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Power quality (PQ) has become an important topic in today’s power system scenario. PQ issues are raised not only in normal three-phase systems but also with the incorporation of different distributed generations (DGs), including renewable energy sources, storage systems, and other systems like diesel generators, fuel cells, etc. The prevalence of these issues comes from the non-linear features and rapid changing of power electronics devices, such as switch-mode converters for adjustable speed drives and diode or thyristor rectifiers. The wide use of these fast switching devices in the utility system leads to an increase in disturbances associated with harmonics and reactive power. The occurrence of PQ disturbances in turn creates several unwanted effects on the utility system. Therefore, many researchers are working on the enhancement of PQ using different custom power devices (CPDs). In this work, the authors highlight the significance of the PQ in the utility network, its effect, and its solution, using different CPDs, such as passive, active, and hybrid filters. Further, the authors point out several compensation strategies, including reference signal generation and gating signal strategies. In addition, this paper also presents the role of the active power filter (APF) in different DG systems. Some technical and economic considerations and future developments are also discussed in this literature. For easy reference, a volume of journals of more than 140 publications on this particular subject is reported. The effectiveness of this research work will boost researchers’ ability to select proper control methodology and compensation strategy for various applications of APFs for improving PQ.
Soumya Das; Prakash Ray; Arun Sahoo; Somula Ramasubbareddy; Thanikanti Babu; Nallapaneni Kumar; Rajvikram Elavarasan; Lucian Mihet-Popa. A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement. Energies 2021, 14, 4589 .
AMA StyleSoumya Das, Prakash Ray, Arun Sahoo, Somula Ramasubbareddy, Thanikanti Babu, Nallapaneni Kumar, Rajvikram Elavarasan, Lucian Mihet-Popa. A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement. Energies. 2021; 14 (15):4589.
Chicago/Turabian StyleSoumya Das; Prakash Ray; Arun Sahoo; Somula Ramasubbareddy; Thanikanti Babu; Nallapaneni Kumar; Rajvikram Elavarasan; Lucian Mihet-Popa. 2021. "A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement." Energies 14, no. 15: 4589.
Russia is known to be a country with enormous energy resources both renewables and non-renewables. Much of the country’s effort towards energy generation has been on the development of the non-renewables over the years. This study examined the opportunities and challenges in Russia’s Renewable energy (RE) sector. By coupling both interviews and literature reviews, a total of 8 main opportunities and 7 key challenges were identified and discussed. The Best–Worst-Method was used to assign weights to the various factors using inputs of 30 experienced experts in Russia’s RE sector. According to the obtained results, the most significant opportunity that the country would have to take advantage of is the opportunity to export RE outside the shores of the country, it recorded 27.7 percent. This is followed by the country’s target for the RE sector which scored 18%, hydrogen production and need to meet local energy requirements followed with 12% each. The greatest challenge which also serve as a hindrance to the development of RE in the country is the low attention given to clean technologies from government, it recorded a weight of 31.4%. This is followed by unequal playing field, and strict local content requirements which recorded 17.9% and 13.5%, respectively. The study ended with some strategic recommendations to authorities for the development of the sector.
Ephraim Bonah Agyekum; Nallapaneni Manoj Kumar; Usman Mehmood; Manoj Kumar Panjwani; Hassan Haes Alhelou; Tomiwa Sunday Adebayo; Amer Al-Hinai. Decarbonize Russia — A Best–Worst Method approach for assessing the renewable energy potentials, opportunities and challenges. Energy Reports 2021, 7, 4498 -4515.
AMA StyleEphraim Bonah Agyekum, Nallapaneni Manoj Kumar, Usman Mehmood, Manoj Kumar Panjwani, Hassan Haes Alhelou, Tomiwa Sunday Adebayo, Amer Al-Hinai. Decarbonize Russia — A Best–Worst Method approach for assessing the renewable energy potentials, opportunities and challenges. Energy Reports. 2021; 7 ():4498-4515.
Chicago/Turabian StyleEphraim Bonah Agyekum; Nallapaneni Manoj Kumar; Usman Mehmood; Manoj Kumar Panjwani; Hassan Haes Alhelou; Tomiwa Sunday Adebayo; Amer Al-Hinai. 2021. "Decarbonize Russia — A Best–Worst Method approach for assessing the renewable energy potentials, opportunities and challenges." Energy Reports 7, no. : 4498-4515.
Hydrothermal scheduling possibility is regarding the possible performance of the power system was suggested in this article. Hydrothermal power production largely relies on constraints, which are unpredictable in reality. To catch the difficulty associated with hydrothermal power to get optimize power production and then to manage the optimization section, a recently improved optimization technique named Salp Swarm Algorithm has been employed. It essentially operates on the style of Salps. A procedure has been tested for supporting the capacity for solving challenges and for checking the outcome of the hydrothermal power system. To approach the problem very practical the valve-point charging outcome has been regarded also.
Ali Thaeer Hammid; Omar I. Awad; Nallapaneni Manoj Kumar. Salp swarm algorithm to solve Short-Term hydrothermal scheduling problem. Materials Today: Proceedings 2021, 1 .
AMA StyleAli Thaeer Hammid, Omar I. Awad, Nallapaneni Manoj Kumar. Salp swarm algorithm to solve Short-Term hydrothermal scheduling problem. Materials Today: Proceedings. 2021; ():1.
Chicago/Turabian StyleAli Thaeer Hammid; Omar I. Awad; Nallapaneni Manoj Kumar. 2021. "Salp swarm algorithm to solve Short-Term hydrothermal scheduling problem." Materials Today: Proceedings , no. : 1.
The installation of grid-connected microgrids ( $\mu {\rm{Gs}}$ ) is considered a suitable solution to enhance the modernization of distributed generation systems into smart grids. This realization has raised the need for the development of an energy management system $({{\rm{EMS}}})$ for achieving efficient monitoring, control, and management of the energy flows in the system. In this article, the fuzzy inference system (FIS) based EMS synthesis is proposed to efficiently control the distribution of energy flows of $\mu {\rm{G}}$ in real time. The FIS is further optimized using a genetic algorithm approach to achieve faster evaluation and robust EMS development. In the development process of the EMS, the graph theory-based representation of the $\mu {\rm{G}}$ s is proposed for efficient representation of the energy demand and energy generation with the energy systems connected in the $\mu {\rm{G}}$ . To assess the performance of the proposed EMS, a photovoltaic generation of 19.95 kWp and an aggregated load of 8 kWp are characterized along with a battery energy storage system to form a $\mu {\rm{G}}$ . The results identified the benefits of the proposed approach regarding profit generated and battery usage during the $\mu {\rm{G}}$ operation.
Varaha Satya Bharath Kurukuru; Ahteshamul Haque; Sanjeevikumar Padmanaban; Mohammed Ali Khan. Rule-Based Inferential System for Microgrid Energy Management System. IEEE Systems Journal 2021, PP, 1 -10.
AMA StyleVaraha Satya Bharath Kurukuru, Ahteshamul Haque, Sanjeevikumar Padmanaban, Mohammed Ali Khan. Rule-Based Inferential System for Microgrid Energy Management System. IEEE Systems Journal. 2021; PP (99):1-10.
Chicago/Turabian StyleVaraha Satya Bharath Kurukuru; Ahteshamul Haque; Sanjeevikumar Padmanaban; Mohammed Ali Khan. 2021. "Rule-Based Inferential System for Microgrid Energy Management System." IEEE Systems Journal PP, no. 99: 1-10.
Despite the drive for increased environmental protection and the achievement of the Sustainable Development Goals (SDGs), coal, oil, and natural gas use continues to dominate Japan’s energy mix. In light of this issue, this research assessed the position of natural gas, oil, and coal energy use in Japan’s environmental mitigation efforts from the perspective of sustainable development with respect to economic growth between 1965 and 2019. In this regard, the study employs Bayer and Hanck cointegration, fully modified Ordinary Least Square (FMOLS), and dynamic ordinary least square (DOLS) to investigate these interconnections. The empirical findings from this study revealed that the utilization of natural gas, oil, and coal energy reduces the sustainability of the environment with oil consumption having the most significant impact. Furthermore, the study validates the environmental Kuznets curve (EKC) hypothesis in Japan. The outcomes of the Gradual shift causality showed that CO2 emissions can predict economic growth, while oil, coal, and energy consumption can predict CO2 emissions in Japan. Given Japan’s ongoing energy crisis, this innovative analysis provides valuable policy insights to stakeholders and authorities in the nation’s energy sector.
Tomiwa Adebayo; Abraham Awosusi; Seun Oladipupo; Ephraim Agyekum; ArunKumar Jayakumar; Nallapaneni Kumar. Dominance of Fossil Fuels in Japan’s National Energy Mix and Implications for Environmental Sustainability. International Journal of Environmental Research and Public Health 2021, 18, 7347 .
AMA StyleTomiwa Adebayo, Abraham Awosusi, Seun Oladipupo, Ephraim Agyekum, ArunKumar Jayakumar, Nallapaneni Kumar. Dominance of Fossil Fuels in Japan’s National Energy Mix and Implications for Environmental Sustainability. International Journal of Environmental Research and Public Health. 2021; 18 (14):7347.
Chicago/Turabian StyleTomiwa Adebayo; Abraham Awosusi; Seun Oladipupo; Ephraim Agyekum; ArunKumar Jayakumar; Nallapaneni Kumar. 2021. "Dominance of Fossil Fuels in Japan’s National Energy Mix and Implications for Environmental Sustainability." International Journal of Environmental Research and Public Health 18, no. 14: 7347.
Water scarcity is increasing in most Indian cities, exemplified by the recent 2019 Chennai water crisis. Though there were measures initiated at both institutional and local levels, water scarcity has continued. One possible solution is to install energy-efficient renewable energy-powered desalination plants (REpDP) for Indian cities, especially those in favorable climatic zones. The modeling of REpDP combined with multi-criteria decision analysis (MCDA) is proposed to prioritize the optimal site and REpDP selection for providing low-cost freshwater. A standalone seawater reverse osmosis (SWRO) based REpDP that delivers water at a rate of 1.5 m3/h is modeled. Based on the SWRO operation; analytical modeling is carried out to optimize the hybrid energy configuration that combines solar, wind, hydrokinetic with backup energy facilities. The Fuzzy-TOPSIS MCDA with five attributes is performed to rank the modeled alternatives for selected coastal cities. The analysis identified Dwarka in the state of Gujarat, India, as the most suitable urban zone. The results also indicated that the electricity and freshwater production cost for the optimal configuration with an energy recovery scheme provide savings up to 10% and 36.4%, respectively. A comparison is made with EDAS and BWM methods. It provides consistency in results with the Fuzzy-TOPSIS.
J. Vishnupriyan; Dhanasekaran Arumugam; Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Pachaivannan Partheeban. Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India. Journal of Cleaner Production 2021, 315, 128146 .
AMA StyleJ. Vishnupriyan, Dhanasekaran Arumugam, Nallapaneni Manoj Kumar, Shauhrat S. Chopra, Pachaivannan Partheeban. Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India. Journal of Cleaner Production. 2021; 315 ():128146.
Chicago/Turabian StyleJ. Vishnupriyan; Dhanasekaran Arumugam; Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Pachaivannan Partheeban. 2021. "Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India." Journal of Cleaner Production 315, no. : 128146.
Achieving environmental sustainability has become a global initiative whilst addressing climate change and its effects. Thus, this research re-assessed the EKC hypothesis in China and considered the effect of hydroelectricity use and urbanization, utilizing data from 1985 to 2019. The autoregressive distributed lag (ARDL) bounds testing method was utilized to assess long-run cointegration, which is reinforced by a structural break. The outcome of the ARDL bounds test confirmed cointegration among the series. Furthermore, the ARDL revealed that both economic growth and urbanization trigger environmental degradation while hydroelectricity improves the quality of the environment. The outcome of the ARDL also validated the EKC hypothesis for China. In addition, the study employed the novel gradual shift causality test to capture causal linkage among the series. The advantage of the gradual shift causality test is that it can capture gradual or smooth shifts and does not necessitate previous information of the number, form of structural break(s), or dates. The outcomes of the causality test revealed causal connections among the series of interest.
Tomiwa Adebayo; Mary Agboola; Husam Rjoub; Ibrahim Adeshola; Ephraim Agyekum; Nallapaneni Kumar. Linking Economic Growth, Urbanization, and Environmental Degradation in China: What Is the Role of Hydroelectricity Consumption? International Journal of Environmental Research and Public Health 2021, 18, 6975 .
AMA StyleTomiwa Adebayo, Mary Agboola, Husam Rjoub, Ibrahim Adeshola, Ephraim Agyekum, Nallapaneni Kumar. Linking Economic Growth, Urbanization, and Environmental Degradation in China: What Is the Role of Hydroelectricity Consumption? International Journal of Environmental Research and Public Health. 2021; 18 (13):6975.
Chicago/Turabian StyleTomiwa Adebayo; Mary Agboola; Husam Rjoub; Ibrahim Adeshola; Ephraim Agyekum; Nallapaneni Kumar. 2021. "Linking Economic Growth, Urbanization, and Environmental Degradation in China: What Is the Role of Hydroelectricity Consumption?" International Journal of Environmental Research and Public Health 18, no. 13: 6975.
This paper introduced an advanced algorithm making hybrid use of Stockwell transform (ST), Hilbert transform (HT) and Alienation coefficient (ACF) for identification, classification and to locate faulty events on transmission line. Signals of Current are processed by application of ST, HT and ACF for computing S-index, H-index and A-index, respectively. These indices are multiplied element by element to compute proposed fault index (FI). A threshold magnitude is decided after testing the algorithm during different fault scenarios and faulty events are recognized when FI exceeds this threshold magnitude. Faults are categorized by identifying the number of phases which are faulty in nature and a ground fault index (GFI). GFI is designed by processing the zero sequence current using ST and used to identify involvement of ground during fault event. A mathematical formulation is framed to estimate location of faults on transmission line. Fault location has been estimated with a mean error less than 1%. Investigated faults include phase to ground (PGF), double phase (PPF), double phase to ground (PPGF) and three phase to ground (TPGF). Algorithm is found effective for faulty scenario such as fault impedance variations, fault incidence angle (FIA) variations, reverse power flow, effect of line loading, effect of noise, transient faults, off-nominal frequency, and presence of harmonic components. Algorithm is also effective for discriminating switching transients from faulty conditions. Effective performance of the algorithm is established by comparing with fault detection and classification approach based on alienation coefficients, discrete Fourier transform (DFT) and time-frequency approach. Study is performed on a two terminal transmission line in MATLAB/Simulink environment. Effectiveness of the algorithm is also established on a real time transmission grid of Rajasthan state of India.
Abhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution 2021, 1 .
AMA StyleAbhishek Gupta, Ramesh Kumar Pachar, Baseem Khan, Om Prakash Mahela, Sanjeevikumar Padmanaban, Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution. 2021; ():1.
Chicago/Turabian StyleAbhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. 2021. "A multivariable transmission line protection scheme using signal processing techniques." IET Generation, Transmission & Distribution , no. : 1.
Waste generation is a continuous process that needs to be managed effectively to ensure environmental safety and public health. The recent circular economy (CE) practices have brought a new shape for the waste management industry, creating value from the generated waste. The shift to a CE represents one of the most significant challenges, particularly in sorting and classifying generated waste. Addressing these challenges would facilitate the recycling industry and helps in promoting remanufacturing. But in the COVID times, most of the generated waste is getting mixed with conventional waste types, especially in the global south. The pandemic has resulted in colossal infectious waste generation. Its handling became the most significant challenge raising fears and concerns over sorting and classifying. Hence, this study proposes an Artificial Intelligence (AI) based automated solution for sorting COVID related medical waste streams from other waste types and, at the same time, ensures data-driven decisions for recycling in the context of CE. Metal, paper, glass waste categories, including the polyethylene terephthalate (PET) waste from the pandemic, are considered. The waste type classification is done based on the image-texture-dependent features, which provided an accurate sorting and classification before the recycling process starts. The features are fused using the proposed decision-level feature fusion scheme. The classification model based on the support vector machine (SVM) classifier performs best (with 96.5 % accuracy, 95.3 % sensitivity, and 95.9 % specificity) in classifying waste types in the context of circular manufacturing and exhibiting the abilities to manage the COVID related medical waste mixed.
Nallapaneni Manoj Kumar; Mazin Abed Mohammed; Karrar Hameed Abdulkareem; Robertas Damasevicius; Salama A. Mostafa; Mashael S. Maashi; Shauhrat S. Chopra. Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice. Process Safety and Environmental Protection 2021, 152, 482 -494.
AMA StyleNallapaneni Manoj Kumar, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Robertas Damasevicius, Salama A. Mostafa, Mashael S. Maashi, Shauhrat S. Chopra. Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice. Process Safety and Environmental Protection. 2021; 152 ():482-494.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Mazin Abed Mohammed; Karrar Hameed Abdulkareem; Robertas Damasevicius; Salama A. Mostafa; Mashael S. Maashi; Shauhrat S. Chopra. 2021. "Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice." Process Safety and Environmental Protection 152, no. : 482-494.
China intends to develop its renewable energy sector in order to cut down on its pollution levels. Concentrated solar power (CSP) technologies are expected to play a key role in this agenda. This study evaluated the technical and economic performance of a 100 MW solar tower CSP in Tibet, China, under different heat transfer fluids (HTF), i.e., Salt (60% NaNO3 40% KNO3) or HTF A, and Salt (46.5% LiF 11.5% NaF 42% KF) or HTF B under two different power cycles, namely supercritical CO2 and Rankine. Results from the study suggest that the Rankine power cycle with HTF A and B recorded capacity factors (CF) of 39% and 40.3%, respectively. The sCO2 power cycle also recorded CFs of 41% and 39.4% for HTF A and HTF B, respectively. A total of 359 GWh of energy was generated by the sCO2 system with HTF B, whereas the sCO2 system with HTF A generated a total of 345 GWh in the first year. The Rankine system with HTF A generated a total of 341 GWh, while the system with B as its HTF produced a total of 353 GWh of electricity in year one. Electricity to grid mainly occurred between 10:00 a.m. to 8:00 p.m. throughout the year. According to the results, the highest levelized cost of energy (LCOE) (real) of 0.1668 USD/kWh was recorded under the Rankine cycle with HTF A. The lowest LCOE (real) of 0.1586 USD/kWh was obtained under the sCO2 cycle with HTF B. In general, all scenarios were economically viable at the study area; however, the sCO2 proved to be more economically feasible according to the simulated results.
Ephraim Agyekum; Tomiwa Adebayo; Festus Bekun; Nallapaneni Kumar; Manoj Panjwani. Effect of Two Different Heat Transfer Fluids on the Performance of Solar Tower CSP by Comparing Recompression Supercritical CO2 and Rankine Power Cycles, China. Energies 2021, 14, 3426 .
AMA StyleEphraim Agyekum, Tomiwa Adebayo, Festus Bekun, Nallapaneni Kumar, Manoj Panjwani. Effect of Two Different Heat Transfer Fluids on the Performance of Solar Tower CSP by Comparing Recompression Supercritical CO2 and Rankine Power Cycles, China. Energies. 2021; 14 (12):3426.
Chicago/Turabian StyleEphraim Agyekum; Tomiwa Adebayo; Festus Bekun; Nallapaneni Kumar; Manoj Panjwani. 2021. "Effect of Two Different Heat Transfer Fluids on the Performance of Solar Tower CSP by Comparing Recompression Supercritical CO2 and Rankine Power Cycles, China." Energies 14, no. 12: 3426.
Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades. Many research articles have been published in solving different test cases of STHTS problem, while establishing the superiority of one type of optimization algorithm over the type, in finding the near global best solution of these complex problems. This paper presents the implementation of an improved version of a variant of the Particle Swarm Optimization algorithm (PSO), known as Accelerated Particle Swarm Optimization (APSO) on three benchmark test cases of STHTS problems. The adaptive and variable nature of the local and global search coefficients for the proposed APSO significantly improve its performance in obtaining the optimal solution for the STHTS test cases. Two of these cases are non-cascaded cases of STHTS problem (NCSTHTS) and one case is cascaded case of STHTS problem (CSTHTS). The results are compared with the results of the previous implementations of the other algorithms as presented in the literature. Due to the stochastic nature of the meta-heuristic algorithms, the parametric and non-parametric statistical tests have been implemented to establish the superiority of results of one type of algorithm over the results of the other type of algorithms.
Muhammad Salman Fakhar; Syed Abdul Rahman Kashif; Sheroze Liaquat; Akhtar Rasool; Sanjeevikumar Padmanaban; Muhammad Ahmad Iqbal; Muhammad Anas Baig; Baseem Khan. Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling. IEEE Access 2021, 9, 77784 -77797.
AMA StyleMuhammad Salman Fakhar, Syed Abdul Rahman Kashif, Sheroze Liaquat, Akhtar Rasool, Sanjeevikumar Padmanaban, Muhammad Ahmad Iqbal, Muhammad Anas Baig, Baseem Khan. Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling. IEEE Access. 2021; 9 ():77784-77797.
Chicago/Turabian StyleMuhammad Salman Fakhar; Syed Abdul Rahman Kashif; Sheroze Liaquat; Akhtar Rasool; Sanjeevikumar Padmanaban; Muhammad Ahmad Iqbal; Muhammad Anas Baig; Baseem Khan. 2021. "Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling." IEEE Access 9, no. : 77784-77797.
The paper represents a comprehensive review of the wind farm layout and reliability assessment of the wind farm integrated electrical power system. The authors have done a review on the proliferation of renewable energy which raises the uncertainties in the electrical power system. The uncertainties including wind speed and wake effect are important to deal with when an isolated microgrid is considered. The scenario becomes vigilant when the wind farms are integrated with the main grid. Due to uncertainties, the study of reliability evaluation of a wind integrated power system would become significant to analyse the electrical power system behaviour effectively. So, the paper discusses the layout optimisation methods of wind turbines considering the uncertainty parameters, mainly the wake effect. In this regard, the different wake models and optimisation methods based on a single-objective and multi-objective functions are reviewed in detail with the proper comparisons. The paper serves as a better illustration of the competency of these optimisation methods on the optimal wind turbine location on a wind farm. Furthermore, the paper extends the view on the reliability and cost assessment, and reliability improvement techniques of the wind integrated power system. This article provides comprehensive information, yields an attractive and subsequent tool for research requirements for the researchers to design the wind farm layout, and assessed the reliability of a wind integrated power system.
Sachin Kumar; R.K. Saket; Dharmendra Kumar Dheer; P. Sanjeevikumar; Jens Bo Holm‐Nielsen; Frede Blaabjerg. Layout optimisation algorithms and reliability assessment of wind farm for microgrid integration: A comprehensive review. IET Renewable Power Generation 2021, 1 .
AMA StyleSachin Kumar, R.K. Saket, Dharmendra Kumar Dheer, P. Sanjeevikumar, Jens Bo Holm‐Nielsen, Frede Blaabjerg. Layout optimisation algorithms and reliability assessment of wind farm for microgrid integration: A comprehensive review. IET Renewable Power Generation. 2021; ():1.
Chicago/Turabian StyleSachin Kumar; R.K. Saket; Dharmendra Kumar Dheer; P. Sanjeevikumar; Jens Bo Holm‐Nielsen; Frede Blaabjerg. 2021. "Layout optimisation algorithms and reliability assessment of wind farm for microgrid integration: A comprehensive review." IET Renewable Power Generation , no. : 1.
In this article, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in the cascaded H-Bridge multilevel inverter for solar photovoltaic (PV). Harmonics are extracted by the excellent choice of opting switching angles by exploiting the Selective Harmonic Elimination (SHE) PWM technique accompanying a unified algorithm in order to optimize and reduce the Total Harmonic Distortion (THD). ANN is trained with optimum switching angles, and the estimates generated by the ANN are the initial guess for NR. In this study, the CHB-MLI is combined with a traditional boost converter, it boosts the PV voltage to a superior dc-link voltage Perturb and Observe (P&O) based Maximum Power Point Tracking (MPPT) algorithm is used for getting a stable output and efficient operation of solar PV. The proposed system is proved over an eleven-level H-bridge inverter, the work is carried out in MATLAB/Simulink environment, and the respective results are confirmed that the proposed technique is efficient, and offers an actual firing angles with a few iterations results in a better capability of confronting local optima values. The suggested algorithm is justified by the experimental development of eleven-level cascaded H-bridge inverter.
Sanjeevikumar Padmanaban; C. Dhanamjayulu; Baseem Khan. Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications. IEEE Access 2021, 9, 75058 -75070.
AMA StyleSanjeevikumar Padmanaban, C. Dhanamjayulu, Baseem Khan. Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications. IEEE Access. 2021; 9 ():75058-75070.
Chicago/Turabian StyleSanjeevikumar Padmanaban; C. Dhanamjayulu; Baseem Khan. 2021. "Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications." IEEE Access 9, no. : 75058-75070.
This research work has designed an algorithm to identify islanding events using the current signals in a distribution grid interfaced with renewable energy (RE) sources situated in remote areas. A median-based islanding recognition factor (MIRF) is designed by processing the current signal using Stockwell transform (ST). A current rate of change of islanding recognition factor (CRCIRF) is computed by differentiating the root mean square (RMS) current concerning time. The MIRF and CRCIRF are multiplied element by element to calculate the current-based islanding recognition factor (IRFC) used to recognize islanding events and non-islanding events. Simple decision rules are used to discriminate Islanding events from the faulty and the operational events by comparing peak magnitude of IRFC with pre-set threshold values. This IDM effectively recognizes islanding events in the presence of noise with 10 dB signal-to-noise ratio (SNR) level. The performance of IDM is established on a practical distribution feeder. Developed work is executed in MATLAB/Simulink.
Om Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access 2021, 9, 69798 -69813.
AMA StyleOm Prakash Mahela, Yagya Sharma, Shoyab Ali, Baseem Khan, Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access. 2021; 9 ():69798-69813.
Chicago/Turabian StyleOm Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. 2021. "Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform." IEEE Access 9, no. : 69798-69813.
Voltage source converter based multi – terminal DC grids (VSC – MTDC) are widely used for integration of renewable resources. Control of these grids requires vector control method, which includes inner and outer current controllers, tuning of these controllers is very important. Conventionally used tuning methods consider approximated linear model to tune the proportional – integral (PI) parameters of voltage source converter (VSC) which fails to produce optimum disturbance rejection results. In this research an Ant Colony Optimization (ACO) technique is used to get the optimum parameters of inner and outer power control layers for multi – terminal DC system. ACO is applied simultaneously on inner and outer control layers and results are compared with classical tuning method and well established meta - herustic technique, Particle Swarm Optimization (PSO) using MATLAB software. Dynamic models of VSC – MTDC are developed in PSCAD/EMTDC to exalt the qualities of the presented tuning method. In this paper, a four terminal VSC – MTDC has been used under different sequence of events of disturbances e.g. load change on AC side, active power reference change for inverter and rectifier mode and disconnection of one terminal to evaluate the robustness of ACO algorithm with respect to classical method. The proposed tuning method gives superior results under different disturbance compared to conventional method.
Ali Ahmad; Syed Abdul Rahman Kashif; Ali Nasir; Akhtar Rasool; Sheroze Liaquat; Sanjeevikumar Padmanaban; Lucian Mihet-Popa. Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization. IEEE Access 2021, 9, 59910 -59919.
AMA StyleAli Ahmad, Syed Abdul Rahman Kashif, Ali Nasir, Akhtar Rasool, Sheroze Liaquat, Sanjeevikumar Padmanaban, Lucian Mihet-Popa. Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization. IEEE Access. 2021; 9 ():59910-59919.
Chicago/Turabian StyleAli Ahmad; Syed Abdul Rahman Kashif; Ali Nasir; Akhtar Rasool; Sheroze Liaquat; Sanjeevikumar Padmanaban; Lucian Mihet-Popa. 2021. "Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization." IEEE Access 9, no. : 59910-59919.
The key criteria of the short-term hydrothermal scheduling (StHS) problem is to minimize the gross fuel cost for electricity production by scheduling the hydrothermal power generators considering the constraints related to power balance; the gross release of water, and storage limitations of the reservoir, and the operating limitations of the thermal generators and hydropower plants. For addressing the same problem, numerous algorithms were being used, and related studies exist in the literature; however, they possess limitations concerning the solution state and the number of iterations it takes to reach the solution state. Hence, this article proposes using an enhanced cuckoo search algorithm (CSA) called the rigid cuckoo search algorithm (RCSA), a modified version of the traditional CSA for solving the StHS problem. The proposed RCSA improves the solution state and decreases the iteration numbers related to the CSA with a modified Lévy flight. Here, the movement distances are divided into multiple possible steps, which has infinite diversity. The effectiveness of RCSA has been validated by considering the hydrothermal power system. The observed results reveal the superior performance of RCSA among all other compared algorithms that recently have been used for the StHS problem. It is also observed that the RCSA approach has achieved minimum gross costs than other techniques. Thus, the proposed RCSA proves to be a highly effective and convenient approach for addressing the StHS problems
Cui Zheyuan; Ali Hammid; Ali Kareem; Mingxin Jiang; Muamer Mohammed; Nallapaneni Kumar. A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem. Sustainability 2021, 13, 4277 .
AMA StyleCui Zheyuan, Ali Hammid, Ali Kareem, Mingxin Jiang, Muamer Mohammed, Nallapaneni Kumar. A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem. Sustainability. 2021; 13 (8):4277.
Chicago/Turabian StyleCui Zheyuan; Ali Hammid; Ali Kareem; Mingxin Jiang; Muamer Mohammed; Nallapaneni Kumar. 2021. "A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem." Sustainability 13, no. 8: 4277.
The United Nations (UN) have formulated seventeen Sustainable Development Goals (SDGs) and thus, humans were trying to traverse the sustainable path. Meanwhile, the COVID-19 pandemic has emerged and forced out the ephemeral conventional approaches. Thus, the post-COVID world indicates the need for sustainable development and strategies in par with the ecosystem. The authors propose this study as a guide to direct the post-pandemic scenario into the sustainable pathway by prioritizing energy sustainability to engage the actions for achieving the SDGs. The analysis in this study commences with the investigation of pronounced impacts in the energy sector with its influence on the progress towards sustainability. To pursue the path of energy sustainability, a qualitative analysis is performed in a parallel approach from the key viewpoint of the renewable and sustainable energy transition, digital transformation of the energy sector and energy affordability in the post-COVID world. A SWOT-AHP hybrid methodology is employed to identify the significance of each strategy or issues to be focused on immediately in the post-COVID world. The study also discusses energy sustainability from political bodies and policy makers’ perspective, and the actual scenario where we are headed is revealed with the aid of process-tracing method. Furthermore, a novel quantitative analysis is established to represent the SDG’s interaction and the result shows that the SDG 7 is the underpinning goal in relative to other SDGs. In context with it, the mapping of energy sustainability to the sustainable world is accomplished. The ultimate inference from envisioning the SDGs through energy sustainability shows that a sustainable world would result after the pandemic. However, the changes in the energy market, investment preferences and more importantly, the decisions influenced by the political bodies in the post-COVID-world is decisive in achieving the same in a stipulated time frame.
Rajvikram Madurai Elavarasan; Rishi Pugazhendhi; Taskin Jamal; Joanna Dyduch; M.T. Arif; Nallapaneni Manoj Kumar; Gm Shafiullah; Shauhrat S. Chopra; Mithulananthan Nadarajah. Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world. Applied Energy 2021, 292, 116665 .
AMA StyleRajvikram Madurai Elavarasan, Rishi Pugazhendhi, Taskin Jamal, Joanna Dyduch, M.T. Arif, Nallapaneni Manoj Kumar, Gm Shafiullah, Shauhrat S. Chopra, Mithulananthan Nadarajah. Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world. Applied Energy. 2021; 292 ():116665.
Chicago/Turabian StyleRajvikram Madurai Elavarasan; Rishi Pugazhendhi; Taskin Jamal; Joanna Dyduch; M.T. Arif; Nallapaneni Manoj Kumar; Gm Shafiullah; Shauhrat S. Chopra; Mithulananthan Nadarajah. 2021. "Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world." Applied Energy 292, no. : 116665.
The demand for renewable energy to sustain today’s vulnerability towards depleting fossil fuels is a crucial agenda for research. Various inverter topologies have been proposed to convert renewable sources into a usable form. But output THD, additional filtering components at line frequency (leading to bulky circuitry), lower efficiency, etc., are some of the limitations faced in all those topologies. This paper aims to change a voltage source inverter’s traditional behavior, which generates lesser output voltage with higher THD. The paper proposes a closed-loop non-ideal differential boost inverter (DBI) employing a PI controller. The optimization techniques such as, genetic algorithm (GA) and bacterial foraging optimization algorithm (BFOA) are incorporated to accentuate the PI controller’s performance to produce a better response during line and load disturbance conditions with reduced THD. DBI performance is evaluated on a laboratory prototype with different loading conditions. A comparison between the algorithms and the previous topologies from the literature survey has also been provided to validate this research’s claims. This paper’s required simulation study is carried out using MATLAB, and real-time validation is carried out using dSPACE 1104 with sampling time of one μs.
G. Arunkumar; Dhanamjayulu C; Sanjeevikumar Padmanaban; B Rajanarayan Prusty; Baseem Khan. Implementation of Optimization-Based PI Controller Tuning for Non-Ideal Differential Boost Inverter. IEEE Access 2021, 9, 58677 -58688.
AMA StyleG. Arunkumar, Dhanamjayulu C, Sanjeevikumar Padmanaban, B Rajanarayan Prusty, Baseem Khan. Implementation of Optimization-Based PI Controller Tuning for Non-Ideal Differential Boost Inverter. IEEE Access. 2021; 9 (99):58677-58688.
Chicago/Turabian StyleG. Arunkumar; Dhanamjayulu C; Sanjeevikumar Padmanaban; B Rajanarayan Prusty; Baseem Khan. 2021. "Implementation of Optimization-Based PI Controller Tuning for Non-Ideal Differential Boost Inverter." IEEE Access 9, no. 99: 58677-58688.
Recently, development in intelligent transportation systems (ITS) requires the input of various kinds of data in real-time and from multiple sources, which imposes additional research and application challenges. Ongoing studies on Data Fusion (DF) have produced significant improvement in ITS and manifested an enormous impact on its growth. This paper reviews the implementation of DF methods in ITS to facilitate traffic flow analysis (TFA) and solutions that entail the prediction of various traffic variables such as driving behavior, travel time, speed, density, incident, and traffic flow. It attempts to identify and discuss real-time and multi-sensor data sources that are used for various traffic domains, including road/highway management, traffic states estimation, and traffic controller optimization. Moreover, it attempts to associate abstractions of data level fusion, feature level fusion, and decision level fusion on DF methods to better understand the role of DF in TFA and ITS. Consequently, the main objective of this paper is to review DF methods used for real-time and multi-sensor (heterogeneous) TFA studies. The review outcomes are (i) a guideline of constructing DF methods which involve preprocessing, filtering, decision, and evaluation as core steps, (ii) a description of the recent DF algorithms or methods that adopt real-time and multi-sensor sources data and the impact of these data sources on the improvement of TFA, (iii) an examination of the testing and evaluation methodologies and the popular datasets and (iv) an identification of several research gaps, some current challenges, and new research trends.
Shafiza Ariffin Kashinath; Salama A. Mostafa; Aida Mustapha; Hairulnizam Mahdin; David Lim; Moamin A. Mahmoud; Mazin Abed Mohammed; Bander Ali Saleh Al-Rimy; Mohd Farhan Md Fudzee; Tan Jhon Yang. Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis. IEEE Access 2021, 9, 51258 -51276.
AMA StyleShafiza Ariffin Kashinath, Salama A. Mostafa, Aida Mustapha, Hairulnizam Mahdin, David Lim, Moamin A. Mahmoud, Mazin Abed Mohammed, Bander Ali Saleh Al-Rimy, Mohd Farhan Md Fudzee, Tan Jhon Yang. Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis. IEEE Access. 2021; 9 (99):51258-51276.
Chicago/Turabian StyleShafiza Ariffin Kashinath; Salama A. Mostafa; Aida Mustapha; Hairulnizam Mahdin; David Lim; Moamin A. Mahmoud; Mazin Abed Mohammed; Bander Ali Saleh Al-Rimy; Mohd Farhan Md Fudzee; Tan Jhon Yang. 2021. "Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis." IEEE Access 9, no. 99: 51258-51276.
Choice of hybrid electric vehicles (HEVs) in transportation systems is becoming more prominent for optimized energy consumption. HEVs are attaining tremendous appreciation due to their eco-friendly performance and assistance in smart grid notion. The variation of energy storage systems in HEV (such as batteries, supercapacitors or ultracapacitors, fuel cells, and so on) with numerous control strategies create variation in HEV types. Therefore, choosing an appropriate control strategy for HEV applications becomes complicated. This paper reflects a comprehensive review of the imperative information of energy storage systems related to HEVs and procurable optimization topologies based on various control strategies and vehicle technologies. The research work classifies different control strategies considering four configurations: fuel cell-battery, battery-ultracapacitor, fuel cell-ultracapacitor, and battery-fuel cell-ultracapacitor. Relative analysis among different control techniques is carried out based on the control aspects and operating conditions to illustrate these techniques’ pros and cons. A parametric comparison and a cross-comparison are provided for different hybrid configurations to present a comparative study based on dynamic performance, battery lifetime, energy efficiency, fuel consumption, emission, robustness, and so on. The study also analyzes the experimental platform, the amelioration of driving cycles, mathematical models of each control technique to demonstrate the reliability in practical applications. The presented recapitulation is believed to be a reliable base for the researchers, policymakers, and influencers who continuously develop HEVs with energy-efficient control strategies.
Amit Kumer Podder; Oishikha Chakraborty; Sayemul Islam; Nallapaneni Manoj Kumar; Hassan Haes Alhelou. Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications. IEEE Access 2021, 9, 51865 -51895.
AMA StyleAmit Kumer Podder, Oishikha Chakraborty, Sayemul Islam, Nallapaneni Manoj Kumar, Hassan Haes Alhelou. Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications. IEEE Access. 2021; 9 (99):51865-51895.
Chicago/Turabian StyleAmit Kumer Podder; Oishikha Chakraborty; Sayemul Islam; Nallapaneni Manoj Kumar; Hassan Haes Alhelou. 2021. "Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications." IEEE Access 9, no. 99: 51865-51895.