i-manager Publications

i-manager's Journal on Power Systems Engineering (JPS)

Current Issue Vol. 11 Issue 3

Voltage Stability and Power Loss Minimization with STATCOM using Particle Swarm Optimization and Hybrid Firefly Particle Swarm Optimization Algorithms
Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage
Performance Analysis of Distribution System under Different Loading Conditions using Test Bench
Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate
Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors

Most Cited

Volume 10 Issue 3 August - October 2022

Article

Bagasse-Based Sugar Cogeneration Potential in India: A Source of Renewable Energy

Samsher Kadir Sheikh* , Manish Jain**

* Department of Electrical Engineering, Dr Vithalrao Vikhe Patil College of Engineering, Ahmednagar, Maharashtra, India.

** Department of Electrical and Electronics, Mandsaur University, Mandsaur, Madhya Pradesh, India.

Sheikh, S. K., and Jain, M. (2022). Bagasse-Based Sugar Cogeneration Potential in India: A Source of Renewable Energy. i-manager’s Journal on Power Systems Engineering, 10(3), 1-6. https://doi.org/10.26634/jps.10.3.19177

Abstract

India has been suffering from an acute shortage of electricity for several decades. The main reason is that there is a large gap between the demand and supply of electricity. Therefore, the government of India has recently promoted cogeneration in the sugar industry. The national power generation potential from bagasse cogeneration, according to the Ministry of New and Renewable Energy (MNRE), a study by the Government of India, is about 3,500 MW, while Maharashtra's potential is 1,250 MW. Indian Sugar Industries has the potential to produce an excess capacity of up to 5,000 MW in all sugar mills. Maharashtra again became India's leading sugar-producing state five years later. It overtook Uttar Pradesh in sugar production. The total sugar production in Maharashtra is 138 thousand metric tonnes for 2021–2022. In India, the sugar industry is the second-largest agro-industry and contributes significantly to the socioeconomic development of the country. Sugarcane is the main raw material for sugar production in India. Sugar cogeneration is the concept of producing two types of energy from one fuel. One form of energy must always be heated, and the other may be electricity or mechanical energy. In the cogeneration industry, very high-efficiency levels in the range of 75% to 90% can be achieved.

References

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Research Paper

Photovoltaic-Based Electric Vehicle Charging Station using GA Algorithm

Sweta Pandey* , Surekha Bhusnur, Naushin Anjum*

*-*** Bhilai Institute of Technology, Durg, Chhattisgarh, India.

Pandey, S., Bhusnur, S., and Anjum, N. (2022). Photovoltaic-Based Electric Vehicle Charging Station using GA Algorithm. i-manager’s Journal on Power Systems Engineering, 10(3), 7-16. https://doi.org/10.26634/jps.10.3.19172

Abstract

Detailed modeling of rapid charging Electric Vehicle (EV) stations connected to a hybrid grid-Renewable Energy Systems (RES), such as solar, mini-hydro, and wind, has been proposed. This assists in maximizing profit and lowering grid energy consumption. Since Photovoltaic (PV) systems exhibit several peaks under partial shading conditions; it is very difficult to track the global maximum point. Therefore, a broad search is needed to solve this nonlinear problem. Due to the variety of solutions, GA is preferred for solar MPPT. In comparison to the Genetic Algorithm (GA) and Maximum Power Point Tracking (MPPT) technique, the economic considerations obtained optimizes profit. It is also obvious that the proposed strategy lowers the grid's influence on the system network by capping the amount of electricity that may be exchanged between the system network and the grid. The voltage and current of PV array with GA method and GA MPPT technique results on the utility grid respectively.

References

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[2]. Alik, R., & Jusoh, A. (2018). An enhanced P&O checking algorithm MPPT for high tracking efficiency of partially shaded PV module. Solar Energy, 163, 570-580. https://doi.org/10.1016/j.solener.2017.12.050

[3]. Benkercha, R., Moulahoum, S., & Colak, I. (2017, December). Modelling of fuzzy logic controller of a maximum power point tracker based on artificial neural network. In 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 485-492). IEEE. https://doi.org/10.1109/ICMLA.2017.0-114

[4]. Ding, K., Bian, X., Liu, H., & Peng, T. (2012). A MATLABsimulink- based PV module model and its application under conditions of nonuniform irradiance. IEEE Transactions on Energy Conversion, 27(4), 864-872. https://doi.org/10.1109/TEC.2012.2216529

[5]. Ge, X., Ahmed, F. W., Rezvani, A., Aljojo, N., Samad, S., & Foong, L. K. (2020). Implementation of a novel hybrid BAT-Fuzzy controller based MPPT for grid-connected PVbattery system. Control Engineering Practice, 98, 104380. https://doi.org/10.1016/j.conengprac.2020.104380

[6]. Habib, S., Kamran, M., & Rashid, U. (2015). Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks-A review. Journal of Power Sources, 277, 205-214. https://doi.org/10.1016/j.jpowsour.2014.12.020

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[8]. Kermadi, M., & Berkouk, E. M. (2015, May). A maximum power point tracker based on particle swarm optimization for PV-battery energy system under partial shading conditions. In 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT) (pp. 1-6). IEEE. https://doi.org/10.1109/CEIT.2015.7233061

[9]. Kermadi, M., Salam, Z., Ahmed, J., & Berkouk, E. M. (2018). An effective hybrid maximum power point tracker of photovoltaic arrays for complex partial shading conditions. IEEE Transactions on Industrial Electronics, 66(9), 6990-7000. https://doi.org/10.1109/TIE.2018.2877202

[10]. Kota, V. R., & Bhukya, M. N. (2017). A novel linear tangents based P&O scheme for MPPT of a PV system. Renewable and Sustainable Energy Reviews, 71, 257-267. https://doi.org/10.1016/j.rser.2016.12.054

[11]. Li, C., Chen, Y., Zhou, D., Liu, J., & Zeng, J. (2016). A high-performance adaptive incremental conductance MPPT algorithm for photovoltaic systems. Energies, 9(4), 288. https://doi.org/10.3390/en9040288

[12]. Li, Y., Samad, S., Ahmed, F. W., Abdulkareem, S. S., Hao, S., & Rezvani, A. (2020). Analysis and enhancement of PV efficiency with hybrid MSFLA–FLC MPPT method under different environmental conditions. Journal of Cleaner Production, 271, 122195. https://doi.org/10.1016/j.jclepro.2020.122195

[13]. Mohapatra, A., Nayak, B., Das, P., & Mohanty, K. B. (2017). A review on MPPT techniques of PV system under partial shading condition. Renewable and Sustainable Energy Reviews, 80, 854-867. https://doi.org/10.1016/j.rser.2017.05.083

[14]. Patel, H., Gupta, M., & Bohre, A. K. (2016, December). Mathematical modeling and performance analysis of MPPT based solar PV system. In 2016 International Conference on Electrical Power and Energy Systems (ICEPES) (pp. 157-162). IEEE. https://doi.org/10.1109/ICEPES.2016.7915923

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[17]. Ranjan, K., & Kumar, N. (2016, July). Modelling and simulation of Perturb and Observe algorithm on solar PV system using different converters in MATLAB/SIMULINK. In 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) (pp. 1-6). IEEE. https://doi.org/10.1109/ICPEICES.2016.7853373

[18]. Titri, S., Larbes, C., Toumi, K. Y., & Benatchba, K. (2017). A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions. Applied Soft Computing, 58, 465-479. https://doi.org/10.1016/j.asoc.2017.05.017

[19]. Viswambaran, V. K., Ghani, A., & Zhou, E. (2016, December). Modelling and simulation of maximum power point tracking algorithms & review of MPPT techniques for PV applications. In 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA) (pp. 1-4). IEEE. https://doi.org/10.1109/ICEDSA.2016.7818506

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Research Paper

Combined Neural Network and Fuzzy Control for Maximum Power Point Tracking In Solar PV System

Keshaw Ram* , B. Chiranjeev Rao, Raina Jain*

* Department of Electrical and Electronics Engineering, Shri Shankaracharya Group of Institutions, Bhilai, India.

Department of Power System Engineering, Swami Vivekanand Technical University, Bhilai, India.

* Department of Electrical and Electronics Engineering, Chouksey Engineering College, Bilaspur, India.

Ram, K., Rao, B. C., and Jain, R. (2022). Combined Neural Network and Fuzzy Control for Maximum Power Point Tracking in Solar PV System. i-manager’s Journal on Power Systems Engineering, 10(3), 17-24. https://doi.org/10.26634/jps.10.3.19159

Abstract

The most effective renewable energy in the future among energy. Using photovoltaic (PV) panels is the most effective approach to utilize solar energy for electrical power. The photovoltaic panel that uses solar energy has non-linear voltage-current and voltage-control properties. The control yield from the solar-powered PV board is highest at a certain voltage point. The maximum power point voltage is the voltage at which the PV board produces the most power. The construction of the solar-powered PV board and a description of its features have been presented. In order to acquire the highest control point voltage, the difference between the real Maximum Power Point Tracking (MPPT) voltage and the MPPT voltage deduced from the Artificial Neural Network (ANN) arrangement is displayed, and it is successfully accepted. The result appears to be an exact match for the accuracy of ANN. The PV board's highest control point can be successfully and accurately tracked using the ANN display that was obtained. From the various results obtained, it becomes obvious that the suggested computation proves to be considerably simpler in following the PV board's most extreme control point. The reaction time is drastically reduced when the proposed control approach is used since the PV voltage closely tracks the highest control point voltage. Additionally, the proposed strategy's precision is incredibly logical. In every irradiance and temperature scenario, the control framework performs well.

References

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[4]. Beltran, A. A. (2019, October). Standalone Solar PV Maximum Power Point Tracking Using Interval Type-2 Fuzzy Logic. In 2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE) (pp. 534-537). IEEE. https://doi.org/10.1109/ECICE47484.2019.8942747

[5]. Canny, D., & Yusivar, F. (2018, August). Maximum power point tracking (MPPT) algorithm simulation based on fuzzy logic controller on solar cell with boost converter. In 2018 2nd International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 117-121). IEEE.

[6]. de Souza, A. C., Melo, F. C., Oliveira, T. L., & Tavares, C. E. (2016). Performance analysis of the computational implementation of a simplified PV model and MPPT algorithm. IEEE Latin America Transactions, 14(2), 792-798. https://doi.org/10.1109/TLA.2016.7437224

[7]. Ding, K., Bian, X., Liu, H., & Peng, T. (2012). A MATLABsimulink- based PV module model and its application under conditions of nonuniform irradiance. IEEE Transactions on Energy Conversion, 27(4), 864-872. https://doi.org/10.1109/TEC.2012.2216529

[8]. Djalab, A., Bessous, N., Rezaoui, M. M., & Merzouk, I. (2018, December). Study of the effects of partial shading on PV array. In 2018 International Conference on Communications and Electrical Engineering (ICCEE) (pp. 1-5). IEEE. https://doi.org/10.1109/CCEE.2018.8634512

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Review Paper

Solar Energy Applications for Agriculture: A Review

Manoj Khoja*

Department of Petroleum Engineering and Earth Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

Khoja, M. (2022). Solar Energy Applications for Agriculture: A Review. i-manager’s Journal on Power Systems Engineering, 10(3), 25-32. https://doi.org/10.26634/jps.10.3.19031

Abstract

Various solar energy harvesting technologies have been developed and tested for agricultural applications. Renewable energies such as biomass, solar, and wind energy offer long-term energy sources for farmers and can replace other fuels. Many renewable energy technologies are used in agriculture, depending on the type of energy required, the availability of renewable energy sources, and the design of agricultural structures and processes. Solar energy is used in agriculture for a variety of purposes to increase self-sufficiency, save money and bills, and reduce pollution when replaced with other fuels. Solar collectors can be used to dry plants and heat homes, barns, and greenhouses. These include solar thermal and electrical devices such as photovoltaics, solar water pumps, solar dryers, solar greenhouse heating, livestock ventilation, and solar aeration pumps, which can be powered by photovoltaics (solar panels). This article describes different types of applications used for agricultural purposes.

References

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Review Paper

Scope of Hydrogen-Based Vehicles in India: A Review

Shaswat Kumar*

UPES, University in Dehradun, Uttarakhand, India

Kumar, S. (2022). Scope of Hydrogen-Based Vehicles in India: A Review. i-manager’s Journal on Power Systems Engineering, 10(3), 33-43. https://doi.org/10.26634/jps.10.3.19170

Abstract

India is dealing with the problem of high automotive emissions as the number of vehicles on the road is rising. The primary cause of these emissions is the burning of crude oil. India imports crude oil from nations with abundant oil supplies because it lacks the resources to meet all of the country's energy needs for cars. There is a need to look for a carbon-free alternative fuel that is locally accessible in sufficient quantity to suit India's energy needs in order to address the problems related to oil imports and vehicle emissions. Hydrogen is a clean fuel choice among the potential energy sources because its combustion only yields water as a byproduct, and also due to its purity and high energy content, hydrogen energy offers a sustainable alternative to fossil fuels. India has the benefit of producing hydrogen from renewable sources like solar and wind during periods of lower demand because of its continuously expanding renewable energy generation capacity, and Asia is one of the continents with a wealth of these resources. Also, the exponential increase in food waste generation has prompted the scientific community to convert it into value-added resources. The main elements influencing the adoption of hydrogen as a cost-effective energy source in Asian nations are the availability of resources, safety requirements, public acceptance, and appropriate government incentives. The current analysis discusses the need to use hydrogen as an alternative fuel, its production processes, storage concerns, transportation, and the sources that are available. In various Asian nations like Japan, Korea, China, India, and Malaysia, particular focus has been placed on the notion of a renewable hydrogen economy. Perspectives on fuel supply, environmental effects, and social acceptance could help the biohydrogen energy sector evolve in a favorable way.

References

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i-manager's Journal on Power Systems Engineering (JPS)

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Volume 10 Issue 3 August - October 2022

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* Department of Electrical Engineering, Dr Vithalrao Vikhe Patil College of Engineering, Ahmednagar, Maharashtra, India. ** Department of Electrical and Electronics, Mandsaur University, Mandsaur, Madhya Pradesh, India.

Sheikh, S. K., and Jain, M. (2022). Bagasse-Based Sugar Cogeneration Potential in India: A Source of Renewable Energy. i-manager’s Journal on Power Systems Engineering, 10(3), 1-6. https://doi.org/10.26634/jps.10.3.19177

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Photovoltaic-Based Electric Vehicle Charging Station using GA Algorithm

Sweta Pandey* , Surekha Bhusnur**, Naushin Anjum***

*-*** Bhilai Institute of Technology, Durg, Chhattisgarh, India.

Pandey, S., Bhusnur, S., and Anjum, N. (2022). Photovoltaic-Based Electric Vehicle Charging Station using GA Algorithm. i-manager’s Journal on Power Systems Engineering, 10(3), 7-16. https://doi.org/10.26634/jps.10.3.19172

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Combined Neural Network and Fuzzy Control for Maximum Power Point Tracking In Solar PV System

Keshaw Ram* , B. Chiranjeev Rao**, Raina Jain***

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Solar Energy Applications for Agriculture: A Review

Manoj Khoja*

Department of Petroleum Engineering and Earth Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

Khoja, M. (2022). Solar Energy Applications for Agriculture: A Review. i-manager’s Journal on Power Systems Engineering, 10(3), 25-32. https://doi.org/10.26634/jps.10.3.19031

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Scope of Hydrogen-Based Vehicles in India: A Review

Shaswat Kumar*

UPES, University in Dehradun, Uttarakhand, India

Kumar, S. (2022). Scope of Hydrogen-Based Vehicles in India: A Review. i-manager’s Journal on Power Systems Engineering, 10(3), 33-43. https://doi.org/10.26634/jps.10.3.19170

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* Department of Electrical Engineering, Dr Vithalrao Vikhe Patil College of Engineering, Ahmednagar, Maharashtra, India.

** Department of Electrical and Electronics, Mandsaur University, Mandsaur, Madhya Pradesh, India.

Sweta Pandey* , Surekha Bhusnur, Naushin Anjum*

Keshaw Ram* , B. Chiranjeev Rao, Raina Jain*