The dual threats of energy depletion and global warming place the development of methods for harnessing renewable energy resources at the center of public interest. Solar energy is one of the most promising renewable energy resources. Sun trackers can substantially improve the electricity production of a photovoltaic (PV) system. This paper proposes a novel design of a dual-axis solar tracking PV system which utilizes the feedback control theory along with a four-quadrant light dependent resistor (LDR) sensor and simple electronic circuits to provide robust system performance. The proposed system uses a unique dual-axis AC motor and a stand-alone PV inverter to accomplish solar tracking. The control implementation is a technical innovation that is a simple and effective design. In addition, a scaled-down laboratory prototype is constructed to verify the feasibility of the scheme. The effectiveness of the Sun tracker is confirmed experimentally. To conclude, the results of this study may serve as valuable references for future solar energy applications.

With the skyrocketing growth in global photovoltaic (PV) power capacity, fault detection of PV systems has gained prodigious importance in recent years. It has been known that in PV system the DC series arc fault is more difficult to be detected than parallel arc fault. With the proposed technologies of characteristic extraction, filtering and fault identification, a novel efficient detection algorithm protecting a PV system against DC series arc fault is proposed. The detection algorithm is realized on an arc fault detector (AFD) based on a cost-effective TMS320F28335 digital signal processor (DSP). To verify the feasibility and effectiveness of the proposed AFD, a relevant experiment PV system is conducted to compare with two commercial AFDs by various testing states. A great deal of empirical evidence shows that the detection performance of the proposed AFD outperforms the commercially available AFDs. The research may be of some reference value for similar work in the future.

High impedance faults(HIFs) often draw too little current to activate conventional overcurrent protection, making the detection of a HIF event a difficult task. A practical and implementable solution to HIF detection and location is presented. In the proposed methodology, wavelet transform used for extracting features of HIFs signals and neural network used for HIF detection are used to develop a novel HIF detector called enhanced FTU(feeder terminal unit). The designed enhanced FTU is a high-performance HIF detector that is the retrofitting of the ready-made FTU with an embedded digital signal processor(DSP) and a high-frequency current sensor. The enhanced FTU monitors the operation of distribution feeder system and sends a fault flag signal to Feeder Dispatch and Control Center(FDCC) when a HIF occurs. Based on the Feeder Automation(FA) mechanism, the HIF detection, isolation, and service restoration(FDIR) can be activated. Consequently, the power reliability can be significantly improved by reducing the outage area and repair time. The validation of the presented technique was evaluated through staged fault testing. Compared with the existing related research, the proposed enhanced FTU is available and feasible.

With the advance of science and technology, people have a desire for convenient and comfortable living. Creating comfortable and healthy indoor environments is a major consideration for designing smart homes. As handheld devices become increasingly powerful and ubiquitous, this paper proposes an innovative use of smart handheld devices (SHD), using MIT App Inventor and fuzzy control, to perform the real-time monitoring and smart control of the designed intelligent windowsill system (IWS) in a smart home. A compact weather station that consists of environment sensors was constructed in the IWS for measuring of indoor illuminance, temperature-humidity, carbon dioxide (CO₂) concentration and outdoor rain and wind direction. According to the measured environment information, the proposed system can automatically send a command to a fuzzy microcontroller performed by Arduino UNO to fully or partly open the electric curtain and electric window for adapting to climate changes in the indoor and outdoor environment. Moreover, the IWS can automatically close windows for rain splashing on the window. The presented novel control method for the windowsill not only expands the SHD applications, but greatly enhances convenience to users. To validate the feasibility and effectiveness of the IWS, a laboratory prototype was built and confirmed experimentally.

Data acquisition and supervisory control are usually performed using client-server architecture and centralized control in conventional power systems. However, the message transmission and fault clearing are too slow for large-scale complex power systems. Microgrid systems have various types of distributed energy resources (DERs) which are quite different in characteristics and capacities, thus, the client-server architecture and centralized control are inadequate to control and operate in microgrids. Based on MATLAB/Simulink (ver.R2012a) simulation software and Java Agent Development Framework (JADE) (JADE 4.1.1-revision 6532), this paper proposes a novel fault protection technology that used multi-agent system (MAS) to perform fault detection, fault isolation and service restoration in microgrids. A new topology identification method using the YBus Matrix Algorithm is presented to successfully recognize the network configurations. The identification technology can respond to microgrid variations. Furthermore, the interactive communications among intelligent electronic devices (IEDs), circuit breakers (CBs), and agents are clarified during fault occurrence. The simulation results show that the proposed MAS-based microgrids can promptly isolate faults and protect the system against faults in real time.

Load-shedding is an effective control strategy to balance power generation and load demand, which is essential to maintain power system stability. Based on IEC 61850 protocols, this paper integrates a supervisory control and data acquisition (SCADA) platform and intelligent electronic devices (IEDs) to propose a new dynamic load-shedding (DLS) control strategy applied in a microgrid (MG) system. Once the power imbalances occur, the proposed DLS strategy calculates the appropriate amount of load shedding and determines the importance of each bus to prioritize loads. To evaluate the feasibility and applicability of the proposed DLS strategy, this work applies to a specific MG, which is located in Penghu, Taiwan, and compares the existing conventional under-frequency relay protections. Validation is performed by the Power System Simulator for Engineering (PSS/E) software simulations in three realistic scenarios. The use of artificial neural networks (ANNs) and metaheuristic algorithms to forecast power imbalances has been widely investigated recently. Readers require a strong background in mathematics to realize the principles. In contrast, the proposed protection strategy is easy to understand and implement without complicated algorithms but rather logical concepts. This is one of the significant contributions of the work.