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This paper presents a statistical framework for assessing wireless systems performance using hierarchical data mining techniques. We consider WCDMA (wideband code division multiple access) systems with two-branch STTD (space time transmit…
Photogalvanic solar cells, the original dye based solar cell, have yet to fulfill their promise as a low fabrication cost, scalable energy conversion system. The efficient performance of photogalvanic cells relies on high dye solubility and…
Accurate estimation of solar irradiance is essential for reliable modelling of solar photovoltaic (PV) power production. In Ireland's highly variable maritime climate, where ground-based measurement stations are sparsely distributed,…
Commercial building Heating, Ventilation, and Air Conditioning (HVAC) systems can provide flexibility to the electricity grid. Some researchers have found it convenient to model HVAC systems as virtual batteries. These models also better…
A novel unsupervised machine learning approach for analyzing time-series data is applied to the topic of photovoltaic (PV) system degradation rate estimation, sometimes referred to as energy-yield degradation analysis. This approach only…
Solar photovoltaic (PV) technology has merged as an efficient and versatile method for converting the Sun's vast energy into electricity. Innovation in developing new materials and solar cell architectures is required to ensure lightweight,…
Renewable energy technologies including solar and wind inevitably play a leading role in meeting the growing demand for a decarbonized and clean power grid. However, these technologies are highly dependent of meteorological conditions of…
In this paper, a computationally lightweight algorithm is introduced for hybrid PV/Battery/Load systems that is price responsive, responds fast, does not require powerful hardware, and considers the operational limitations of the system.…
Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior…
With the growth of residential rooftop PV adoption in recent decades, the problem of effective layout design has become increasingly important in recent years. Although a number of automated methods have been introduced, these tend to rely…
Developing a unified small-signal model for modern, large-scale power systems that remains accurate across a wide range of operating ranges presents a formidable challenge. Traditional methods, spanning mechanistic modeling, modal…
Hidden Markov models have successfully been applied as models of discrete time series in many fields. Often, when applied in practice, the parameters of these models have to be estimated. The currently predominating identification methods,…
Accurate household electrical energy demand prediction is essential for effectively managing sustainable Energy Communities. Integrated with the Energy Management System, these communities aim to optimise operational costs. However, most…
With the advancement of energy Internet and energy system integration, the increasing adoption of distributed photovoltaic (PV) systems presents new challenges on smart monitoring and measurement for utility companies, particularly in…
Concentrator Photovoltaic (CPV) systems use high efficiency multi-junction solar cells with efficiencies >40%, but the module efficiency is often much lower. The increased complexity of a CPV module, with optics, receiver and the tracker…
One of the most important issues in the operation of a photovoltaic (PV) system is extracting maximum power from the PV array, especially in partial shading condition (PSC). Under PSC, P-V characteristic of PV arrays will have multiple peak…
The integration of renewable energy sources in microgrids introduces significant operational challenges due to their intermittent nature and the mismatch between generation and demand patterns. Effective demand response (DR) strategies are…
This paper presents a novel architecture for model predictive control (MPC) based indoor climate control of multi-zone buildings to provide energy efficiency. Unlike prior works we do not assume the availability of a high-resolution…
Accurate forecasting in the e-commerce finance domain is particularly challenging due to irregular invoice schedules, payment deferrals, and user-specific behavioral variability. These factors, combined with sparse datasets and short…
This study focuses on the novel municipal-scale rural integrated energy system (RIES), which encompasses energy supply and application. By constructing a seven-dimensional evaluation system including energy efficiency, energy supply,…