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Development of a neural network model for solid municipal waste detection

AIP Conference Proceedings 2023年第1期2833卷

作者： Aleksandra Sivova Nikita Kostromin Elena Dushechkina Andreea Panea Department of power engineering Bauman Moscow State Technical University Moscow 105005 Russia Department of computer science and control systems Bauman Moscow State Technical University Moscow 105005 Russia

The article describes the results of developing a minimum viable product for the automatic sorting of municipal solid waste. A neural network model for detecting municipal solid waste was developed for automatic waste sorting. This neural network model has trained on the TACO (trash annotations in context) dataset, which was augmented with collected data from the Internet. A brief theory of neural networks is given: what is the object detection and how it is performed, the quality parameters of neural networks (metrics), which were used to increase the quality of the neural network model. Based on the analysis of the obtained metrics (precision, recall, f1-score), the best parameters for the developed neural network model are selected. Particular attention is paid to the prospects of using the detection of objects (municipal solid waste) to reduce the area of old and suspend the formation of new waste disposal sites (landfills). The consequences of the formation of landfills for both the environment and animals, including humans, are given. The degree of importance of the presented material is high for scientists and engineers of the countries, where the percentage of recyclable waste does not reach even 10%, as well as for novice developers of neural network models.

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Enhanced Subspace Distribution Matching for Fast Visual Domain Adaptation

Enhanced Subspace Distribution Matching for Fast Visual Doma...

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作者： Kang, Qi Yao, Siya Zhou, Mengchu Zhang, Kai Abusorrah, Abdullah Department of Control Science and Engineering Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ United States Department of Electrical and Computer Engineering Faculty of Engineering and Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah21481 Saudi Arabia Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

In computer vision, when labeled images of the target domain are highly insufficient, it is challenging to build an accurate classifier. Domain adaptation stands for an effective solution to address it by utilizing available and related source domain which has sufficient labeled images, even when there is a substantial difference in properties and distributions of these two domains. Yet, most prior approaches merely reduce subspace conditional or marginal distribution differences between domains but entirely ignoring label dependence (LD) information of source data in subspace. This article proposes a novel approach of domain adaptation, called enhanced subspace distribution matching (ESDM), which makes good use of label information to enhance the distribution matching between the source and target domains in a shared subspace. It reduces both conditional and marginal distributions in a shared subspace during a procedure of kernel principal dimensionality reduction and also preserves source data LD information to the maximum extent, thereby significantly improving cross domain subspace distribution matching. We also provide a learning algorithm with highly affordable computation, which solves the ESDM optimization problem without using time-consuming iterations. Results confirm that it can well outperform several recent domain adaptation methods on image classification tasks in terms of classification accuracy and running time. The results can be used in social cognition, person reidentification, and human-machine interactions. © 2014 IEEE.

关键词： Image classification

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A fast and effective maximum power point tracking method under various weather conditions for grid-connected photovoltaic systems

A fast and effective maximum power point tracking method und...

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IEEE Conference on power Electronics and Renewable Energy (CPERE)

作者： Karam Khairullah Mohammed Saad Mekhilef Muhyaddin Rawa Control and Mechatronics Engineering Department School of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia School of Software and Electrical Engineering Faculty of Science Engineering and Technology Swinburne University of Technology Hawthorn VIC Australia Smart Grids Research Group Center of Research Excellence in Renewable Energy and power Systems King Abdulaziz University Jeddah Saudi Arabia Department Of Electrical and computer Engineering Faculty of engineering K. A Care Energy Research and Innovation Center King Abdulaziz University Jeddah Saudi Arabia

Photovoltaic systems (PV) are exposed to various weather conditions during the day and getting the maximum power of a PV system is one of its major challenges. While the conventional methods take time to track the maximum power accompanying the fluctuation around the maximum power. Consequently, several metaheuristic algorithms have been presented to overcome the fluctuating around the maximum power. On the other hand optimization methods will search into entire the PV curve to extract the maximum power. This leads to unnecessary search points during the uniform shading conditions which decrease the convergence speed towards the maximum power. In overcoming the tracking time issues as well as the capacity to distinguish between uniform and partial shading conditions, a quick and efficient tracking technique connected to the grid system was presented in this paper. The proposed system, has been tested using MATLAB/SIMULINK, which includes a boost converter to track the maximum power with a sampling time of 0.05 seconds, While a voltage source converter (VSC) is used to transfer the power generated by solar panels to the grid. The simulation results demonstrated that the proposed method was successfully implemented, with an average tracking time of 0.412 s for different weather conditions. Moreover, the comparison with the conventional method of perturb and observe (P& O) has been presented to evaluate the proposed method’s efficiency.

关键词： Maximum power point trackers Renewable energy sources Fluctuations Simulation Optimization methods power electronics Solar panels

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Generator Frequency as a Useful Signal in Devices for Measuring Magnetic Field Strength Based on Fluxgate Sensors

Generator Frequency as a Useful Signal in Devices for Measur...

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2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019

作者： Nikishechkin, A. Dubrovin, L. MSTU 'Stankin' Computer Control Systems Department Moscow Russia Russian University of Transport Department of Electric Power Transport Moscow Russia

ISBN: (纸本)9781728100616

The article is devoted to the construction of measuring devices based on fluxgate sensors. The possibility of using as a useful signal, carrying information about the magnitude of the measured magnetic field, the frequency of the generator, performed on the logic elements and powering the excitation winding of the fluxgate, is considered. In such a generator, the field winding becomes in fact an element of the generator itself. Therefore, the measured magnetic field through the excitation winding affects the operation of the generator, which leads to a change in its frequency. The article shows that the magnitude of the frequency change is sufficient to talk about the possibility of a non-standard frequency measurement method for constructing devices based on flux-probes. It is shown that the use of frequency as a useful signal has its advantages. It has been established experimentally that the flux-probe effectively works not only at a specific frequency specified in its passport data, but also within fairly wide limits. It is shown that the frequency changes fall within the range in which the flux probe operates most efficiently. The article provides an original generator circuit for powering the excitation winding of a fluxgate and implementing a frequency-measurement method for constructing devices for measuring magnetic field strength. © 2019 IEEE.

关键词： Probes

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Optimal Sizing and Pricing of Renewable power to Ammonia systems Considering the Limited Flexibility of Ammonia Synthesis

arXiv

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arXiv 2022年

作者： Yu, Zhipeng Lin, Jin Liu, Feng Li, Jiarong Zhao, Yuxuan Song, Yonghua Song, Yanhua Zhang, XinZhen The State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Sichuan Energy Internet Reasearch Institute Tsinghua University Chengdu610213 China The Department of Electrical and Computer Engineering University of Macau 999078 China The Department of Electrical Engineering Tsinghua University Beijing100087 China Shenzhen Edo Renewable Co. Ltd Shenzhen518067 China

Converting renewable energy into ammonia has been recognized as a promising way to realize "green hydrogen substitution" in the chemical industry. However, renewable power to ammonia (RePtA) requires an essential investment in facilities to provide a buffer against the strong volatility of renewable energy and the limited flexibility of ammonia synthesis, which involves the three main stakeholders, namely, power, hydrogen, and ammonia. Therefore, the sizing and pricing of RePtA play a core role in balancing the interest demands of investors. This paper proposes an optimal sizing and pricing method for RePtA system planning. First, power to ammonia (P2A) is modeled as a flexible load, especially considering the limited flexibility of ammonia synthesis, which has been verified using real dynamic regulation data. Second, the multi-investor economic (MIE) model is established considering both external and internal trading modes. Then, a two-stage decomposed sizing and pricing method is proposed to solve the problem caused by the strong coupling of planning, operation, and trading, and information gap decision theory (IGDT) method is utilized to handle the uncertainty of renewable generation. Finally, real data from a real-life system in Inner Mongolia are utilized to verify the proposed approach. The results show that the system proposed has a yield of 8.15%. Copyright © 2022, The Authors. All rights reserved.

关键词： Costs

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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power Demand Forcasting System with Reconfigurable User Interface Using Redundant Operation Data

Power Demand Forcasting System with Reconfigurable User Inte...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Takuya Arata Shingo Yamaguchi Ichiro Toyoshima Graduate School of Sciences and Technology for Innovation Yamaguchi University Japan Power Control Computer Systems Department Fuchu Operations TOSHIBA Energy Systems & Solutions Corporation

ISBN: (数字)9781728151861

ISBN: (纸本)9781728151878

We propose a screen design personalization method for information systems. This method inputs the screen transition diagram of the information system and the user's screen operation history, finds a redundant part (called redundant operation) from the screen operation history, improves the screen transition diagram so that the operation does not occur, Output. The redundant operation is a series of redundant screen transitions that occur because the data items necessary for data entry must be referred to on the system screen of the information system. Since the redundant operation varies depending on the usage and environment of the user, the screen transition diagram of the output varies depending on the user, and as a result, personalization of the information system is achieved. In this research, we take up the power demand forecasting system. Since regression analysis is used for power demand prediction, it is necessary to adjust many parameters in order to perform appropriate demand prediction. This has led to complex screen transitions in the power demand prediction system. In this study, we personalized the screen design for the power demand forecasting system. The personalized power demand forecasting system can provide screen transitions suitable for the usage environment of the system.

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Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots

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Sustainable Cities and Society 2021年 74卷 103197-103197页

作者： Mansour-Saatloo, Amin Ebadi, Ramin Mirzaei, Mohammad Amin Zare, Kazem Mohammadi-Ivatloo, Behnam Marzband, Mousa Anvari-Moghaddam, Amjad Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical Engineering Sahand University of Technology Tabriz Iran Northumbria University Electrical Power and Control Systems Research Group Ellison PlaceNewcastle upon TyneNE1 8ST United Kingdom Aalborg University Aalborg9220 Denmark Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia

There is little room for doubt that distributed generation systems including renewable energy, microgrids (MGs), combined heat and power (CHP) units and storage systems have been of particular importance in sustaining low-carbon and cost-effective operations due to the tremendous increase in greenhouse gas emissions in recent years. Additionally, hydrogen-based power technologies have earned a great deal of publicity that hydrogen can serve as a zero-emission fuel for electrical power and thermal energy production. In this regard, the current paper proposes an optimal energy management strategy for a combined hydrogen, heat, and power MG (CHHP-MG) with hydrogen fueling stations (HFSs) for hydrogen vehicles (HVs), electric vehicle parking lots (EVPLs) and fuel cell micro-CHP (FC-MCHP) units to meet power and heat requirements. In order to reduce the regular operating expense, the presented CHHP-MG could also communicate with both electricity and hydrogen markets. In addition, to compensate for the associated heat and hydrogen requirements, power-to-X technologies such as the power to heat (P2HT) and power to hydrogen (P2H) are integrated. In order to improve flexibility and build a low carbon MG, multi-energy storage (MES) system along with heat and power demand response (HPDR) programs will be taken into consideration. As the uncertainties associated with the predicted wind and photovoltaic power have a major impact on the energy management of the CHHP-MG, a multi-objective information gap decision theory (IGDT)-based robust approach is applied as an effective non-probabilistic modeling technique for handling such uncertainties. The empirical results show that the proposed model can efficiently handle the uncertainties and reduce the overall operation cost by 76.35%. © 2021 Elsevier Ltd

关键词： Energy management

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METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS IN SANITARY INSTALLATIONS 21

METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS ...

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21st International Multidisciplinary Scientific Geoconference: Water Resources, Forest, Marine and Ocean Ecosystems, SGEM 202

作者： Czajkowski, Adrian Remiorz, Leszek Pawlak, Sebastian Remiorz, Eryk Szygula, Jakub Miscea.pl Engineering Sp. z o.o. Poland Department of Power Engineering and Turbomachinery Faculty of Energy and Environmental Engineering Silesian University of Technology Poland Doctoral School The Silesian University of Technology Poland Faculty of Mechanical Engineering Scientific and Didactic Laboratory of Nanotechnology and Materials Technologies Poland Department of Mining Mechanization and Robotisation Faculty of Mining Safety Engineering and Industrial Automation Silesian University of Technology Poland Department of Distributed Systems and Informatic Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9786197603361

The article presents the issue of scale deposits in sanitary installations. Scale contributes to improper operation of sanitary devices and leads to their degradation. Scale build-up in pipes and measuring elements results in higher water consumption due to inaccurate estimation of this resource consumption. The consequence is that devices based on process automation do not work properly due to disturbances in the actual water flow. The formation of deposits also leads to economic and ecological losses, as sanitary installations elements have to be replaced, which affects the increased use of raw materials and the generation of waste. This is not in line with current trends and global objectives related to circular economy. Scale also results in increased energy consumption and reduced energy efficiency. This is due to the resistance of the flows and the increased work of the pumps. Scale has insulating properties, which results in less efficient heat transfer. In this stady, a mathematical model was developed to detect the formation of scale deposits in sanitary installations. On this basis, it is possible to control the quality status of sanitary installation components. In this way, by taking appropriate action at an early stage of the formation of deposits, it can extend the life of the installation. Having information on scale deposits, it will help avoid wasting water and lead to more accurate measurement of water flows. This is important for the proper operation of devices such as heat pumps, where their operation is automated and requires precise measurements of the energy processes taking place. Scale is a significant problem for households, and also for factories or public institutions that are exposed to hard water environments. © 2021 International Multidisciplinary Scientific Geoconference. All rights reserved.

关键词： Deposits

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Thermal Modelling and controller Design of an Alkaline Electrolysis System under Dynamic Operating Conditions

arXiv

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arXiv 2022年

作者： Qi, Ruomei Li, Jiarong Lin, Jin Song, Yonghua Wang, Jiepeng Cui, Qiangqiang Qiu, Yiwei Tang, Ming Wang, Jian State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China Tsinghua-Sichuan Energy Internet Research Institute Chengdu China Department of Electrical and Computer Engineering University of Macau China School of Materials Science and Engineering Shanghai University Shanghai China Purification Equipment Research Institute of CSIC Handan China College of Electrical Engineering Sichuan University Chengdu China

Thermal management is vital for the efficient and safe operation of alkaline electrolysis systems. Traditional alkaline electrolysis systems use simple proportional-integral-differentiation (PID) controllers to maintain the stack temperature near the rated value. However, in renewable-to-hydrogen scenarios, the stack temperature is disturbed by load fluctuations, and the temperature overshoot phenomenon occurs which can exceed the upper limit and harm the stack. This paper focuses on the thermal modelling and controller design of an alkaline electrolysis system under dynamic operating conditions. A control-oriented thermal model is established in the form of a third-order time-delay process, which is used for simulation and controller design. Based on this model, we propose two novel controllers to reduce temperature overshoot: one is a current feed-forward PID controller (PID-I), the other is a model predictive controller (MPC). Their performances are tested on a lab-scale system and the experimental results are satisfying: the temperature overshoot is reduced by 2.2◦C with the PID-I controller, and no obvious overshoot is observed with the MPC controller. Furthermore, the thermal dynamic performance of an MW-scale alkaline electrolysis system is analyzed by simulation, which shows that the temperature overshoot phenomenon is more general in large systems. The proposed method allows for higher temperature set points which can improve system efficiency by 1%. © 2022, CC BY.

关键词： controllers

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