Control Applications in Modern Power System

DC-DC converters have a wide range of applications in power electronics industries. This paper focused on the design of non-ideal buck converter for CCM mode along with type-III compensator for its closed loop operation. The type-III compensator lets us boost the phase angle more than 90°, practically up to 160°. By the use of type-III compensator, we can obtain a stable and fast transient response with small steady-state error. Finally, the MATLAB simulation result will help to compare between the open loop and closed loop converter response.

Due to the high proliferation of distributed energy resources, forecasting ability is an essential thing for the power system state estimator. In this paper, dynamic state estimation is modeled as a multivariate time series forecasting problem. Detailed analysis is carried out to understand the patterns and characteristics of voltage-time series. A Vector Auto-Regression (VAR) model is fitted with the training data, and the various parameters required for building a Vector Error Correction Model (VECM) are found out. Finally, VECM is employed for the first time to forecast the voltage values both for single and multiple time steps. The main contribution of the paper is the development of VECM model for power system state forecasting.

Market grounded pricing of electrical energy provides consumers with the liberty of lowering their electricity bill by shifting the load to lower price slots. First part of the work presented in this paper is the outcome of application of DSM techniques to residential consumers. The proposed algorithm schedules the charging time for household inverter battery for the next day considering day ahead pricing, hence lowering the peak demand on utility and generating savings to consumers. Second part of the paper proposes an optimizing algorithm for charging PHEVs parked in a parking garage at a work place. Based on power demand and duration of stay, PHEVs are prioritized and charged. Part of the demand is met by solar PV panels and rest from utility mains. MATLAB tools have been used for performance evaluation and algorithm implementation.

This paper presents a new differential evolution-artificial electric field algorithm (DE-AEFA) for stabilizing frequency and voltage of combined load frequency control (LFC) and automatic voltage regulator (AVR) of a two-area hybrid system simultaneously. The proposed DE-AEFA algorithm is applied to optimize the gains of proportional-integral-derivative (PID) controller. The secondary controller in combined is optimized based on various performance indices and their combinations. Moreover, the secondary controller is not adequate to maintain the system stability during large disturbances. So, additional control devices are necessary to maintain system stable under large load variations. Therefore, redox flow batteries (RFBs) and interline power flow controller (IPFC) coordinated control strategy are used to damp out the variations in dynamic responses under large disturbances.

An interconnect power system is often divided into different control area as they are operated by different utilities. These areas are connected by one or more circuit with help of transmission line which are called tie line. For proper operation system, frequency should be kept near constant and power flow between different areas should control at scheduled value despite the deviation of load in different area. Load frequency control is the study of how to control frequency deviation. This frequency deviation can be controlled using the prospered designed controllers. Two controllers, PID and 2-DOF (Degree of freedom)-PID controller, are used as auxiliary controller one after one in the system. Both controller’s parameter will be optimized by firefly algorithm which is a bio-inspired algorithm. A comparison is done between the results of both controller for settling time, oscillation, peak overshoot/undershoot.

In this paper, a refreshing tuning of proportional-integral-derivative (PID) controller in the combined effect of load frequency control (LFC) and automatic voltage regulator (AVR) by using differential evolution-artificial electric field algorithm (DE-AEFA). Error squared over integral (ISE) performance index is considered as fitness function for optimization. Moreover, DE-AEFA algorithm performance is compared with the classical algorithms like particle swarm optimization (PSO) and artificial electric field algorithms (AEFA). However, the secondary controller is not adequate to control the system deviations under large disturbances. So, an additional controller is necessary. For this, the system with coordinated control strategy of thyristor controlled series compensator (TCSC) and superconducting magnetic energy storage (SMES) devices has been implemented. Investigation reveals improvement in system dynamic response with TCSC injection. The combination of SMES and TCSC boosts up the system performance.

The research work presented here shows the fuzzy-PID control scheme for operation of a hybrid power system. The multiple technologies have been combined together to produce power in a hybrid electric power system. The model considered in present work contains different types of renewable energy components to create a hybrid power system. The solar photovoltaic cells and wind turbine are used to produce hybrid power. Thus, produced power has been stored in various energy storage devices. Various components such as ultracapacitor, battery, flywheel systems, etc. are used to store the produced energy. To maintain a constant power flow, grid frequency deviation is need to be minimized. This paper investigates the performance of various control controllers: PID and fuzzy-PID to maintain constant power flow to the load. The constraints of various controllers are tuned with grey wolf optimization (GWO) technique. It has been found that GWO tuned fuzzy-PID controller outperforms the other controllers which minimizes the frequency deviation to provide constant power flow.

Reduced-order modelling is now becoming an important tool in almost all Engineering fields. Therefore, motivated by various real Engineering problems, this study contributes, a new classical approach of reduced-order modelling for continuous linear time-invariant (LTI) systems. The suggested method is based on the concept of direct comparison of the coefficients of the reduced and computational expensive higher dimension given system. In this method, the coefficients of the numerator and denominator of the original and the required reduced dimensional system are directly compared. Furthermore, the efficiency of the proposed method is observed not only when testing in a reference system with a linear continuous single-input single-output (SISO), but also in relation to the design of a controller in the power system. First of all, an automatic voltage regulator (AVR) used in power generation is reduced using the proposed method. The proposed AVR model is used to develop a proportional integral derivative (PID) controller for the original high-dimension AVR system. Also, an evolutionary algorithm, namely, particle swarm optimization (PSO), is used to search for unknown parameters such as Kp, Ki, and Kd of the PID controller taking Integral Time-Absolute Error (ITAE) as error criterion.

This paper presents a novel scheme of dynamic state estimation (DSE) for power system states based on Unscented Kalman Filter (UKF). For the purpose of DSE using UKF, complex line current and complex bus voltage are utilized as a set of measurement vector that is obtained from PMUs, considering PMUs placed at all the buses (PPAB) and also PMUs placed at optimal location (PPOL). Unscented transformation (UT) technique has been utilized for the implementation of UKF that gives direct procedure of transforming mean and co-variance information. UKF has been compared with traditional weighted least square estimation (WLSE) to show the supremacy of UKF-based DSE. A major issue in power system state estimation is to tackle with highly nonlinear mathematical equation of power system network. This nonlinear equation is linearized utilizing Taylor series expansion in which derivative operator is involved. In view of this, a new approach of DSE has been formulated which is exempted from the derivative operator which is a major challenge in power system state estimation. The suggested DSE approach based on UKF utilizes linear relationship between complex PMU measurements and complex state variables and is derivative-free approach. The proposed method has been implemented on IEEE 6,14,30,57, and 118 bus systems. The obtained results show that the suggested approach is better compared to WLS-based SE scheme.

During winter season, in foggy environment, accidents are evident on national highways and many people succumb to death due to these accidents especially in Northern and Eastern region of India. To avoid such accidents, the authors have proposed a Raspberry Pi-based image processing approach to save the life of human being. An ultrasonic sensor detects the obstacle/vehicle and measures the distance. Once the obstacle is within the range, the edge detection algorithm processes the fog image and produces enhanced quality images displayed to the vehicle driver. The advantage of the proposed approach is that with the information achieved from ultrasonic sensor, the driver may have to apply the sudden brake to avoid accidents with the front-side vehicles but the backside vehicle may collide with his/her vehicle. But the enhanced image spatial information is useful to the driver in taking the decision whether to apply the brake or overtake the obstacle form left/right side to avoid accidents from backside vehicles also. Further, the high processing capacity of Raspberry Pi produces results within fraction of seconds (real time) to give sufficient amount of time to the driver to take appropriate decision to save life.

In this chapter a fractional order (FO) based PD structured static synchronous series compensator (SSSC) is proposed to enhance power system stability. The controller parameters are tuned by using the modified sine cosine algorithm (MSCA) which is developed in this chapter. The controller performance in a single-machine infinite bus system is verified with different loading conditions. Furthermore, to demonstrate the effectiveness of the developed MSCA algorithm the MATLAB/SIMULINK results obtained are compare with the results obtained with genetic algorithm (GA), particle swarm optimization (PSO), and conventional SCA. The comparison between MSCA with those of other algorithms confirms its dominance in the current context.

An active power filter (APF) based on optimized PI controller is proposed for harmonic mitigation in power quality enhancement. It employs the metaheuristic techniques like eagle perching optimization (EPO) and harmony search algorithm (HSA) to obtain the minimum THD in the system under rated operating condition. The proposed system is verified through MATLAB Simulink environment.

The performance of the standard PID controller is unsatisfactory for processes that vary over time. In those scenarios, adaptive controllers can adjust the control behavior by adjusting the process dynamics and unwanted load changes. The desired process performance parameters are given in the model reference adaptive control (MRAC) as a reference model (RM). The adaptation method modifies the control outcome by the difference between reference model and the performance of actual process with a fixed adaptation gain (γ). This research explores the various MRAC technology for under-damped second-order process and with dead time. The first one is focused on the MIT rule, the second is the modified MRAC method. The modified controller assures better response, improved set point tracking with less oscillation and lower oscillations during unfavorable loading changes. This fact is also confirmed by using various performance indexes under closed-loop operation. Using Simulink, the methods are showcased.

This manuscript emphasizes analytical and experimental study of 1-phase grid integrated solar photovoltaic generation systems. A comparison between sole stage and double stage topology for solar grid-connected system is presented. A small scale double stage solar photovoltaic generation system is modelled and simulated. A fuzzy logic perturb and observe maximum power point tracking controller is implemented. A model predictive current controller with switching frequency constrain is proposed for the grid side interfacing inverter. The controller reduces the harmonic distortions present in the output current of the grid interfacing converter. It is also characterized by fast dynamics regulating the output power factor consistent with the fluctuating load demands. The cogency of the proposed controller is authenticated by experimental implementation using dSPACE 1104 real-time controller.

The increasing renewables penetration leads to reduction in system inertia and may have negative impact on damping of low-frequency oscillations (LFOs). In this paper, a technique to improve the system small signal stability is proposed using a robust coordinated tuning approach of damping controllers. An improved fitness function is proposed to simultaneously maximize the LFO modes damping ratio and shift the eigenvalues to left-hand side of s-plane. The coordinated tuning is achieved using an advanced meta-heuristic technique Marine Predators Algorithm (MPA). The results of MPA are compared with other techniques to prove its superiority in handling this complex problem. The study has been carried out on benchmark IEEE 39-bus test system. Further, eigenvalue analysis and time-domain simulations are executed to demonstrate the capability of suggested control approach. The critical scenarios are simulated to test the robustness of the coordinated tuning. The results substantiate the potency of proposed strategy and robustness in improving the LFOs damping under varying system operating conditions.

IoT-based systems are widely used for monitoring purposes through remote servers. These systems find their applications in recording as well as monitoring real-time data. This chapter discusses cloud-based monitoring, for variation in voltages using ESP32S, ThingSpeak in an experimental setup. The experimental setup comprises a DC source, boost converter, potential divider, ESP32S and ThingSpeak as a remote server for monitoring. The real-time data about the voltage is visualized in a remote system using ThingSpeak. This data is user friendly and allows private as well as public information. The data can be useful for analysis, study performance and to reproduce flaws in real-time system. Thus, the IoT-based system finds its utility worldwide with high encryption.

The conventional reclosing system generally follows the prefixed operating time to close the breaker followed by any transient fault. In a microgrid system with a storage facility, the uninterrupted power supply can be provided with the help of a storage system for a short time period. For that time period, the faulty section is generally disconnected from the rest of the healthy system and again reconnected after the clearance of the fault. In that case, if the fault clearance phenomenon will take more time than the battery system will not able to manage huge load demand and may get out of the system and this will lead to an unstable system condition. To avoid such a condition, in this work an adaptive reclosing approach is proposed which will reclose the breaker immediately after the clearance of the fault condition instead of following the conventional setting. The current signal measured at the local end can be processed by the intrinsic time decomposition technique and the energy function of the first intrinsic mode function (IMF) provides accurate information about the fault clearance. By using such an index, adaptive reclosing is possible in a microgrid system. To verify the response of the proposed method, different standard microgrid system models such as distribution network located in Aalborg, Denmark and modified IEEE 13 bus distribution network with hybrid distributed generators (DG) and battery energy storage system (BESS) are considered and simulated using EMTDC/PSCAD software. Different fault cases, islanding condition and non-islanding cases are simulated to verify the response of the proposed technique.

Because of the expansion in industrialization for the different advancement programs, energy emergency is being looked at by many developing nations like India. India is supplied with these assets, which are both practical and financially exploitable. Small scale power generation close to the purchaser premises is accepting a lot of consideration in the on-going years for its utilization in remote and rustic networks in view of the expense and complexities which is associated with the grid augmentation. India is the main nation to set up a service for non-conventional energy assets. A significant number of the Indian states show dynamic advancement in Renewable Energy Sources (RES) programs, however many of the states are yet lingering behind because of numerous issues that should be kept away from. Integration of RES into traditional energy framework is one of the most feasible advancements to meet the voltage regulation energy request productively. Be that as it may, this advance emerges a ton of difficulties which are important to be dealt with for smooth activity of the system. Voltage regulation is the most noteworthy specialized test that is in general breaking point measure of infiltration of inexhaustible distribution generators (DGs) into the transmission arrange. This paper endeavours to introduce a voltage regulation of hybrid energy. Furthermore, the proposed investigation additionally gives the experiences to the potential solution for voltage rise issue. The simulation results, gained by executing the proposed structure showing system, show the practicality of the proposed demonstrate and construe the centrality of security constraints in the microgrid energy the board systems.

Community microgrid can be one of the efficient option for supplying rural loads or local area operation. Community microgrid is the most reliable and economical concept for meeting the current trends along with individual advantages of each microgrid. Community microgrid with the group of hybrid DC/AC microgrids can be connected with suitable techniques for maintaining the quality and continuity of power to the assigned area. These systems may operate either in grid connected or islanded mode. The implementation of community microgrid calls for efficient strategies of power exchange with utility grid and also reliability and stability of interconnected system has to be maintained. This paper discusses the important control and coordinating techniques of community microgrid system.

With concern of environment and less availability of conventional energy sources, renewable energy has grabbed more attention for future source of energy due to its abundant availability. Effective utilization of available renewable energy sources is necessary to fulfill the increasing demand for electricity. Now-a-days Distributed Renewable Energy Sources installed over consumer premises is more advantages than a large aggregated system, which overcome the problems of locational and temporal characteristics of renewable energy. Benefits of Distributed Renewable Energy Systems enlighten the Integrated Renewable Energy Model (IREM) with battery backup to full fill the rural and faraway area’s Electrification. Assuming the present scenario, with advancement in technologies Medium Cost High Ratings (MCHR) appliance used as all possible loads. In this paper, one of the concepts are highlighted that can be adapted to full fill the power demand. For which Energy management concept is used to increase the effective utilization of renewable energy sources and optimal sizing is verified and compared by two well-enhanced techniques: particle swarm optimization (PSO) and Jaya algorithm. Objective function of this optimization is Cost parameters involving Total Overall Net Cost (TONC) of generation and Cost of Energy (CE).

The Smart Grid is an improvement on the traditional method of distributing the power supply to the factories along with controlling it at residential areas accordingly. The idea is to digitize the power consumption by various high-load devices on the grid. When the load on the electricity grid rises, power cut becomes necessary. But complete power cuts are uncalled for when main culprits are high-load appliances. That is why in this work, the load-level information is instantly transferred from the regional grid to residential areas. It is then used to regulate only high-load devices in households. The consumer’s bill preferences are kept in mind while calculating the overall monthly expenditure. They can even look at informative graphs depicting their monthly power consumption. Before any power regulation or if the consumer’s monthly bill exceeds their set preference, an alert will be sent through email. This is a huge improvement as this approach is smarter and more energy-efficient than ever before.

To deal with the current environmental problems the hydrogen production seems to be a sustainable fuel solution. The most frequent way of extracting hydrogen is electrolysis. Solar energy is an abundant source of energy that is freely available globally and can be used for electricity generation. Solar Photovoltaic (PV) systems can thus be employed for powering water electrolysers to produce hydrogen. In this paper, we develop a fuzzy set-based model for computing the efficiency of a water electrolyser powered by a solar PV array. The accuracy of the model is tested against the field database used for its construction and a good fit has been obtained. The developed model can therefore be recommended for subsequent simulation-based investigations.

India is a country having various temperature zones from north to south and east to west. Zone wise challenges are the barrier to achieve 100 GW electricity from Solar Photovoltaic (PV) technology. The significant challenges are the scarcity of land and grid synchronization, which depends upon prime factors like radiation and temperature. Not only radiation but the temperature is also a prominent parameter, its impact must be studied temperature zone wise. The micro-level study will provide a closer look at the performance in context to the economical and technical aspects. Keeping this in mind a study and analysis is carried for a 50 kWp system, which is installed on the roof of the official building of the university in Mathura in which m-Si technology-based PV modules are used. It is seen that the required land area for c-Si, m-Si, A-Si, thin-film, and HIT technology is 828, 906, 1621, 1179, and 680 m2, respectively also With respect to HIT, c-Si 38% and m-Si 31% provides more instability in open-circuit voltage while, a-Si 28%, and thin-film provides 28% less voltage instability for same average radiation. Hence a power plant system based on HIT gives the better trade-off between area and voltage instability.

This paper investigated an effective water evaporation optimization algorithm based approach to improve the effectiveness of the distribution network. The optimal accommodation of multiple photovoltaic (PVs) generation source and its coordination with network reconfiguration is used to minimize the network energy loss. The coordination of PVs and dynamic network reconfiguration of the distribution network is a complicated optimization problem. The problem of dynamic reconfiguration of the distribution network is mixed-integer, non-differentiable, and of an extremely complex combinatorial nature. Besides, the constraint of radiality usually rises the complexity of the evolutionary meta-heuristic optimization algorithms. The developed methodology is based on the foundation of graph theory, which limits the search space and also prevents repetitive mesh checks. The developed methodology is proficient and ensures that only possible radial topologies are generated. This coordinated operational planning is subjected to the distribution system constraints such as limits of feeder current, limits of node voltage, and power balance, etc. The suggested methodology is tested on the IEEE radial 33-bus distribution system. The results show that optimal accommodation of multiple PVs and its coordination with dynamic network reconfiguration reduces the network loss to 20.24% and also maintains node voltage within the specified limits.

The renewable energy generation has to lead the power systems of the world to establish a new era in developing a sustained environment for energy proliferation. The demand for energy has routed us to fulfilling the need based on sustainability, security and affordability for humanity. And that credibility in the production of energy with harmony and making it eco-friendly for the well-being of society is possible with the refurbishment of technology. The perennial renewable energy is PV-Wind system has to lead the researchers to think more widely and here we have proposed the PV-Wind Hybrid system. In this, the controlling of MPPT of the (Photovoltaic) PV system is done by Neural Network-based Model Predictive Controller for maximizing the output of the system. And for increasing the authenticity and proficiency of the system we have used Model Reference Controller with PI controller for controlling the pitch angle of PMSG based Wind Turbine. In Hybrid network of PV-Wind, the accession of prowess DVR system is implemented with the ANFIS Controller for accretion of the production of the system and supplying of consistent power for an efficient system. The simulations were performed using MATLAB/Simulink and the results-oriented are justified.

The problem of Economic Dispatching (ED) is crucial to the functioning of the power grid because it provides the generators with an optimum schedule such that the overall generation running costs are minimized while fulfilling the generator and system constraints. Conventional ED takes little account of the valve’s point load on cost curve, the probability of rising and reducing fuel. The above problems cannot be overlooked, because they are a more practical solution to ED’s problem. The ED problem is called dynamic economic dispatch (DED), taking into account the ramp limits and valve point effects. The purpose of this work is to solve the problem of a ten generators DED system using modified particle swarm optimization (MPSO) approach. The solution achieved by MPSO provides the best possible solution compared to PSO, and the outcomes are discussed properly.

This paper outlines some electromagnetic compatibility (EMC) tests according to the acknowledged international standards, and some causes of and solutions of the problem of electromagnetic interference. The EMC stability of several electric energy meters widely distributed in the Slovak electricity distribution system was tested in the EMC chamber Comtest EMC 1710-1. The experimental results of the study of electromagnetic interference influence on power meters’ error are obtained and analyzed, and probable reasons for failure of immunity tests and recommendations to avoid failures are given.

Analysis of small-signal stability of a multi-machine power system is done incorporating flexible AC transmission systems (FACTS) and power system stabilizer (PSS). Static VAR compensator (SVC) and thyristor controlled series reactor (TCSC) are presented in this paper. The model is linearized before developing the system matrix. Different meta-heuristics are employed for proper tuning of controller parameters, and results are compared. For individual effects of the addition of SVC and TCSC, the model is also analyzed. With the hope of further improving the overall system stability, the small-signal stability analysis is investigated in presence of FACTS in coordination with PSS.

Proper threshold setting provides accurate and reliable decisions by fault detector (FD) during faults in transmission system. For identification of such threshold, extensive case studies are needed to be investigated by varying different possible fault parameters of the power system components. If the upper and lower limits of fault parameters are separated by large magnitude, then identification of threshold is a complex task. This paper introduces an optimal threshold setting mechanism for FD by using teaching and learning-based optimization algorithm (TLBO) under large variations of fault parameters which enhances the overall performance of the FD. Later, the performance of the FD assisted with optimal threshold achieved by TLBO is tested under different case studies and comparisons are provided with particle swarm optimization (PSO)-assisted threshold-based FD. All the results are carried out in MATLAB-SIMULINK software environment.

Multi-threshold CMOS (MTCMOS) is a well known technique for limiting both leakage current and standby energy consumption in non operatory mode of any circuit. Although, this technique suffers from energy consumption during mode transitions. Here, a new stacking MTCMOS structure is presented which reduces the magnitude of leakage current and gives a method to limit the energy consumption in transition mode. The proposed design has been mathematically analyzed to meet the respective goals, i.e. minimizing the leakage current and minimizing the static energy as well as mode transition energy. In order to calcualte the effectiveness of proposed design, the simulation has been performed on a 1-bit full adder circuit using cadence Spectre 90-nm CMOS technology. This technique reduces the value of leakage current and static energy consumption as well as mode transition energy significantly as contrast to the conventional MTCMOS circuit.

In the paper, an algorithm of backward/forward is suggested to solve the load flow of the radial AC microgrids which are controlled by their droops operating in islanded mode. These systems lack a slack bus. The unknown variable is the frequency of the system. The algorithm is established on the backward/forward sweep which is having an advantage that these are derivative free. With the conventional BFS method new equations have been consistently expanded and included. The only mathematics involved is the calculation of flow variables such as apparent powers and the complex currents. The power flow for a 33-bus test system has been solved with the algorithm. The algorithm has been performed under MATLAB environment. The suggested method is uncomplicated, precise, and easy to implement which can be utilized as an appropriate tool for the planning and the analysis of microgrid.

Reliability of power system is associated with the difficulty of measuring the capability of the transmission and generation system to supply adequate and appropriate power at foremost load position. Monte Carlo simulation (MCS) model consists of the sampling of states, evaluation of states, and estimation of reliability parameter in reliability examination of the electrical system. Here, states are sampled from the state space and indices are computed by statistical inference. Reliability parameters have broadly two sets for estimation of reliability: deterministic and probabilistic. This paper deliberates the review on power system reliability evaluation using MCS. Power system components can be modelled in different states and the bidirectional transitions between these states are used to evaluate the associated cumulative probability of each state. MCS uses a random number to estimate the reliability parameter. Random sampling and sequential simulation are two methodologies used in MCS technique. A detailed review of composite system reliability through MCS is discussed in this paper. The paper discusses an algorithm to estimate the sampled data of power system reliability study using MCS technique. MCS makes system more efficient in terms of computation of reliability parameters.

In the era of ever increasing deregulation in power systems, load growth due to improvement of global economic rise, industrial infrastructure development, social living status of people, the power system faces new challenges every single day. However, the power system has to operate under these ever changing conditions in order to meet the load demand satisfying constraints pertaining to technical, environmental, and regulatory issues. In order to achieve this, system must be stable. Of all stabilities related to power system, voltage stability achieves significant importance because of its inherent nature of gradually endangering the power system operation leading to system blackouts. The major reason for voltage instability is the system operation under stressed conditions which is a consequence of many technical issues such as limited generation, increased loading, and transmission congestion. In this situation, it is essential to supervise the power system for an extensive range of system circumstances in order to assess voltage stability. FACTS devices prove to be extremely useful in enhancing the voltage stability limits of the power system. Hence, keeping in view, the current scenario of power system deregulation, it is intended to study the effects of incorporating renewable energy sources in power system network and the effectiveness of FACTS devices in improving the voltage stability margin. The proposed work has been implemented on modified IEEE 14 bus test system and the results are analyzed.

Energy savings has become the essential part for the growth of any country. India is targeting the generation of electrical energy by the non-conventional resources. In this part, the solar energy is most popular among all non-conventional energy resources; and hereby, the techno-economic analysis of the grid-type roof-top photovoltaic (GRPV) system becomes important for system forecasting. This paper present energy & economic analysis of 100 KW GRPV system. This GRPV system is designed and constructed at NITRA, Ghaziabad, India. The step-by-step-based approach for the energy & economy analysis is covered in the presented study (specifically for GRPV system). Also the embodied energy (EEin) calculation and benefit–cost–savings analysis are covered in the study.

It is generally observed in India that buses are responsible for a lot of traffic obstruction owing to many factors such as improper driving, premature stoppage in traffic, and misaligned stoppage at bus stops and due to these reasons and may more the bus transportation service in the National Capital Reason has come to be deemed as unsafe and unreliable by many commuters and they have thus come to rely on other forms of transportation like global positional system enabled cabs, motorcycles, and auto rickshaws which are adding to the growing traffic crisis. To tackle the formerly mentioned problems, the bus transportation needs to become more organized and reliable and to achieve the same, this paper focuses on the design of an application that utilizes RFID tags and intercommunication of specialized hardware to ensure that bus transportation does not obstruct the flow of traffic near bus stops as is generally observed while also improving reliability of the same so that more general population switches to public transportation thus resulting in an approximated significant reduction in number of vehicles on road while also reducing the possibility of obstruction of traffic flow caused by buses leading to reduction in overall commute time and smoother flow of traffic along with up gradation of existing infrastructure to accommodate the charging of smartphones, an in house ticketing kiosk and operation of informative video interfaces powered via mounted solar panels in turn making bus transportation more reliable, convenient, organized, and viable.

Smart buildings have become a hot bed of innovation over the past 4 to 5 years. The Internet of things (IoT) is constantly making the devices more connected and more intelligent. Smart buildings are more-off a wholly integrated system using IoT sensors and building automation to control various aspects like HVAC, lighting, security along with user-centric functions like meeting room scheduling and way finding. With increased number of IoT devices, there is a huge influx of data that needs to be handled in a proper secure manner else problems surface out due to data compromise resulting in cyberthreats. Also, wireless technologies are leveraged to a huge extent to achieve smarter applications which in return results to unintended exposure to radio frequencies causing health issues. The scope of work for this paper is to analyze the different aspects of smart buildings from technological perspectives and its harmful effects on building ecosystem as a whole.

Content-based image retrieval (CBIR) systems find a lively application in various fields like medical diagnosis, crime prevention, art collection, textile industry, etc. CBIRs continue to be an active domain of research due to increasing image databases and complex user queries being generated. The major challenge faced by such systems is the existence of a semantic gap between low-level features and human perception of the object’s images. Many CBIR systems exist in literature which aims to reduce this gap so as to produce precise search results for complex user queries. So this article aims to analyze and survey such systems based on the preprocessing, feature extraction, and classification techniques they employ for image retrieval while simultaneously focussing on the associated advantages and disadvantages for each of the discussed schemes.

The paper consists of a prototype model of multi-utility mist vehicle (MUMV) for firefighting with fully automated by the combination of AC motor, DC motor, reciprocating pumps and chain drive in order to work in a vital role in confined areas. In this proposed prototype model, diaphragm pump is utilized to pressurize the water and discharge through fine orifice spray nozzles. Further, the pump inside the vehicle regulates the pressure required to generate the water mist and the regulated pressurized water which flows through the nozzle comes out as water mist. The proposed prototype model has been tested on different combinations of pumps and nozzles in order to ensure that consumes small amount of water and time taken for firefighting. Thus, the results revealed that the proposed prototype model is efficient in controlling fire as well as to extinguish the fire.

Electrical energy has become an essential and basic need across the world today. The demand for electrical energy has been increasing which has caused an increase in the load in unexpected ways as the world approaches deregulated power systems and yet such systems are poorly controlled. Voltage instability can occur due to unexpected increment in load in highly loaded systems. Therefore, security analysis is an important aspect in securing the power system with contingency switching. Evaluating overall performance index (OPI) is needed and crucial in controlling the power systems in such an environment. Connecting the thyristor-controlled series capacitor (TCSC) to the system provides an effective way of contingency ranking of the most severe lines by evaluating the OPI and also enhances the security of lines. The main objective of this paper is to rank the most severe line through integration of TCSC to the system. Voltage and active power performance index is evaluated using Newton’s load flow study to predict the most severe line based on the highest OPI that can further extended for analysis of security of network topology.

Cloud computing is gaining popularity in view of its accessibility, availability, flexibility, cost-effectiveness and many more. Accordingly, several firms are hosting cloud-oriented applications for fulfilling their business requirements. Consequently, cloud service providers (CSPs) are facing various challenges and striving for cost-effective solutions. One resembling challenge is energy consumption by datacenters as it substantially affects our environment by generating carbon footprints. To abate this challenge, renewable energy (RE) sources, such as solar, wind and hydropower, play an integral role. It also curtails the usage of non-renewable energy (NRE) sources, such as oil, gas, coal and hydroelectricity. Recent research has shown that the user requests are assigned to the datacenters based on the highest available RE resources, cost, static ordering and many others without any emphasis on utilization. In this paper, we propose a RE-based task consolidation (TC) algorithm, called minimum utilization (MinUtil), to assign the user requests to the datacenters by considering the utilization of user requests and resources. Here, TC is used to improve the utilization of resources. The utilization of NRE resources is restricted to a pre-determined threshold in order to reduce the generation of carbon footprints. We simulate the proposed algorithm using MATLAB and perform the simulation runs on four generated datasets concerning the findings in terms of energy consumption (EC), overall cost (OC) and number of used RE (|URE|) resources. We compare the outcomes with two existing algorithms, called round robin (RR) and random, to show the efficacy of the proposed algorithm.

The author proposed a methodology to install the AC–DC hybrid microgrid to face the scarcity of electricity. The microgrid provided reliable electricity at a competitive price for the consumers and social welfare. A mathematical multi-objective problem is formulated to optimize the microgrid system and algorithm to manage power generated through different renewable resources. The microgrid consists of solar PV, wind turbine, biogas power plant, and battery storage system. The author also proposed the mathematical model for all RES and optimized the system using the Pareto front technique. This study provides a demonstration of present microgrid power management concept, controllers and their scenario.

The battery management system is a protection device used in power lithium-ion batteries of off-grid generation systems and electric vehicles. Such systems need to control the battery charge and discharge and identify and correct any battery problems. Battery cells degrade unequally since they are not built identically. Because of that, nowadays, many functions of the battery management system depend on measurements on each cell or stack of cells that compose the battery pack, necessary to ensure the system’s safety and integrity. A new methodology to identify batteries with damaged cells is presented in this study and locate their positions in the electrical circuit, using only terminal measurements and artificial neural networks. The proposed method was tested in a set of five cells, and high precision was obtained in the simulation results.

Precise solar generation forecasting is dependent on parameters like temperature, radiation, humidity, and the time of day conditions. These conditions when combined play a role in forecasting the output of solar energy system. In this paper, considering the above-mentioned four variables, a simple and accurate method for prediction of solar power generation with the help of fuzzy logic model based on the Mamdani method has been proposed. Simultaneous correlation of the weather-dependent variables has been evaluated, and solar power generation is forecasted at a particular location in Delhi using the proposed methodology. A solar data logger system has been used to log the ambient weather conditions along with the instantaneous solar power output. The fuzzy system is then trained on the logged values with the comparative analysis of the forecasted power versus the real-time data. The fuzzy model has also been trained on the National Renewable Energy Laboratory dataset for further accuracy.

Airborne wind technology eliminates the structure costs and reaches higher altitudes for extracting the power from stronger winds. The main objective is to perform the aerodynamic test on the airfoil kite with lightweight, low-power wireless devices for better data reception. The kite maneuvers in eight shapes to deliver maximum power; therefore, the positioning device has to be low powered, low weight, and weatherproof, to avoid indeterminacy in airfoil flight at 200–300 m altitude. The device consists of ultra-low-power TI CC1310 SimpleLink Sub-1Ghz wireless Microcontroller Unit (MCU), GPS Sensor, Inertial Measurement Unit (IMU) to find the speed, direction, longitude, latitude, and altitude, roll, pitch, and yaw at the ground station, for controlling the tethered wings autonomously. The base station receives data at 868 MHz optimum frequency at 50 kbps data rate; the optimized frequency is estimated using a virtual toolbox and a field test.

The diesel engine today is an essential part of automotive, industrial, and power generation applications like trucks, buses, excavators, and gensets. As India transitions to the Bharat Stage (BS) IV norms for construction segment in October 2020, there is a need to have better control of the combustion process of the diesel engine to meet the stringent emissions and performance needs of the customers/applications. The market today has extensive population of mechanical engines, but these engine systems will fail to meet the stringent norms coming into effect, as conventional system has inherent problems of finer controls. These drawbacks can be alleviated by use of the electronic engines, but not without an increase in the complexity of the architecture, viz. huge number of sensors and actuators and an electronic controls module to process and controls these. Integration of electronic engine can also be used to enhance engine performance, safety of the operation and the engine itself. This paper portrays the procedure to approve a portion of the electronic engine highlights like sensor out of range, programming, and equipment logic by means of unit and framework level testing utilizing Hardware-In-the-Loop (HIL) recreation and testing methods. Consequently, this examination clarified how HIL permits testing on a virtual real-time engine.

Interaction between the cyber layer and physical layer of the smart grid promise improved performance and large benefits. These benefits are limited due to the low resilience nature of the cyberinfrastructure. Any change in physical layer topology affects the cyber layer and vice versa. This paper proposes an intelligent technique to monitor the smart grid against cyber intrusions using a connected Hybrid Cyber-Physical Graph (HCPG). Cyber-Physical topology of the smart grid can be modeled using this method. If the node is healthy, the weight of the node is 1, in case any layer, i.e., cyber or physical is affected, the weight of the node changes to 0.5. If cyber and the physical layer, both are affected due to intrusion the node-set value changes to 0. The proposed method represents an effective technique to monitor detection time and malicious nodes. To evaluate the performance of the technique IEEE-9 test system is used with the help of MATLAB software.

This research communication presents a grounded impedance multiplier circuit with the employment of two voltage-differencing buffered amplifiers. As the designed configuration is free from the employment of any external resistance except the impedance which needs to be multiplied, hence, it can be considered as an active-only configuration. Multiplication factor offered by the presented circuit enjoys electronic controllability. Due to the employment of active elements only, the proposed configuration is perfectly fit for on-chip implementation. The presented multiplier configuration also enjoys, no requirement for trans-conductance matching of both the VDBAs, the low sensitivity of multiplication factor, and excellent performance even considering the non-ideal model of VDBAs. The behavior of the constructed impedance multiplier is validated by the PSPICE simulation with CMOS VDBA.