With the rapid development of Electrical Vehicles (EVs), there is s significant addition of battery charging loads on the electrical grid. The increasing trend of high-rise buildings with the capability to mount heavy structure have created the possibility to mount building top wind power generators. These high rise buildings have large parking lots and space for EVs and their charging ports. This work focuses on using the building mounted small wind turbines to charge the EV batteries. Since the wind speed is intermittent, it needs to be connected with the grid to ensure that battery charged even if wind speed is not sufficient. In this work, wind power is used to charge the EVs battery. In this paper the wind energy is converted into electric energy with the help of a Self Excited Induction Generator (SEIG). The AC output is produced from SCIG is further converted into DC for charging the EV battery. The charger is also connected to the grid as a backup to ensure a continuous supply of energy for charging the batteries. Here the phaseshifted fullbridge (PSFB) topology is used for charging the batteries. The simulation results are obtained using MATLAB for the proposed wind-based charging station.

This paper presents a vigorous control design and a robust controller for a Multifunctional grid interconnected inverter [MFGII] beneath disturbed load conditions. This MFGII controller algorithm uses DQ theory to assess the unacceptable parts of grid current such as harmonics, and required load reactive current. This decoupled method of control design makes normal Grid interconnected inverter to MFGII and also helps in reducing the computational burden whch further makes the system more robust. Furthermore, Adaptive Fuzzy sliding mode control (AFSMC) algorithm prepares the system sturdy and effective in improving the dynamic performance during uncertainties. Henceforward, settling time and overshoot are reduced with fast dynamic response. The MFGII infuses the RES to grid at PCC which in addition to Real power injection also provides reactive power compensation, balance the load and mitigate harmonics. The results obtained from FOSMC are compared with AFSMC under the variation of solar irradiation and load.

This article proposes a super twisting sliding mode controller (ST-SMC) for its novel application in the domain of PV grid-connected water pumping system. The ST-SMC is intended to inject both active and reactive power with sinusoidal current of low total harmonic distortion (THD) to the non-linear load such as water pumping system. Excess active power generated by the PV array is fed to the grid and reactive power requirements of the load are fulfilled by the ST-SMC controlled inverter. The proposed control methodology is tested on the DC link voltage, maximum active power extracted from PV array, reactive power supplied by the inverter, and the THD of inverter current. The ST-SMC reduces chattering, provides easy real-time implementation, and offers insensitivity to parameter variations and model uncertainties. Thus, the proposed control strategy is able to maximize the extracted energy from PV while regulating DC–link voltages and achieving a power factor compensation and reduces the harmonics from inverter current. The proposed control methodology is implemented in MATLAB/Simulink and its performance is compared with conventional PI-based control method.

This paper reports an adaptive neural fuzzy inference system (ANFIS) based controller for a grid-connected tidal turbine (GCTT) system based on permanent magnet synchronous generator (PMSG). An energy storage system (ESS) provides the balance of power at the DC link to improve system stability under low-voltage ride-through (LVRT) conditions and tidal power fluctuations. The grid code suggests the required reactive power demanded by the grid during a fault. An ANFIS-based controller coordinates with the TT rotor speed and state-of-charge (SOC) to fulfill grid code requirements. During the occurrence of a fault, the operating conditions of the GCTT and the SOC of ESS may differ. So, it becomes necessary to establish coordination between both the TT rotor speed and the SOC of ESS. It results in different operating conditions of the GCTT and the ESS. The proposed control method generates the reference power for the machine-side converter of GCTT based on the current rotor speed and SOC of the ESS. Extensive numerical simulations have been performed on the MATLAB® Simulink platform to prove effectiveness of the proposed control method.

This Article Presents a Versatile Multi Objective Control Approach to Control Photovoltaic (PV) Powered Micro-grid side Multipurpose Grid Integrated inverter (µ11 A.Naveen Kumar, Dr I. JacobRaglendG-MPGII). This envisaged system uses SRF Theory to establish Modified Multi-objective Flexible Synchronous reference frame (MMOFSRF) based control strategy to control µG-MPGII. This µG-MPGII can be employed to 1) Establish complete control on grid real power based on State of charge of battery (SOC) & load profile, 2) Works as distributed power quality enhancer with features of eliminating dominant harmonics produced by nonlinear loads at point of common coupling (PCC), injecting required reactive power for the load and improving power factor 3) Balance the utility grid currents under unbalanced load system. The transfer function model of proposed system is derived and analyzed for stability assessment through frequency response characteristics. The efficacy, dynamic Pursuance and multifunctional features of proposed system are verified by conducting comprehensive simulation studies in MATLAB/SIMULINK.

This paper proposes a lively calculation of MFGIIs under unequalled weights and under the fundamental voltage conditions for Multifunctional Grid Tie inverters. For design of an MFGII controller, the proposed calculation uses rapid power speculation. An estimator for Positive Fundamental Components (PFCE) is used to monitor unwanted components of a pile current such as tone, reactive current and negative plan components. The PFCE is an open-circle lightweight calculation. Unbelievable goodness is then refined with the inconvenience of less machine. Furthermore, a sliding mode (SMC) controller is used to improve a special display and energy against the limit range as a transmission voltage controller. The MFGII interfaces with the microgrid to the critical grid at a common connection point (PCC). A proposed control computing enables the MFGII to redeem open resources, mitigate music and balance a pile in the vicinity of a unique power implantation. This paper provides an unmistakable sample evaluation of SAPF, explicitly under two current control philosophies, quick dynamical and sensitive power speculations (p-q) and composite border comparison theory (d-q). The reference current for a channel is generated in two procedures, compensating either for open power or a constant current part in a power structure.

This paper assesses and investigates the fundamental sorts of organization geographies which incorporate the transport, star, ring and lattice topology. This article besides examines every topology's points of interest and weaknesses when utilized. A rundown of investigation was likewise made in an even structure to gather and make it more obvious things. From that point forward, the paper talks about various circumstances where a specific topology can be used.This paper discuses about the Organizations with more resources are already able to afford the expense of the most current advances, but they may still choose for the conventional if they need it. Businesses can be categorized according to their capitalization.This kind of geography is well-liked in small businesses since it is simple to use and understand.

Radiation from the sun is an amount that is produced each hour by the Sun and is a critical information for the outline and decide the productivity of a photovoltaic plant and ambient temperature enormously influence the execution of the solar power. In this paper a new approach is projected for analysis on style and control of grid solar system the project is based on power control of tie line. This technique of low stress on utilization of customized control topology. The working principle of described method is that the grid is developed by the solar system for the distribution of energy and tie line control is developed with the help of two parameters viz. frequency and power. For obtaining this we are using here maximum power point tracking (mppt )and boost converter for increasing the efficiency of photovoltaic cell. The maximum power point tracking is an important function in all photo voltaic power systems. The simulation results shows that the proposed mppt control can avoid tracking deviation and result in improved performance in both dynamic response and steady state response.

In this paper, we propose a model named Hugo, that acts as a distributed, scalable cloud controller which can handle basic operations like creation, deletion and migration of virtual machines(VMs). It achieves higher utilization by overcommitting the physical machine(PM). We describe each and every component along with their functionalities that garner to form the structural support for the model proposed. Algorithmic implementations namely Wiener filter algorithm for resource prediction, heuristic for energy efficient VM migration are discussed. Distributed nature of the model along with its contribution to scalability is fairly explained in this paper.

The term Soft Computing (SC) encompasses many techniques which include: Fuzzy Logic (FL), NeuroComputing (NC), Probabilistic Reasoning (PR), Evolutionary Computing (EC) or Genetic Algorithms (GA), Chaotic Systems (CS), Belief Network (BN) and part of Learning Theory (LT) (Zadeh, 1965, 1994, 1995; Mellit and Kalogirou, 2008). SC techniques are different from analytical approach in that they employ computing techniques that are capable of representing imprecise, uncertain and vague concepts (Voracek, 2001a; Kulak et al., 2005; Kahraman, 2007; Guarino et al., 2009). Analytical or in other words hard computing, approaches on the other hand use binary logic, crisp classification and deterministic reasoning. In their editorial review, (Hoffmann et al., 2005) observed that: “In contrast with hard computing methods that only deal with precision, certainty, and rigor, soft computing is effective in acquiring vague or sub-optimal but efficient and competitive solutions. It takes advantage of intuition, which implies the human mind-based intuitive and subjective thinking is implemented here”. Techniques in SC are able to handle non-linearity and they also offer computational simplicity when compared with the analytical methods. These techniques have been shown to be able to manage large amount of information and mimic biological systems in learning, linguistic conceptualization, optimization and generalization abilities. Soft computing techniques are finding growing acceptance in materials engineering and three of them are popular, namely: (i) Fuzzy Logic (FL), (ii) Artificial Neural Networks (ANN) and (iii) Genetic Algorithms (GA). There are well established methodologies for integrating SC techniques to realize synergistic or hybrid models with which better results could be obtained (Zadeh, 2001). The use of hybrid techniques is also growing. Real world problems have to deal with systems which are non-linear, time-varying in nature with uncertainty and high complexity. The computing of such systems is study of algorithmic processes which describe and transform information: their theory, analysis, design, efficiency, implementation, and application. Conventional computing/Hard computing requires exact mathematical model and lot of computation time. For such problems, methods which are computationally intelligent, possess human like expertise and can adapt to the changing environment, can be used effectively and efficiently. Soft computing utilizes computation, reasoning and inference to diminish computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. Soft Computing with its roots in fuzzy logic, artificial neural network, and evolutionary computation has become one of the most important research field applied to numerous engineering areas such as Aircraft, Communication networks, computer science, power systems and control applications. Soft Computing Techniques comprises of core methodologies: Fuzzy Systems (FS), including Fuzzy Logic (FL); Evolutionary Computation (EC), including Genetic Algorithms (GAs); Artificial Neural Networks (ANN), including Neural Computing (NC); Machine Learning (ML); and Probabilistic Reasoning (PR). Where PR and FL systems are based on knowledge-driven reasoning, whereas, ANN and EC, are data-driven search and optimization approaches.

In Grid connected distribution generation systems Islanding detection is a vital act for reliability and safeness. For islanding detection several methods were proposed, but under multi-source configurations most of them may fail. Islanding can be a possible solution with a properly harmonize and advanced control scheme, to ensure reliable power to the negative loads. An intentional islanding detection control scheme for operation of an inverter-based DG system has been proposed in this paper. An interface control was designed for providing the constant power under grid connected mode of operations. In the absence of the grid, the algorithm will make the inverter to work in voltage control mode. An load shedding algorithm is used to remove the deviations in the generation and load.

This paper deals with a multi objective control strategy to control the double boost sepic converter (DBSEPIC) based grid interconnected inverter using synchronous reference frame (SRF) control. In the process of renewable integration grid interactive inverter with suggested control can be economize as a 1) power allocation and control between the inverter and grid for load, 2) retrenchment of harmonics in source current, 3) reactive power compensation. In this proposed SRF control strategy there are two different types of controllers are used one is PI controller and another one fractional order sliding mode controller (FOSMC). The simplicity of PI controller and robustness of FOSMC utilised here. The performance of two controllers is compared in terms settling time, peak overshoot and THD through simulation results.

Shunt Active Power Filter (SAPF) are widely used for the reduction of Harmonics. In this study, a Fractional Order (FOPI) PI controller is designed to improve the performance of SAPF by maintaining a constant DC-Link voltage. The parameters of the FOPI control is tuned using a well known optimization technique, Particle Swarm Optimization (PSO). The results obtained are compared with a PI controller generally used for same application. The result shows that the proposed study provides better results in maintaining the voltage level and indirectly reducing the Harmonics.

Due to the nonlinear characteristics between the input & output parameters of a liquid flow rate process control, classical optimization technique is limited for this purpose. Hence computational optimization is chosen as an alternative approach. In this paper an ANFIS model was designed using trial and error based on various three different sets of experimental data sets for checking the flexibility, speed & adaptability of these soft computing technique. By the understanding of the Sugeno type ANFIS structure parameters are set to facilitate the hybrid learning rules. However, it is seen that by increasing the number of inputs response time of the model also increased. The results are in good agreement with the experimental results & can be applied to predict the performance of mass flow sensor. For the best ANFIS structure gained in this study RMSE and MAE were calculated as 2.143 & 0.504 respectively.

Micro turbine generators are often used these modern days as distributed energy resource which is connected to distribution system. The main reason using micro turbine generators operated with waste fuels suiting most of the industrial loads of small scale to medium due to advantages like compact size, high speed, good efficiency, less maintenance, low emissions. Permanent magnet turbo generators are required to couple with the micro turbine. The generated output power from turbo PM generator is of high frequency, so AC/DC/AC converter is been used to convert the output AC power of high frequency into the grid frequency for grid interconnection. A huge increase in the loss and temperature of high speed machine is been noticed especially due to the high frequency harmonic currents produced by the power conversion system. This paper presents a multifunctional three phase active power filter(APF) which is used as PWM inverter to start micro turbine and then it is used as active power filter to mitigate current harmonics produced by AC-DC converter. A Synchronous reference frame(SRF) theory based control strategy is implemented for both PWM inverter and active power filter. The complete system is modeled and simulated in Matlab/Simulink software.

The main objective of the project was to differentiate between potatoes and onions and classify them on the basis of sizes - small, medium and large. Thus, for the first task i.e., to differentiate between potatoes and onions, we used a color sensor which can detect the color of the respective vegetable and separate them accordingly. For the second task i.e., to classify them according to the size we used five IR sensors. If any two IR sensors detect the vegetable, then it signifies that it is a small produce and it'll be separated using a flap at a certain angle. Similarly, if three sensors detect then the produce is medium sized and it'll be separated at an angle unlike to that of the small one. Finally, if all the five sensors detect then the produce will be classified as a large produce and will be separated at a different angle other than that of the other two. This procedure applies for both vegetables with potatoes on one side and onions on the other direction. This project shall have an application in both farming and the upliftment of the agricultural sector and the life of farmers.

The present paper describes a study of small signal performance of synchronous machines connected to a large power system network through transmission line under steadystate operation by considering influence of saturation with cross-magnetizing phenomenon between d-and q-axis circuits.In the method, mutual reactance dq X due to the cross magnetizing phenomenon can be consider on the basis of d-q axis magnetic field analysis.The quantitative accuracy requires the magnetic coupling between d-and q-axis circuits be considered.S ubsequently, steady-state reactances are analyzed by considering mutual reactances dq X due to cross magnetizing phenomenon.S ynchronous machines have a nonlinear characteristic due to saturations and cross-magnetization phenomena, so that d-q axes inductances vary depending on the current amplitude and the load angle.Therefore, usually the un-coupled d-q model with constant parameters might not be suitable to represent accurately the performance of the electrical machine.

The main objective of this paper is to design a controller for control of an Induction motor. In this paper, we have proposed v/f control of induction motor using artificial neural network, the network is trained using back propagation algorithm and Levenberg–Marquardt learning is used faster computation. The main approach is to keep voltage and frequency ratio constant to obtain constant flux over the entire range of operation and thus to have precise control of the machine. The effectiveness of the controller is demonstrated using MATLAB/Simulink simulation.

Given how computational power has advanced in the last decade or so, it has become increasingly simplistic to carry out simulation of control systems to evaluate performance, without the need to spend resources on, earlier inevitable experimentation. This work utilizes the computational advancements to evaluate the variation in incidence angle for a solar collector for the city of Vellore, Tamil Nadu throughout the day. A methodology is presented to optimize the incidence angle, which results in an incidence angle being reduced to 0°. Experimental validation of the methodology is also presented in this work.

Purpose The Government of India is proposing the setting up of several new smart cities in the sub-continent. Being an over-populated country, space is at a premium. In congested areas high-rise buildings afford a solution. The purpose of this paper is to present new research involving architecture and computational fluid dynamics (CFDs) must be done at the screening stage of design plans before new cities are laid out. This is achieved in the present study involving a university residential campus with a population of 29,000 comprising of an assortment of high-rise buildings in complex terrain. Design/methodology/approach This paper uses a combination of instrument-fitted drone measurements – (equipped with a barometer, and sensors for obtaining temperature, relative humidity and altitude) along with a computational fluid dynamical analysis to yield deep insights into the ventilation patterns around an assortment of building forms. Findings This study was conducted in a residential complex in the campus of the Vellore Institute of Technology (VIT) India. Based on the deciphered wind velocity pattern, a human thermal comfort study was also conducted. It was concluded that the orientation of the buildings play a pivotal role in enhancing the ventilation rates inside a building. It was observed that a dominant eddy spanning a radius of approximate 34 meters was responsible for much of the air changes within the rooms – the smaller eddies had an insignificant role. This method of ascertaining eddy structures within a study area comprising of an assortment of buildings is essential for accurate prescriptions of glazing ratios on building facades. Research limitations/implications The main research implications pertain to the use of smart ventilation methods in built up environments. The study shows how large eddies drive the momentum transfer and the air changes per hour with rooms in high-rise buildings in complex terrain. In monsoon-driven flows, there are well set preferred directions of wind flow and this enables the characterization of the fully eddy structure in the vicinity of tall buildings. Another research implication would be the development of new turbulence closure models for eddy structure resolution for flow around complex building forms. Practical implications This study introduces a novel protocol at the planning stage of the upcoming residential complexes in proposed smart cities in the sub-continent. The results may well inform architects and structural engineers and help position and orient buildings in confined spaces and also ascertain the optimal glazing ratio, which affects the ventilation pattern. Social implications The results from this study can be used by town planners and architects in urban conurbations in the developing world. The results may well help lower heating ventilation and airconditioning loads. Energy-efficient buildings in developing countries are necessary because most of these have rapidly growing GDPs with a concomitant increase in energy consumption. Originality/value This novel study combining instrument mounted drone and CFDs shows for the first time how architects and town planners with a limited budget position and orient a group of buildings in a complex terrain.