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This work describes a number of soft-computing based solar forecasting techniques that facilitate the modelling of newly installed solar cell. The solar cell model is developed and validated against measured data. Prediction of solar radiation of a particular location depends upon number of inputs. So selection of most relevant input parameters is an important task for getting good predictions. The input parameters of the model used in this paper are sunshine duration, temperature, humidity where as the clearness index is considered as an output parameter. The magnitude of active current associated with PV inverter has been finalised by the solar based irradiation. The reactive current associated with the PV based inverter is controlled through the optimised solar radiation.

This paper presents wavelet transform, independent component based detection of the power quality disturbances in a microgrid. Wavelet transform (WT) is well known for its better time-frequency multi-resolution analysis because of selection of adaptive window size depending inversely with the frequency. This makes it suitable for identification of both stationary and non-stationary characteristics of the power quality disturbances. But, it is analyzed in the study that the detection capability of wavelet is degraded when the input voltage signal contains noise and completely fails when the noise level is increased to 25 dB. Of course, a wavelet-denoising technique is tested to improve the ability of wavelet transform under noisy conditions, but observed to increase the detection time. Hence, independent component analysis (ICA) is proposed for detection based on its property of finding the significant components which are statistically independent and non-Gaussian. In addition, the statistical features are extracted to formulate the input dataset for support vector machine (SVM) to classify different power quality disturbances like sag, swell, interruptions, harmonics, transients, and flickering. A comparative analysis is presented and it is observed from the study that ICA-SVM hybrid combination provides better classification accuracy as comparison to WT-SVM under different operating scenarios.

This work discusses the implementation of JAYA-DE algorithm with Static Var Compensator for optimum voltage control through Reactive Power compensation inside solar based hybrid power system.The stability aspect of isolated solar based hybrid power system is enhanced through compensation of the reactive power by optimized SVC and are further analyzed with different stability criterion. The dynamic performance of the new hybrid technique under intermittent wind power input and variable load show superiority over the conventional control methods.

In this paper, the simulation results of static var compensator (SVC) for improvement of transient stability in a photo voltaic (PV) system integrated power system are presented. A Proportional Integral Derivative (PID) controller was also incorporated with SVC for contributing necessary damping in case of various disturbance conditions. Here, the dynamic stability of the PV based power system was studied in single machine infinite bus (SMIB) and power system. SVC is integrated with the above PV based power system for damping low frequency oscillations produced due to disturbances in the power system. Further a novel soft computing based approach called quasi-oppositional differential search algorithm (QODSA) was for designing an optimal SVC-PID based damping controller. Initially DSA was applied for optimizing the gains of the controller and finally quasi oppositional learning was incorporated to DSA for obtaining the optimal parameters of SVC-PID controller and also for enhancing the convergence speed. The effectiveness of the proposed technique was also tested with particle swarm optimization (PSO) technique. Transient stability analysis for conventional PID controller, PSO based PID controller, DSA based PID controller and QDSA based PID controller was done analytically as well as quantitatively. It can be observed from the simulation results that the proposed QDSA based PID controller outperforms over other techniques in improving power system stability and also damping low frequency oscillations.

Solar photo voltaic cells are increasingly finding application in either grid connected power system or Standalone solar power system. PV cells are being used in combination with other renewable energy sources to form a distributed generation based hybrid power system. Though solar cell ideally contributes lot in hybrid power generation, uncertainty in solar insolation creates disturbances and power quality problem. Variable solar insolation, uncertain weather condition affects the Photo voltaic cell causing voltage disturbance, harmonics and other quality problems. Because of this Efficiency of solar cell is highly affected though harmonics remains low in comparison to conventional AC power supply in both load and source side. This paper analyses a practical set up of solar system in lab VIEW platform and investigates the effect of variable solar radiation on it.

Modified wavelet called wavelet packet transform (WPT) based approach is proposed in this paper for the detection of different disturbances occurring due to faults in grid-connected solar photovoltaic (SPV) power system. The detection performance of WPT is compared with that of wavelet transform under different operating scenarios. Further, performance indices such as energy and standard deviation (SD) are calculated to identify the faults from normal operating conditions. The qualitative and quantitative study suggests better detection performance of WPT over WT under different operating scenarios.