An Effectiveness Modelling Approach for IoT-Based Smart Grids

An Effectiveness Modelling Approach for IoT-Based Smart Grids

Dongming Fan, Yi Ren, Qiang Feng
Copyright: © 2021 |Pages: 20
DOI: 10.4018/978-1-7998-6721-0.ch005
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Abstract

The smart grid is a new paradigm that enables highly efficient energy production, transport, and consumption along the whole chain from the source to the user. The smart grid is the combination of classical power grid with emerging communication and information technologies. IoT-based smart grid will be one of the largest instantiations of the IoT in the future. The effectiveness of IoT-based smart grid is mainly reflected in observability, real-time analysis, decision-making, and self-healing. A proper effectiveness modeling approach should maintain the reliability and maintainability of IoT-based smart grids. In this chapter, a multi-agent-based approach is proposed to model the architecture of IoT-based smart grids. Based on the agent framework, certain common types of agents are provided to describe the operation and restoration process of smart grids. A case study is demonstrated to model an IoT-based smart grid with restoration, and the interactive process with agents is proposed simultaneously.
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1 Introduction

During the past decade, high-capacity and long-transmission power networks have been widely used to meet the growing demand for electricity in the past few decades (Sylla C, 2016; Dranka GG, 2020). There is a mentionable transformation in all segments of the power industry worldwide, from generation to supply. A power system that is more reliable, scalable, secure, interoperable, and manageable while being cost-effective (Bari, 2014) is required by modern society. In the vision of Horizon Europe 2021–2027 (Guo, 2016; Horizon Europe, 2019), the next-generation electric power system will be a “smart grid” (American Public Power Association, 2018), referring to a self-healing-capable grid (Massoud, 2014) that can provide reliable, energy-efficient, and quality power. The configuration of smart grids continues to evolve, as shown in Figure 1 (Fan, 2021).

Figure 1.

Evolution of smart grid (Elsevier, 2021)

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Source: Elsevier, 2021

A smart grid can enhance the current grid system by renewable energy resources, such as wind, solar, etc. (Espe, 2018; Tuballa, 2016). These new power generating systems can be smaller, more environmentally, and can be distributed around the load centres, to maintain the reliability of grids. More specifically, the benefits associated with the smart-grid include (but not limited):

  • More efficient transmission of electricity;

  • Quicker restoration of electricity after power disturbances;

  • Reduced operations and management costs for utilities, and ultimately lower power costs for consumers;

  • Reduced peak demand, which will also help lower electricity rates;

  • Increased integration of large-scale renewable energy systems;

  • Better integration of customer-owner power generation systems, including renewable energy systems;

  • Improved security.

These advantages benefit from the two-way flows of energy and real-time information, which offers tremendous benefits and flexibility to both users and energy providers. These characteristics are inline to the Internet of Things (IoT) domain. IoT is the communications paradigm that can provide the potential of ultimate communication. Its paradigm describes communication not only human to human but also machine to machine without the need of human interference. IoT-based smart grid will be one of the largest instantiations of the IoT in the next future. The effectiveness of IoT-based smart grid is mainly reflected in observability, controllability, real-time analysis, decision-making, and self-healing. A proper effectiveness modelling approach should be implemented to maintain the reliability and maintainability of IoT-based smart grid.

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2 Iot-Based Smart Grid Architecture

Compared to classical power grid, the smart grid highly integrates information and communications technology on the whole energy chain (from producers to end-consumers), through the large-scale deployment of different kind of sensing, actuating and other embedded devices, in addition to the use of smart meters, smart appliances and e-cars, all of them sharing the capacities of computing and communication.

Generally, IoT-based smart grid is usually considered as a three-layer architecture (sensor layer, communication layer and application layer), as shown in Figure 2. The coupled three layers achieve the established functions, and maintain the reliability and maintainability of IoT-based smart grid. In this section, we firstly describe the architecture of IoT-based smart grid, and then discuss the advantages that IoT enabling technologies make the smart grid more powerful and intelligent.

Figure 2.

IoT-based smart grid architecture (Springer, 2018)

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Source: Springer, 2018

Key Terms in this Chapter

Smart Grid: A smart grid is an electrical grid which includes a variety of operation and energy measures, including advanced metering infrastructure, renewable energy resources and so on.

Industrial Artificial Intelligence: Usually refers to the application of artificial intelligence to industry. It is more concerned with the application of such technologies to address industrial pain-points for customer value creation, productivity improvement, cost reduction, site optimization, predictive analysis, and insight discovery.

Internet of Things: The internet of things (IoT) describes the network of physical objects-”things” or objects, which are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.

Edge Computing: Which is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed to improve response times and save bandwidth.

Digital Twins: A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or process.

Multi-Agent System: A multi-agent system is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search, or reinforcement learning.

Reliability Engineering: Which concerned with the ability of a system or component to perform its required functions under stated conditions for a specified time.

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