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Design, techno-economic evaluation, and experimental testing of grid connected rooftop solar photovoltaic systems for commercial buildings

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Frontiers in Energy Research 2024年 12卷

作者： Habib, Salman Tamoor, Muhammad Gulzar, Muhammad Majid Chauhdary, Sohaib Tahir Ahmad, Hasnain Alqahtani, Mohammed Khalid, Muhammad Control and Instrumentation Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering and Technology Government College University Faisalabad Faisalabad Pakistan King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical and Computer Engineering College of Engineering Dhofar University Salalah Oman Department of Electrical Engineering Pakistan Institute of Engineering and Applied Sciences PIEAS Islamabad Pakistan Department of Industrial Engineering and Center for Engineering and Technology Innovations King Khalid University Abha Saudi Arabia Dhahran Saudi Arabia

This study aims to investigate the potential of rooftop solar photovoltaic systems for commercial buildings. Helio-Scope software is utilized to perform simulations to determine the ideal rooftop area for photovoltaic panels. The efficiency of photovoltaic systems is impacted by the shading effects of photovoltaic modules installed in parallel rows. To enhance energy output, the optimal distance between rows is determined, and it is found that 5-feet inter-row spacing provides the best results. The simulation results indicate that with 5-feet inter-row spacing, photovoltaic system has an energy generation of 371.6 MWh, specific yield of 1508.0 kWh/kWp, performance ratio of 82.1%, solar access rate of 98.9%, total solar resource fraction of 96.3% and a total irradiance of 1655.9 kWh/m2. The annual nameplate energy is 425.1 MWh, output energy at irradiance levels is 423.1 MWh, optimal DC output is 378.5 MWh, inverter output is 373.5 MWh, and total energy delivered to the national power grid is 371.6 MWh. The average daily DC inverter input power is 158881.5110 W and the average daily AC inverter output power is 152231.6311 W, showing an inverter efficiency of approximately 95.93%. Moreover, detailed testing of the installed PV system is performed on-site to make sure that equipment’s performance guarantees are achieved, the system is properly installed and its configuration is suitable for commercial operations. The maximum daily output energy generation of an installed photovoltaic (PV) system is 1.33 MWh, and its average energy generation is 1.09 MWh. The voltage of all strings is within the rated range of the inverter, with a maximum voltage of 835 V and a minimum of 698 V, as tested by PV string open-circuit voltage. The inverter efficiency test is also performed, with a maximum efficiency of 98.83% and fill factors ranging from 81.37% to 82.34%. The payback period of a photovoltaic system is 4.22 years and LCOE is 0.0229$/kWh. PV system saved 215569.818 metric to

关键词： Solar power generation

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Local Neighbor Propagation on Graphs for Robust Feature Matching

SSRN

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SSRN 2023年

作者： Guo, Hanlin Xiao, Guobao Su, Lumei Zhou, Jiaxing Wang, Dahan Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control School of Electrical Engineering and Automation Xiamen University of Technology China Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Information Science and Engineering Xiamen University China College of Computer and Control Engineering Minjiang University China Fujian Key Laboratory of Pattern Recognition and Image Understanding School of Computer and Information Engineering Xiamen University of Technology China

Establishing reliable correspondences between two sets of feature points is a critical preprocessing step in many computer vision and pattern recognition tasks. In this paper, we propose a novel robust Local Neighbor Propagation on Graphs based feature matching (LNPG) method, to obtain good correspondences for feature matching. LNPG starts from a novel neighborhood graph construction strategy. The strategy leverages the spatial consistency constraint to generate a series of neighborhood sets, and employs the residual information to preserve the local neighborhood relationships of potential inliers (i.e., true matches). Subsequently, LNPG incorporates local neighbor propagation into the graph to enhance connections between data in different neighborhoods, by using the path-based similarity measurement and the adaptive graph partition. In addition, LNPG includes a novel consistency-filtering-based clustering algorithm for robust feature matching. This clustering algorithm introduces a reliable neighborhood consistency measure function and an effective cluster merging criterion for cluster detection and cluster merging during the clustering process, respectively. Overall, LNPG not only effectively distinguishes inliers from outliers, but also reliably classifies inliers into different transformation models between pairs of images. Experiments on publicly available datasets with different types of image transformations show the superiority of our LNPG in comparison with other state-of-the-art methods. © 2023, The Authors. All rights reserved.

关键词： Clustering algorithms

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A Topology Independent Fast Rerouting Scheme with Hop-by-Hop Forwarding Can Achieve a Full Protection

SSRN

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SSRN 2022年

作者： Geng, Haijun Meng, Zhuo Zhang, Han Shi, Xingang Wang, Zhiliang Yin, Xia Chen, Meng Guo, Yingya The School of Automation and Software Engineering Shanxi University School of Computer and Information Technology China The Institute for Network Sciences and Cyberspace Tsinghua University China The Department of Computer Science and Technology Tsinghua University China The School of Big Data and Software Engineering Chongqing University China The College of Computer and Data Science Fuzhou University China

To support critical applications or guarantee a high quality of service, Internet Service Providers (ISPs) generally deploy a technique called routing protection algorithm for local fast rerouting. Alternate next hops are stored alongside with the default next hops in a router’s forwarding table, and can be immediately activated to invoke a loop free repair path in face of link or node failures, or used for multipath transmission. However, the existing routing protection methods either cannot protect all possible single-failure scenarios in the network or needs the assistance of an auxiliary address. In response to the above problems, the present study proposes a single-failure routing protection algorithm based on hop by hop routing (SPA). The algorithm has the following three advantages: (1) supports hop-by-hop forwarding, (2) supports incremental deployment, and (3) can protect all possible singlefailure scenarios in the network as long as network keep connected. Extensive simulations show that, compared to the state-of-the-art schemes which are adopted by the industry, SPA not only can handle arbitrary single-failure situations in the network but also has a small path stretch. These advantages make SPA a good candidate for practical solution for IP fast reroute when network failure occurs. © 2022, The Authors. All rights reserved.

关键词： Internet service providers

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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

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URSI Radio Science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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GPUSCAN++: Efficient Structural Graph Clustering on GPUs

arXiv

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arXiv 2023年

作者： Yuan, Long Zhou, Zeyu Lin, Xuemin Chen, Zi Zhao, Xiang Zhang, Fan The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China The School of Computer Science and Engineering The University of New South Wales Sydney Australia The Software Engineering Institute East China Normal University Shanghai China The College of Systems Engineering National University of Defense Technology Changsha China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

Structural clustering is one of the most popular graph clustering methods, which has achieved great performance improvement by utilizing GPUs. Even though, the state-of-the-art GPU-based structural clustering algorithm, GPUSCAN, still suffers from efficiency issues since lots of extra costs are introduced for parallelization. Moreover, GPUSCAN assumes that the graph is resident in the GPU memory. However, the GPU memory capacity is limited currently while many real-world graphs are big and cannot fit in the GPU memory, which makes GPUSCAN unable to handle large graphs. Motivated by this, we present a new GPU-based structural clustering algorithm, GPUSCAN++, in this paper. To address the efficiency issue, we propose a new progressive clustering method tailored for GPUs that not only avoid high parallelization costs but also fully exploits the computing resources of GPUs. To address the GPU memory limitation issue, we propose a partition-based algorithm for structural clustering that can process large graphs with limited GPU memory. We conduct experiments on real graphs, and the experimental results demonstrate that our algorithm can achieve up to 168 times speedup compared with the state-of-the-art GPU-based algorithm when the graph can be resident in the GPU memory. Moreover, our algorithm is scalable to handle large graphs. As an example, our algorithm can finish the structural clustering on a graph with 1.8 billion edges using less than 2 GB GPU memory. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphics processing unit

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Dynamics-Based Algorithm-Level Privacy Preservation for Push-Sum Average Consensus

arXiv

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arXiv 2023年

作者： Cheng, Huqiang Xie, Mengying Yang, Xiaowei Lü, Qingguo Li, Huaqing Key Laboratory of Dependable Services Computing in Cyber Physical Society-Ministry of Education College of Computer Science Chongqing University Chongqing401331 China School of Software Engineering South China University of Technology Guangzhou510006 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China

In the intricate dance of multi-agent systems, achieving average consensus is not just vital–it is the backbone of their functionality. In conventional average consensus algorithms, all agents reach an agreement by individual calculations and sharing information with their respective neighbors. Nevertheless, the information interactions that occur in the communication network may make sensitive information be revealed. In this paper, we develop a new privacy-preserving average consensus method on unbalanced directed networks. Specifically, we ensure privacy preservation by carefully embedding randomness in mixing weights to confuse communications and introducing an extra auxiliary parameter to mask the state-updated rule in initial several iterations. In parallel, we exploit the intrinsic robustness of consensus dynamics to guarantee that the average consensus is precisely achieved. Theoretical results demonstrate that the designed algorithms can converge linearly to the exact average consensus value and can guarantee privacy preservation of agents against both honest-but-curious and eavesdropping attacks. © 2023, CC BY.

关键词： Consensus algorithm

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Path planning algorithm for unmanned surface vessels based on COLREGs and Meta-TD3

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Ocean engineering 2025年 334卷

作者： Sun, Xu Li, Gangsheng Liu, Zhaokai Zhang, Ling Yu, Haibo Song, Dalei Wu, Q.M. Jonathan College of Engineering Ocean University of China Qingdao266500 China Department of Education Ocean University of China Qingdao266100 China Department of Statistics and Data Science Southern University of Science and Technology Shenzhen518055 China Fundamental Computer Department Ocean University of China Qingdao266100 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B3P4 Canada School of Control Science and Engineering Shandong University Jinan250061 China

—Unmanned surface vessels (USVs) may encounter unknown obstacles, moving vessels and the influence of sea current while at sea. How to make path planning of USVs under so many complex factors is significant for maritime traffic safety and executing task efficiently. To solve this challenging problem, an improved adaptive interfered fluid dynamic system algorithm is proposed in this paper. The method first designs a corresponding obstacle avoidance strategy according to the International Regulations for Preventing Collisions at Sea (COLREGs), which enables the vessel to perform path planning according to the COLREGs, and introduces simulated sea currents for energy-efficient path planning. Then, a Kalman filtering method is integrated into the algorithm to predict dynamic obstacle trajectories. The Twin Delay Depth Deterministic Strategy Gradient (TD3) is also improved by combining it with meta-learning to increase the adaptability of the method to different environmental conditions. In addition, the reward function is designed to take COLREGs and the sea current into account so that the USV can safely avoid collisions and save energy as much as possible. The experimental results demonstrate that the proposed path planning method can avoid moving obstacles according to COLREGs and can utilize sea currents for energy-saving path planning. © 2025 Elsevier Ltd

关键词： Highway accidents

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Enhanced Small Object Detection Neural Network 2020

Enhanced Small Object Detection Neural Network

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2020 International Conference on Aviation Safety and Information Technology, ICASIT 2020

作者： Liu, Lin Fan, Jiahao Xu, Cong College of Software Engineering Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China Limited Company Jilin China

ISBN: (纸本)9781450375764

Faster-RCNN is an vital deep learning object detection algorithm. Nevertheless, the small object detection effect of Faster-RCNN, which does not use multi-layer feature map, is not good enough. In this paper, a new network architecture called enhanced small object detection neural network (ESOD) is proposed. Two advancements are proposed in ESOD. Firstly, a innovative multilayer combining network which integrating multi-layer feature map is designed to leverage multi-layer convolutional information. Thereupon, the ability of small object detection can be improved. Secondly, the scale-transfer layer (STL) is introduced in the fusion of features which are in high layer and features which are in low layer, which extends the size of the features by reducing the quantity of aisles. In this way, the semantic features of distinct size are acquired without additional parameters. Extensive experimental results on PASCAL VOC 2007 and 2012 datasets indicate that, compared with several commonly used algorithms, ESOD brings better small object detection ability than existing methods for object detection. © 2020 ACM.

关键词： Object detection

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Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models

arXiv

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arXiv 2023年

作者： Zha, Yaohua Wang, Jinpeng Dai, Tao Chen, Bin Wang, Zhi Xia, Shu-Tao Tsinghua Shenzhen International Graduate School Tsinghua University China College of Computer Science and Software Engineering Shenzhen University China Harbin Institute of Technology Shenzhen China Research Center of Artificial Intelligence Peng Cheng Laboratory China

Pre-trained point cloud models have found extensive applications in 3D understanding tasks like object classification and part segmentation. However, the prevailing strategy of full fine-tuning in downstream tasks leads to large per-task storage overhead for model parameters, which limits the efficiency when applying large-scale pre-trained models. Inspired by the recent success of visual prompt tuning (VPT), this paper attempts to explore prompt tuning on pre-trained point cloud models, to pursue an elegant balance between performance and parameter efficiency. We find while instance-agnostic static prompting, e.g. VPT, shows some efficacy in downstream transfer, it is vulnerable to the distribution diversity caused by various types of noises in real-world point cloud data. To conquer this limitation, we propose a novel Instance-aware Dynamic Prompt Tuning (IDPT) strategy for pre-trained point cloud models. The essence of IDPT is to develop a dynamic prompt generation module to perceive semantic prior features of each point cloud instance and generate adaptive prompt tokens to enhance the model's robustness. Notably, extensive experiments demonstrate that IDPT outperforms full fine-tuning in most tasks with a mere 7% of the trainable parameters, providing a promising solution to parameter-efficient learning for pre-trained point cloud models. Code is available at https://***/zyh16143998882/ICCV23-IDPT. © 2023, CC BY.

关键词： Semantics

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Diversifying Agent’s Behaviors in Interactive Decision Models

arXiv

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arXiv 2022年

作者： Pan, Yinghui Zhang, Hanyi Zeng, Yifeng Ma, Biyang Tang, Jing Ming, Zhong Department of Computer and Information Sciences Northumbria University NewcastleNE7 7UX United Kingdom College of Computer Science and Software Engineering Shenzhen University Shenzhen510810 China

Modelling other agents’ behaviors plays an important role in decision models for interactions among multiple agents. To optimise its own decisions, a subject agent needs to model what other agents act simultaneously in an uncertain environment. However, modelling insufficiency occurs when the agents are competitive and the subject agent can not get full knowledge about other agents. Even when the agents are collaborative, they may not share their true behaviors due to their privacy concerns. In this article, we investigate into diversifying behaviors of other agents in the subject agent’s decision model prior to their interactions. Starting with prior knowledge about other agents’ behaviors, we use a linear reduction technique to extract representative behavioral features from the known behaviors. We subsequently generate their new behaviors by expanding the features and propose two diversity measurements to select top-K behaviors. We demonstrate the performance of the new techniques in two well-studied problem domains. This research will contribute to intelligent systems dealing with unknown unknowns in an open artificial intelligence world. Copyright © 2022, The Authors. All rights reserved.

关键词： Intelligent agents

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