The smart grid communication plays a pivotal role in coordinating energy generation, energy transmission, and energy distribution. Cellular technology with long-term evolution (LTE)-based standards has been a preference for smart grid communication networks. However, conventional cellular networks could suffer from radio access network (RAN) congestion when many smart grid devices attempt access simultaneously. Heterogeneous cellular networks (HetNets) are proposed as important techniques to solve this problem because HetNets can alleviate the RAN congestion by off-loading access attempt from a macrocell to small cells. In smart grid, real-time data from phasor measurement units (PMUs) has a stringent delay requirement in order to ensure the stability of the grid. In this paper, we propose a joint resource allocation and power control scheme to improve the end-to-end delay in HetNets by taking into account the simultaneous transmission of PMUs. We formulate the optimization problem as a mixed integer problem and adopt a game-theoretic approach and the best response dynamics algorithm to solve the problem. Simulation results show that the proposed scheme can significantly minimize the end-to-end delay compared to first-in first-out scheduling and round-robin scheduling schemes.Index Terms-End-to-end delay, heterogeneous cellular network, smart grid communication, phasor measurement units.
Abstract-The smart grid communication network adopts a hierarchical structure which consists of three kinds of networks which are Home Area Networks (HANs), Neighborhood Area Networks (NANs), and Wide Area Networks (WANs). The smart grid NANs comprise of the communication infrastructure used to manage the electricity distribution to the end users. Cellular technology with LTE-based standards is a widely-used and forward-looking technology hence becomes a promising technology that can meet the requirements of different applications in NANs. However, the LTE has a limitation to cope with the data traffic characteristics of smart grid applications, thus require for enhancements. Device-to-Device (D2D) communications enable direct data transmissions between devices by exploiting the cellular resources, which could guarantee the improvement of LTE performances. Delay is one of the important communication requirements for the real-time smart grid applications. In this paper, the application of D2D communications for the smart grid NANs is investigated to improve the average end-to-end delay of the system. A relay selection algorithm that considers both the queue state and the channel state of nodes is proposed. The optimization problem is formulated as a constrained Markov decision process (CMDP) and a linear programming method is used to find the optimal policy for the CMDP problem. Simulation results are presented to prove the effectiveness of the proposed scheme.
Tipping or depositing large waste onto land using unauthorized and unlicensed methods are considered as illegal dumping. The increasing rate of illegal dumping becomes a crucial nation issue because this activity causes negative impacts to social, economy and environment. Thus, study on detecting the dumping activities is conducted to control the illegal dumping activities in Malaysia. Raspberry Pi with Python language is used as the microprocessor and a Raspberry Pi camera module with a microwave radar sensor are interfaced to it to capture the image of any vehicles entering the illegal dumping site. The image is captured to recognize the license plate of the vehicle. The method in this study is by using Open Automatic License Plate Recognition (ALPR), Open Computer Vision (CV) libraries and Optical Character Recognition (OCR) to detect the character of the plate registration number. The outcome of the study consists of recognition of Malaysia vehicles’ plate number and the automatic real time email notification on the illegal dumping case. The detection system can be used for case monitoring since the plate number recognition is done in real time. The system can be upgraded to ensure its sustainability in the harsh and isolated environment.
Cellular technology with long-term evolution (LTE)-based standards is a promising technology for smart grid communication networks. However, the integration of cellular technology and smart grid communications is a significant challenge due to the transmission of simultaneous and delay-sensitive smart grid data. The Device-to-device (D2D) communications are proposed as critical solutions to enhance the performance of the LTE. In this paper, we study energy efficiency and delay problems in D2D underlaying cellular communications for the future renewable electric energy delivery and management (FREEDM) system in smart grid with different message sizes and varying channel conditions. We adopt a D2D-assisted relaying framework to assist links that meet poor channel conditions in order to increase the data rate of intelligent energy management devices with large size report. We propose a joint power control and mode selection scheme to deal with the problem and develop a brute-force-based algorithm to find the solutions. We conduct simulations to show the effectiveness of the proposed scheme in balancing the tradeoff between energy efficiency and end-to-end delay and show significant energy efficiency improvements when exploiting the proposed scheme compared to direct and relaying schemes in a variety of different conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.