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 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.
SUMMARY The electrical circuit breaker (CB) is one of the absolutely essential devices in the electrical power system. The evaluation of CB condition and its reliability gain on importance. The contact wear of the CB monitored by Intelligent Electronic Device plays a crucial role in the condition‐based maintenance (CBM). The present contact wear maintenance of the CB is based on the maintenance data provided by original manufacturers to compute the value of the accumulated contact wear. However, the evaluation of the contact wear always has a quite error. It may lead to over‐maintenance or under‐maintenance commonly found in maintenance planning and scheduling. Little literature has been down on the issue. By utilizing the modified hybrid Nelder–Mead simplex search and particle swarm optimization (PSO) algorithm, the paper proposes a curve‐fitting technology to obtain an optimal contact wear equation for realizing the CBM of the CBs. The presented optimal contact wear equation minimizes the sum of squared errors that can be programmed in Intelligent Electronic Device. An effective CBM planning can enhance electricity substation reliability and cut maintenance costs. Compared with the conventional Nelder–Mead simplex search and PSO and PSO algorithms, two case studies are given to verify the effectiveness of the proposed method. The work may provide some valuable references for the related workers and researchers. Copyright © 2015 John Wiley & Sons, Ltd.
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