IoT Orchestration-Based Optimal Energy Cost Decision Mechanism with ESS Power Optimization for Peer-to-Peer Energy Trading in Nanogrid

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

Smart Cities Pub Date : 2023-08-22 DOI:10.3390/smartcities6050101

Faiza Qayyum, Harun Jamil, Naeem Iqbal, Do-Hyeun Kim

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引用次数: 1

Abstract

The Internet of things has revolutionized various domains, such as healthcare and navigation systems, by introducing mission-critical capabilities. However, the untapped potential of IoT in the energy sector is a topic of contention. Shifting from traditional mission-critical electric smart grid systems to IoT-based orchestrated frameworks has become crucial to improve performance by leveraging IoT task orchestration technology. Energy trading cost and ESS power optimization have long been concerns in the scientific community. To address these issues, our proposed architecture consists of two primary modules: (1) a nanogrid energy trading cost and ESS power optimization strategy that utilizes particle swarm optimization (PSO), with two objective functions, and (2) an IoT-enabled task orchestration system designed for improved peer-to-peer nanogrid energy trading, incorporating virtual control through orchestration technology. We employ IoT sensors and Raspberry Pi-based Edge technology to virtually operate the entire nanogrid energy trading architecture, encompassing the aforementioned modules. IoT task orchestration automates the interaction between components for service execution, involving five main steps: task generation, device virtualization, task mapping, task scheduling, and task allocation and deployment. Evaluating the proposed model using a real dataset from nanogrid houses demonstrates the significant role of optimization in minimizing energy trading cost and optimizing ESS power utilization. Furthermore, the IoT orchestration results highlight the potential for virtual operation in significantly enhancing system performance.

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基于物联网编排的纳米电网点对点能源交易ESS功率优化最优能源成本决策机制

物联网通过引入关键任务功能，彻底改变了医疗保健和导航系统等各个领域。然而，物联网在能源领域尚未开发的潜力是一个有争议的话题。从传统的任务关键型智能电网系统转向基于物联网的协调框架，对于利用物联网任务协调技术提高性能至关重要。能源交易成本和ESS功率优化一直是科学界关注的问题。为了解决这些问题，我们提出的体系结构由两个主要模块组成：（1）利用粒子群优化（PSO）的纳米电网能源交易成本和ESS功率优化策略，具有两个目标函数；（2）为改进对等纳米电网能源交易而设计的物联网任务协调系统，通过编排技术结合虚拟控制。我们采用物联网传感器和基于树莓派的Edge技术来虚拟操作整个纳米电网能源交易架构，包括上述模块。物联网任务编排自动化了服务执行组件之间的交互，涉及五个主要步骤：任务生成、设备虚拟化、任务映射、任务调度以及任务分配和部署。使用来自纳米电网公司的真实数据集评估所提出的模型表明了优化在最小化能源交易成本和优化ESS电力利用方面的重要作用。此外，物联网协调结果突出了虚拟操作在显著提高系统性能方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Cities Multiple-

CiteScore

11.20

自引率

6.20%

发文量

审稿时长

11 weeks

期刊介绍： Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.