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Performance of Monofacial and Bifacial Solar System for 5MW grid-connected solar power plant with Fixed Tilt and Tracking: Design, Simulation and investigating the effect of temperature

Performance of Monofacial and Bifacial Solar System for 5MW ...

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Conference on Electrical Power Distribution Networks (EPDC)

作者： Mostafa Eidiani Afrooz Ghavami Hossein Zeynal Zuhaina Zakaria Energy Security and Sustainable Energy Institute Modarres 4 P.C.: *** Mashhad Iran Master of Electrical Engineering-Energy Systems Planning and Management Researcher Esfarayen Iran Dept. of Electrical and Computer Eng Buein Zahra Technical University Buein Zahra Qazvin Iran School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Malaysia

ISBN: (数字)9798350385502

ISBN: (纸本)9798350385519

In this paper, a 5000 kW grid-connected photovoltaic system of Haft-Hoze Natural Park, 7 km southeast of Mashhad City, has been designed and simulated. This power plant is for two monofacial and bifacial systems in both fixed and tilted planes and trackers modes in PVSYST software. It is simulated and designed and the simulation data is compared in both cases. In this paper, the effect of temperature on solar panel performance is investigated first. This work has been done in three stages. At first, by keeping the solar radiation constant, the effect of temperature on the output performance of the panel. In the next step, the P-V curves at different ambient temperatures and changes in solar radiation have been investigated. In the following, it shows the effect of PV panel temperature on PV panel output performance at different intensities of solar radiation. The simulation results of the 5000 kW solar power plant, in a fixed tilted plane for the monofacial system, energy injected into the grid and performance ratio are 8291 MWh and 0.850. The bifacial system, energy injected into the grid, and performance ratio are 8730 MWh and 0.896. In the Trackers mode, for the monofacial system, energy injected to the grid and performance ratio are 9558 MWh and 0.838. For the bifacial system, energy injected into the grid and performance ratio are 10025 MWh and 0.880.

关键词： Temperature distribution Simulation Urban areas Power distribution Software Solar system Solar radiation

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Exploratory Data Analysis using Autoviz for Machine Learning Classification Problem

Exploratory Data Analysis using Autoviz for Machine Learning...

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Emerging Innovations and Advanced Computing (INNOCOMP), International Conference on

作者： Guru Prasad M S Praveen Gujjar J Arnav Kotiyal Prasanna Kumar H R Raghavendra M Devadas Afsar Jahan Department of Computer Science and Engg. Graphic Era (Deemed to be University) Dehradun India Faculty of Management Studies JAIN (Deemed-to-be University) Bengaluru India Dept. of Information Science & Engg. Visvesvaraya Technological University PESITM Shivamogga India Department of Computer Science and Engineering Gitam School of Technology Gitam University Bengaluru India Department of Computer Application Graphic Era (Deemed to be University) Dehradun India

ISBN: (数字)9798350376470

ISBN: (纸本)9798350376487

As the field of machine learning continues to advance, the importance of effective exploratory data analysis (EDA) cannot be overstated, especially in the context of classification problems. This research paper introduces an innovative and automated approach to exploratory data analysis using Autoviz, a powerful Python library designed to streamline the visualization process for machine learning datasets. The study aims to demonstrate the efficacy of Autoviz in meaningful insights, facilitating feature understanding, and supporting data preprocessing for classification tasks. Furthermore, the paper discusses how Autoviz assists in feature selection by highlighting the relevance and importance of each feature about the target variable. This feature-centric analysis contributes to optimizing machine learning models by guiding the selection of relevant input features, thereby improving model accuracy and interpretability. Autoviz is a Python library designed to automate the exploratory data analysis (EDA) process for machine learning tasks. It is specifically tailored to generate a variety of visualizations that aid in understanding the structure and characteristics of a dataset. The results indicate that Autoviz significantly reduces the time and effort required for exploratory data analysis while maintaining the quality and dept. of insights obtained. The differences between Autoviz and Pycaret is discussed in this paper. It has been observed that AutoViz automates the process of exploring and analyzing data, while PyCaret is designed for the comparison, construction, and tuning of machine learning models.

关键词： Analytical models Technological innovation Data analysis Navigation Data visualization Machine learning Feature extraction

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Performance of Bifacial Solar System for 1MW grid-connected solar power plant in Mashhad, Iran: Design, Simulation and Economic Analysis

Performance of Bifacial Solar System for 1MW grid-connected ...

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Technology and Energy management (ICTEM), International Conference on

作者： Mostafa Eidiani Hossein Zeynal Afrooz Ghavami Zuhaina Zakaria Energy Security and Sustainable Energy Institute Modarres 4P.C.: *** Mashhad Iran Dept. of Electrical and Computer Eng Buein Zahra Technical University Buein Zahra Qazvin Iran Master of Electrical Engineering-Energy Systems Planning and Management Researcher Esfarayen Iran School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Malaysia

ISBN: (数字)9798350329797

ISBN: (纸本)9798350329803

In this paper, a 1 MW solar power plant has been designed by bifacial panels in Mashhad and from an economic and environmental perspective, it examined the issue. Determining the distance of the panels from each other, the appropriate angle of the panels has been checked to estimate the optimal efficiency of the system. In addition to producing 1812 megawatt hours per year, the system has a Performance Ratio (PR) of $93.42 \%$, and the return on investment (ROI) and Net Present Cost (NPC) are respectively $31.4 \%$ and 7’892’184.18 h-t. As a result, a bifacial solar module’s energy output is affected by a number of factors: the installation height of the solar module, the reflection coefficient of the surface below the module, tilt angles and pitch. Therefore, in this project, the performance of each of these parameters has been investigated and evaluated for different values in the power plant. Pvsyst is used as simulation software to design and simulate PV systems.

关键词： Photovoltaic systems Costs Buildings Software Solar system Reflection coefficient Energy management

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The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

The Goldilocks Framework: Towards Selecting the Optimal Appr...

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AI engineering - Software engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Rimman Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies’ industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.

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Nothing About Us Without Us: a participatory design for an Inclusive Signing Tiago Robot

Nothing About Us Without Us: a participatory design for an I...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Emanuele Antonioni Cristiana Sanalitro Olga Capirci Alessio Di Renzo Maria Beatrice D'Aversa Domenico Bloisi Lun Wang Ermanno Bartoli Lorenzo Diaco Valentina Presutti Daniele Nardi Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy International Telematic University UNINETTUNO Rome Italy Institute for Cognitive Sciences and Technologies - National Research Council (ISTC-CNR) Rome Italy School of LIS - SILIS Group Rome Italy Dept. of Mathematics Computer Science and Economics University of Basilicata Potenza Italy LILEC University of Bologna Bologna Italy

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

The success of the interaction between the robotics community and the users of these services is an aspect of considerable importance in the drafting of the development plan of any technology. This aspect becomes even more relevant when dealing with sensitive services and issues such as those related to interaction with specific subgroups of any population. Over the years, there have been few successes in integrating and proposing technologies related to deafness and sign language. Instead, in this paper, we propose an account of successful interaction between a signatory robot and the Italian deaf community, which occurred during the Smart City Robotics Challenge (SciRoc) 2021 competition 1 . Thanks to the use of a participatory design and the involvement of experts belonging to the deaf community from the early stages of the project, it was possible to create a technology that has achieved significant results in terms of acceptance by the community itself and could lead to significant results in the technology development as well.

关键词： Deafness Social networking (online) Smart cities Sociology Collaboration Gesture recognition Organizations

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FDP-GAMLP: New Financial Distress Prediction Technique based on Genetic Algorithm and Multi-Layer Perceptron 19

FDP-GAMLP: New Financial Distress Prediction Technique based...

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19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

作者： Khedr, Ahmed M. Bannany, Magdi El Saif, Abdul-Wahid A. University of Sharjah Computer Science Dept. Sharjah27272 United Arab Emirates College of Business Administration Umm Al Quwain University Umm Al Quwain356 United Arab Emirates Ain Shams University Faculty of Business Cairo11566 Egypt King Fahd University of Petroleum & Minerals Control and Instrumentation Engineering Department Dhahran Saudi Arabia

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

Developing a reliable financial distress prediction model has been a long-standing research area. Recently, machine learning algorithms have been increasingly popular in the area. In this paper, a hybrid approach of Genetic Algorithm (GA) and Multi-Layer Perceptron (MLP) for Financial Distress Prediction (FDP) (FDP-GAMLP) is proposed. FDP-GAMLP emphasizes on GA-based tuning of the four major hyper-parameters, namely network width, network dept., network optimizer, and dense layer activation function, which can influence on whether the algorithm explodes or converges. An improved GA is utilized to optimize the MLP model's hyper-parameters for better prediction. The prediction performance is evaluated using real data set with samples of companies from countries in Middle East region. The resampling technique using k-fold evaluation metrics is adopted to get unbiased and most accurate results. The simulation results show that FDP-GAMLP outperforms the classical machine learning models in terms of predictive accuracy. © 2022 IEEE.

关键词： Genetic algorithms

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Challenges in developing and deploying AI in the engineering, procurement and construction industry

Challenges in developing and deploying AI in the engineering...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Rimma Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

AI in the engineering, Procurement and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Several research papers exist describing the potential of AI, and many surveys and white papers have been published indicating the challenges of AI deployment in the EPC industry. However, there is a recognizable shortage of in-dept. studies of deployment experience in academic literature, particularly those focusing on the experiences of EPC companies involved in large-scale project execution with high safety standards, such as the petrochemical or energy sector. The novelty of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

关键词： Industries Procurement Companies Manuals Petrochemicals Software Safety

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Regional Vegetation Cover Prediction Using Spatial Image Features and Semantic Segmentation

SSRN

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SSRN 2022年

作者： Chirkhare, Ganesh Hablani, Ramchand Balamwar, Sanjay Dept. of Computer Science and Engg. Shri Ramdeobaba College of Engineering & Management Nagpur440013 India Maharashtra Remote Sensing Application Centre Nagpur440011 India

Vegetation indices play a vital role in monitoring dissimilarity in vegetation. This paper presents a better procedure for the purpose of analysis and representation of multi-spectral satellite images based upon Atmospherically Resistant Vegetation Index (ARVI) and U-Net. The vegetation detection methods were applied to color images which consist of R, G, B and near-infrared (NIR) bands. Common approaches usually apply the Normalized Difference Vegetation Index (NDVI) to indicate the greenery of environment. However, there are some potential errors and inaccuracies with NDVI, one of the most important imperfection is that it is incorrect for changes in solar incidence angle, this method also produces inaccurate data due to varying factors including shadowing, air moisture, and variations in the soil. It has been found that using ARVI and deep learning helps in eliminating these errors up to some extent, and correct the inaccuracies of NDVI, which results in slight improved and near accurate vegetation segmentation. This method can be utilized for prediction of vegetation in a region for the purpose of city planning and reforestation. © 2022, The Authors. All rights reserved.

关键词： Vegetation

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Role of Online Shopping Websites in Consumer Satisfaction Based Statistical Analysis

Role of Online Shopping Websites in Consumer Satisfaction Ba...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Mohit Mittal Hardeep Singh Shaifali Chauhan Swadha Gupta Knowtion GmbH Karlsruhe Germany Dept. of Computer Engineering & Technology Guru Nanak Dev University (of Affiliation) Amritsar India Prestige Institute of Management Gwalior India Deptt. Of Comp. Sci. and Engg. Thapar Institute of Engineering and Technology Patiala India

Nowadays, online shopping is very popular as there are many platforms are available. To dig into the consumer behavior for shopping there are many researchers, industries are working to provide the model to analyze consumer satisfaction. As people are searching a lot over the websites according to their interests, so the data is collected by the platforms and do analysis over it to find the consumer behaviour to improve their search and improve the platforms accordingly. Therefore, there is also need to analyze the selfcongurance, impulse buying and price sensitivity parameters which are directly or indirectly impact on the consumer satisfaction. Our aim is to develop a model to analyzes above mentioned parameters and find the relationship between each other. We also suggested some hypotheses and evaluate based statistical technique. The overall result is quiet satisfying.

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Multi-Agent Systems for Collaborative Financial Decision-Making Over Distributed Network Architectures 3

Multi-Agent Systems for Collaborative Financial Decision-Mak...

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3rd International Conference on Advancement in Computation and computer Technologies, InCACCT 2025

作者： Fnu, Himani Kaushik, Keshav Gaur, Priyanka Saratchandran, Divya Valsala Thapliyal, Anju Gairola Sidhu, Kawerinder Singh Singh, Vineeta Wipro Ltd ChicagoIL United States Sharda School of Computer Science & Engineering Sharda University Greater Noida India Dept. of Computer Applications Chandigarh Group of Colleges Jhanjheri Mohali India Bath and Body Works Inc. Ohio43054 United States Management and Commerce Department Institute of Technology and Management Uttarakhand Dehradun India UIM Uttaranchal University Dehradun India Chhatrapati Shahu ji Maharaj University Uttar Pradesh Kanpur India

ISBN: (纸本)9798331543891

In financial collaborative decision-making use case, we focus on Multi-Agent Systems (MAS) based financial decision making through distributed network architectures. The study analyses agent collaboration efficiency, system scalability, communication overhead, and decision-making accuracy through simulating different scenarios. These results show that the system adapts to varying dynamic conditions, since it continues producing high performance as the number of agents and connectivity of the network both increase. To illustrate, heatmaps and comparisons of overhead and decision texts show less communication overhead and better decisions than traditional centralized approaches can generate. The results confirm the suitability of MAS for complex financial target patterns, thus providing a scalable, efficient and robust solution for the next generation of financial decision support systems. These findings help extend MAS-inspired approaches to distributed, high-stakes decision making environments. © 2025 IEEE.

关键词： Network function virtualization

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