Electrical load forecasting is crucial to achieving better efficiency, reliability, and power quality in modern power systems. Applying short‐term load forecasting, a balance can be preserved between supply and demand; the cost of electricity production will also be decreased. Several methods are proposed for short‐term load forecasting in smart grids in recent years and each of them has its own advantages and weaknesses. Among these methods, popularity is increasing in machine learning techniques. This study is to review three common artificial intelligence load forecasting methods, including long short‐term memory, group method of data handling, and adaptive neuro‐fuzzy inference system that have been used to forecast load in a smart grid consisting of a photovoltaic, wind turbine, battery energy storage system, and electric vehicle charging stations. The performance of these methods is evaluated given accuracy and the system's hardware requirements. The noisy condition of the system is also investigated when these methods are used for load forecasting. The results show that the long short‐term memory model is more accurate than the group method of data handling and adaptive neuro‐fuzzy inference system models. However, this method requires much better hardware requirements.

Except in trivial cases, an unknown angle is always extracted from a knowledge of its sine and cosine. These two numbers determine the angle unambiguously; and yet no universally accepted notation expresses that angle as a function of those numbers in a single statement. Some authors use “atan2” for this purpose. I argue that this name is not appropriate, and its description as a “four‐quadrant inverse tangent” is misleading. I propose two interchangeable names “” as candidates for the sought‐after function.

To understand the influences of beam height and side‐to‐midspan ratio on the mechanical characteristics of straddle monorail large‐span continuous steel truss rail beams, the first phase of Wuhu Rail Transit Line 2, a section of continuous steel truss rail beams, is taken as the engineering background. The specific numerical values of the beam heights and side‐to‐midspan ratios of some large‐span bridges, which have been built in China and abroad, are analyzed and counted. Combined with the unique characteristics of continuous steel truss rail beams, the two design variables of side‐to‐midspan ratio and beam height are scientifically valued. The two‐variable direct grid search method is used, and the finite element software Midas Civil is employed to calculate and analyze the mechanical properties of the selected structural system. The main beam deflection, vertical fundamental frequency, beam end corner, and six other aspects are taken as the research focus of the optimization analysis. The above six aspects coordinate bridge strength, stiffness, and stability. They also consider comprehensively and enhance the scientificity of the results. Data indicate that when the side‐to‐midspan ratio and beam height are small, it is beneficial to the structural stress and deformation. However, to prevent the occurrence of the reaction force of the support, the side‐to‐midspan ratio should be greater than 0.2; when the beam height is constant, the ratio increases from 0.56 to 0.74, and the safety factor increases by about 14%. The side‐to‐midspan ratio of 0.56 and the beam height of 1.86 m are the recommended solutions. The scheme features reasonable structural stress and deformation, material saving, and low cost.

The measurement quality of a software defined radio system was investigated and discussed for medical diagnostics in the frequency band of interest 500 MHz–2 GHz. A calibration approach was proposed in order to deal with the random phase problem, and the obtained performance was evaluated and benchmarked against a vector network analyser. The results suggest that the measurement quality of the software defined radio system is mainly limited by the signal leakage from the transmitter to the receiver. Good agreement between the measurement data obtained with the software defined ratio system and the network analyser was achieved when the transmission loss is less than 70 dB. With some a priori knowledge of the measured object, the software defined radio system is able to perform accurate measurement when the transmission loss is even higher.

Here, a novel control technique for Five‐Phase Induction Motor (FPIM) drives using a field‐programmable gate array (FPGA) controller is proposed. Open‐loop control is analysed in terms of the performance and measurement of various power quality factors, such as voltage harmonics, current harmonics, total harmonic distortion, crest factor, unbalanced, short and long‐term flickering, K‐factor, real power, reactive power, apparent power, and power factor. This study experimentally demonstrated a closed‐loop system with both PID and DTC controls for the FPIM. Diminished torque pulsation is obtained by efficiently utilizing the voltage vectors from the total states of 2⁵ = 32. A novel EG voltage vector sequence was proposed for DTC techniques and compared with small, medium, and large voltage vector sequences. Proposed innovative control programming techniques in spartan‐6 XC6SLX25 series FPGA for switching the five‐phase two‐level inverter to reduce the total harmonics distortion by less than 2%.