Accurate electricity consumption forecasting is essential for effective power management, especially in the presence of unpredictable events that disrupt typical consumption patterns. Using the COVID-19 pandemic as a case study for such unpredictable events, this study proposes an improved hybrid LSTM-XGBoost model with adapted wavelets to capture complex, irregular fluctuations in energy demand. The model first applies wavelet decomposition to the original data, extracting multiple frequency components that highlight short-term variations and long-term trends. By incorporating these wavelet coefficients as features, the model is sensitized to anomalous events, resulting in more accurate forecasts over a more extended period without the need for frequent retraining. The hybrid approach takes advantage of the LSTM’s ability to model temporal sequences and uses XGBoost to adjust for residual errors. Experimental results show that the model can effectively forecast energy demand with minimal error, especially on regular weekdays, and achieves robust performance in the face of unforeseen anomalies. This methodology shows a promising aspect for improving the reliability of energy forecasting models with potential applications in smart grid management and sustainable energy planning.

Maximum power point trackers (MPPTs) play an essential role in extracting power from photovoltaic (PV) panels as they make the solar panels to operate at the maximum power point (MPP) whatever the changes of environmental conditions are. For this reason, they take an important place in the increase of PV system efficiency. MPPTs are driven by MPPT algorithms and a number of MPPT algorithms are proposed in the literature. The comparison of the MPPT algorithms in literature are made by a sun simulator based test system under laboratory conditions for short durations. However, in this study, the performances of four most commonly used MPPT algorithms are compared under real environmental conditions for longer periods. A dual identical experimental setup is designed to make a comparison between two the considered MPPT algorithms as synchronized. As a result of this study, the ranking among these algorithms are presented and the results show that Incremental Conductance (IC) algorithm gives the best performance

In industrial electromechanical manufacturing, ensuring the accuracy of electrical partial discharge measurements is crucial for the reliability and efficiency of electrical power systems. The cornerstone of such precision is a well-designed partial discharge calibrator that strictly aligns with the IEC 60270 standard parameters, including apparent charge, rise time, and pulse repetition frequency. This research delineates the systematic development and subsequent performance evaluations of an innovative industrial partial discharge calibrator. The calibrator uniquely integrates advanced functionality while maintaining cost efficiency, offering an alternative to the current partial discharge calibrator market. Its design allows for a broad spectrum of pulse frequency adjustments, making it adaptable to various apparent charge bandwidths and highlighting its adaptability for high-voltage applications. Building upon the foundational understanding of partial discharge as characterized by standards such as IEC 60270, the study underscores the calibrator’s capacity to elevate the standards of partial discharge measurements within high-voltage equipment.

Ice load on transmission lines is a critical factor that affects their cost and operation. National standards specify how ice load is considered in the design of power lines and poles. These standards generally use empirical relations that assume that the ice load on each phase accumulates uniformly and cylindrically. However, field tests and fault records show that the actual ice load on conductors is often not cylindrical due to altitude, wind strength and direction, and terrain topography. This study firstly defines several parameters to describe asymmetrical ice load. This load can cause additional vertical force on the line, conductor swing angle deviation, and sag changes. Since empirical equations are only valid for cylindrical ice load, the cross-sectional shape of the conductor must be transferred to millimeter paper, and calculations performed using one of several numerical integral methods. The coefficients for asymmetric ice are calculated in kg⁄m (N⁄m) using an AutoCAD model in the numerical study.

LEDs are used in many areas today. Street lighting is one of them and high-power LEDs are utilized in this area. Electrical energy is converted into light with an efficiency in 10-25% range. The rest is converted into heat. The generated heat is largely caused from LED chip. Furthermore, Driver circuit would also causes heat rise. Removing of this heat from the system is important in order to LED system efficiency because increasing of temperature causes a reduction of luminous flux. Excellent thermal management plays a significant role in terms of efficiency, reliability and durability. In this study, losses are caused from the LED chip and the heat sink which are part of the LED lighting systems are examined. These elements are thermally analyzed. The impacts of these losses on efficiency will be presented.