Showing papers by "Sanjeevikumar Padmanaban published in 2023"

Performance Improvement of Weak Grid-Connected Wind Energy System Using FLSRF-Controlled DSTATCOM

Abstract: Wind energy (WE) is emerging as a green and clean energy source. The power quality (PQ) significantly deteriorates when WE sources are connected to the weak ac grid. This is due to the variable wind speed, the impedance of weak grids, and nonlinear loads. This article proposes a methodology to improve the PQ in the weak grid with WE penetration using additional distribution static compensator (DSTATCOM). Fuzzy logic (FL) controller is implemented in the conventional synchronous reference frame (SRF) scheme to minimize the oscillations in the voltage signals. Also, a feedforward block of the WE source is incorporated in the FLSRF control scheme for adapting changes associated with the wind speed. The proposed control scheme accommodates the changes related to the grid’s strength, wind speed, load currents, and dc-link voltage dynamics to estimate the switching signals for the DSTATCOM. The MATLAB simulation and experimental studies established the effectiveness of the proposed method for enhancing the PQ performance of weak grid-connected WE sources in the presence of nonlinear loads.

Design and Implementation of a PV-Fed Grid-Integrated Wireless Electric Vehicle Battery Charger Present in a Residential Environment

Abstract: The power transfer technique used to charge electric vehicles (EVs) has gone through a large development lately. Developing a purely autonomous vehicle has motivated researchers to implement the wireless power transfer technique to charge the EV battery. Previously developed EV used a pure grid-dependent charging system, increasing the net energy consumption from the grid. The vehicle weight also reduces the vehicle's reliability with the increase in the size of the battery. This limitation is eliminated by the proposed technique that uses a wireless EV battery charging system with a utility grid. This article presents an improved system for supplying photovoltaic (PV) power to an EV used in a grid-interfaced residential system. This power electronic converter-based interfacing system facilitates a bidirectional power flow technique for feeding extra PV panel power to the grid and charging the EV using utility grid power during the unavailability of solar power. A bidirectional cycloconverter is employed, which delivers a variable frequency concerning modes of operation of the system. The experimental prototype employs an opal-RT real-time simulator for integrating the proposed system into the grid. This article presents the comparison of the simulation and experimentation results of the wireless EV charging system.

Multi-Objective Optimization Algorithms for a Hybrid AC/DC Microgrid Using RES: A Comprehensive Review

Abstract: Optimization methods for a hybrid microgrid system that integrated renewable energy sources (RES) and supplies reliable power to remote areas, were considered in order to overcome the intermittent nature of RESs. The hybrid AC/DC microgrid system was constructed with a solar photovoltaic system, wind turbine, battery storage, converter, and diesel generator. There is a steady increase in the utilization of hybrid renewable energy sources with hybrid AC/DC microgrids; consequently, it is necessary to solve optimization techniques. Therefore, the present study proposed utilizing multi-objective optimization methods using evolutionary algorithms. In this context, a few papers were reviewed regarding multi-objective optimization to determine the capacity and optimal design of a hybrid AC/DC microgrid with RESs. Here, the optimal system consisted of the minimum cost of energy, minimum net present cost, low operating cost, low carbon emissions and a high renewable fraction. These were determined by using multi-objective optimization (MOO) algorithms. The sizing optimization of the hybrid AC/DC microgrid was based on the multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO). Similarly, multi-objective optimization with different evolutionary algorithms (MOGA, MOGOA etc.) reduces energy cost and net present cost, and increases the reliability of islanded hybrid microgrid systems.

Reactive Power Matching Through Virtual Variable Impedance for Parallel Virtual Synchronous Generator Control Scheme

Abstract: Virtual synchronous generator (VSG) control has received much attention for interfacing renewable energy sources, thus creating a low-inertia microgrid. However, proportional reactive power-sharing and voltage accuracy is still a serious concern due to unequal feeder impedances between VSG controlled DGs and the point of power coupling. This article proposes a virtual variable impedance (VVI) based VSG control technique to mitigate the reactive power sharing error by improving the line-impedance ratio among multiple DGs. The proposed VVI control is designed to estimate the value of variable virtual impedance by establishing an exponential relationship with the inverter's output reactive power. The reactive power communication method is also introduced to identify the proportion of reactive power share being injected by the DG. The effectiveness of the proposed VVI control is further analyzed through the small-signal stability analysis and Lyapunov stability analysis of a multi-VSG system. Finally, the proposed controller is tested in MATLAB/Simulink software and on an experimental setup that includes inverter hardware and dSPACE simulator. Results have shown that the proposed method allow only 0.026% of reactive power sharing error as compared to the conventional droop control and state-of-the-art virtual capacitor-based droop control that experiences 2.86% and 2.8% error, respectively.

Frequency Control of Power System with Distributed Sources by Adaptive Type 2 Fuzzy PID Controller

Abstract: The unpredictability of solar and wind energy sources affects contemporary power networks and adds frequency variations. An appropriate intelligent controller is necessary to balance electricity between generation and demand. As a result, in this research, we present a sine-cosine adaptive improved equilibrium optimization (SCaIEO) method tuned to Adaptive Type 2 Fuzzy PID Controller (AT2FPID) for frequency management of cutting-edge power systems. The efficiency of the SCaIEO approach is assessed by comparing it to the original equilibrium optimization (EO) and other comparable algorithms for the test function. Moreover, engineering applications of the SCaIEO technique are carried out by constructing an AT2FPID controller to manage the frequency of power systems that include renewable energy and dispersed sources. First, we show that SCaIEO outperforms EO, Particle Swarm Optimization, Genetic Algorithm, Moth Flame Optimization, and Gravitational Search Algorithm in the PID controller (Gravity Search Algorithm). The AT2FPID is next evaluated, and the SCaIEO AT2FPID controller’s dominance is proven by equating the outcome to the original, PID Type 1 Fuzzy PID, Type 2 Fuzzy PID controller.

Integrated motor drive for vehicle electrification: a step toward a more sustainable and efficient transportation system

Abstract: The transportation sector is a big source of greenhouse gas (GHG) emissions. It is responsible for about 20% of all carbon dioxide (CO2) emissions in the world, and most of those emissions come from road transportation. The development of greater efficiency vehicles with much reduced fuel consumption and GHG emissions is critical for vehicle electrification and a sustainable transportation system. Electric vehicles (EVs) offer higher energy efficiency than internal combustion engines and emit no CO2 during operation. For future vehicle electrification, cost-effective electric powertrain options are required. The current state of development of two major components of the EV powertrain: motors and drives, is introduced in this editorial.

Advanced DC–DC converter topologies for solar energy harvesting applications: a review

Abstract: In this study, the advanced topologies of a DC–DC converter for applications involving the harvesting of solar energy are discussed. This work’s primary contribution is a guide for choosing the most effective topology for a DC–DC converter when developing solar energy collection systems. Several topologies of a DC–DC converter for solar energy harvesting applications are compared in terms of the range of power levels they can oversee, the complexity of the underlying hardware, the cost of implementation, the tracking efficiency and the overall efficiency of the converter. This article explains five innovative approaches for adapting boost converters to function as standard DC–DC converters to capture solar energy, consisting of (i) voltage-multiplier cell, (2) coupled inductor, (3) coupled inductor and switch capacitor, (4) cascaded topology and (5) voltage-lift technique. Because of the boost converter’s restrictions, it is necessary to deliver high performance. The comparison findings demonstrate that the voltage-lift-based boost-converter topology performs more effectively than the alternatives. In conclusion, the information presented in this paper can be utilized when developing solar energy collection systems to determine the sort of direct current to direct current converter that will be most effective.

Assessment of spatial and temporal modelling on greenhouse gas emissions from electricity generation

Abstract: This paper highlights the importance of precise assessments of greenhouse gas (GHG) emissions associated with power generation for effective policy making in environmental sustainability. The current assessment approaches based on historical data or estimated generation using energy models may not accurately reflect the reality of future power systems due to the impact of spatial-temporal and techno-economic characteristics of generation mix and load demands. To address this, the paper presents a comprehensive methodology for accurately quantifying the geographical and temporal variations in GHG emissions associated with generating units’ operation, startup, and shutdown at an hourly resolution. The methodology is based on a detailed electricity model that considers various sources of generation, techno-economic, and spatial-temporal characteristics of system components. The study demonstrates the effectiveness of the methodology in quantifying GHG emissions in the IEEE RTS-GLMC system, with a focus on CO2, N2O, and CH4. The analysis reveals significant variations in GHG emissions among different generation buses and hours of the year, attributed to the high proportion of renewable energy in the generation mix. The paper emphasizes the inadequacy of examining marginal environmental impacts based on GHG emission intensity alone and suggests a more thorough analysis based on total GHG emissions generation. Finally, the paper emphasizes the crucial role of time-varying and marginal assessment techniques in identifying effective strategies for reducing GHG emissions in the electricity sector, including optimizing the operation and capacity of generation units, energy storage systems, and electric vehicles, including their locations.

A State-of-the-Art Review on Heat Extraction Methodologies of Photovoltaic/Thermal System

Abstract: One of the critical emerging branches of solar technology is photovoltaic/thermal (PV/T) systems that amalgamate solar collectors and solar photovoltaic panels into a unit to produce heat and electricity from stochastic solar insolation. In sunny countries, the conversion efficiency ( $\eta$ ) reduces due to the elevated temperature of solar cells because solar panels absorb a sizeable portion of solar insolation as heat. The critical function of PV/T is to minimize the temperature of photovoltaic modules and enhance their electricity production with yielded thermal energy used for other applications. Energy and exergy are two essential aspects of examining an energy system. The exergy analysis of such systems is of great concern because it works on the quality of energy. The energy and thermal and electrical efficiencies are enhanced by applying proper cooling media in the PV/T. This brief provides a comprehensive review of the air, fluids, and PCM-based cooling media of the PV/T systems. A thorough review of various recently published research in the heat extraction methodologies of PV/T systems has been incorporated into this study. Based on the rigorous review, future recommendations for the implementation of cooling medias are also included in this study. The vivid tabular analysis of heat extraction methodologies provides a proper guideline for the researchers. This review work will provide a deep insight into the investigated area for the industrialists and researchers working in the field of PV/T technology.

Deep Transfer Learning-Enabled Energy Management Strategy for Smart Home Sensor Networks

Abstract: The applications of wireless sensor networks are extensively used to detect and control home residents’ activities in smart homes. However, the sensors are battery-powered, so keeping them in active mode consumes tremendous energy. In this regard, we propose a solution to activate the smart home sensors based on detecting the upcoming activities using a Deep Long-Short Term Memory (DLSTM) model. The pre-trained model is then transferred to the same and different Target Domains (TDs) to reduce the time for training. The proposed system applies to preprocess and feature mapping steps to both the source and target data to make grounds for efficient transfer. Further, applying the trained model to the TD may miss the essential activities. Therefore, a reinforcement learning model is applied in the TD. To handle unusual activities in real-time, guard sensors are appointed among the idle sensors. The performance evaluation shows that the proposed scheme detects the activities with an accuracy of 96.1%. Additionally, the proposed scheme outperforms the sentry and prediction-based schemes in energy consumption of the sensors and network lifetime.

Adoption of Blockchain Platform for Security Enhancement in Energy Transaction

Abstract: Renewable energy has become a reality in the present and is being preferred by countries to become a considerable part of the central grid. With the increasing adoption of renewables it will soon become crucial to have a platform which would facilitate secure transaction of energy for consumers as well as producers. This paper discusses and implements a Blockchain based platform which enhances and establishes a secure method to exchange energy. It would also lower the operation costs and accommodate other technologies like the IoT. A basic market mechanism has been developed for peer-to-peer (P2P) transaction of energy where different types of entities can be directly involved. Another concept which is discussed in the paper is the consensus mechanism and whether the model market could hold the security and privacy of the individual users.