This page has only limited features, please log in for full access.

Prof. Rajvikram Madurai Elavarasan
SRI VENKATESWARA COLLEGE OF ENGINEERING

Basic Info


Research Keywords & Expertise

0 Cooling System
0 Energy & the Environment
0 Solar Energy
0 wind energy conversion system
0 RENEWWABLE EENRGY,SOLAR ENERGY

Fingerprints

Energy & the Environment
Solar Energy

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 28 August 2021 in Energies
Reads 0
Downloads 0

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability.

ACS Style

Ramakrishna S. S. Nuvvula; Devaraj Elangovan; Kishore Srinivasa Teegala; Rajvikram Madurai Elavarasan; Rabiul Islam; Ravikiran Inapakurthi. Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO. Energies 2021, 14, 5368 .

AMA Style

Ramakrishna S. S. Nuvvula, Devaraj Elangovan, Kishore Srinivasa Teegala, Rajvikram Madurai Elavarasan, Rabiul Islam, Ravikiran Inapakurthi. Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO. Energies. 2021; 14 (17):5368.

Chicago/Turabian Style

Ramakrishna S. S. Nuvvula; Devaraj Elangovan; Kishore Srinivasa Teegala; Rajvikram Madurai Elavarasan; Rabiul Islam; Ravikiran Inapakurthi. 2021. "Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO." Energies 14, no. 17: 5368.

Journal article
Published: 23 August 2021 in Energies
Reads 0
Downloads 0

The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced when additional DGs are installed. Moreover, considering the stochastic and sporadic nature of solar irradiance, the practical size of DG has been suggested based on analysis that may be adopted while designing the actual photovoltaic (PV) plant for usage. The obtained simulation outcomes are compared with the latest state-of-the-art literature and suggest that the proposed HHO is capable of processing complex high dimensional benchmark functions and has capability to handle problems pertaining to electrical distribution in an effective manner.

ACS Style

Suprava Chakraborty; Sumit Verma; Aprajita Salgotra; Rajvikram Madurai Elavarasan; Devaraj Elangovan; Lucian Mihet-Popa. Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects. Energies 2021, 14, 5206 .

AMA Style

Suprava Chakraborty, Sumit Verma, Aprajita Salgotra, Rajvikram Madurai Elavarasan, Devaraj Elangovan, Lucian Mihet-Popa. Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects. Energies. 2021; 14 (16):5206.

Chicago/Turabian Style

Suprava Chakraborty; Sumit Verma; Aprajita Salgotra; Rajvikram Madurai Elavarasan; Devaraj Elangovan; Lucian Mihet-Popa. 2021. "Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects." Energies 14, no. 16: 5206.

Review
Published: 29 July 2021 in Energies
Reads 0
Downloads 0

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.

ACS Style

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 Style

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 (15):4589.

Chicago/Turabian Style

Soumya 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.

Journal article
Published: 29 June 2021 in Journal of Cleaner Production
Reads 0
Downloads 0

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.

ACS Style

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 Style

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.

Chicago/Turabian Style

J. 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.

Journal article
Published: 27 June 2021 in Bioresource Technology
Reads 0
Downloads 0

Bioconversion of food waste into sophorolipid-based biosurfactants is a promising emerging technology. It is important to evaluate the environmental impacts associated with the latest advancements in sophorolipid production as it matures to maximize sustainability on scale-up. This study takes a dynamic Life Cycle Assessment (dLCA) approach to address the inherent uncertainties and evaluate the environmental performances. It demonstrates the dLCA framework by conducting the new traversal of food waste-derived industrial-scale sophorolipid production, with the combination of Techno-Economic Analysis (TEA). A systematic investigation of the environmental-economic implications of the two pathways to produce SL crystals and syrup. The global warming potential (GWP) for 1 kg of SL crystals and syrup was 7.9 kg CO2 eq. and 5.7 kg CO2 eq., respectively. The Ashby-like charts based on the LCA and TEA results at the pilot plant highlighted the trade-offs between systemic environmental costs and economic benefits for design decisions.

ACS Style

Xiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies. Bioresource Technology 2021, 337, 125474 .

AMA Style

Xiaomeng Hu, Karpagam Subramanian, Huaimin Wang, Sophie L.K.W. Roelants, Wim Soetaert, Guneet Kaur, Carol Sze Ki Lin, Shauhrat S. Chopra. Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies. Bioresource Technology. 2021; 337 ():125474.

Chicago/Turabian Style

Xiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. 2021. "Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies." Bioresource Technology 337, no. : 125474.

Journal article
Published: 19 June 2021 in Process Safety and Environmental Protection
Reads 0
Downloads 0

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.

ACS Style

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 Style

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.

Chicago/Turabian Style

Nallapaneni 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.

Journal article
Published: 07 June 2021 in IEEE Access
Reads 0
Downloads 0

Existing power grids (PGs) and in-home energy management controllers do not offer its users the choice to maintain comfort and provide a bearable solution in terms of low cost and reduced carbon emission. This work is based on energy usage scheduling and management under electric utility and renewable energy sources i.e., solar energy (SE), controllable heat and power (CHP) and wind energy (WE) together. Efficient integration of renewable energy sources (RES) and battery storage system (BSS) have been suggested to solve the energy management problem, reduce the bill cost, peak-to-average ratio (PAR) and carbon emission. User’s electricity bill reduction have been achieved by proposed power usage scheduling method and integrating low cost RESs. PAR minimization have been achieved through shifting the demand in response to real time price from high-peak hours to low-peak hours. In this context, load scheduling and energy storage system management controller (LSEMC) is proposed which is based on heuristic algorithms i.e., genetic algorithm (GA), wind driven optimization (WDO), binary particle swarm optimization (BPSO), bacterial foraging optimization (BFO) and our suggested hybrid of GA, WDO and PSO (HGPDO) algorithm. The performance of the heuristic algorithms and proposed scheme is evaluated numerically. Results demonstrate that our proposed algorithm and the LSEMC reduces the electricity bill, PAR and CO 2 in Case 1, by 58.69%, 52.78% and 72.40%, in Case 2, by 47.55%, 45.02% and 92.90% and in Case 3, by 33.6%, 54.35% and 91.64%, respectively as compared with unscheduled. Moreover, the user comfort by our proposed HGPDO algorithm in terms of delay, thermal, air quality and visual improves by 35.55%, 16.66%, 91.64% and 45%, respectively.

ACS Style

Ateeq Ur Rehman; Zahid Wadud; Rajvikram Madurai Elavarasan; Ghulam Hafeez; Imran Khan; Zeeshan Shafiq; Hassan Haes Alhelou. An Optimal Power Usage Scheduling in Smart Grid Integrated With Renewable Energy Sources for Energy Management. IEEE Access 2021, 9, 84619 -84638.

AMA Style

Ateeq Ur Rehman, Zahid Wadud, Rajvikram Madurai Elavarasan, Ghulam Hafeez, Imran Khan, Zeeshan Shafiq, Hassan Haes Alhelou. An Optimal Power Usage Scheduling in Smart Grid Integrated With Renewable Energy Sources for Energy Management. IEEE Access. 2021; 9 ():84619-84638.

Chicago/Turabian Style

Ateeq Ur Rehman; Zahid Wadud; Rajvikram Madurai Elavarasan; Ghulam Hafeez; Imran Khan; Zeeshan Shafiq; Hassan Haes Alhelou. 2021. "An Optimal Power Usage Scheduling in Smart Grid Integrated With Renewable Energy Sources for Energy Management." IEEE Access 9, no. : 84619-84638.

Journal article
Published: 25 May 2021 in Energies
Reads 0
Downloads 0

In this study, a modified non-uniform adiabatic section in a Two-Phase Closed Thermosiphon (TPCT) is proposed where the uniform section was replaced by convergent and divergent (C-D) sections. The heat transfer analysis was performed on the modified TPCT and their findings were compared with standard TPCT. The deionized water (DI) in the proportion of 30 vol% is filled in both the TPCTs. Further, the heat transfer performance analysis was carried out for three different orientations, such as 0°, 45° and 90°, and heat input was varied from 50 to 250 W. The effect of these geometrical changes and inclination angles on the heat transfer performance of both the TPCT were evaluated to compare the thermal resistance, wall temperature variation and heat transfer coefficient. The non-dimensional numbers such as Weber (WE), Bond (BO), Condensation (CO) and Kutateladze (KU) were investigated based on heat fluxes for both TPCTs. By introducing the convergent-divergent section nearer to the condenser, the pressure before and after the C-D section was increased and decreased. This enhances the heat transfer in the evaporator slightly up to 2% and 1.4% at horizontal and 45° orientation, respectively, in Non-Uniformed Adiabatic Section (NUAS) TPCT when compared to Uniformed Adiabatic Section (UAS) TPCT. The thermal resistance of NUAS TPCT was reduced by up to 4.5% relative to UAS TPCT in horizontal and 45°. The results of the non-dimensional number also confirmed that NUAS TPCT provided better performance by enhancing 2% more pool boiling characteristics, interaction forces and condensate returns. Several factors such as gravity assistance, fluid accumulation, pressure drop and thermal resistance exert an influence on the heat transfer performance of the proposed NUAS TPCT at various orientation angles. However, different type of cross-sectional variations subjected to orientation changes may also get influenced by several other parameters that in turn affect the heat transfer performance distinctly.

ACS Style

Mohanraj Chandran; Rajvikram Madurai Elavarasan; Ramesh Neelakandan; Umashankar Subramaniam; Rishi Pugazhendhi. Influence of Geometrical Changes in an Adiabatic Portion on the Heat Transfer Performance of a Two-Phase Closed Thermosiphon System. Energies 2021, 14, 3070 .

AMA Style

Mohanraj Chandran, Rajvikram Madurai Elavarasan, Ramesh Neelakandan, Umashankar Subramaniam, Rishi Pugazhendhi. Influence of Geometrical Changes in an Adiabatic Portion on the Heat Transfer Performance of a Two-Phase Closed Thermosiphon System. Energies. 2021; 14 (11):3070.

Chicago/Turabian Style

Mohanraj Chandran; Rajvikram Madurai Elavarasan; Ramesh Neelakandan; Umashankar Subramaniam; Rishi Pugazhendhi. 2021. "Influence of Geometrical Changes in an Adiabatic Portion on the Heat Transfer Performance of a Two-Phase Closed Thermosiphon System." Energies 14, no. 11: 3070.

Journal article
Published: 15 May 2021 in Energies
Reads 0
Downloads 0

Soaring energy demand and the establishment of various trends in the energy market have paved the way for developing demand-side management (DSM) from the consumer side. This paper proposes a reinforced DSM (RDSM) approach that uses an enhanced binary gray wolf optimization algorithm (EBGWO) that benefits the consumer premises with load scheduling, and peak demand reduction. To date, DSM research has been carried out for residential, commercial and industrial loads, whereas DSM approaches for educational loads have been less studied. The institution load also consumes much utility energy during peak hours, making institutional consumers pay a high amount of cost for energy consumption during peak hours. The proposed objective is to reduce the total electricity cost and to improve the operating efficiency of the entire load profile at an educational institution. The proposed architecture integrates the solar PV (SPV) generation that supplies the user-comfort loads during peak operating hours. User comfort is determined with a metric termed the user comfort index (UCI). The novelty of the proposed work is highlighted by modeling a separate class of loads for temperature-controlled air conditioners (AC), supplying the user comfort loads from SPV generation and determining user comfort with percentage UCI. The improved transfer function used in the proposed EBGWO algorithm performs faster in optimizing nonlinear objective problems. The electricity price in the peak hours is high compared to the off-peak hours. The proposed EBGWO algorithm shift and schedules the loads from the peak hours to off-peak hours, and incorporating SPV in satisfying the user comfort loads aids in reducing the power consumption from the utility during peak hours. Thus, the proposed EBGWO algorithm greatly helps the consumer side decrease the peak-to-average ratio (PAR), improve user comfort significantly, reduce the peak demand, and save the institution’s electricity cost by USD 653.046.

ACS Style

Karthick Tamilarasu; Charles Sathiasamuel; Jeslin Joseph; Rajvikram Madurai Elavarasan; Lucian Mihet-Popa. Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort. Energies 2021, 14, 2855 .

AMA Style

Karthick Tamilarasu, Charles Sathiasamuel, Jeslin Joseph, Rajvikram Madurai Elavarasan, Lucian Mihet-Popa. Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort. Energies. 2021; 14 (10):2855.

Chicago/Turabian Style

Karthick Tamilarasu; Charles Sathiasamuel; Jeslin Joseph; Rajvikram Madurai Elavarasan; Lucian Mihet-Popa. 2021. "Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort." Energies 14, no. 10: 2855.

Journal article
Published: 10 May 2021 in IEEE Access
Reads 0
Downloads 0

Fossil fuel-based energy sources are the major contributors to greenhouse gas (GHG) emission and thus the use of renewable energy (RE) is becoming the best alternative to cater for the increasing energy demand in both developing and developed nations. Chipendeke is a rural community in Zimbabwe, in which electricity demand is partially served by the only micro-hydro plant and hence, load shedding is a regular practice to keep essential services running. This study explored suitable opportunity to identify a feasible system with different energy sources that can fullfil the current and projected future load demand of the community. A techno-economic feasibility study for a hybrid RE based power system (REPS) is examined considering various energy sources and cost functions. Six different system configurations have been designed with different sizing combinations to identify the most optimum solution for the locality considering techno-economic and environmental viability. The performance metrics considered to evaluate the best suitable model are; Net Present Cost (NPC), Cost of Energy (COE), Renewable Fraction (RF), excess energy and seasonal load variations. In-depth, sensitivity analyses have been performed to investigate the variations of the studied models with a little variation of input variables. Of the studied configurations, an off-grid hybrid Hydro/PV/DG/Battery system was found to be the most economically feasible compared to other configurations. This system had the lowest NPC and COE of $307,657 and $0.165/kWh respectively and the highest RF of 87.5%. The proposed hybrid system could apply to any other remote areas in the region and anywhere worldwide.

ACS Style

Gm Shafiullah; Tjedza Masola; Remember Samu; Rajvikram Madurai Elavarasan; Sharmina Begum; Umashankar Subramaniam; Mohd Fakhizan Romlie; Mohammad Chowdhury; M. T. Arif. Prospects of Hybrid Renewable Energy-Based Power System: A Case Study, Post Analysis of Chipendeke Micro-Hydro, Zimbabwe. IEEE Access 2021, 9, 73433 -73452.

AMA Style

Gm Shafiullah, Tjedza Masola, Remember Samu, Rajvikram Madurai Elavarasan, Sharmina Begum, Umashankar Subramaniam, Mohd Fakhizan Romlie, Mohammad Chowdhury, M. T. Arif. Prospects of Hybrid Renewable Energy-Based Power System: A Case Study, Post Analysis of Chipendeke Micro-Hydro, Zimbabwe. IEEE Access. 2021; 9 (99):73433-73452.

Chicago/Turabian Style

Gm Shafiullah; Tjedza Masola; Remember Samu; Rajvikram Madurai Elavarasan; Sharmina Begum; Umashankar Subramaniam; Mohd Fakhizan Romlie; Mohammad Chowdhury; M. T. Arif. 2021. "Prospects of Hybrid Renewable Energy-Based Power System: A Case Study, Post Analysis of Chipendeke Micro-Hydro, Zimbabwe." IEEE Access 9, no. 99: 73433-73452.

Journal article
Published: 10 May 2021 in IEEE Access
Reads 0
Downloads 0

At present, the disturbances like the voltage fluctuations, resulting from the grid’s complexities and unbalanced load conditions, create severe power quality concerns like total harmonic distortion (THD) and voltage unbalance factor (VUF) of the grid voltage. Though the custom power devices such as distribution-static compensators (D-STATCOMs) improve these power quality concerns, however, the accompanying controller plays the substantial role. Therefore, this paper proposes a fractional-order sliding mode control (FOSMC) for a D-STATCOM to compensate the low power distribution system by injecting/absorbing a specific extent of the reactive power under disturbances. FOSMC is a non-linear robust control in which the sliding surface is designed by using the Riemann-Liouville ( RL ) function and the chattering phenomenon is minimized by using the exponential reaching law. The stability of FOSMC is evidenced by employing the Lyapunov stability criteria. Moreover, the performance of the proposed FOSMC is further accessed while doing its parametric variations. The complete system is demonstrated with a model of 400V, 180kVA radial distributor along with D-STATCOM under two test scenarios in MATLAB/Simulink environment. The results of the proposed controller are compared with the fixed frequency sliding mode control (FFSMC) and conventional proportional-integral (PI) control. The results validate the superiority of the proposed controller in terms of rapid tracking, fast convergence, and overall damping with very low THD and VUF.

ACS Style

Toqeer Ahmed; Asad Waqar; Rajvikram Madurai Elavarasan; Junaid Imtiaz; Manoharan Premkumar; Umashankar Subramaniam. Analysis of Fractional Order Sliding Mode Control in a D-STATCOM Integrated Power Distribution System. IEEE Access 2021, 9, 70337 -70352.

AMA Style

Toqeer Ahmed, Asad Waqar, Rajvikram Madurai Elavarasan, Junaid Imtiaz, Manoharan Premkumar, Umashankar Subramaniam. Analysis of Fractional Order Sliding Mode Control in a D-STATCOM Integrated Power Distribution System. IEEE Access. 2021; 9 ():70337-70352.

Chicago/Turabian Style

Toqeer Ahmed; Asad Waqar; Rajvikram Madurai Elavarasan; Junaid Imtiaz; Manoharan Premkumar; Umashankar Subramaniam. 2021. "Analysis of Fractional Order Sliding Mode Control in a D-STATCOM Integrated Power Distribution System." IEEE Access 9, no. : 70337-70352.

Journal article
Published: 30 April 2021 in Applied Sciences
Reads 0
Downloads 0

The prediction of severe weather events such as hurricanes is always a challenging task in the history of climate research, and many deep learning models have been developed for predicting the severity of weather events. When a disastrous hurricane strikes a coastal region, it causes serious hazards to human life and habitats and also reflects a prodigious amount of economic losses. Therefore, it is necessary to build models to improve the prediction accuracy and to avoid such significant losses in all aspects. However, it is impractical to predict or monitor every storm formation in real time. Though various techniques exist for diagnosing the tropical cyclone intensity such as convolutional neural networks (CNN), convolutional auto-encoders, recurrent neural network (RNN), etc., there are some challenges involved in estimating the tropical cyclone intensity. This study emphasizes estimating the tropical cyclone intensity to identify the different categories of hurricanes and to perform post-disaster management. An improved deep convolutional neural network (CNN) model is used for predicting the weakest to strongest hurricanes with the intensity values using infrared satellite imagery data and wind speed data from HURDAT2 database. The model achieves a lower Root mean squared error (RMSE) value of 7.6 knots and a Mean squared error (MSE) value of 6.68 knots by adding the batch normalization and dropout layers in the CNN model. Further, it is crucial to predict and evaluate the post-disaster damage for implementing advance measures and planning for the resources. The fine-tuning of the pre-trained visual geometry group (VGG 19) model is accomplished to predict the extent of damage and to perform automatic annotation for the image using the satellite imagery data of Greater Houston. VGG 19 is also trained using video datasets for classifying various types of severe weather events and to annotate the weather event automatically. An accuracy of 98% is achieved for hurricane damage prediction and 97% accuracy for classifying severe weather events. The results proved that the proposed models for hurricane intensity estimation and its damage prediction enhances the learning ability, which can ultimately help scientists and meteorologists to comprehend the formation of storm events. Finally, the mitigation steps in reducing the hurricane risks are addressed.

ACS Style

Jayanthi Devaraj; Sumathi Ganesan; Rajvikram Elavarasan; Umashankar Subramaniam. A Novel Deep Learning Based Model for Tropical Intensity Estimation and Post-Disaster Management of Hurricanes. Applied Sciences 2021, 11, 4129 .

AMA Style

Jayanthi Devaraj, Sumathi Ganesan, Rajvikram Elavarasan, Umashankar Subramaniam. A Novel Deep Learning Based Model for Tropical Intensity Estimation and Post-Disaster Management of Hurricanes. Applied Sciences. 2021; 11 (9):4129.

Chicago/Turabian Style

Jayanthi Devaraj; Sumathi Ganesan; Rajvikram Elavarasan; Umashankar Subramaniam. 2021. "A Novel Deep Learning Based Model for Tropical Intensity Estimation and Post-Disaster Management of Hurricanes." Applied Sciences 11, no. 9: 4129.

Review
Published: 29 April 2021 in Sustainability
Reads 0
Downloads 0

Lighting is a fundamental requirement of our daily life. A lot of research and development is carried out in the field of daylight harvesting, which is the need of the hour. One of the most desirable attributes of daylight harvesting is that daylight is available universally and it is a very clean and cost-efficient form of energy. By using the various methods of daylight harvesting, it is possible to attain the global Sustainable Development Goals. Daylight harvesting in the most fundamental sense is the lighting strategy control of the artificial light in an interior space where daylight is also present so that the required illumination level is achieved. This way, a lot of energy can be saved. Recently, in addition to energy efficiency, other factors such as cost-efficiency, user requirements such as uniform illuminance, and different levels of illuminance at different points are being considered. To simulate the actual daylight contribution for an office building in urban Chennai, India before construction, ECO TECH software is used by providing the inputs such as building orientation, and reflectance’s values of the ceiling, wall, and floor to analyze the overall percentage of daylight penetration available versus the percentage prescribed in the Indian Green Building Council to obtain the credit points. Thus, the impact of architectural design on daylight harvesting and daylight predictive technology has experimented with office building in Chennai, India. This article will give an insight into the current trends in daylight harvesting technology and intends to provide a deeper understanding and spark a research interest in this widely potential field.

ACS Style

Gnana Odiyur Vathanam; Karthikeyan Kalyanasundaram; Rajvikram Elavarasan; Shabir Hussain Khahro; Umashankar Subramaniam; Rishi Pugazhendhi; Mehana Ramesh; Rishi Gopalakrishnan. A Review on Effective Use of Daylight Harvesting Using Intelligent Lighting Control Systems for Sustainable Office Buildings in India. Sustainability 2021, 13, 4973 .

AMA Style

Gnana Odiyur Vathanam, Karthikeyan Kalyanasundaram, Rajvikram Elavarasan, Shabir Hussain Khahro, Umashankar Subramaniam, Rishi Pugazhendhi, Mehana Ramesh, Rishi Gopalakrishnan. A Review on Effective Use of Daylight Harvesting Using Intelligent Lighting Control Systems for Sustainable Office Buildings in India. Sustainability. 2021; 13 (9):4973.

Chicago/Turabian Style

Gnana Odiyur Vathanam; Karthikeyan Kalyanasundaram; Rajvikram Elavarasan; Shabir Hussain Khahro; Umashankar Subramaniam; Rishi Pugazhendhi; Mehana Ramesh; Rishi Gopalakrishnan. 2021. "A Review on Effective Use of Daylight Harvesting Using Intelligent Lighting Control Systems for Sustainable Office Buildings in India." Sustainability 13, no. 9: 4973.

Journal article
Published: 26 April 2021 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009′s H1N1 swine flu and 2003′s severe acute respiratory syndrome (SARS) outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in Pakistan are scarce. The current research aims to overcome this research void and contributes by expanding the theoretical mechanism of theory of planned behavior (TPB) to include three novel dimensions (risk perceptions of the pandemic, perceived benefits of face masks, and unavailability of face masks) to comprehensively analyze the factors that motivate people to, or inhibit people from, wearing face masks. The study is based on an inclusive questionnaire survey of a sample of 738 respondents in the provincial capitals of Pakistan, namely, Lahore, Peshawar, Karachi, Gilgit, and Quetta. Structural equation modeling (SEM) is used to analyze the proposed hypotheses. The results show that attitude, social norms, risk perceptions of the pandemic, and perceived benefits of face masks are the major influencing factors that positively affect public WTW face masks, whereas the cost of face masks and unavailability of face masks tend to have opposite effects. The results emphasize the need to enhance risk perceptions by publicizing the deadly effects of COVID-19 on the environment and society, ensure the availability of face masks at an affordable price, and make integrated and coherent efforts to highlight the benefits that face masks offer.

ACS Style

Muhammad Irfan; Nadeem Akhtar; Munir Ahmad; Farrukh Shahzad; Rajvikram Elavarasan; Haitao Wu; Chuxiao Yang. Assessing Public Willingness to Wear Face Masks during the COVID-19 Pandemic: Fresh Insights from the Theory of Planned Behavior. International Journal of Environmental Research and Public Health 2021, 18, 4577 .

AMA Style

Muhammad Irfan, Nadeem Akhtar, Munir Ahmad, Farrukh Shahzad, Rajvikram Elavarasan, Haitao Wu, Chuxiao Yang. Assessing Public Willingness to Wear Face Masks during the COVID-19 Pandemic: Fresh Insights from the Theory of Planned Behavior. International Journal of Environmental Research and Public Health. 2021; 18 (9):4577.

Chicago/Turabian Style

Muhammad Irfan; Nadeem Akhtar; Munir Ahmad; Farrukh Shahzad; Rajvikram Elavarasan; Haitao Wu; Chuxiao Yang. 2021. "Assessing Public Willingness to Wear Face Masks during the COVID-19 Pandemic: Fresh Insights from the Theory of Planned Behavior." International Journal of Environmental Research and Public Health 18, no. 9: 4577.

Journal article
Published: 25 April 2021 in Journal of Industrial Ecology
Reads 0
Downloads 0

Industrial symbiosis (IS) promotes collaboration among traditionally unrelated industries, finding ways to use waste from one as a raw material for another. To enhance IS sustainability, it is essential that involved firms are aware of potential costs and benefits of new exchanges to make informed decisions. Previous assessments have primarily focused on environmental and financial implications of potenial IS synergies, but social implications are rarely addressed. Even when considered, only a limited set of social indicators, such as job creation, development of social ties, and trust among partners, are used. Such an unbalanced focus on sustainability aspects may contribute to problem shifting and suboptimal selection of new synergies. A comprehensive life cycle sustainability assessment (LCSA) of IS, covering all three dimensions is clearly lacking. Conventionally, a triple bottom line (TBL) approach is used to evaluate sustainability; however, we explore the concept of capitals and develop a capital‐based LCSA framework as a means to evaluate sustainability of IS by examining the stocks and flows of eight different types of capital, or resources creating value, in a system. Measuring stocks and flows is conceptually much closer to the actual definition of sustainability (meeting the needs of the present by maintaining the available stocks without compromising the future needs), when compared to the TBL approach of simply aggregating environmental, social, and economic impact assessment results. This novel LCSA approach is tested at a facility with active IS, The Plant in Chicago, considering three alternative fuel usage scenarios for baking bread at an on‐site bakery.

ACS Style

Karpagam Subramanian; Shauhrat S. Chopra; Weslynne S. Ashton. Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies. Journal of Industrial Ecology 2021, 1 .

AMA Style

Karpagam Subramanian, Shauhrat S. Chopra, Weslynne S. Ashton. Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies. Journal of Industrial Ecology. 2021; ():1.

Chicago/Turabian Style

Karpagam Subramanian; Shauhrat S. Chopra; Weslynne S. Ashton. 2021. "Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies." Journal of Industrial Ecology , no. : 1.

Journal article
Published: 23 April 2021 in Applied Sciences
Reads 0
Downloads 0

Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.

ACS Style

Poushali Pal; Parvathy Krishnamoorthy; Devabalaji Rukmani; S. Antony; Simon Ocheme; Umashankar Subramanian; Rajvikram Elavarasan; Narottam Das; Hany Hasanien. Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework. Applied Sciences 2021, 11, 3814 .

AMA Style

Poushali Pal, Parvathy Krishnamoorthy, Devabalaji Rukmani, S. Antony, Simon Ocheme, Umashankar Subramanian, Rajvikram Elavarasan, Narottam Das, Hany Hasanien. Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework. Applied Sciences. 2021; 11 (9):3814.

Chicago/Turabian Style

Poushali Pal; Parvathy Krishnamoorthy; Devabalaji Rukmani; S. Antony; Simon Ocheme; Umashankar Subramanian; Rajvikram Elavarasan; Narottam Das; Hany Hasanien. 2021. "Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework." Applied Sciences 11, no. 9: 3814.

Research article
Published: 15 April 2021 in International Transactions on Electrical Energy Systems
Reads 0
Downloads 0

Microgrid is an ideal solution to many problems that exist in conventional electrical grids mainly electrical power reliability concerns. Power quality disturbances are of equal concern as power reliability since they have a direct impact on load's life and performance. Microgrid is unable to tackle power quality‐related problems in electrical grids without additional support. A unified power quality conditioner (UPQC) is top‐ranked power quality compensation device; it minimizes the vulnerability toward power quality problems through its series and shunt compensators, which are connected via two voltage source converters (VSCs). However, the performance of UPQC mainly depends on the controllers directing the VSCs. In this article, the authors have proposed a new controller for microgrid connected UPQC, which controls the switching of VSCs of UPQC by taking the derivative of error at three different stages and then integrates it over time, while being supplemented by three gains, to improve its stability and performance toward power quality problems. The authors have also used fuzzy logic‐based sensing to trigger the switching of series or shunt compensators to condition any voltage sag/swell, voltage transients, current harmonics, current unbalance, and voltage unbalance problem. The stability assessment of proposed controller has been carried out by using Lyapunov stability criteria and bode plots. The performance has been analyzed through simulations in MATLAB/Simulink environment on a 400 V, 5.63 kVA LV distribution system. The results have been compared with the classical PI controller and validate that the proposed controller gives a better performance in terms of considered power quality problems like voltage sag/swell, transients and current unbalances and harmonics. The total harmonic distortion with the proposed controller has been reduced to 3.32%. Furthermore, as compared to other standard controllers, the proposed controller ends up in less complexity, fast response time, and stable performance.

ACS Style

Ahsan Iqbal; Asad Waqar; Rajvikram Madurai Elavarasan; Manoharan Premkumar; Toqeer Ahmed; Umashankar Subramaniam; Saad Mekhilef. Stability assessment and performance analysis of new controller for power quality conditioning in microgrids. International Transactions on Electrical Energy Systems 2021, 31, e12891 .

AMA Style

Ahsan Iqbal, Asad Waqar, Rajvikram Madurai Elavarasan, Manoharan Premkumar, Toqeer Ahmed, Umashankar Subramaniam, Saad Mekhilef. Stability assessment and performance analysis of new controller for power quality conditioning in microgrids. International Transactions on Electrical Energy Systems. 2021; 31 (6):e12891.

Chicago/Turabian Style

Ahsan Iqbal; Asad Waqar; Rajvikram Madurai Elavarasan; Manoharan Premkumar; Toqeer Ahmed; Umashankar Subramaniam; Saad Mekhilef. 2021. "Stability assessment and performance analysis of new controller for power quality conditioning in microgrids." International Transactions on Electrical Energy Systems 31, no. 6: e12891.

Review
Published: 12 April 2021 in International Journal of Energy Research
Reads 0
Downloads 0

With the growth of forecasting models, energy forecasting is used for better planning, operation, and management in the electric grid. It is important to improve the accuracy of forecasting for a faster decision‐making process. Big data can handle large scale of datasets and extract the patterns fed to the deep learning models that improve the accuracy than the traditional models and hence, recently started its application in energy forecasting. In this study, an in‐depth insight is initially derived by investigating artificial intelligence (AI) and machine learning (ML) techniques with their strengths and weaknesses, enhancing the consistency of renewable energy integration and modernizing the overall grid. However, Deep learning (DL) algorithms have the capability to handle big data by capturing the inherent non‐linear features through automatic feature extraction methods. Hence, an extensive and exhaustive review of generative, hybrid, and discriminative DL models is being examined for short‐term, medium‐term, and long‐term forecasting of renewable energy, energy consumption, demand, and supply etc. This study also explores the different data decomposition strategies used to build forecasting models. The recent success of DL is being investigated, and the insights of paradoxes in parameter optimization during the training of the model are identified. The impact of weather prediction in the wind and solar energy forecasting is examined in detail. From the existing literatures, it has seen that the average mean absolute percentage error (MAPE) value of solar and wind energy forecasting is 10.29% and 6.7% respectively. Current technology barriers involved in implementing these models for energy forecasting and the recommendations to overcome the existing system barriers are identified. An in‐depth analysis, discussions of the results, and the scope for improvement are provided in this study including the potential directions for future research in the energy forecasting.

ACS Style

Jayanthi Devaraj; Rajvikram Madurai Elavarasan; Gm Shafiullah; Taskin Jamal; Irfan Khan. A holistic review on energy forecasting using big data and deep learning models. International Journal of Energy Research 2021, 45, 13489 -13530.

AMA Style

Jayanthi Devaraj, Rajvikram Madurai Elavarasan, Gm Shafiullah, Taskin Jamal, Irfan Khan. A holistic review on energy forecasting using big data and deep learning models. International Journal of Energy Research. 2021; 45 (9):13489-13530.

Chicago/Turabian Style

Jayanthi Devaraj; Rajvikram Madurai Elavarasan; Gm Shafiullah; Taskin Jamal; Irfan Khan. 2021. "A holistic review on energy forecasting using big data and deep learning models." International Journal of Energy Research 45, no. 9: 13489-13530.

Journal article
Published: 11 April 2021 in Applied Energy
Reads 0
Downloads 0

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.

ACS Style

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 Style

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.

Chicago/Turabian Style

Rajvikram 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.

Journal article
Published: 06 April 2021 in IEEE Access
Reads 0
Downloads 0

The study of this work is to highlight the key metrics of various topologies in terms of output power, Fill Factor (FF), Mismatch Losses (ML) and efficiency. The idea behind this work is to analyze and obtain the performance of different topologies under various shading patterns. The major problem which comes across the path of Photovoltaic (PV) system performance is partial shading. The solution to this problem is to reconfigure the panels to achieve better results under shading conditions. For this, different configurations such as Series Parallel (SP), Total Cross Tied (TCT), Physical Relocation of Module with Fixed Electrical Connections (PRM-FEC), SuDoKu and Magic Square (MS) has been discussed, analyzed and compared using MATLAB/SIMULINK. Simulation approach is used to describe the working and evaluation of all configurations. By the results obtained, it is clearly visible that MS method have achieved largest output power of 2877 W, highest efficieny of 10.24 %, FF is 0.481 and lowest ML of 772 W among all the configurations under Long Narrow (LnN) pattern.

ACS Style

Snigdha Sharma; Lokesh Varshney; Rajvikram Madurai Elavarasan; Akanksha Singh S. Vardhan; Aanchal Singh S. Vardhan; R. K. Saket; Umashankar Subramaniam; Eklas Hossain. Performance Enhancement of PV System Configurations Under Partial Shading Conditions Using MS Method. IEEE Access 2021, 9, 56630 -56644.

AMA Style

Snigdha Sharma, Lokesh Varshney, Rajvikram Madurai Elavarasan, Akanksha Singh S. Vardhan, Aanchal Singh S. Vardhan, R. K. Saket, Umashankar Subramaniam, Eklas Hossain. Performance Enhancement of PV System Configurations Under Partial Shading Conditions Using MS Method. IEEE Access. 2021; 9 (99):56630-56644.

Chicago/Turabian Style

Snigdha Sharma; Lokesh Varshney; Rajvikram Madurai Elavarasan; Akanksha Singh S. Vardhan; Aanchal Singh S. Vardhan; R. K. Saket; Umashankar Subramaniam; Eklas Hossain. 2021. "Performance Enhancement of PV System Configurations Under Partial Shading Conditions Using MS Method." IEEE Access 9, no. 99: 56630-56644.