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The Necessity for Modernizing the Coupled Structure of Intelligent Transportation Systems and Multi‐Energy Networks

Mohammadreza Daneshvar1, Amjad Anvari‐Moghaddam2, and Reza Razzaghi3

1 Department of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

2 Department of Energy (AAU Energy), Aalborg University, Aalborg, Denmark

3 Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Victoria, Australia

1.1 Introduction

In recent years, the growing need for all carriers of energy has driven energy networks to be reconstructed in a way to effectively match energy supply and demand [1]. In this transformation, grid modernization is introduced to pave the realization of required changes that make the energy structure cleaner, more efficient, affordable, sustainable, flexible, stable, and secure than the previous paradigm [2]. One of the prominent features of modernized energy networks is the adoption of renewable energy sources (RESs) in energy generation premises [3]. This evolution is intended to facilitate the decarbonization plans for an energy transition toward a carbon‐free and green energy structure. However, such a development was not only accompanied by economic and environmental benefits, but also critical challenges have emerged, especially concerning uncertain outputs of RESs [4]. Multi‐energy systems along with other energy storage, management, and energy trading technologies are proposed to address such challenges in the modern energy grid [5]. However, effectively responding to such concerns requires more than just using the mentioned solutions. Indeed, dynamic energy balancing is more difficult from the network viewpoint when it is equipped with 100% RESs given the stochastic nature of energy production. In such a circumstance, interconnecting different sectors of energy grids can make an appropriate multi‐energy coupling that supports the whole structure of the system in continuous energy serving. One of these important sectors is transportation. The transportation network encompasses different parts such as power lines, air routes, railways, and road networks that possess diverse energy‐consumed systems like electric vehicles (EVs), buses, boats, etc. [6]. By including various energy‐dependent devices, the transportation network plays a vital role in energy interactions across the grid. As future energy networks are planned to be eco‐friendly infrastructure with fully clean energy production [7], the transportation sector is also not exempt from this green economy movement. Hence, exploiting carbon‐free energy systems is necessary for realizing a green transportation network. In this regard, recent advances in the technology of multi‐carrier energy devices offer great opportunities for generating, storing, and converting different carriers of energy to each other [8]. Therefore, the operation of coupled intelligent transportation networks and multi‐carrier energy units can procure appropriate conditions for implementing net‐zero emission plans and realizing a green transportation network. This issue highlights the necessity for developing the application of multi‐energy systems to their usage in the transportation network. This chapter aims to further clarify various dimensions of this necessity.

1.2 Applications of Intelligent Transportation Systems

Recent years have witnessed a considerable rise in energy demand along with the rapid development in the technologies of smart devices for smart grids. The deployment of intelligent systems is not only limited to the residential sector, but also the transportation premise has benefited in controlling a variety of energy interactions. Such evolutions have driven the system to face huge volumes of data generated by smart devices across the grid. This data is taken into account as valuable information for the decision‐making process of the transportation network. How the mentioned information needs to be used for managing various processes as well as completing different duties is the main reason for creating transportation management systems (TMSs). The TMS is from the area of transportation that sets up for improving flexibility, load optimization, and effective route planning [9]. The utilization of machine learning (ML) techniques along with artificial intelligence (AI) has made TMSs more intelligent, enabling them to achieve accurate performance. The emergence of intelligent devices in recent decades has resulted in the development of diverse information systems for planning, mapping, routing, and logistics. The exploitation of such systems has significantly increased the capabilities of data processing leading to the appearance of intelligent transportation systems (ITSs) [10]. Indeed, ITS is a system with the ability to take appropriate decisions for different states of the transportation network using the data from vehicles with smart devices. The received data from the sensors and intelligent devices are monitored by ITSs to extract useful information that can be effectively used by businesses and governments for taking purposeful decisions. The used feedback mechanism enables ITSs to continuously improve the performance of different systems across the transportation network. ITSs consist of a set of subsystems to achieve such improvements that are indicated in Figure 1.1 [11].

As one of the ITSs’ subsystems, intelligent public transportation systems are for controlling the public transportation network, maintaining the performance of the transportation structure, and providing up‐to‐date information regarding the network operation and trips for the decision‐makers and passengers [12]. As a context‐aware solution to effectively control and manage the traffic challenges of the transportation network, the intelligent traffic control and management system has been developed that uses real‐time data coming from predictive analytics as well as connected road infrastructure [13]. The intelligent parking management system relies on satisfying the requirements of the Internet of things (IoT) device management, vehicle management, and user information management for managing vehicle parking [14]. The intelligent traffic information system is responsible for effectively monitoring traffic by using IoT to create interoperability among heterogeneous interconnected devices to avoid vehicle traffic congestion [15]. The application of IoT is not just limited to the mentioned ITSs’ subsystems, but its integration with AI also procures appropriate platforms for safety management and emergency conditions. Given the significant role of pavement maintenance in megacities, the intelligent pavement management system pursues the key goal of scheduling road reviews as well as managing complaints [16]. Indeed, such systems can be most efficient in improving management capability, driving economic growth, and supporting the sustainability of the transportation network when accurate data is available from sensors. In this regard, different applications of ITSs can be classified into four main classes that are illustrated in Figure 1.2 [17].

Figure 1.1 Different subsystems for the development of ITSs.

Source: Adapted from [11].

All presented applications for ITSs in Figure 1.2 are based on using the collected data from vehicles aiming to improve the transportation process, facilitate public transportation services, and increase driver safety. Thus, ITSs not only ease the decision‐making process for government authorities, but they can also manage and control planning for the transportation network in an appropriate manner, resulting in efficient road management, better driver experience, and a proper degree of passenger comfort [9].

Figure 1.2 Main applications of ITSs.

Source: Adapted from [17].

1.3 Coupled Structure of ITSs and Multi‐Energy Networks

The described applications of ITSs highlight their undeniable place in the future energy network infrastructure. The rise in transport demand has substantially increased for different types of transportation services in recent years. In this respect, vehicles with traditional fossil fuels were mainly responsible for satisfying the transport demand in the transportation network. However, considerable advancements in the technology of clean energy systems have changed the mentioned trend in the usage of fossil fuel‐based devices in the transportation sector. The environmental problems caused by traditional systems have driven the transportation sector to operate carbon‐free devices in both personal vehicles and public transport services. Moreover, recent endeavors have been focused on significantly declining the carbon emissions in the transportation premise and actualizing green transportation more than ever before. However, rapid developments in energy technologies do not accept such a reduction degree and define ambitious goals in constructing zero‐emission transportation networks. Therefore, the modernization of the transportation network is accompanied by realizing 100% RES goals in the grid modernization process. However, uncertainties in clean energy production by RESs have procured difficult conditions for making such decarbonization plans reliably implementable in the...