Electricity is a vital resource for various human activities, supporting customers’ lifestyles in today’s modern technologically driven society. Effective demand-side management (DSM) can alleviate ever-increasing electricity demands that arise from customers in downstream sectors of a smart grid. Compared with the traditional means of energy management systems, non-intrusive appliance load monitoring (NIALM) monitors relevant electrical appliances in a non-intrusive manner. Fog (edge) computing addresses the need to capture, process and analyze data generated and gathered by Internet of Things (IoT) end devices, and is an advanced IoT paradigm for applications in which resources, such as computing capability, of a central data center acted as cloud computing are placed at the edge of the network. The literature leaves NIALM developed over fog-cloud computing and conducted as part of a home energy management system (HEMS). In this study, a Smart HEMS prototype based on Tridium’s Niagara Framework^® has been established over fog (edge)-cloud computing, where NIALM as an IoT application in energy management has also been investigated in the framework. The SHEMS prototype established over fog-cloud computing in this study utilizes an artificial neural network-based NIALM approach to non-intrusively monitor relevant electrical appliances without an intrusive deployment of plug-load power meters (smart plugs), where a two-stage NIALM approach is completed. The core entity of the SHEMS prototype is based on a compact, cognitive, embedded IoT controller that connects IoT end devices, such as sensors and meters, and serves as a gateway in a smart house/smart building for residential DSM. As demonstrated and reported in this study, the established SHEMS prototype using the investigated two-stage NIALM approach is feasible and usable.

This paper describes the design and implementation of three-level power converters for wind-driven permanent-magnet synchronous generators with unbalanced loads. To increase voltage stress and reduce current harmonics in the electrical power generated by a wind generator, a three-phase, three-level rectifier is used. Because a synchronous rotating frame is used on the AC-input side, the use of a neutral-point-clamped controller is proposed to increase the power factor to unity and reduce current harmonics. Furthermore, a novel six-leg inverter is proposed for transferring energy from the DC voltage to a three-phase, four-wire AC source with a constant voltage and a constant frequency. The power converters also contain output transformers and filters for power buffering and filtering, respectively. All three output phase voltages are fed back to control the inverter output during load variations. A digital signal processor is used as the core control device for implementing a 1.5 kV, 75 kW drive system. Experimental data show that the power factor is successfully increased to unity and the total current harmonic distortion is 3.2% on the AC-input side. The entire system can attain an efficiency of 91%, and the voltage error between the upper and lower capacitors is approximately zero. Experimental results that confirm the high performance of the proposed system are presented.

This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC‐link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low‐pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low‐pass filter and is more economical because of its short computation time compared with other types of adaptive filters.

An important challenge for modern data centers is to provide users with low-latency, high-quality, and interactive services. To improve effective application throughput, much work has been done to take into account application deadline in the design of the network flow schedule for transmission of the queried data. This raises a critical question: does application-level throughput necessarily translate to better quality of service for users? We note that queries responses typically include a set of semantically related documents (within a flow), and that while some documents are highly related to that query, others are not. This motivates us to consider the degree of a document's semantic relatedness in the design of an efficient data transmission scheme for data centers. To understand the performance upper bound, we derive a mixed integer linear programming (MILP) model for the above problem, which can be regarded as the schedule of a network subflow problem and is hence complicated. Thus, we propose the importance-aware transmission control protocol (ITCP), a distributed event-driven rate-based delivery control protocol, for server-centric data center networks. ITCP jointly considers the subflow importance, size, and deadline, as well as the characteristics of the underlying infrastructure to maximize the goodput of the most relevant responses of a query. The results of both real and synthetic data simulations show that ITCP outperforms recent works in terms of mean average precision of top $k$ data and the sum of application-level importance.

This study developed and implemented a driving power supply for light-emitting diode (LED) array streetlamps. The power stage was a quasi-resonant (QR)-flyback converter, its input power was the alternating-current power, and the LED array streetlamp was driven by the direct-current output power. The developed QR-flyback converter was operated in discontinuous conduction mode, and the pulse-width modulation (PWM) control chip was used to switch and conduct at the resonant valley of the drain-source voltage on the metal-oxide-semiconductor field-effect transistor (MOSFET) switch to reduce the switching loss. Moreover, the PWM control chip had a disable function, which was connected with a bright and extinguishable control circuit, and the high/low voltage level signal output by the Arduino development board can be used to control the output power of the QR-flyback converter, achieving bright and extinguishable controls for the LED array streetlamp.

This study analyzed the efficiency impact of a MOSFET output parasitic capacitance ($C_{oss}$) on a full-bridge LLC DC/DC converter. The core of the converter was the control chip for a half-bridge LLC DC/DC converter, and the output signal of the chip controlled the first-arm power transistors of the primary side of the converter. The coupling transformer reversed the output signal to control the primary side of the second arm of the power transistor. The full-bridge converter comprises a half-bridge control chip that converts the high-voltage DC power supply to a low-voltage DC power supply, which is then synchronously rectified and supplied to the load. The primary side of the power transistor achieves a zero-voltage switching (ZVS) state through the resonance of the LLC converter. This design gives the converter high power density and a simple structure. Furthermore, to determine the appropriate output parasitic capacitance for improving converter efficiency, this study analyzed the effect of the output parasitic capacitance on the switching loss and conduction loss of the power transistor on the basis of the output parasitic capacitance of the primary-side power transistor. A 1200 W converter prototype was fabricated in this study, and when the output was 300 W, efficiency increased from 92.603% to 93.462%, a 0.859% increase. The empirical results verified the feasibility of the proposed theory.