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Due to their superior capabilities for manufacturing lightweight automotive components, aluminium metal matrix composites have gained a lot of attention in the last few years. Aluminium metal matrix composites are an exceptional class of metal matrix composites that can solve all the major problems related to the automobile industry. Aluminium matrix composites in the disc braking system have already been employed and studied by many scientists. However, the developed materials are not yet always sufficiently accurate and reliable. In this article, a new enhanced metal matrix composite material is used and studied to improve the efficiency of an ordinary car’s braking system. To improve the accuracy of the designated braking system, an innovative hybrid aluminium matrix composite (Al6061/SiC/Gr)-based brake rotor has been developed, and its effectiveness has been determined by finite element analysis. From the simulation, the product performance confirmed that the hybrid aluminium matrix composite (Al6061/SiC/Gr)-based brake rotor has the potential to replace the standard cast iron brake disc. The new enhanced hybrid composite material used in this study can be used for the efficient design of various braking parts.

The introduction of a new fishing technology in a small riverine village of Odisha resulted in paradoxical socio-economic outcomes. The fresh and flowing water pisciculture through the innovative Pen technology, which was based on an enclosure aquaculture system, bound from all sides by a close-knit row of multiple pens, improved productivity, income and employment levels of the fishing community. But the new technology also aggravated extant gender inequalities in the village, located on the banks of the river Mahanadi. The gendering of access to, control over and use of Pen culture in the fishing village of Naraj decided the winners and losers in this technological change. Systematic social closure and institutional bias not only ensured the exclusion of fisherwomen from accessing and utilising the new productive technology and related resources in Naraj but also reinforced the traditional male domination in the fishery sector.

This study seeks to counter interpretations of tribal movements as reflecting parochial and perverse ethno-territorial aspirations, mostly in irrational violent forms. It compares two peaceful protest movements against wildlife sanctuaries located in different geographical and political-economic settings in the eastern Indian state of Odisha. As rational collective actions, both movements relied on the agency of project-affected persons who questioned state attempts to de-politicise development in the name of scientific conservation. The study shows how the legitimate concerns of such project-affected citizens were overshadowed by politics and the context-specific dialectical interface between three different factors, namely availability of indigenous organisational resources, political opportunity structures and identity construction.

This research work includes the effect of Zeolite-A catalyst on the thermal degradation behavior of six different consumer plastic wastes like high density polyethylene (HDPE), polypropylene (PP), polyethylene terephthalate (PET), polymethylene methacralate (PMMA), polystyrene (PS) and polytetrafluoro ethylene (PTFE) through kinetic approach by using thermogravimetric analysis (TGA) data. Kinetic parameters such as reaction order, activation energy, and Arrhenius constant for the degradation of different waste plastics is determined using model fitting Coats–Redfern method. All the plastics show one-step degradation in the temperature range of 300–600°C. There is a significant decrease in activation energy (Ea) for the thermo-catalytic decomposition of the plastics in presence of Zeolite A catalyst. The extent of catalytic effect is found different for different plastics in the order of HDPE < PP < PS < PET < PMMA < PTFE. The order of the thermal degradation reaction is also found different for different types of plastics. The order of the reaction is altered in case of PET, PS and PTFE in presence of the catalyst but it is unaffected in case of remaining plastics. This treatment would reduce the energy consumption of pyrolysis process and also make the process economical viable.

The objective of this paper was to determine the optimum process parameters of an electric discharge machine while machining a new hybrid aluminum metal matrix composite. In this study, a new hybrid aluminum metal matrix composite was prepared, with silicon carbide and graphite particles used as reinforcements, with the help of the stir casting method. The selected electric discharge machining parameters in this study were peak current (I), voltage (V), pulse-on time (Ton), and tool material, while the response parameters were material removal rate and surface roughness. To machine the fabricated samples, two different types of tool materials (copper and brass) were used as electric discharge machine electrodes, and each had a diameter (Ø) of 12.0 mm. The optimal settings of the electric discharge machining parameters were determined through experiments planned, conducted, and analyzed using the Taguchi (L18) technique. An analysis of variance and confirmatory tests were used to check the contribution of each machining parameter. It was found that the material removal rate increased with the increase in pulse-on time and pulse current, whereas the material removal rate decreased with the increase in voltage. On the other hand, reduced surface roughness could only be achieved when current, voltage, and pulse duration were low. It was also found that the selected electric discharge machining electrodes had a significant effect on both the material removal rate and the surface roughness.

Aluminum based hybrid metal matrix composite have found extensive applications in field of automobiles. This paper investigates the significant effect of machining parameters like pulse-on time (T-on), pulse-off time (T-off), voltage (V) and current (I) on material removal rate (MRR). In this study the aluminum metal matrix composite with SiCp and Grp was casted. Hybrid Aluminum metal matrix composite was machined using one tool materials (Copper) of ɸ12 mm for experiments. The design matrix and mathematical models were developed by RSM (response surface methodology) using the Design expert 9.0.6 software. The experimental results show the impact of change in parametric values on material removal rate for hybrid metal matrix composite. To check the signification of model the ANOVA (Analysis of variance) technique was used. The SEM (Scanning electron microscope) was done to study the surface characteristics of the machined samples.

Magnetic materials have become more and more user friendly in recent days particularly in an electronic based infrastructure. The study proposes a direct drive permanent magnet based Synchronous Generator as Tidal turbine in a hybrid tidal wave energy conversion system (TWECS) and discusses its performance for better stability. The objective of the study is to analyse the role of permanent magnet based generator in TWECS for overall improvement of stability through reactive power management. The isolated TWECS becomes unstable either by random load variations or by non uniform wind and tidal power inputs. Consequently the overall stability of the TWECS is brought to stable and normal stage by the control of reactive power with the inclusion of the custom power based devices. In addition to the effects of permanent magnet in case of DDPMSG for improving the overall system stability, optimisation tools like PSO, GSA and PSOGSA are added for further improvement in system performance.

Stability of a standalone hybrid power system (HPS) in a smart grid is always a challenging task. Further, the operational stability of the power system depends on the associated communication infrastructure. Therefore, it is always crucial to pick up a controller that can assure system's stability along with performance, despite disturbances like (load and input wind variations) with communication delays. Present study focuses on reactive power management and voltage stability issues of an isolated HPS. The stability aspects of HPS are improved through reactive power compensation, by custom power devices like static var compensator. The control aspects of SVC as well as the whole hybrid system are taken care by H∞ linear matrix inequalities approach. Further, H-infinity control, Lyapunov stability along with linear matrix inequalities techniques estimate the delay boundary of controllers. The iterative performance of the proportional–integral–derivative controllers, and robust H∞ damping controller of the HPS, are designed through LMI approach. Later experimental study of the HPS is done, with a prototype model in dSPACE real-time control environment. In this case, dSPACE 1104 is added for data acquisition and control. Adaptability and robustness of the proposed controllers are verified under fluctuating loads and uncertain wind power input.

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.

Synthetic membranes are currently employed for multiple separation applications in various industries. They may have been prepared from organic or inorganic materials. Present research majorly focuses on polymeric (i.e., organic) membranes because they show better flexibility, pore formation mechanism, and thermal and chemical stability, and demand less area for installation. Dendritic, carbon nanotube, graphene and graphene oxide, metal and metal oxide, zwitter-ionic, and zeolite-based membranes are among the most promised water treatment membranes. This paper critically reviews the ongoing developments to utilize nanocomposite membranes to purify water. Various membranes have been reported to study their resistance and fouling properties. A special focus is given towards multiple ways in which these nanocomposite membranes can be employed. Therefore, this review provides a platform to develop the awareness of current research and motivate its readers to make further progress for utilizing nanocomposite membranes in water purification.

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.

Harish Kumar Garg was not included as an author in the published article [...]

Solar energy is going to play a measure role in the future global energy supply. Its acceptance has already been on rise in developing countries like India, where there is acute shortage of energy due to economic and other climatic reasons. Forecasting or predicting the future output of solar energy is a much needed step to integrate high insolation of solar energy to the nation's power grid. Due to the fluctuating nature of solar energy, an efficient use is possible depending on reliable forecast information and its availability in various time and spatial scales. The current status of forecasting of solar irradiance for energy generation proposes a review of solar radiation prediction and its application in a rapidly increasing economy like India. Various models are developed for analysis which can be developed either by empirical, soft computing or by simulation approach.

In sodium cooled Fast Breeder Reactors; power control is achieved through control rods which are driven by Induction motor with Electromagnetic brake. The motor will be energised upon release of brake unit. The brake coil will be energised to release the brake. The coil is of 48 V DC. If the brake is not released properly due to low flux developed in the brake coil, inter-turn short, liner wear; then there is a chance of Induction Motor getting damaged due to high frequency Surge generated due to interruption of locked rotor current. Hence the performance of brake unit in this application is highly critical. Voltage build-up time for brake power supply is checked. Magnetic field developed by various EM brake units has been measured and plotted as a function of applied voltage. Brake coil has been modelled in FEMM and Electromagnetic Finite Element Analysis has been carried out for determining the number of turns and fill factor of the coil. Brake unit has been dismantled and the effect of brake liner and the friction plate on pulling force of coil is observed. The same has been simulated in FEMM for computing the EM force on movable armature (disk) at various distances from the brake coil. Experiments and simulation results were used for diagnosing the cause of non-release of the EM brake. This paper discuses various causes of failure to the brake unit and to avoid recurrence of similar failure event.

Accurate forecasting of solar energy is a key issue for a meaningful integration of the solar power plants into the grid. Solar photovoltaic technology is most preferable and vital technology in comparison with all other sources of renewable energy. We know that the solar energy is very irregular so the output of solar photo voltaic system (SPV) is diverted by the atmospheric conditions like temperatures, humidity, wind velocity, solar irradiance and other climatological facts. It’s necessary to predict solar energy to minimize the uncertainty in power harnessing from solar photovoltaic system. In this work fuzzy logic model and ANFIS model have been developed for manipulating solar irradiation (w/m2) data to forecast short duration solar irradiation. Further the normalization in between the input and output is set in between 0.1 and 0.9 for reducing confluence problems. Acquired results are matched up to the manipulated data and valid results are found out.

This paper projects an isolated hybrid model of Offshore wind-diesel-tidal turbine and discusses the stability and reactive power management issue of the whole system. The hybrid system often loses its stability as it becomes prone to uncertain load and input parameters and therefore the necessity of Reactive power management becomes necessary. The overall stability of the hybrid offshore wind-diesel-tidal turbine is made possible by the management of reactive power in the hybrid system through the application of FACTS devices. And therefore the dynamic hybrid model of the DFIG and DDPMSG based offshore wind-diesel-tidal turbine is analysed for stability with different input parameters like wind and tidal energies. For detailed modelling and simulation, a small signal model of the whole hybrid system is designed and reactive power management of the system is achieved by the incorporation of a STATCOM controller. For improvement of stability and reactive power compensation of the hybrid system, GA and PSO optimised STATCOM controller is used.

This paper proposes a robust H-infinity STATCOM controller for compensating reactive power in stand-alone micro grid consisting of a PV–Wind–Diesel hybrid system. In order to carry out MATLAB based simulation, a small signal linear model of the stand-alone hybrid power system is considered, comprising of a photo voltaic cell, a DFIG based wind turbine and a diesel generator. Synchronous generator based DG acts as a backup for the hybrid system. Generally these standalone systems experience frequent variation of loads, wind power input and solar radiation, which affect the vital system parameters like reactive power, terminal voltage and frequency to a great extent. These variations of system parameters with variation of load inputs are studied and its impact on overall system stability and reactive power compensation is properly monitored. Furthermore the system performance is improved and the robustness of the controller is enhanced with the incorporation of GA and PSO.

Solar radiation data plays a crucial role in solar energy research and application. It provides the vital information about the energy that strikes the earth and is highly useful for modeling and design of solar thermal technologies and solar photovoltaic applications. As Conventional energy sources are depleting day by day, it becomes necessary to use renewable energy sources like Solar, Wind, and Biomass etc. Amongst all forms of renewable energy sources, solar energy is widely accepted as it is quite abundant throughout the world. In many developing countries solar radiation data are not always available either due to the unavailability of measuring instruments or due to the absence of meteorological stations. It is also true that many countries fail to afford the costly measurement equipments and techniques involved for measuring solar radiation. Thus, it is quite essential to develop models to measure accurate solar radiation by using Various meteorological parameters such as(latitude, longitude and Altitude)/Climatological parameters (i.e. Sunshine duration, Humidity,clearness index, months, temperature, cloudiness, wind velocity, atmospheric pressure, diffuse radiation, beam radiation, Global radiation extra terrestrial radiation, evaporation) etc. The objective of this paper is to i) To Study and review the model and techniques used for prediction of solar radiation. ii) To identify the research gap and the best methods available in the literature review. iii) To recommend appropriate techniques for solar energy predictions so that researchers find it more convenient and do their research implementations using these techniques for various applications.

This paper focuses on reactive power management as well as stability enhancement in a standalone hybrid power system (SHPS) with a proposed back stepping sliding mode controller based STATCOM. A comprehensive dynamic model of the standalone hybrid power system(SHPS) having a combination of wind turbine generator, diesel engine backup and storage device is represented with its control scheme. Detailed model of the DFIG based wind energy conversion system (WECS) has been proposed for the SHPS and is experimentally analyzed through dSPACE DS1104 for transient stability improvement with variable load dynamics. At the beginning a sliding mode controlling approach has been implemented for the non linear standalone power system and later a back stepping sliding mode controller (BSSMC) approach is initiated for both rotor and grid side converters. Further studies regarding voltage stability have been implemented with Eigen value, bode and nyquist analysis.

The dc-link capacitor of traction inverters in electric vehicles is a key component. In this paper, the dc-link capacitor current harmonics of an NPC inverter are identified as crucial design elements. In a first step, these harmonics are derived analytically and an electrical and thermal model of the capacitor are deducted. Secondly, the neutral-point balancing is evaluated. A new balancing scheme is proposed and its impact on the inverter harmonics is analyzed. The analytical considerations are verified on a test-bench setup. Finally, design rules are given to determine suitable dc-link capacitors.

With the innovations of different computing technologies, several simulation tools have surfaced. They are the upgraded form of simulation tools with better performance capability and less cost. RT-LAB is an open real-time simulating software which is completely compatible with MATLAB/SIMULINK environment. The technology has completely revolutionized the performance of model based design. Because of its flexibility and scalability, this advance technology is implemented in many systems and control applications adding computing power to simulation at the time of need. Basically the real time simulator consists of tools such as real time distributed simulation package (RT-LAB) and algorithm tool boxes. While RT-LAB executes the simulink block diagram of PC-Cluster, the algorithmic tool boxes help in design of stiff electric circuits and their controllers. The real time simulation and Hardware in the loop (HIL) applications contribute a lot in different engineering designs such as Power electronics and electrical systems.

Present research paper focuses reactive power management & voltage instability issues of a wind energy based dispersed power generating station. The iterative performances of PID controller as well as the robust H ∞ damping controller of the hybrid power system is designed through linear matrix inequalities (LMI) approach. The stability aspects of dispersed wind energy based HPS are considered for discussion where the issue of reactive power compensation is addressed by linear static var compensator (SVC) controller. The control aspects of SVC as well as the whole hybrid system are taken care by H ∞ linear matrix inequalities approach. The iterative LMI method has been implemented for tuning the gains of PID controller with H ∞ design by the help of iterative LMI. The wind-diesel hybrid system is also implemented experimentally where a proto type hardware model has been established by taking the help of dSPACE real time control environment. In this case dSPACE 1104 is added for data acquisition and control. Experimental results obtained during practical case analysis justify the simulation results of MATLAB. Adaptability and robustness of the proposed controllers are achieved under fluctuating loads and wind power uncertainty.

Several hospitals face nurse staffing shortages for surgeries. This research focuses on building a system with a Baxter robot capable of identifying surgical tools using computer vision and delivering them to the surgeon on demand. This would deal with the issue of nurse unavailability during simple surgical procedures. The key aspects of the project were testing the accuracies of various artificial neural networks (ANNs) in classifying surgical instruments and programming Baxter to implement a surgical tool delivery system using magnets at the tip of its 7 degrees of freedom (DOF) robotic arms. The methodology consisted of first implementing algorithms to enable Baxter to do pick and deliver tasks for surgical tools, and second, gathering HuMoments of various tools using the cameras on Baxter's arm, which were then used to train the ANNs. Tool detection accuracies of ANNs with hidden layer neuron number varying from 5–50 and learning rates varying from 0.005‒0.1 were collected. Then, the tool identification and tool delivery system were merged together to create a turn-by-turn dynamic tool tracking and delivery system, which retrieved tools, based on the surgeons input, through a Leap Motion Controller. In addition to delivery, the system was modified to retrieve used tools from the surgeon, using a computer vision-based approach. The optimal ANN configuration consisted of an ensemble of various ANNs working together and achieved a detection accuracy of 93%. The average time taken for a mock abdominal incision surgery with the system is expected to be around 10 minutes and 30 seconds.

Ergonomic design of a product considers design, cognitive and behavioral information during the design stage with a view to improve the comfort level of the user and aesthetic look of the product. However, a large number of products are available in the market place possessing a wide range of features to address the ergonomic considerations. Many times, the features may be redundant and hardly enhance interaction between the user and the product leading to user dissatisfaction. But few important features focusing its functionality and physical comfort can possibly address the usability of product and improve satisfaction level of the user. This paper proposes a fuzzy multi-attribute decision making (MADM) approach integrating both subjective and objective weights for each criterion so that superior ergonomically designed product can be evaluated. The methodology is explained with the help of an example of selection of an office chair. Three popular approaches have been considered to compare the ranking of alternatives. Keywords: Multi-attribute decision making (MADM), TOPSIS (Techniques for Order Preference by Similarity to Identical Solution), VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenjea), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations)

This paper gives a novel idea of application of ANN based SVC controller for Reactive Power compensation in an isolated hybrid system and also discusses the improvement of stability in the hybrid system. For detailed analysis a small signal linear model of the hybrid wind- Diesel- tidal model is considered with different loading conditions. The reactive power compensation and stability analysis have been thoroughly analysed by a SVC Controller. A feed forward neural network with back propagation technique is designed to tune the parameters of SVC controller. Simulation result shows that the system parameters attend steady state value with lesser time and complexities.

This paper gives a novel idea of application of fuzzy based UPFC controller for Reactive Power compensation in an isolated hybrid system and also discusses the improvement of stability in the hybrid system. For detailed analysis a small signal linear model of the hybrid wind- Diesel- tidal model is considered with different loading conditions. The reactive power compensation and stability analysis have been thoroughly analysed by a UPFC Controller. A fuzzy logic controller is designed to tune the parameters of UPFC controller. Simulation result shows that the system parameters attend steady state value with lesser time and complexities.

This paper gives a novel idea of application of ANN based SVC controller for voltage stability improvement in an isolated wind-diesel-micro hydro hybrid system. For detailed analysis a small signal linear model of the hybrid wind- Diesel-micro hydro model is considered with different loading conditions. The voltage stability analysis has been thoroughly analysed by a SVC Controller and is further improved by a feed forward neural network with back propagation technique which is designed to tune the parameters of SVC controller. Detailed stability analysis has been done with different criterias like bode, nyquist and eigen value synthesis. Simulation result justifies the working of the isolated systems performance which shows that the system parameters attend steady state value with lesser time and complexities.

The liberalization of the power markets gained a remarkable momentum in the context of trading electricity as a commodity. With the upsurge in restructuring of the power markets, electricity price plays a dominant role in the current deregulated market scenario which is majorly influenced by the economics being governed. Electricity price has got great affect on the market and is used as a basic information device to evaluate the future markets. However, highly volatile nature of the electricity price makes it even more difficult to forecast. In order to achieve better forecast from any model, the volatility of the electricity price need to be considered. This paper proposes a price forecasting approach combining wavelet, SARIMA and GJR-GARCH models. The input price series is transformed using wavelet transform and the obtained approximate and detail components are predicted separately using SARIMA and GJR-GARCH model respectively. The case study of New South Wales electricity market is considered to check the performance of the proposed model.

An assessment of the dynamic interactions between generators will provide valuable information which could improve control action and hence maintain stability in the interconnected system. The paper presents the study on dynamic interaction in terms of coherency established among the generators following a particular event. Time Frequency Coherency (TFC) method is applied to trace the coherency among the generators. The dominant inter-area modes on which TFC is applied has been extracted from empirical mode decomposition of the swing curve. The phase difference between the dominant modes will verify and refine the coherency results. The potential of TFC in power system application has been evaluated on test cases, power system model & Phasor Measurement Unit (PMU) signals. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Recognition of the significance of public wage employment programmes in tackling unpredictable community “covariate” shocks and ensuring livelihood security of the rural poor has led to the enactment of the Mahatma Gandhi National Rural Employment Guarantee Act, with state guarantee of work. Implementation of the Act, our empirical findings tell us, has become the site of tangible exchanges between state and society, with factors such as the level of material support for it, the balance of power between the local state and the poor on the ground, and the larger socio-economic structure determining programme outcomes.

The realisation of SGSY (Swarnajayanti Gram Swarozgar Yojana) programme outcomes was circumscribed by the weak links in the long implementation chain involving several intermediate stages and complementary resources, but more importantly by the failure to tackle powerlessness of the poor rural women through social mobilisation and to circumvent the structural inadequacies afflicting their quest for sustainable livelihood security in an otherwise backward area. As only a tool and an enabling element, micro-finance could go only so far in fighting rural poverty and could be useful only if it allows the poor to become more productive in creating wealth under favourable conditions.

The objective of the paper is to study the reactive power regulation and stability study of an isolated wind-fuel cell hybrid power system. A Fuzzy sliding mode-based STATCOM controller has been considered for compensating reactive energy in a wind-diesel-fuel cell-based remote hybrid power system. For detailed analysis and simulation, a transfer function small signal model of the hybrid power system has been considered. A double-fed induction generator-based wind turbine and fuel cell are the main constituents of hybrid system with a diesel generator as backup. The system performance is studied with a random variation of loads and wind power input. Further the system performance is improved and analyzed with the incorporation of Fuzzy sliding mode-based STATCOM controller.

This paper presents ANFIS-based control for DFIG-based Tidal Current Turbine for stability improvement of offshore hybrid power system. The small signal transfer function models of DFIG-based tidal turbines are considered and an ANFIS control is proposed in order to improve the stability of converter lying in both grid end and generator end. The simulink model has been created in MATLAB and after proper simulation the effectiveness of the compensator is achieved.

This paper discusses the enhancement of voltage stability and damping in isolated hybrid system. Fuzzified compensation has been carried out with TCSC for proper enhancement of stability and reactive power. The wind energy conversion system with linear approximation is experimented with different loading conditions. Overall compensation has been achieved with TCSC Controller for different loadings and uncertain wind power inputs. Both proportional and integral constants are properly tuned and the optimized results are achieved with Fuzzy controller. The results vindicate the performance of the proposed compensator and desired results are achieved.

This paper proposes Particle swarm optimization based TCSC Compensator in solar-wind hybrid station for Reactive power management and transient stability analysis. It also aims to select the setting parameters of TCSC (Thyristor Controlled Series Compensator) controller using Particle Swarm Optimization (PSO)and Genetic Algorithm (GA) to mitigate small signal oscillations. The standalone hybrid system has been simulated under different loading conditions for which a transfer function model has been considered. Impacts due to variable load, Wind power input and solar insolation have been studied and the detailed behavior of the system has been studied during normal and fault condition. Simulation results related to Reactive power compensation and voltage stability have been improvised with PSO.

Solar energy is regarded as the most vital non conventional energy sources among all fossil fuels. For the purpose of modeling of solar energy conversion device solar radiation data is most essential. Hence, accurate measurement or prediction of solar radiation data is important for a particular location. The proposed system uses a Nonlinear Autoregressive Network with Exogenous Input (NARX) model to predict solar radiation. NARX approach is used to estimate daily global solar radiation by using meteorological parameters such as sunshine duration, temperature, humidity. Solar data in Bhubaneswar, India have been used in the present case. The data for the period of 2002–2005 are used for training the NARX network while the data for the year 2006 is used for testing. The results of NARX network are evaluated on the basis of mean square error and regression coefficient.

Price forecasting has become essential tool in deregulated electricity market. It is used by utility operators for bidding in the competitive market to increase their profits and services. The models for electricity price forecasting can be mainly categorized into (i) Statistical models, (ii) Artificial Intelligence models & (iii) Hybrid models. AI based models, i.e., ANN have gained popularity in the recent years due to their black box nature and non-linear mapping capability, it is generally trained using back propagation algorithm, which has got some serious limitations like large training time, local minima etc. In this work, comparison of various training algorithms for ANN has been presented for accurate electricity price forecasting problem, the results obtained are contrasted with the generic ANN model trained using back propagation (BP) algorithm and other popular training algorithm. It is found that the generic ANN with Levenberg-Marquardt (LM) training method provides better result as compared to other models.

This paper is mainly focused on the implementation of fuzzy logic based UPFC controller in the isolated wind-diesel-micro hydro system for management of reactive power and enhancement of voltage stability. For better analysis a linearised small signal transfer function system is considered for different load inputs. The fuzzy based UPFC controller has been tunned to improve the reactive power of the off grid system. Simulation in MATLAB environment has been carried out and the effectiveness of fuzzy tuned controller is established..

This paper discusses reactive power regulation and stability study in an isolated wind type microgrid. This paper proposes a STATCOM controller for compensating reactive energy in a wind-diesel based stand-alone hybrid power system. The transfer function small signal model of the stand-alone hybrid power system has been considered which consists of a photo voltaic cell, a double fed Induction generator based wind turbine and a Diesel generator as a backup. The system performance is watched with variation of reactive power loads, variable wind power input and non linear solar radiation variation and the impact upon voltage stability and reactive power compensation is studied. Further the system performance is improved and analyzed with the incorporation of GA, PSO.

The paper presents a comparative study of monthly average solar radiation data using different soft computing approaches for Eastern regions of India. Soft computing tools like Multi layer Perceptron (MLP), Artificial Neuro Fuzzy Inference System (ANFIS), and Radial Basis Function (RBF) are used for the said analysis for three cities, i.e. Kolkata, Bhubaneswar and Vishakhapatnam. The input parameters used in these tools are ratio of sunshine hours (S/S0), average temperature ratio (T/T0), relative humidity ratio (R/R0). The monthly average data recorded during the period 1984–1999 for the region mentioned has been considered as training data. The purpose of the study is to compare the accuracy of measured radiation value with the output parameter of solar radiation through different models and using different techniques. The performance of the model is evaluated by comparing the predicted and measured parameters in terms of absolute relative error among ANFIS, MLP and RBF.

Several hospitals face nurse staffing shortages for surgeries. This research focuses on building a system with Baxter robot capable of identifying surgical tools using computer vision and delivering them to the surgeon on demand. This would deal with the issue of nurse unavailability during simple surgical procedures. The key aspects of the project were: testing the accuracies of various Artificial Neural Networks (ANNs) in classifying surgical instruments, and programming Baxter to implement a surgical tool delivery system using magnets at the tip of its 7-DOF robotic arms. The methodology consisted of, first, implementing algorithms to enable Baxter to do pick and deliver tasks for surgical tools, and second, gathering Hu-Moments of various tools using the cameras on Baxter's arm, which were then used to train the ANNs. Tool detection accuracies of ANNs with hidden layer neuron number varying from 5 – 50 and learning rates varying from 0.005 - 0.1 were collected. Then, the tool identification and tool delivery system were merged together to create a turn by turn dynamic tool tracking and delivery system, which retrieved tools, based on the surgeons input, through a Leap Motion sensor. In addition to delivery, the system was modified to retrieve used tools back from the surgeon, using a computer vision based approach. The optimal ANN configuration consisted of an ensemble of various ANNs working together and achieved a detection accuracy of 93%. The average time taken for a mock abdominal incision surgery with the system is expected to be around 10 min and 30 sec.