Standardization is essential for any technological advancement to have widespread adoption, ensure interoperability, enhance compatibility and create a consistent user experience across various platforms and sectors. In industries, Programmable Logic Controllers (PLCs) and Human-Machine Interfaces (HMIs) play a crucial role in automating processes, improving operational efficiency, ensuring safety and providing real-time monitoring and control. The evolution of the Internet of Things (IoT) has significantly improved the industrial automation process to a higher level by enhancing the connectivity and data-sharing capabilities of PLCs and HMIs, enabling predictive maintenance and remote management. To meet the increasing demand and seamless integration of diverse industrial devices, many modern PLCs have built-in support for IoT implementation (IoT-ready PLCs) using industrial communication protocols like Ethernet Industrial Protocol (Ethernet/IP), PROFINET, Modbus, etc., with a standard interface. On the other hand, many old PLCs (legacy PLCs) continue to remain influential in industrial automation, managing complex processes. However, they lack built-in support for IoT integration due to different communication interfaces, proprietary protocols, and obsolete technology. Interconnecting these legacy PLCs under a shared network for data exchange, diagnosis, and remote monitoring in the industrial setup is challenging. It demands a huge capital expenditure to replace the existing legacy PLC infrastructure with IoT-ready PLCs. This challenge needs to be addressed through standardization and middleware solutions. This paper presents the integration of different PLCs deployed at diverse locations for the Industrial Lighting Management System (LMS) with a centralized HMI through a shared network using IoT Technologies.

Adequate illumination is integral to performing any activity in manufacturing industries. In large-scale industries, various capacities and quantities of high bay luminaires (roof lights) are installed and distributed over the factory roofs to achieve the required illumination. Such enormous quantum is traditionally controlled by grouping them under multiple digital time switches distributed at diverse locations. The arduous activity of frequent rescheduling of time switches on a need basis is addressed by adopting a centralised controller called the Lighting Management System (LMS). However, the LMS lacks individual control of each distribution point (point-based) of roof lights due to limited control wires, leading to substantial energy wastage. This paper presents the design and implementation of point-based switching control using the Modbus Remote Terminal Unit (RTU) protocol on the existing control cable.

New policies are commenced all over the globe to diminish the use of fossil fuels, which gives rise to the augmented utilization of solar energy (SE). The photovoltaic (PV) system’s performance is extremely environmental variables reliant. Long-range transmission of SE is incompetent as well as complex to carry in the PV system. It can be affected by disparate sorts of faults, which cause severe energy loss all through the system operation. Thus, it is vital to incessantly monitor the solar PV (SPV) system to detect as well classify the faults by preventing energy losses. The IoT applications in SE production engage sensor devices that are fixed to the generation, and transmission, together with distribution equipment. These devices assist in monitoring the operation of the SPV power plant (SPVPP) system remotely in real-time. Presenting a new algorithm that can perform fault detection and classification in a PV system to a higher level of accuracy is the major contribution of this work. Thus, this work designs as well as develops an IoT platform for carrying out analytical tasks that can analyze data generated as of IoT operating systems to detect as well as classify faults in the SPVPP. Initially, the data collected from the dataset is pre-processed in which data duplication is performed using Hadoop distributed file system (HDFS) and then the fault is detected from the pre-processed data using the cosine function based k-means clustering (CFKC) technique in the SPV system. Finally, the obtained fault data is fed into the optimized deep learning centered ENN (ODENN) method which classifies the faults. The proposed techniques detect as well as classify the faults effectively that are experimentally proved by means of comparing them with the prevailing techniques, namely ENN, ANN and SVM, along with KNN in terms of some quality measures. The obtained results for ODENN showed an accuracy of 98.99%, specificity of 97.6%, and a sensitivity of 97.02%.

Today, Solar Photovoltaic (SPV) energy, an advancing and attractive clean technology with zero carbon emissions, is widely used. It is crucial to pay serious attention to the maintenance and application of Solar Power Generation (SPG) to harness it effectively. The design was more costly, and the automatic monitoring is not precise. The main objective of the work related to designed and built up the Internet of Things (IoT) platform to monitor the SPV Power Plants (SPVPP) to solve the issue. IoT platform designing and Data Analytics (DA) are the two phases of the proposed methodology. For building the IoT device in the IoT platform designing phase, diverse lower-cost sensors with higher end-to-end delivery ratio, higher network lifetime, throughput, residual energy, and better energy consumption are considered. Then, Sigfox communication technology is employed at the Low-Power Wireless Area Network (LPWAN) communication layer for lower-cost communication. Therefore, in the DA phase, the sensor monitored values are evaluated. In the analysis phase, which is the most significant part of the work, the input data are first pre-processed to avoid errors. Next, to monitor the Energy Loss (EL), the fault, and Potential Energy (PE), the solar features are extracted as of the pre-processed data. The significance of utilizing the Transformation Search centered Seagull Optimization (TSSO) algorithm, the significant features are chosen as of the extracted features. Therefore, the computational time of the solar monitoring has been decreased by the Feature Selection (FS). Next, the features are input into the Gaussian Kernelized Deep Learning Neural Network (GKDLNN) algorithm, which predicts the faults, PE, and EL. In the experimental evaluation, solar generation is assessed based on Wind Speed (WS), temperature, time, and Global Solar Radiation (GSR). The systems are satisfactory and produce more power during the time interval from 12:00 PM to 1:00 PM. The performance of the proposed method is evaluated based on performance metrics and compared with existing research techniques. When compared to these techniques, the proposed framework achieves superior results with improved precision, accuracy, F-measure, and recall.

ABSTRACT Modeling of solar photovoltaic cell is an essential requirement in the computations involved in solar photovoltaic power systems. Some metaheuristic algorithms are used for determining the cell parameters in the literature, however, more investigation is required with reference to varying solar irradiation and temperature to improve the accuracy of the models. Hence, this paper proposes firefly algorithm for identification of the cell parameters accurate enough to construct the cell characteristics under varying solar irradiation and temperature conditions. Experimental results obtained at standard irradiation and temperature of 1000 W/m2, 25°C, and at other irradiation levels such as 80 0 W/m2 and 600 W/m2, temperature levels such as 40°C and 50°C were presented along with simulated values. The value of series resistance, shunt resistance and diode ideality factor for temperatures from 20°C to 60°C and irradiation of 400 W/m2 to 1000 W/m2 are computed using this proposed method. A comparison of the proposed method with other researchers at irradiation of 1000, 800, and 600 W/m2 and 25°C was provided. The results of implementation show that there is a good agreement between computed values and data sheet values. The proposed method will definitely be useful for large scale solar photovoltaic designers, researchers, simulators.

This article presents a novel single axis solar tracking system to enable more solar radiation striking on the photovoltaic (PV) panel. The working principle is based on second-order lever principle. The single axis movement is carried out by balancing the mass of water together with the part mass of the PV panel on one side (left) of the fulcrum and the mass of the PV panel on the other side (right) of the fulcrum. Here the necessity of an external motor for axial movement of the PV panel is avoided. The design and performance of the proposed second-order lever single axis solar tracking system is studied for a period of 90 days (from January 2022 to March 2022). The proposed 20 Wp system prototype model is compared with the conventional single axis solar tracking (CSAST) system of the same rating. The working principle of the proposed system along with the operation of peripheral circuitry and gadgets are discussed. Finally, the percentage of increase in the solar power output in comparison with the CSAST system is estimated along with techno-economic analysis.

Operational requirements of photovoltaic (PV) modules result in their inherent exposure to harsh environmental conditions. The performance of solar cells decreases with increasing temperature, with both efficiency and power output getting affected. High ambient temperature coupled with irradiance absorption leads to an elevated photovoltaic cell operating temperature, adversely affecting the panels' lifespan. Superhydrophobic nanocoatings are the preferred solution to reduce the accumulation of dust (soiling) over the surface of the panels. This article aims to study the effects of nanocoatings on module operating temperature and temperature-dependent cell parameters, such as open-circuit voltage ( Voc ), short-circuit current ( Isc ) and power generation. The application of nanocoating over the surface of solar panels reduces the operating temperatures while improving power generation in a temperate location with high annual atmospheric temperatures.

Purpose. This article proposes a new control monitoring grid connected hybrid system. The proposed system, automatic detection or monitoring of fault occurrence in the photovoltaic application is extremely mandatory in the recent days since the system gets severely damaged by the occurrence of different faults, which in turn results in performance degradation and malfunctioning of the system. The novelty of the proposed work consists in presenting solar power monitoring and power control based Internet of things algorithm. In consideration to this viewpoint, the present study proposes the Internet of Things (IoT) based automatic fault detection approach, which is highly beneficial in preventing the system damage since it is capable enough to identify the emergence of fault on time without any complexities to generate Dc voltage and maintain the constant voltage for grid connected hybrid system. Methods. The proposed DC-DC Boost converter is employed in this system to maximize the photovoltaic output in an efficient manner whereas the Perturb and Observe algorithm is implemented to accomplish the process of maximum power point tracking irrespective of the changes in the climatic conditions and then the Arduino microcontroller is employed to analyse the faults in the system through different sensors. Eventually, the IoT based monitoring using fuzzy nonlinear autoregressive exogenous approach is implemented for classifying the faults in an efficient manner to provide accurate solution of fault occurrence for preventing the system from failure or damage. Results. The results obtained clearly show that the power quality issue, the proposed system to overcome through monitoring of fault solar panel and improving of power quality. The obtained output from the hybrid system is fed to the grid through a 3ϕ voltage source inverter is more reliable and maintained power quality. The power obtained from the entire hybrid setup is measured by the sensor present in the IoT based module. The experimental validation is carried out in ATmega328P based Arduino UNO for validating the present system in an efficient manner. Originality. The automatic Fault detection and monitoring of solar photovoltaic system and compensation of grid stability in distribution network based IoT approach is utilized along with sensor controller. Practical value. The work concerns a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. It tracks and manages network statistics for safe and efficient power delivery. The study is validated by the simulation results based on real interfacing and real time implementation.

Power generation of photovoltaic (PV) modules undergoes harsh environmental conditions. Accumulation of dust on the surface of PV modules, also referred to as soiling is one of the important factors. It limits the penetration of solar energy onto the solar cell and reduces the energy output. This article aims to study the detrimental effects of soiling losses on solar modules in a real-time industrial environment. The role of hydrophobic nanocoatings in mitigating these losses is also investigated. Reduction in accumulation of dust, both in terms of the particle composition and deposition densities, shows significant improvements in reducing the transmission loss. In this article, we tested and validated the performance of hydrophobic nanocoatings on PV modules, at Bharat Heavy Electricals Limited campus in Tiruchirappalli, Tamil Nadu, India [10°48′18′′N,78°41′8′′E]. Application of the nanocoating demonstrated a significant increase in power generation under various climatic conditions in the location.

This research work is concerned with maximum power point tracking (MPPT) in photovoltaic (PV) systems under partially shaded conditions (PSCs) through an improved particle swarm optimisation (PSO). The traditional PSO is investigated toward MPPT and the reasons for delayed convergence characteristics are investigated. Then, a modified PSO is proposed, in which population is reduced sequentially by eliminating less-promising particles. The new concept is applied to a 30 kW PV plant situated in a school building and the results are analysed. The new methodology is also experimentally verified on a 400 W prototype PV system in the laboratory. Enhanced energy harvesting from the existing 30 kW PV plant is highlighted considering realistic shading patterns and full bright conditions of solar insolation. The computed and measured results clearly demonstrate that the new PSO is a promising candidate for MPPT in PV systems under PSC.

This study presents the investigation of benefits obtained in a mirror integrated standalone photovoltaic (PV) test system of 0.3 kW capacity. The enhancement of energy extraction is possible only through fixing the mirror at an optimal angle facing towards the PV panel. Hence, the optimal condition for the maximum energy extraction in a year at a specific location is derived and presented considering the total irradiation falling on the panel. A detailed estimation on performance indices and feasibility analysis for the mirror integrated solar PV system (MISPVS) is carried out for one year from May 2018 to April 2019 for the test system with and without mirror arrangement. The total energy generated from the MISPVS during the monitoring period is found to increase from 359.10 kWh to 468.10 kWh which is around 130.3% when compared with the traditional solar PV system (TSPVS). Finally, the experimental results show that the system efficiency and capacity utilisation factor of the proposed system is enhanced to 13.09 and 17.81%, respectively.

This paper presents a review of existing PV augmented mirroring schemes along with an enhanced energy extraction scheme for an existing solar PV system. Here, an array of plane mirrors is placed in the inter row spacing of the PV arrays at a suitable angle (theta(ms)) to enhance the sunlight harvesting on the panel. The theory of solar PV mirroring (SPVm) system is presented considering the variation of sun elevation angle (theta(e)) at the solar noon for all day of a year. The performance of the proposed system is monitored and compared with respect to a conventional SPV system of the same capacity for a duration of one year from January 2018 to December 2018 along with the weather conditions at the test site (Tiruchirappalli, India, 10.7542 degrees N, 78.7862 degrees E). The condition for optimal mirror angle is obtained based on the global irradiation impinged on the surface of the solar PV module at the test site. Detailed statistical performance analysis on annual energy yield is calculated for the test period. Also, the limitation of the proposed system due to increase in PV cell temperature is discussed. It is observed from the experimental result that an energy extraction of around 30% higher than the conventional SPV system is obtained. Finally, a feasibility analysis on the impact and economic aspects on an industrial PV plant of 5 MW capacity in the same location is carried out. The system degradation inclusive of PV cell temperature and mirror degradation is suitably considered in the feasibility study. It is found that an expected IRR for SPV and SPVm system is around 11.99% and 13.45%, respectively.

Traditionally, butter extraction is done by churning a rod in curd or fresh milk cream. The duration of the churning process depends on a few parameters namely quantity, quality and initial temperature of the curd and speed of the churning. Usually, butter extraction is done in open loop and the process is stopped when good quality of butter is separated. The main objective of this research paper is to reiterate the traditional manufacturing process of butter extraction system by>1.Design a belt - drive based butter extraction machine with the help of an electric motor. This design will include both the electrical and mechanical aspects.>2.Fabrication of proto type as per proposed design.>3.Performance evaluation of developed butter extraction system.The successful development of this butter extraction system will reduce drudgery and time taken associated with the conventional method of butter extraction and therefore thus will improve the butter yield and less time taken for butter extraction.

Abanishwar Chakrabarti 465, 469, 845, 882, 1007 Abdul Azeem 218, 496, 900 Abdul Hamid Bhat 372 Abhijit Kadam 773 Abhijit Kshirsagar 254, 1044 Abhilash Krishna D G 622 Abhinandan Basak 271 Abhisek Ukil 623 Abhishek Banik 1001 Abhishek K. Tripathi 547 Abhishek Kar 533, 714 Abhishek Majumder 910 Aby Joseph 232, 465 Adarsh Pandey 854 Adil Sarwar 218, 749 Aditya Narula 699 Aditya Zade 194 Adrish Bhaumik 78 Ajad Howeldar 437 Ajit Srivastava 45 Akansha Garg 569 Akhil Vinayak B 599, 986 Akhilesh K 853 Akshatha S 903 Akshay Khadse 180

Conventionally, butter is extracted by agitating dairy products, such as curd, fermented milk or fresh cream. A stirring rod is used to stir the curd or fresh cream inside a cylindrical vessel manually either using ropes or with crank assembly. This process is adopted in all the village households of agricultural communities in India and other developing countries. The process of butter extraction is also mechanized using electric motors and is being used in dairy industries where production of huge quantity of butter is involved; however, a butter extraction system suitable for household application, where less quantity of butter is produced. This will be one of the main sources of revenue for villagers. This present butter extraction method is demands huge physical work and lacks in efficiency and quality. Without standard guidelines for procedure or standard steps to follow, the present process is difficult to reiterate. The focus of this paper is to update the current manual method to electric driven butter extraction system for small-scale application. The butter churner is stirred vigorously in both front and backward directions with the electric drive, which will help in separating the butter from the cream or curd. The operation of butter extraction system is observed to be a non-linear system due to variable churning speed requirement. The main aim of this paper is to propose the design aspects, which includes electrical and mechanical design of butter extraction system to have better performance in terms of productivity rate, saving time and simplicity of use.

A dual input LED lighting scheme with constant illumination is proposed in this paper. The scheme employs a photovoltaic array as the first input and a battery as the second one. A microcontroller is programmed to operate a changeover switch as well as a DC-DC converter for uninterrupted and constant illumination in work place. The scheme is suitable for conference halls, laboratories, clean rooms, marriage halls, theaters, etc. The complete modeling, design and experimentation of the proposed scheme are explained and the economic viability of the scheme is justified.

Majority of people in India live in villages and main source of income comes from agriculture. Many houses in the villages possess cattle of different varieties and milk products such as curd, butter yield additional income. Traditionally butter is extracted by manually churning curd. This paper proposes an autonomous system based on fuzzy logic principles to extract maximum butter minimum time. The apparatus for butter extraction consists of a PV panel, DC-DC converter and a d.c. motor. The butter extraction is conceived as a non-linear process and relevant inputs and outputs are mapped into fuzzy sets. The rule base is then designed. The proposed scheme is validated through simulation results.

This paper discusses the results obtained from a solar powered LED roadway lighting system in a reputed manufacturing industry in India. This system is an alternative to conventional grid powered high pressure sodium vapour roadway lighting existing in the industry. Design of LED lighting system for replacing the existing high pressure sodium vapour lamp considering the pupil lumens is discussed in detail. Sizing of solar photovoltaic modules and battery capacity for the project along with development of charge controller and LED driver are deliberated in the paper. A few salient features of solar powered LED roadway lighting system such as module mounting design, operational performance, economic feasibility of the system etc. are also well documented in this work.

Present day industrialization faces a major challenge of power shortage which adversely affects the industrial production due to energy crisis. Governments devised various schemes to support renewable energy generation in order to supplement the conventional energy resources; a range of incentives, subsidies, soft loans, and tax credits are introduced to increase power capacity through renewable energy resources such as solar, wind, and biomass. This paper emphasizes on a photovoltaic and battery fed autonomous induction motor drive system suitable for small scale industries which were either suffering due to long power outages or inaccessibility of grid power. The two sources are suitably integrated through a DC-DC converter system and then connected to a multilevel inverter. A battery charger is integrated with the system which ensures near-full battery voltage always and improves reliability of the system. The proposed scheme is presented with different modes of operation and also experimented with a real time application.

This paper describes the design and development of an eco-friendly lighting system installed in a modular office room, where artificial lights are indispensable even during daytime. While solar powered lighting systems are recently introduced, the major challenges such as design of suitable power converters as well as power management still persist. In this work, the conventional light fittings are replaced with LED fittings and grid power is replaced by solar photovoltaic power. Optimum configuration of components to design a solar powered LED day-lighting for modular office application is well explained in this paper. A cost comparison between conventional lighting system and solar powered LED lighting system show the real energy conservation achieved by this implement.