Reliability Assessment of Microgrid-Integrated Electrical Distribution System

Due to the transition of traditional power system to smart structure, integration of renewable energy sources is of great importance. It is performed by using distributed generators and Micro grid. Integration of renewable sources is very useful for the reliability enhancement of distribution system as energy can be supplied locally at distributed level. Therefore, this chapter provides an overview of various reliability methods which are utilized for finding the impact of renewable energy generation on distribution system reliability assessment. These renewable energy sources are integrated in the distribution system at distributed and Micro grid level. Various characteristics of renewable energy sources are discussed to model them. A general problem of reliability assessment in terms of reliability indices is also discussed.

A Thermoelastic Piezoelectric Fixed Rod Exposed to an Axial Moving Heat Source via a Dual-Phase-Lag Model

Piezoelectric ceramics are used more in the active control of noise and vibration with sensors and actuators. As a result, a one-dimensional homogeneous thermoelastic fixed piezoelectric rod subjected to a moving heat flow has been considered. The heating rod is affected by three fields, namely, thermal, mechanical, and electric potential. In order to design a reliable smart structure, this study is necessary and the thermopiezoelectric behavior of piezoelectric ceramics must be understood clearly. The Laplace transform method is applied to acquire the distributions of stress, deformation, and temperature fields. The effect of heat source velocity and phase lag parameters on the considered physical fields is displayed graphically, and the results are compared with other models of thermoelasticity. The present findings could find possible applications for designing receiving portions of transformers of Rosen type for voltage magnification.

Effects of Trailing Edge Deflections Driven by Shape Memory Alloy Actuators on the Transonic Aerodynamic Characteristics of a Super Critical Airfoil

A smart structure to actuate a morphing trailing edge based on the super critical airfoil NASA sc-0714(2) was designed and verified in a transonic wind tunnel. The pressure distribution over the wing was measured to evaluate the structure ability and effects of trailing edge deflections on the aerodynamic characteristics. In the experiment, Mach number was from 0.4 to 0.8, and the angle of attack was from 0° to 6°. The results showed that the smart structure based on shape memory alloy could carry aerodynamic loads under transonic flow and deflect the trailing edge. When the driving force was constant, deformation would be influenced by the Mach number and angle of attack. Increasing the Mach number weakened the actuation capability of the smart structure, which decreased the deflection angle and rate of the trailing edge. The influence of the angle of attack is more complex, and couples with the influence of the Mach number. The higher the Mach number, the stronger the influence of the angles of attack. Additionally, the trailing edge deflection would dramatically change the flow structure over the airfoil, such as the shock wave position and strength. If separation was caused by the trailing edge deflection, the limitation of the smart structure would be further found.

Electromechanical impedance based self-diagnosis of piezoelectric smart structure using principal component analysis and LibSVM

The long-term use of a piezoelectric smart structure make it difficult to judge whether the structure or piezoelectric lead zirconate titanate (PZT) is damaged when the signal changes. If the sensor fault occurs, the cases and degrees of the fault are unknown based on the electromechanical impedance method. Therefore, after the principal component analysis (PCA) of six characteristic indexes, a two-component solution that could explain 99.2% of the variance in the original indexes was obtained to judge whether the damage comes from the PZT. Then LibSVM was used to make an effective identification of four sensor faults (pseudo soldering, debonding, wear, and breakage) and their three damage degrees. The result shows that the identification accuracy of damaged PZT reached 97.5%. The absolute scores of PCA comprehensive evaluation for structural damages are less than 0.5 while for sensor faults are greater than 0.6. By comparing the scores of the samples under unknown conditions with the set threshold, whether the sensor faults occur is effectively judged; the intact and 12 possible damage states of PZT can be all classified correctly with the model trained by LibSVM. It is feasible to use LibSVM to classify the cases and degrees of sensor faults.

Flexible Smart Material With Excellent Energy Harvesting

The field of power harvesting has experienced significant growth over the past few years due to the ever-increasing desire to produce portable and wireless electronics with extended lifespans. The present work aims to introduce an approach to harvesting electrical energy from a mechanically excited piezoelectric element and investigates a power analytical model generated by a smart structure of type polyvinylidene fluoride(PVDF) that can be stuck onto fabrics and flexible substrates, although we report the effects of various substrates and investigates the sticking of these substrates on the characterization of the piezoelectric material.

Electromechanical Impedance Based Self-Diagnosis of Piezoelectric Smart Structure Using Principal Component Analysis and LibSVM

The long-term use of a piezoelectric smart structure make it difficult to judge whether the structure or piezoelectric lead zirconate titanate (PZT) is damaged when the signal changes. If the sensor fault occurs, the cases and degrees of the fault are unknown based on the electromechanical impedance method. Therefore, after the principal component analysis (PCA) of six characteristic indexes, a two-component solution which could explain 99.2% of the variance in the original indexes was obtained to judge whether the damage comes from the PZT. Then LibSVM was used to make an effective identification of four sensor faults (pseudo soldering, debonding, wear, and breakage) and their three damage degrees. The result shows that the identification accuracy of damaged PZT reached 97.5%. The absolute scores of PCA comprehensive evaluation for structural damages are less than 0.5 while for sensor faults are greater than 0.6. By comparing the scores of the samples under unknown conditions with the set threshold, whether the sensor faults occur is effectively judged; the intact and 12 possible damage states of PZT can be all classified correctly with the model trained by LibSVM. It is feasible to use LibSVM to classify the cases and degrees of sensor faults.

A Smart Structure for Environmental Sustainability in Rose Fields

Indian floriculture industry has grown by multiple folds in the past decade and has become one of the top ten leading producers of varieties of flower production. This tremendous growth of floriculture industry has proportionally also contributed to the depletion of environmental system. The current work narrows down to handle the environmental hazards of rose farming in the floriculture industry through technology-driven fertilization process. The composition and quantity of nutrients, and the period of its application is very crucial for the plant’s growth.The smart fertigation process helps in providing a balanced nutrient dose to the plants.The internet of things (IoT) is defined as a network of physical objects called as “things” that have embedded with sensors and software that allow these objects to communicate with each other. These objects areaccessed, monitored and controlled remotely. While the reduction of one of the nutrients might result in poor development of the plant, overfeeding of nutrients leads of stagnation of salts and soil wilting. The paper proposes a smart IoT-based fertilizer application infrastructure for an optimal growth of plants with under a controlled usage of fertilizers.The dependency of fertilizers and insecticides during each stage of the plant development is monitored and a smart fertigation infrastructure is built to automate the process of feeding the plants with appropriate chemicals at appropriate intervals.