- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Rapid evaluation of micro-scale photovoltaic solar energy systems using empirical methods combined with deep learning neural networks to support systems’ manufacturers
摘要： Solar energy is becoming one of the most attractive renewable sources. In many cases, due to a wide range of financial or installation limitations, off-grid small scale micro power panels are favoured as modular systems to power lighting in gardens or to be integrated together to power small devices such as mobile phone chargers and distributed smart city facilities and services. Manufacturers and systems’ integrators have a wide range of options of micro-scale photo voltaic panels to choose from. This makes the selection of the right panel a challenging task and risky investment. To address this and to help manufacturers, this paper suggests and evaluates a novel approach based on integrating empirical lab-testing with short-term real data and neural networks to assess the performance of micro-scale photovoltaic panels and their suitability for a specific application in specific environment. The paper outlines the combination of lab testing power output under seasonal and hourly conditions during the year combined with environmental and operating conditions such as temperature, dust accumulation and tilt angle performance. Based on the lab results, a short in-situ experimental work is implemented and the performance over the year in the selected location in Kuwait is evaluated using deep learning neural networks. The findings of this approach are compared with simulation and long-term real data. The results show a maximum error of 23% of the neural network output when compared with the actual data, and a correlation values with previous work within 87.3% and 91.9% which indicate that the proposed approach could provide an experimental rapid and accurate assessment of the expected power output. Hence, supporting the rapid decision-making process for manufacturers and reducing investment risks.
关键词： Solar energy,neural networks,smart cities,system manufacturing,photovoltaic,micro-scale,urban environment
更新于2025-09-19 17:13:59
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[IEEE GLOBECOM 2019 - 2019 IEEE Global Communications Conference - Waikoloa, HI, USA (2019.12.9-2019.12.13)] 2019 IEEE Global Communications Conference (GLOBECOM) - Trajectory Design of Laser-Powered Multi-Drone Enabled Data Collection System for Smart Cities
摘要： This paper considers a multi-drone enabled data collection system for smart cities, where there are two kinds i.e., Low Altitude Platforms (LAPs) and a High Altitude Platform (HAP). In the proposed system, the LAPs perform data collection tasks for smart cities and the solar-powered HAP provides energy to the LAPs using wireless laser beams. We aim to minimize the total laser charging energy of the HAP, by jointly optimizing the LAPs’ trajectory and the laser charging duration for each LAP, subject to the energy capacity constraints of the LAPs. This problem is formulated as a mixed-integer and non-convex Drones Traveling Problem (DTP), which is a combinatorial optimization problem and NP-hard. We propose an efficient and novel search algorithm named Drones Traveling Algorithm (DTA) to obtain a near-optimal solution. Simulation results show that DTA can deal with the large-scale DTP (i.e., more than 400 data collection points) efficiently. Moreover, the DTA only uses 5 iterations to obtain the near-optimal solution whereas the normal Genetic Algorithm needs nearly 10000 iterations and still fails to obtain an acceptable solution.
关键词： Low Altitude Platforms,Internet of Things,Multiple Traveling Salesmen Problem,Smart Cities,Trajectory Optimization
更新于2025-09-19 17:13:59
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[IEEE 2018 IEEE 5G World Forum (5GWF) - Silicon Valley, CA, USA (2018.7.9-2018.7.11)] 2018 IEEE 5G World Forum (5GWF) - Engineering the 5G Environment
摘要： This summary paper examines how engineered electromagnetic surfaces can be applied to alter the way radio signals propagate in dense urban environments in order to enhance coverage or improve densification, thereby enabling the engineering of the environment in a way that enhances radio spectrum use in smart cities. Examples of designs and deployments in the Wi-Fi and millimeter-wave bands are presented for both indoor and outdoor applications.
关键词： Electromagnetic engineered surfaces,smart cities,5G communications,millimeter-waves
更新于2025-09-11 14:15:04
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Image-Based Visibility Estimation Algorithm for Intelligent Transportation Systems
摘要： Posted road speed limits contribute to the safety of driving, yet when certain driving conditions occur, such as fog or severe darkness, they become less meaningful to the drivers. To overcome this limitation, there is a need for adaptive speed limits system to improve road safety under varying driving conditions. In that vein, a visibility range estimation algorithm for real-time adaptive speed limits control in intelligent transportation systems is proposed in this paper. The information required to specify the speed limit is captured via a road side unit that collects environmental data and captures road images, which are then analyzed locally or on the cloud. The proposed analysis is performed using two image processing algorithms, namely, the improved dark channel prior (DCP) and weighted image entropy (WIE), and the support vector machine (SVM) classi?er is used to produce a visibility indicator in real-time. Results obtained from the analysis of various parts of highways in Canada, provided by the Ministry of Transportation of Ontario (MTO), show that the proposed technique can generate credible visibility indicators to motorists. The analytical results corroborated by extensive ?eld measurements con?rmed the advantage of the proposed system when compared to other visibility estimation methods such as the conventional DCP and WIE, where the proposed system results exhibit about 25% accuracy enhancement over the other considered techniques. Moreover, the proposed DCP is about 26% faster than the conventional DCP. The obtained promising results potentiate the integration of the proposed technique in real-life scenarios.
关键词： image processing,dark channel prior,intelligent transportation system,SVM,Visibility,smart cities,entropy,machine learning
更新于2025-09-11 14:15:04