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In modern era, one of the rising power quality (PQ) concern is harmonics distortion (HD). The HD is usually produced by increase in the utilization of nonlinear user loads at domestic level. It not only spoils the PQ but also have harmful effects on electrical appliances. So, this paper presents a new approach to mitigate the HD in home appliances rapidly by utilizing the active band pass filter (ABPF). The fast Fourier transform (FFT) technique is employed for the detection of harmonics in appliances. The band pass filter dramatically affects the response time of active filter. The suggested control methodology is capable to eliminate harmonics from distorted input voltage waveform and provides a pure sinusoidal waveform. The prototype of this model is also implemented. Experimental results along with simulation show that the proposed model is quite effective in eliminating HD despite load variations and also useful to compensate the reactive power in electronic home appliances. Hence, this technique is cost effective for domestic users with high quality performance in all aspects.

The prediction and forecasting of faults occurring in photovoltaic (PV) system is one of the important aspect to escalate the reliability, output power generation, proficiency, lifetime and effectiveness of overall system. In this article, the behavior of PV array is studied under various faulty circumstances and new approach has offered for the better performance assessment of PV array. This approach is established on the analysis of peculiarities displayed by voltage power (V-P) and voltage-current (V-I) characteristics curves of PV array under different faulty conditions. The proposed technique can be used to identify and classify the five common faults in PV system. These progressive faults (includes open circuit, line-to-line, partial shading, degradation and bridging faults) have been occurred at the basic components of PV cell and at the connection point between PV modules. The characteristic curves under normal and faulty conditions have been compared by utilizing Matlab/Simulink environment. Hence, the suggested method can be utilized to determine the important fact about the health PV array.

In this modern era, technology has advanced to such an extent to make our daily life more proficient and convenient. This paper presents the design and implementation of vending machine (VM) for students, which operates on radio frequency identification technology (RFID). Hence, it turns the VM into smart shopping booth (SSB). The SSB gives the access only through RFID card and vend different products according to the desire of student. The SSB is equipped with RFID reader and student identity card that holds the RFID tag. When the student identity card is scanned for verification and then after selecting the required products, will be dispensed off if a student has available balance in his/her identity card and SMS will be sent to students about remaining balance in their cards by GSM technology. The programming for controller is done by using proton IDE language. The SSB is the customized idea of vending machine and it attempts to resolve various issues that appeared in coin/note based VM. The student identity card RFID based technology is a breakthrough towards a paperless and cashless environment. Moreover, it is very beneficial in saving the precious time of students due to fast paced life and also user friendly. RFID based SSB also improved the communication and sensing capabilities of VM. Hence, our suggested approach outperforms in all aspects.

Partial shading condition (PSC) is the most serious concern of a photovoltaic (PV) system as it pointedly decreases the proficiency of PV system. The PV system generates numerous peaks in its output power characteristics curve under PSC. To track a global maximum power point (GMPP) with-in a suitable time limit, a consistent method is thus required. For achieving high performance, enhanced convergence and less power fluctuations during cloudy sky, conventional PSO is altered. The main objective of this paper is to identify the maximum power point (MPP) by utilizing an improved particle swarm optimization (IPSO) under PSC. To authenticate the proficiency of the proposed algorithm under diverse PSC, analysis between two commonly employed conventional PSO and Improved PSO MPPT techniques is made through theoretical analysis and digital simulation by using Matlab/Simulink. The obtained simulation result shows the fast tracking speed, extraordinary consistency and high exactness in tracing the GMPP.

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