-based ensemble model
Short-term wind power forecasting is crucial for the efficient operation of power systems with high wind power penetration. Many forecasting approaches have been developed in the past to forecast short-term wind power. In recent years, artificial neural network-based approaches (ANNs) have been one …
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Wind regime characterization, and short-term wind speed and power forecasting using multivariable LSTM and NARX networks in the Andes Mountains, Ecuador
En los últimos años, la investigación ha revelado que los diseños hidroeléctricos en Ecuador no han considerado adecuadamente la sensibilidad al cambio climático. Además, las condiciones climáticas determinan las variaciones en la generación de electricidad a partir de esta fuente de energía …
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Photovoltaic power analysis and prediction using machine learning methods
The stochastic nature of Photovoltaic power directly affects the stability of the grid. PV power forecasting allows power stations to know beforehand how much PV power will be available, which ensures that the grid remains in stabilized condition. PV power from India is analyzed and predicted using …
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Vision-Based Solar Forecasting with Deep Learning
Solar power is expected to play a leading role in the current electrification of our economy and its shift towards a low-carbon energy supply. This source of energy has numerous advantages including a wide availability and low costs, but also some limitations such as space and material usage. In …
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Forecasting wind power for the day-ahead market using numerical weather prediction models and computational intelligence techniques
Wind power forecasting is essential for the integration of large amounts of wind power into the electric grid, especially during large rapid changes of wind generation. These changes, known as ramp events, may cause instability in the power grid. Therefore, detailed information of future ramp …
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Data mining and graph theory focused solutions to Smart Grid challenges
The Smart Grid represents a transition of the power and energy industry into a new era of improved efficiency, reliability, availability, and security, while contributing to economic and environmental health. However, several challenges must be addressed for real-life implementation of Smart Grids. …
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Integrating Transactive Energy and Machine Learning For Re-Energizing Wastewater Treatment Plants
… electricity per day and often relies on the grid power generated by burning fossil fuels. Wind- and solar-based distributed generation emerged as a clean energy solution to achieve environmental sustainability and net-zero performance. This study investigates power consumption trends in WWTP …
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Forecasting Wind Direction Across Very Short and Short Term Time Horizons for Wind Turbine Control
… systems can provide incremental improvements in power efficiency across both individual turbines and the collective wind farm. Yaw control strategies commonly apply low-pass őlters of wind directions observed by the turbine in the most recent 10 minutes to determine turbine reactions to the …
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Structure combination of forecasting models with application in the energy sector
… of neural networks, and highlights their use in forecasting within the energy sector. Research gaps are identified and the questions to be addressed in this research are set, thus leading to three empirical studies. The first study provides a detailed sensitivity analysis of the goodness-of-fit …
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Strategies for Managing Cool Thermal Energy Storage with Day-ahead PV and Building Load Forecasting at a District Level
… integrated the CTES with Photovoltaics (PV) power forecasting and building load forecasting at a district level for a more optimal charge/discharge management. A district comprises several buildings of different load profiles, all connected to the same cooling system with central CTES. The …
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Gaussian process models for SCADA data based wind turbine performance/condition monitoring
… price and residential probabilistic load forecasting, solar power forecasting. However, the application of GPs to wind turbine condition monitoring has to date been limited and not much explored.;This thesis focuses on GP based wind turbine condition monitoring that utilises data from …
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Development and Deployment of Renewable and Sustainable Energy Technologies
… as an appealing alternative to conventional power generated from fossil fuel. This is leading to significant levels of distributed renewable generation being installed on distribution circuits. Although renewable generation brings many advantages, circuit problems are created due to its …