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This paper presents a new photovoltaic (PV) power systems laboratory module that was developed to experimentally reinforce students' understanding of design principles, operation, and control of photovoltaic power conversion systems. The laboratory module is project-based and is designed to support a renewable energy course. By using MATLAB real-time software tools in combination with digital signal processor (DSP) hardware tools, the module enables students to: 1) design and build dc-dc and dc-ac power converters; 2) design and implement control algorithms for maximum power point tracking (MPPT) and voltage and current regulation; and 3) design and fabricate a printed circuit board for voltage and current sensing, isolation, and gate driving. In these hands-on experiments, by designing and building their hardware and software integrated systems themselves, students learn by doing and experience the engineering transformative process of building a product out of an idea. This paper is motivated by the dearth of literature on the application of project-based learning methodology to PV systems. The module description, the pedagogical and evaluation methodologies adopted, and reflections on the implementations are discussed.

This paper proposes a hierarchical multi-stage approach based on a distributed level phasor measurement unit (µPMU) at local controllers and a phasor data concentrator (PDC) at the central control unit to restore system voltage when it exceeds the limits recommended by the IEEE 1547-2018 standard. The proposed algorithm does not need an accurate system model or employ optimization solutions. Therefore, it has less implementation complexity and would be popular among distribution network service providers (DNSPs) and distribution network operators (DNOs) as it does not suffer from cost and computational complexity limitations. A PMU-PDC-based communication platform has been developed as a more efficient alternative to the supervisory control and data acquisition (SCADA) system, and provides superior characteristics, including a higher sample rate, higher data resolutions, and faster communication. The proposed coordinated algorithm aims to postpone power generation curtailment in distributed energy resources (DERs) with overvoltage problems (local DERs) by incorporating all the DERs that are not subjected to voltage violation (remote DERs) by absorbing their maximum reactive power capacity. If the system voltage has not recovered after absorbing all of the reactive power capacity of all the DERs, a reduced active power curtailment proposed by the algorithm is then applied to the system to control the voltage. The proposed strategy has been simulated in MATLAB and applied to IEEE 13-bus and IEEE 33-bus radial distribution benchmark systems to validate the performance of the system, in terms of its ability to coordinate voltage control and the accuracy of the PMU-PDC-based communication interface. [ABSTRACT FROM AUTHOR]

This paper presents a new technique for automatic monitoring of power quality events, which is based on the multi-resolution S-transform and Parseval's theorem. In the proposed technique, the S-transform is used to produce instantaneous frequency vectors of the signals, and then the energies of these vectors, based on the Parseval's theorem, are utilized for automatically monitoring and classification of power quality events. The advantage of the proposed algorithm is its ability to distinguish different power quality classes easily. In addition, the magnitude, duration, and frequency content of the disturbances can be accurately identified in order to characterize the disturbances. The paper provides the theoretical background of the technique and presents a wide range of analyses to demonstrate its effectiveness. Index Terms--Automatic classification, Parseval's theorem, power quality monitoring, S-transform.

There is a need to analyze power-quality (PQ) signals and to extract their distinctive features to take preventative actions in power systems. This paper offers an effective solution to automatically classify PQ signals using Hilbert and Clarke Transforms as new feature extraction techniques. Both techniques accommodate Nearest Neighbor Technique for automatic recognition of PQ events. The Hilbert transform is introduced as single-phase monitoring technique, while with the Clarke Transformation all the three-phases can be monitored simultaneously. The performance of each technique is compared with the most recent techniques (S-Transform and Wavelet Transform) using an extensive number of simulated PQ events that are divided into nine classes. In addition, the paper investigates the optimum selection of number of neighbors to minimize the classification errors in Nearest Neighbor Technique. Index Terms--Automatic recognition, Clarke transformation, Hilbert transform, power quality (PQ), S-transform, wavelet transform.

This paper proposes an enhanced control scheme for a direct drive variable speed wind turbine with an interior permanent magnet (IPM) synchronous generator. The proposed control scheme incorporates maximum torque per ampere (MTPA) trajectory and maximum power extraction, which ensures the generation of required torque for maximum power extraction with minimum stator current. This in turn minimizes stator copper loss and excessive heat generated in the IPM synchronous generator. The performance of the proposed control scheme has been validated through rigours simulation and experimental studies under varying wind speed conditions. The simulation and experimental results demonstrate the efficacy of the proposed control method. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents simple methods of determining parameters of interior permanent magnet (IPM) synchronous generator such as magnet flux ( λM), d-axis inductance ( Ld) and q-axis inductance ( Lq) of IPM synchronous generator, which are used to control the wind turbine generator. These methods are simple and do not require any complex theory, signal injection or special equipment. Moreover, a sensorless speed estimator is proposed to estimate the speed of the generator without using speed sensor. The measured parameters are used in this speed estimator. The elimination of speed sensor will enhance the system robustness and reduce the design complexity and system cost for a small-scale wind turbine considered in this paper. The effectiveness of parameter measurement methods and sensorless speed estimator is demonstrated by experimental results. Experimental results show that the proposed speed estimator that uses the measured parameters can estimate the generator speed with a small error. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents a new photovoltaic (PV) power systems laboratory module that was developed to experimentally reinforce students' understanding of design principles, operation, and control of photovoltaic power conversion systems. The laboratory module is project-based and is designed to support a renewable energy course. By using MATLAB real-time software tools in combination with digital signal processor (DSP) hardware tools, the module enables students to: 1) design and build dc–dc and dc–ac power converters; 2) design and implement control algorithms for maximum power point tracking (MPPT) and voltage and current regulation; and 3) design and fabricate a printed circuit board for voltage and current sensing, isolation, and gate driving. In these hands-on experiments, by designing and building their hardware and software integrated systems themselves, students learn by doing and experience the engineering transformative process of building a product out of an idea. This paper is motivated by the dearth of literature on the application of project-based learning methodology to PV systems. The module description, the pedagogical and evaluation methodologies adopted, and reflections on the implementations are discussed. [ABSTRACT FROM PUBLISHER]