Current Signal Transduction Therapy - Volume 13, Issue 1, 2018

Background: Economic Load Dispatch (ELD) is the process of applying necessary load demand between generators in power system that satisfies all units, so as to decrease the cost of operation. In order to solve the ELD problem, meta-heuristic algorithms are preferred. The combination of Fire Fly (FF) algorithm and Genetic Algorithm (GA) is used in this research to solve the ELD problem and optimize the wind energy output. Methods: The wind turbine rotates by the force of the wind from nature. The optimum values of the input parameters of wind turbine such as Cp, λ are predicted using Genetic Algorithm. Thus, the wind turbine output is optimized. The output of the generator is optimized by the MPPT methods in practice. The MPPT method deployed here is Incremental Conductance method. The wind energy output is AC in nature. It is converted to DC using rectifier action. Then the boost converter further boosts the output value. The inverter action converts the DC into AC and fed to grid. The fuel operating cost of the wind energy system is reduced by means of the FFA thus solves the ELD problem. The wind energy system with optimized power to grid is implemented using MATLAB SIMULINK tool and ELD is solved and executed by means of MATLAB coding. Results: The input parameters of wind turbine such as Cp and λ values are predicted by means of genetic algorithm, in order to obtain optimal output from the turbine. The power coefficients (CP) and tip speed λ value of the wind turbine are found out, thus the wind turbine output is optimized. The generator output is optimized by MPPT technique. Conclusion: By adopting Genetic Algorithm the input parameter value required for wind turbine is predicted. The economic load dispatch problem is solved and cost function is minimized by deploying Firefly algorithm. The wind power output is optimized by hybrid GA-FFA and the optimized power is fed to grid thus enhancing grid efficiency. The results obtained were tested using MATLAB/SIMULINK platform.

In this work the maximum power point tracking of solar photovoltaic panels that are operating in the same area for a common load but subjected to an unequal solar insolation levels. It is proposed that a separate DC to DC converter is used for each of the panels. Sliding mode controller is adopted for the MPPT. The MATLAB SIMULINK simulation and the experimental verification validates that the proposed idea harvests more power than the common optimised duty cycle that is used in a single power converter. Methods: In the existing scheme where a number of panel are operating in parallel a common DC to DC converter is used. For the purpose of MPPT and optimisation technique is used to arrive at the duty cycle to be adopted in the common DC to DC converter. Such a method guarantees the overall maximum possible power output for that particular method using a single DC to DC converter with a single duty cycle. It does not guarantee the maximisation of the power output of the individual solar PV panels which is the actual maximum power harvestable for the given environmental condition. In the proposed technique, applicable to solar trees where a number of panels are physically arranged in different angles so as to harvest maximum power all through the day, it is more effective to use individual dc to dc converters with individual duty cycles. In this work the sliding mode control based on the PV terminal voltage is adopted. Results: The proposed idea is simple, no rigorous mathematical implications, requires less number of sensors, and requires no explicitly PWM circuits. It can be used readily in real life applications.

In this paper, stability and performance analysis of Adaptive Neuro-Fuzzy Inference System (ANFIS) tuned Proportional Integral Derivative (PID) speed controller has been presented for Brushless DC motor. The stability of the proposed controller is examined using Lyapunov and Nyquist stability criterion. The performance of the proposed controller is analyzed for a step change in speed input and sudden load disturbance conditions and also compared with fuzzy PID, super twisting sliding mode control, and PID controllers. Sensitivity of the proposed controller is analyzed with parameter variation in inertia, permanent magnet flux, resistance and inductance of the motor. From the results, it is evident that the proposed controller is more stable and outperforms the other considered controllers in all performance aspects.

Background: The Cuk converter is used to control DC link voltage between the PV and VSI. The CCM is implemented in Cuk converter to control the DC bus voltage and this helps to minimize the losses in DC-DC converter. Methods: The speed of the BLDC motor is controlled by voltage source inverter with PWM control. The PWM pulse is generated by using Hall Effect sensor. Results: The PWM switching of BLDC motor provides reduced switching losses and increasing the efficiency. Conclusions: The prototype model of this circuit also developed and its performance characteristics also verified. The switching losses are reduced by using Cuk converter. The VSI also reduced the switching losses by operation in 120 degree conduction mode. The speed of the BLDC motor is effectively controlled by hall signals.

Background: The industrial wireless automation system enables the monitoring and control of processes. It may be difficult to recharge the battery of sensors installed in harmful environments. Hence optimization of the power is the major issue to be addressed while implementing the network. The proposed hybrid data transmission approaches optimize data accuracy and energy efficiency of a wireless sensor node deployed in any industry. Methods: In the time-driven method, the sensor nodes periodically sense the environment and transmit the data continuously over time. In the event-driven method, the sensor nodes transmit data only when there is a drastic change in the occurrence of a certain event. Results: Based on the nature of the process, applications are classified as, less critical, critical and most critical. The time-driven based hybrid transmission approach is suggested for the most critical applications because they need to be monitored continuously so as to attain data accuracy. In the case of critical applications, the data is not required to be sent continuously, but instead it can be sampled and transmitted once in two seconds. Though the above suggested methods intended to provide better outcomes in terms of power utilization, in the case of process control applications, most critical and critical applications need to be monitored continuously. Hence such applications could be done as a heterogeneous industrial automation network, which is the combination of wired and wireless connectivity. This can be implemented by replacing all the signal cables with wireless communication system, regular power supply must be provided for the radio module attached with final control elements and also to the transmitters involved in most critical applications. For the least critical applications, the data can be sampled and transmitted once in four seconds. Conclusion: Simulation has been performed for time-driven based and duty-cycling based hybrid transmission approaches. The results can guide process engineers in selecting the transmission approach for optimizing the power of IWAS based on the critical level of the process. In the case of a critical process, the time-driven based hybrid transmission approach may be used, and in the case of a less critical process, the duty-cycling based hybrid transmission approach could be selected. By selecting appropriate transmission approach the life time of IWAS could be improved.

Background: The whole thought is to demonstrate the parallel parking framework for self-ruling robots with the help of real-time embedded boards. Autonomous systems are outlined and developed by considering the non-holonomic requirements. PID controller is used to accomplish the servo reaction. The path planning scheme is created for parallel stopping of selfruling vehicles by gaining data from the sensor. Methods: The three vital stages engaged in safety parking are scanning, positioning and maneuvering. The scanning stage filters the stopping condition by ultrasonic separation estimating sensors. The positioning stage advances the vehicle and in reverse. It is mostly used to alter the appropriate separation from the begin point to turn point before moving. The parallel stopping of self-ruling robots with non-holonomic requirements are mimicked through MATLAB environment and prototype implementation is carried out through embedded platform. Results: Initially, open loop response of the non-holonomic vehicle is unstable and nonlinear in nature. Therefore the PID controller is used to control the response of the non-holonomic vehicle with minimum error based on the set point. The goal of this research is to attain the parallel parking scheme for non-holonomic vehicles, which is attained with the help of real time implementation. This implementation has been carried out using embedded processor with PID algorithm, sensors and actuators. Conclusion: Hence the paper depicts the structure of non-holonomic robotic vehicle and control with the help of PID controller. The parallel parking scheme has established using MATLAB programming and verified with the help of real time prototype. The paper proposed an idea of automated parking system in contrast to manual parking by the driver. The consumption of space, energy and time are minimized due to the automated parking scheme. Due to human error and negligence, harms such as collisions and accidents are occurred. These harms are reduced by implementing the parallel parking scheme in an intelligent manner. In future, Fuzzy based PD controller will be developed and implemented for the enhancement of parallel parking algorithm in robots.

Background: Distributed Generation (DG) is facing a rapid development as a new means of power generation. DG is affecting the power quality of the system due to uncertainty condition and fault. Artificial Neuro Fuzzy Inference System (ANFIS) based DVR controller is planned to regulate the voltage at the Point of Common Coupling (PCC) within the limits and stabilize the operation of the system in the event of disturbances. The simulated results reveal that ANFIS based control scheme shows better performance compared to traditional controller. Methods: This system analysis the performance of dq0 based Proportional Integral and Adaptive Neuro Fuzzy Inference System controllers with DVR, which incorporates a solar system as a DC voltage source. Incremental Conductance MPPT Algorithm method tracks the maximum power point of solar system. An ANFIS based DVR controller method is implemented for the maximum injected voltage, ANFIS based on Takagi Sugeno Fuzzy inference System (FIS) is introduced. The generated fuzzy rules can be trained by using neural network and attain desired output. So as to mitigate the voltage sags /swells condition in the test system. Results: It is observed from the results, ANFIS based DVR controller can compensate the load voltage is kept at a constant value and to maintain the stable operation of DG systems under, voltage sag/swell and fault conditions, further harmonic voltage is compensated and the voltage is made sinusoidal. Conclusions: ANFIS based DVR conditioner has better dynamic response and Total Harmonic Distortion is less compared with conventional controller.

In this paper grid connected Solar/Wind/Diesel generator powered Electric Vehicle (EV) charging station with Vehicle to Grid (V2G) is designed. Solar/Wind/Diesel generator powered charging station consists of a Photovoltaic array and Wind Energy system, three unidirectional converters, Maximum Power Point Tracker(MPPT), Raspberry Pi controller, 20 Bidirectional DC/DC converter associated with 20 Electric Vehicle charging station. Three phase bidirectional DC/AC (Direct Current/Alternating Current) converter is connected to the grid. The main contribution of this work is to design EV charging station, in addition to charging priority set with respect to State of Charge (SOC) level of EV's battery. If the availability of Solar/Wind power is sufficient to charge the connected EV's, then they are charged with Solar/Wind. If the demand is increased, power is extracted from the Diesel at peak load time and from the grid at base load time. Once the vehicle is plugged in charging station the customer can either buy or sell the power. If buy option is opted for, the priority of charging EVs battery is set in the ascending order of the battery's SOC level. As a result, Energy Management is effectively done and every customer can be satisfied. If sell option is opted for, the power is extracted from the vehicles to the grid, based on customers willingness of selling power. All control functions are done by Raspberry Pi controller. The whole process is monitored and controlled by using Internet of Things (IoT). Simulation is done through the MATLAB /SIMULINK and thus the results give good performance of the proposed method.

Background: Globally, an energy efficient electric drive is a vital role in the industrial application. Since, an industry has a number of electrical motors which are consuming significant energy. Hence, several researchers are motivated to search for energy efficient electrical motor. The Switched Reluctance Motor (SRM) is the energy efficient motor that of other. Meanwhile, SRM has rugged structure, inherent fault tolerance characteristics and cost-effective that of synchronous and induction machines. However, the usage of such a motor is limited due to torque ripples, friction and windage losses, acoustic noise and power losses due to control circuit. Methods: This research work, proposed a novel designed SRM which is achieved by optimizing stator and rotor pole arc. The stator pole arc is modified from 32° to 36° and the 30° to 28° for rotor pole arc, respectively. Furthermore, stator coil excitation is depending on the control circuit, it have switches. This switch is causes significant power loss and so power quality issues are ascended. Henceforth, the paper proposed a new novel control circuit made by single transistor. After that, SRM's, non- linear modelling was executed using a fuzzy logic technique. After that, SRM's, non- linear modelling was executed using a fuzzy logic technique. Results: From the experimental validation found that, pole arc modification significantly increased efficiency of SRM as well as reduced the torque ripples. Likewise, Fuzzy approach enhances the experimental study. Conclusions: Based on the experiment analysis, the efficiency of pole arc modified switched reluctance motor is significantly increased that of others. Moreover, the fuzzy logic approach is reduced energy losses thus is has good correlation with experimental analysis. This work can be easily applied to SRMs for reducing the power consumption and hence achieving high efficiency.

Background: Allergic diseases, such as atopic dermatitis and allergic asthma, are associated with increased inflammation and interleukin-4 (IL-4) signaling. An inhibitor of the IL-4 receptor, dupimulab, was approved recently for dermatitis. This goal of this review is to elucidate the mechanism and effects of IL-4 signaling. Methods: We reviewed information available in immunology and molecular biology textbooks, and research and review articles to accomplish our goal. Results: The increased inflammation, in allergic diseases, is due to inflammatory cytokines released from innate leukocytes and local tissue. The increased IL-4 signaling activates the helper Th2 cells to release IL-4, and the allergic effects. The IL-4 binds to its receptors to activate JAK1/JAK3 mediated nuclear translocation of the phosphorylated STAT6 dimer, which stimulates the expression of IgE antibodies in B-cells. The released IgE stimulates the release of histamines from mast cells, alters the expression of genes associated with fibrosis, and induces apoptosis of epidermal or epithelial cells. The resultant IL-4 effects in allergic diseases include pruritus or wheezing, fibrosis and/or altered expression of extracellular matrix proteins, and loss of epidermal or epithelial barrier function. Conclusion: The specific inhibition of the Il-4 signaling, through dupimulab that binds the IL-4 α receptor subunit, would be effective in the specific inhibition of the allergic response in patients with allergic dermatitis or asthma.