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The recent advancements in demand-side management techniques add significant benefits to the distribution systems. One such technique is transactive energy management systems (TEMS) which motivate the energy end-users to take part in local energy trading. The end-users can effectively increase the monetary benefits by trading the surplus generation/demand within the local energy market (LEM). The LEM operator frames a viable market clearing strategy to fix the market clearing price to enhance the monetary benefits of all the market players. In this study, LEM architecture with different market clearing strategies is proposed for TEMS to ensure profitable power transactions between the neighboring end-users. An optimal energy management algorithm is also proposed for time scheduling the operation of flexible loads and batteries, considering dynamics in end-users’ behavior, variations in utility parameters, and the intermittent nature of renewable power generation. Further, an optimal load scheduling algorithm is developed at the end-users’ premises to improve the profits in the LEM. Correspondingly, the trading strategies are extended to increase market reliability by penalizing participants for their abnormal activities in energy trading. The proposed framework is validated with different case studies considering ten residential participants in a locality.

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.

The renewable sources integration with the DC micro grid is playing vital role in the current distribution system for providing the necessary clean power. The available of abundant renewable sources can be integrated through the DC link medium. The intermittent nature of renewable sources and dynamic switching of loads affects the quality of supply and DC link voltage respectively. It may fails to supply the power continuously. Reliability of power supply can be achieved with the use of integration of storage system. Here, the solar photovoltaic (SPV) array is fed with battery storage, fuel cell through the DC link medium. Utilizing SPV array maximum power is tracked using intelligent controller based maximum power point tracking (MPPT) technique. The battery storage with the DC link integration made through the bi-directional DC-DC converter with the help of the battery charge controller. Fuel cell is used as a base source and it’s fed with the DC link system. Finally, the simulation of SPV array, battery storage with fuel cell integration is performed under dynamic switching of loads. The variations in the source and switching of load performance are simulated in the MATLAB/Simulation software.

The global warming is increasing rapidly with the increase in the power generation using non-renewables. Renewables are the best possible solution to overcome the hazardous effects of non-renewable...

Distributed electricity resources (DERs) are power generating sources which are installed to meet the increasing peak demand. Renewable and zilch emission characteristics are making them as a perfect choice in distribution system. But the designing of protection scheme for the fruitful operation of distribution system (DS) places a challenging task for power system engineers. As the population of the solar based electrical DERs increase in the electrical DS, the fault current contribution from these resources becomes comparatively less with the fault current from utility substation. In this research commentary, voltage and current based protection algorithm is offered which can accurately detect the fault current from solar in-feed DS. The proposed algorithm is implemented in IEEE 30 bus reference DS. The relay mis-coordination problem is solved by using differential evolution algorithm (DEA). Keywords: Distributed energy resources (DERs), Voltage based time inverse over current relay characteristics, Solar in-feed distribution systems (DS), Differential evolution algorithm (DEA)

Smart cities are going to be the need for the future generation. For any city to be smart, two major things to look at are its energy consumption and the safety of citizens. The aim of this work is to optimize energy consumption in public lighting and to make roads safer by ensuring quick dispatch of emergency services upon detection of an accident or any abnormal condition on the roads. Public lighting has a huge energy consumption. For public lighting energy optimization, the proposed system uses a microwave Doppler motion sensor interfaced with Arduino to detect vehicle movement and switch on corresponding lights to illuminate the road, hence saving a lot of energy against traditional street lights that are kept on for the entire duration of the night. A number of lives are lost annually in road accidents due to emergency services reaching a few minutes later than needed. To tackle this issue, the proposed system demonstrates a prototype model to detect an accident, or any abnormal condition such as a roadblock and inform the nearby authorities to take necessary action. The novelty of this system is that it is placed on roads rather than vehicles which makes it independent of vehicle type and is accessible and affordable to all.

In the current scenario, providing continuous power supply and meeting the peak load demand are becoming the prime challenges in the power sector. The existing nonrenewable energy source causes global warming, environmental pollution, and inability to provide necessary clean power due to the presence of modern technology, population growth, domestic appliances, agriculture sectors, and interconnection of a number of nonlinear loads. This problem can be avoided using hybrid power generation. In this paper, the necessary power and peak demand are provided by inviting the integration of a grid-connected photovoltaic with battery storage hybrid system. The solar photovoltaic power is integrated with the DC link of a syncro converter through the boost converter. The switching control function of the boost converter is operated with an intelligent controller to step up the voltage and track the maximum power from the intermittent nature of solar photovoltaic system. The Radial Basis Function Neural (RBFN) network-based intelligent controller is utilized for tracking the smoothening of the maximum power under dynamic irradiance and temperature conditions. The battery storage system is connected to a DC link through an appropriate DC–DC converter. The battery storage system stabilizes the DC link voltage using a voltage droop control. The performance of the proposed system is simulated in a grid-connected mode under variable load conditions using MATLAB–SIMULINK software.

Despite many decades of research on the photovoltaic cells, still it is a great struggle to get efficiencies more than 25%. Transmission of low energy photons & thermalization of high energy photons are the two losses which form the backbone of the Shockley – Queisser limit. In this paper, a way to diminish both these losses along with modified Perturb and Observe MPPT method, which will boost the overall efficiency up to 35% is demonstrated. At first Singlet Exciton Fission is utilized as a down converting process for photons with energy greater than silicon bandgap of 1.12 eV in which a single high energy photon fissions into two photons of half the energy. Then, Triplet-Triplet Annihilation (TTA) is utilized as an up converting process for photons with energy less than 1.12 eV & wavelength more than 1100 nm in which two low-energy photons get converted into a single high-energy photon of twice the energy and finally Modified Perturb & Observe MPPT method with ZVS technique is used to reduce the DC to DC converter losses.

In this paper an analysis of a 15MW system consisting of 6 fully rated converter (FRC) wind turbines and 2 generators connected to a 20kV external grid via a wind farm controller and capacitor bank is carried out. The study includes the power curve, variation of power generation with wind speed and fault studies during the voltage dip for three different systems of operation namely purely wind based, wind based without controller and Hybrid system of wind farm. The capability of system to sustain fault conditions (LVRT) and attain normalcy after fault period is analyzed and hence describing the reliability of system. The designing and results of the case system is done using DIgsilent Powerfactory software tool.

Atom search optimization (ASO) is a new star among metaheuristic techniques with very contestant offerings. It is based on the atomic movement naturally, where atoms interact with each other through interaction forces resulting from the potential of Lennard-Jones and constraint forces resulting from the potential of bond-length. In this paper, ASO is used to solve optimal power flow (OPF) problem. The proposed method optimal power flow using atom search optimization (OPF-ASO) has been applied to the standard IEEE 30-bus test system for different objectives. In addition, in addition, the results obtained using OPF-ASO were compared to those obtained using other techniques mentioned in the literature. Results obtained and compared indicate that OPF-ASO provides a robust, high quality solution with different complexities.

Electrical energy is the most fundamental elements of infrastructure and it is important for economic development and progress of any nation. As a result of population explosion and economic development, energy utilization has been increasing at a dramatically faster rate in India. The rapid growth of a nation’s economy places heavy demand for electric power. A large portion of the electric demand is fulfilled by fossil fuel which discharges harmful gases in the atmosphere. In order to reduce greenhouse gas emission and to develop efficient and reliable ways to harness energy, renewable sources can be viewed as one of the best possible alternatives. The main aim of the power producers should be to develop smart and sustainable energy systems for the country. This paper documents the current status and potential of renewable energy in India along with role of private power producers. This paper also reviews the major operations and contribution of private power producers in the power sector.

The solar photovoltaic system plays vital role in the modern DC micro grid systems due to clean power and freely available in nature. The abundant and day variability solar power is intermittent in nature. The availability of solar power efficiently and effectively utilizes with the use of battery storage systems. In this work, the solar photovoltaic with the battery storage system is investigated. The stochastic nature of solar power is extracted using intelligent controller based maximum power point tracking method. The battery storage system is interface with the DC link through the bi-directional DC-DC converter. The battery charge controller is implemented with the proportional and integral control. The solar photovoltaic with battery storage system provides the flexible power to the load continuously based on the battery state of the charge. The dynamic variations in the source and load performance are simulated in the MATLAB-Simulink software.

The proposed work intends to design a single channel boost power factor correction (PFC) AC to DC converter for wide range of power applications. Unlike the traditional approaches of PFC this topology manages to eliminate the ripple in input as well as in output current and voltage waveforms, reduces peak current and switching losses. Conventional controllers cannot obtain a good current shaping because of non-linear characteristics of converter at light loads and inaccurate average current samples in DCM mode. This inappropriate current profile also causes poor efficiency. A new digital hybrid control scheme which includes the sampling correction during reference current generation is employed for shaping the good input current in both CCM/DCM mode and also allows the smooth transition between two modes as the load changes. The proposed scheme also improves the reference current tracking at low load conditions. A satisfactory performance of 1KW PFC converter working at 50 KHz switching frequency with hybrid CCM/DCM control scheme is validated by simulation results at various load conditions. The obtained results of power indices comply with IEEE 519-1992 and IEC 61000-3-2 standards.

In the present trend, the grid-connected solar photovoltaic systems are playing a major role in supporting the utility peak power and providing the quality of power supply. The installation of solar photovoltaic system is reasonable cost for producing the power. But the solar power may not meet the utility peak demand continuously due to the intermittent nature of solar power. To make continuous supply, the battery storage system is proposed with the bidirectional convert using PI controller. In this work, the grid integration of solar photovoltaic with battery storage system is proposed using the hysteresis current controller for conditioning the electrical power. The solar power is extracted using fuzzy-based maximum power point tracking methods under dynamic variations in the irradiance and temperature. The extracted power is integrate with DC link, and the voltage at DC link is stabilized with the help of battery storage system. The DC link is integrated with the grid through the inverter using a hysteresis current control technique with the PI controller. The inverter and battery storage controllers are used for providing quality of power supply and can meet the necessary peak demand. The performance of the grid-connected solar photovoltaic and battery storage systems is simulated in MATLAB–Simulink software under the dynamic irradiance and the temperature variations.

This research paper presents a novel sequential wavelet-artificial neural network (ANN) with embedded ANN-particle swarm optimization (PSO) for short-term day-ahead forecasting of market clearing price (MCP) in the Indian energy exchange. A precise price forecasting helps suppliers to set up bidding strategies, make investment decisions and be cautious against risks. Conversely, consumers can use price forecasting to exploit appropriate power purchasing strategies for maximum utility utilization. Here the most influential historical data, namely purchase bid and MCP, are considered for training the feed-forward back-propagation neural network. The proposed model involves three sequential phases. Initially, the raw historical data are smoothened by removing the high-frequency components using a wavelet transform method which may enable better training of neural network. Then, ANN is used to train historical patterns. More number of trials is carried out, and the final weights that give the least training error are stored. In the final phase, the stored weights that are obtained from various trials are used as the initial population for the embedded ANN-PSO model. Here the performance of the proposed forecasting model is carried out using three error indices, namely mean absolute percentage error, normalized mean square error and error variance.

Smart grid software integrates various software components in Generation, Transmission, Distribution, Smart Metering and Cloud systems. The smart grid architecture is evolving with new features and to accommodate legacy software elements. Smart grid integrated software is an evolving approach in line with modern Information and Communication technology. In this paper, the authors propose a software requirement framework for the smart grid architecture with a focus on Embedded Systems. A state of art idea is considered, to extract software development practices in automotive domain for smart grid systems. Multi layered software architecture to implement the proposed requirements, is also analyzed. Complete analysis of sub-systems, devices and their operations are done to derive the framework. Master-Slave software architecture model is considered amongst the various Electronic Control Units (ECUs) present in the smart grid environment. All the smart grid software modules and their data exchange attributes are also evaluated. Interface requirements within the smart grid sub-systems are dealt in details.

In this paper, a cuckoo search (CS) algorithm-based neuro-fuzzy controller (NFC) is developed to improve the performance of unified power quality conditioner (UPQC). The CS algorithm is used for optimising the output of neural network (NN) so that the classification output of the NN is enhanced. The inputs of the networks are error and change of error voltage of the PQ issue signal of nonlinear load which are calculated by comparison with the reference signal. Next, the output of network, i.e. regulated (compensated) voltage, is optimised by the CS algorithm. From the output of CS, an optimum rule-based fuzzy interference system is developed and the PQ problem is compensated. The CS-NFC-based UPQC is implemented in MATLAB/Simulink and the PQ issue clearing performance is analysed. The PQ issue clearing performance of proposed UPQC is compared with traditional UPQC, NFC-UPQC, GA-NFC-UPQC and adaptive GA-NFC-UPQC. The CS-NFC-based UPQC controller has lesser error deviation of 2.8% with traditional UPQC, 2.1...

Background/Objectives: Vivaldi antenna is a prime candidate for wide band applications. This work involves a design of miniaturized tapered slot antenna operating with X-band frequency to achieve wide scan capability, wide beam, maximum gain and minimum return loss for active phased array antenna. Methods/Statistical Analysis: The design of Vivaldi Exponentially Tapered Slot Antenna (VETSA) and analysis of radiation patterns, return loss, beam width and scan angle are done through the use of electromagnetic simulation software HFSS. The analysis was carried out in 3D and 2D. Further, testing and measurement of fabricated Vivaldi antenna using Vector Network Analyzer and radiation patterns are observed in Anechoic Chamber. Design of linear array and planar array is also presented. Findings: VETSA satisfies the requirements on the maximum reflection coefficient < -10 dB for ±60o scan from broadside in E-and H-planes. The realized antenna showed a symmetric pattern, minimum return loss, better 3-dB beam width in principal planes with gain of 3-dB, and VSWR ≤ 2 in X-band frequency. The result of linear array with 9-elements demonstrates good radiation characteristics with gain of 13 dB with low SLL including coupling effects in the X-band operating frequency. The uniformly illuminated array beam pattern shows that the array can scan over the desired scan volume of ±60o in E-plane and ±55o in H-plane. VETSA is a promising candidate to operate in wideband frequency with wide scanning performance in airborne radar applications. Application/Improvements: The designed antenna structure and array are good candidates and is expected to find applications in integration with monolithic millimeter-wave integrated circuits on combat aircraft.

This paper focuses on efficient hybrid microgrid which consists of wind and solar power generating sources with an efficient and reliable grid connection. The proposed system will execute modified Perturb and observe maximum power point tracking technique for both wind and solar generating unit to maximize the simultaneous extraction of energy from the entire power generation unit under different weather and load conditions. This system eliminates the need to synchronize the system frequency, phase and voltage, which allows flexible operation of multiple parallel connected wind and solar generators at the grid. The simulation output of proposed system will be demonstrated under different weather and load conditions.

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 consumption of power is more due to high invention and more number loads. The most of the loads are nonlinear loads, causes the harmonic currents in the system. These harmonic currents in turn create system resonance, capacitor overloading, decrease in efficiency, voltage magnitude changes. Power quality has become an increasing concern to utilities and customers. The power transmitting in a distribution line is needed to be of high quality. One of the major power quality issues is considered in the distribution system called Voltage sag and can mitigate with the help of dynamic voltage restorer. In this paper, Focusing on the novel integration of solar PV-Battery based Dynamic Voltage Restorer is implementing in the distribution system to meet the necessary power and for power quality improvement. Solar photovoltaic with boost converter is implemented by incremental conductance method to track the Maximum power. The performance of solar photovoltaic, Battery with Dynamic Voltage restorer is simulated under dynamic conditions of the load in MATLAB-SIMULINK software.

In this research, we propose an image security scheme using hybrid compression techniques. In this scheme, the data is being provided two-fold security by both encryption stage and hiding stage. The data/message which has to be secured undergoes encryption technique at the initial stage. In this stage, the permutation algorithm is employed which requires a pair of numbers as a key to permute the original message. Following the encryption stage, the deformed message is then embedded onto a JPEG image by considering the low and high quantization tables. The main motivation behind this research work is to provide image security through compression. The final result is an encrypted and compressed JPEG image with a different image quality. The receiver has to perform the reverse process to extract the original data/information. The performance analysis is performed in terms of PSNR for different quantization tables.

A novel channel based rescheduling scheme for modern turbo convolution code is proposed by the inclusi on of suboptimal and low-complex max-log-MAP algorithm. Demands for dedicated custom solutions in mobile communications and its related applications leads t o a reconfigurable architecture for Turbo convoluti on code. This study comprises the design and performance evolution of the proposed reconfigurable architecture for channel coding scheme in MIMO-High Speed Downlink Packet Access (MIMO-HSDPA). To attain effective performance close to shannon limit in a multi chann el system, flexible reconfigurable architecture is realized with 28 nm cyclone V GX 5CGXFC5C6 FPGA. We achieved throughput of 13.5 Mbps compared with the conventional HSDPA standards while consuming 53 mW.

In this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The main motivation behind this research work is to classify the brain tissue. By comparing the proposed method with other conventional methods, it is clear that our algorithm can estimate the correct tissues WM, GM and CSF much more accurately than the existing algorithms with respect to ground truth image patterns. We achieved an accuracy rate of 98.9% for Gray matter segmentation, 94.1% for White matter segmentation and 90.8% for CSF segmentation.

The WECS based Doubly Fed Induction Generator (DFIG) system is presented in this paper which includes different MPPT control strategies for a grid connected system. The GSC gives the flow of power from the rotor part of DFIG up to the grid and the modulation of DC voltage. Here the cuckoo search algorithm based on MPPT is designed, to obtain a higher power from the changing speed wind turbine. The algorithms such as Perturb and Observe (P&O), Proportional Integral (PI) control and Fuzzy Logic Controller (FLC) are compared and their performances are evaluated. To design and develop the cuckoo search optimization based on MPPT for WECS, and to obtain optimum voltage regulation and power, thus improving the working performance, reducing the domain time and minimizing the performance indices. To simulate the different MPPT control methods, MATLAB/Simulink environment is used here.

Problem statement: The visual effects of blocking artifacts can be reduce by using deblocking filter. Also with out smoothing the natural edges,the perceived quality of video sequence can be enchanced. This study propose a method to remove blocking artifacts in low bit-rate block based video coding. Approach: The proposed algorithm has two separate filtering modes, which are selected by pixel behavior around the block boundary. In each mode, proper one-dimensional filtering operations are performed across the block boundary along horizontal and vertical directions, respectively. In the first mode corresponding flat regions, a strong filter is applied inside the block as well as on the block boundary, because the flat regions are more sensitive to the Human Visual System (HVS) and the artifacts propagated from the previous frame due to motion compensation are distributed inside the block. In the second mode corresponding to other regions, a sophisticated smoothing filter, which is based on the frequency information around block boundaries, is used to reduce blocking artifacts adaptively without introducing undesired blur. Even though the proposed deblocking filter is quite simple, it improves both subjective and objective image quality for various image features. Results and Conclusion: Deblocking filter improves the PSNR of about 0.1 dB for video encoded using MPEG-4 and H.264 without using its own in-loop deblocking filter. It has proven to be good in the reduction of the very annoying blocking artifacts caused by video compression.

Background: Robot kinematics suggests and interprets the relationship exists between the kinematic position connectivity and acceleration of each link. In any of the robot manipulator the kinematics solution may be forward kinematics or inverse kinematics. To determine the joint values for a provided desired end effector orientation and position, the inverse kinematics principle is applied. Inverse kinematics is the usage of kinematics equations of a robot to find out the joint parameters that gives a targeted position of the end-effector. Methods/Statistical Analysis: In this paper, inverse kinematic solution for a five joint robot involving intelligent prediction response method has been developed and the result will be analyzed based on the performance. The intelligent prediction response method will give the performance based result, which shows the five various angles of an industrial robot. The single variation in the joint angle will be analyzed for every joint angles. This method based inverse kinematics solution is much more useful in real-time adaptive robot control where shorter calculation times are required. Findings: The MATLAB 13.0 is used to find the solution for a set of joint parameters. The actual reading and MATLAB program was found acceptable level. Applications/Improvements: To solution provided for the inverse kinematics problem with number of joint angles using the intelligent prediction response method such as artificial neural network is used.

Congestion management is the technical challenges in a deregulated power system environment. In Congestion Management the allocation of Congestion cost, Generation cost, losses are a main issue. In this research paper optimal generation levels in deregulated markets are determined. The major problem in deregulated system is congestion in the transmission lines, which limits transfer ability of a power system with existing generation capacity. Locational marginal price (LMP) of every generator at every bus is to determine by using nodal pricing method. Determination of Locational Marginal Price and maximization of the social welfare are objective functions in congestion management. The Simulations are done by using power system analysis tool box(PSAT-MATLAB)software in IEEE 6 bus test system and IEEE 14 bus system.