IoT-Orchestration based nanogrid energy management system and optimal time-aware scheduling for efficient energy usage in nanogrid. (November 2022)

• Record Type: Journal Article
• Authors: Qayyum, Faiza; Jamil, Harun; Jamil, Faisal; Ahmad, Shabir; Kim, Do-Hyeun
• Is Part Of: International journal of electrical power & energy systems. Volume 142:Part A(2022)
• Publication Date: 2022-11
• Subjects: Internet of things -- Complex problem solving -- Critical IoT systems -- Microgrid -- Nanogrid -- Optimization -- Scheduling -- Task modeling -- Task orchestration; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108292
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The proposed study focuses on exploiting the potential of IoT technology in mission-critical energy management systems; IoT-orchestration is enabled for nanogrid energy management architecture that focuses on minimizing the use of non-renewables and maximizing the use of renewables; The orchestration module automatically generates the energy tasks and assigns them to the corresponding physical devices, which leads to enhanced efficiency and robustness in comparison with conventional energy management architectures; The study also proposes a time-aware task scheduling algorithm wherein the task's surplus time is optimized to determine the best execution order; Compared to conventional scheduling techniques, the proposed algorithm improved energy tasks' latency, response time, and round trip time (RTT). Abstract: Internet of Things (IoT) has brought an immense revolution in diverse fields related to mission-critical systems including healthcare and navigation systems. We argue that the potential of IoT has not been fully exploited in the energy sector. There is a dire need to shift the traditional paradigm of mission-critical electric power architectures to IoT-enabled fully orchestrated architectures to enhance the overall performance. In this study, we present a novel IoT task orchestration architecture for efficient energy management of a nanogrid system that focuses on minimizing the use of non-renewable energy resources and maximizing the use of renewable energy resources. Since network orchestration deals with automating the interaction between multiple components involved to execute a particular service, therefore, scheduling the relevant processes within strict deadlines becomes the core pillar of the system's performance. The mission-critical systems with urgent task execution often suffer from missing task deadlines issues. To overcome this issue, we present a task scheduling algorithm that incorporates the optimized surplus time, and efficiently executes the energy management-related tasks contemplating to their types. The study utilizes sensors to obtain data from physical IoT devices, including photovoltaic (PV), Energy Storage System (ESS), and diesel generator (DG). The performance of the proposed model is evaluated using data set of nanogrid houses. The outcomes revealed that IoT-task orchestration has played a pivotal role in efficient energy management for nanogrid missioncritical systems. Furthermore, the comparison showed that the task starvation rate is reduced to 16% and 12% when compared with state-of-the-art scheduling algorithms.