1.1. Power Grid and SG

The conventional electric power system linked large power stations to a high-voltage transmission system, which then supplied energy directly to customers through a distribution system. The power stations primarily used fossil fuels and hydro turbines to generate electricity. The transmission system expanded from smaller regional grids into a vast interconnected network, which was managed using coordinated operating and planning procedures (Table 1). Energy consumption and peak demand increased at expected rates, while technology progressed within a structured operational and regulatory framework [1, 7]. An intelligent system that can consider the need of the zones and the availability of energy from the different sources in the areas is necessary without human intervention. SGs increase connectivity, automation, and coordination between these suppliers, consumers, and networks that perform long-distance transmission or local distribution tasks (Table 1) [8].

The ability of power consumption to be reduced during the peak hours, which is referred to as demand side management, is one of the advantages of a modernized electricity network; facilitating the connection of distributed energy sources—such as photovoltaic panels, small wind turbines, microhydroelectric systems, and combined heat and power units in buildings—to the distribution network, along with incorporating energy storage into the grid to balance generation loads and prevent disruptions such as the widespread cascading power failures shown in Figure 1. The increased efficiency and reliability of the SG reduces expenditure and CO₂ emissions. More so, the involvement of the government is rapidly focusing on energy security terms, and investing in the SG might interestingly reduce dependence on nonhousehold energy sources.

It can also enhance the grid’s resilience against military, whether physical or cyber in nature. The SG is also known by other terms, such as “Smart Electric Grid,” “Smart Power Grid,” “Intelli-Grid,” and “Future Grid” [1, 9–17].”

Internet of Things (IoT) is used for the generation, transmission, distribution, and consumption of power, among other SG components. The integration of IoT in the SG enhances the monitoring, control, and optimization of the entire power system. It enables a more responsive, efficient, and resilient grid, addressing challenges associated with reliability, sustainability, and overall performance. It has been employed for managing distributed power grids, such as renewable energy resources, and monitoring and maintaining energy consumption as well as production [18–21]. The use of IoT devices in the future SG infrastructure has several advantages that include increased power system dependability, enhanced supervisory control and data acquisition (SCADA) capabilities, improved network asset monitoring and management, and enhanced infrastructure for metering. Notably, the enabling of a real-time network that monitors IoT devices [22, 23] is one of the advantages offered by SG, integrating the current electricity grid with intelligent information systems based on the integration of quick and dependable communication.

The SG industry is confronted with a range of challenges in the form of IoT systems. Cloud services and other communication protocols are currently evolving standards in IoT systems as well as the security concerns related to device performance. More so, the transition to SGs requires a strong and secure wireless communication infrastructure. The IoT components of a SG are considered as the network’s vulnerable link because an attacker can compromise to gain access to the system and launch additional attacks [21].

In Figure 2, wide area network (WAN) is a system that can be a valuable tool to optimize the power generation and transmission on a SG. It uses sensors, communication networks, and other advanced technologies that allow for better management and optimization of the entire power system. By leveraging these technologies, a SG can achieve better situational awareness, improved response to dynamic conditions, and overall enhanced management of the power system. The implementation of WAN can help to monitor and control the power grid from a centralized location and allow for better management of energy usage. For example, renewable energy resources such as wind and solar energy resources generate power intermittently and make it difficult to predict the availability of energy. By using WAN, the power grid can be monitored in real time allowing for better management of renewable energy sources. This helps to ensure that renewable energy is utilized efficiently and effectively, reducing waste and maximizing the use of renewable energy sources [24–26].

Near area network (NAN) is another type of network that can be used in SG. While WAN is used for wide area monitoring and control, NAN is used for near area monitoring and control. NAN is typically used for monitoring and controlling devices that are located within a specific area such as a home or a building. NAN can be used for power distribution and for better management of energy usage within a specific area as shown in Figure 2. By using sensors, the power distribution system can be monitored in real time and allow for faster responses to any issues that arise. For example, NAN is used in electric vehicle (EV) charging. NAN can significantly contribute to the monitoring, control, and efficient use of energy in EV charging stations as these technologies play a vital role in creating a more intelligent and responsive charging infrastructure as part of the broader efforts to build smart and sustainable energy systems [26].

Home area network (HAN) is another type of network that can be used in SG. HAN is typically used for monitoring and controlling devices within a home or a building. HAN can be used for power presumption and allows a better management of energy usage within a specific area. For example, smart home appliances such as refrigerators and air conditioners can be equipped with IoT sensors, allowing for real-time monitoring. By utilizing HAN, these appliances can be controlled and optimized for energy usage and also help to reduce energy waste and improve the efficiency of energy usage [24, 26, 27].

2.1. SG

The SG, known as the next-generation power grid, employs two-way communication of electricity and information to build an automated energy delivery network that is widely dispersed. Interestingly, three integrated parts are fully included, namely, power generation, transmission, and distribution [28, 29].

Modernizing the grid to implement the concept of a “SG” involves integrating advanced technologies and communication systems to enhance the efficiency, reliability, and sustainability of power generation, transmission, and distribution. Notably, a “digital upgrade” of the generation, distribution, and long-distance transmission networks is what is known as “SG,” and it aims to improve present operations by reducing losses and also opening up new markets for the production of alternative energy [8].

2.2. Power Generation

Power generation systems confront several difficulties in the face of climate change and a growing environmental consciousness. One major source of air and water pollution is the usage of fossil fuels, which is why the general public is becoming more and more against it [30]. The emission-free energy sources are those that are renewable (such as solar, wind, hydro, geothermal, and biomass). Technologies utilizing renewable energy resources are one of the best options since they can considerably increase global power output while emitting fewer greenhouse emissions [31–33].

2.3. Power Transmission Lines

Power transmission lines in a SG deliver the electricity from generation sources to end consumers to ensure supply power to the residential and industrial buildings. To meet the demand for real-time capability and reliability, the condition of the transmission line should be guaranteed to be more affordable. To utilize that, SG infrastructures including sensors require monitoring and detecting any fault in the power transmission lines during the delivery of the power. Additionally, monitoring the transmission line can enhance the security of power delivery by taking into consideration high efficiency and reliability. Infrastructures supporting communication and networking will be necessary for the smart transmission grid [13, 34].

2.4. Power Distribution

The topic of future distribution system design has received a lot of attention recently. The terms “SG” and “future distribution system” are used in this discussion. Regarding functionality, a SG should provide additional capabilities such as self-repair, robust reliability, efficient energy control, and instantaneous price adjustments. This is crucial due to the involvement of multiple parties in the process, and distribution has been lagging on some of these advances. The distribution of power has been incorporated with information and communication technology [35].

2.5. Energy Efficiency and Energy Storage

Currently, the growing energy consumption over the past few decades has increased operation costs in the electrical industry, which has resulted in the release of significant volumes of greenhouse gases into the atmosphere [36]. The SG is anticipated to boost the effectiveness of the existing electrical system, manage erratic power output based on renewable resources, lessen the need for fossil fuel-based energy sources, and ensure the stability of the power supply [37]. Additionally, battery energy storage systems (BESSs) can be utilized to boost a PV installation’s self-consumption and stack auxiliary services [38].

2.6. Integration in SG and Renewable Energy

The inclusion of renewable power generation units as emerging distributed generations covers a broad spectrum, ranging from large-scale units integrated into the transmission infrastructure to medium-scale units integrated into the distribution infrastructure as shown in Figure 3. Nevertheless, the deployment of small-scale units on commercial or residential buildings can pose challenges regarding dispatchability. The controllability of these resources is crucial both for managing their operation and for ensuring the smooth functioning of the electricity system [40].

Advanced metering infrastructure (AMI) with high reliability: AMI is a key component in SG. AMI collects data, measures abnormality in SG, exchanges information between smart meters, monitors electricity quality and distributes energy, and analyzes user consumption patterns.

Smart house: A smart home may be used to communicate with users. Singapore improves their services to satisfy marketing demand, boost quality of service, manage smart appliances, read power consumption data acquired by smart meters, and keep an eye on renewable energy resources.

EV assistant management systems typically consist of an EV, a charging station, and a monitoring station that oversees the process. Users may search for the parking details and nearby charging stations using GPS, and the nearest available charging station will be immediately recommended by GPS. The monitoring center controls the management of automotive batteries, charging stations, and equipment.

Transmission line monitoring: To identify and fix fault concerns, wireless broadband communication technologies may be used to monitor the transmission lines [19].

3.1. Feeling Things

Feeling things can be applied to several areas of energy management, including energy consumption, transmission, distribution, and renewable energy sources [19, 47, 48]. By using sensors and other devices to collect data on energy usage, SG systems can adjust energy usage to meet the needs and preferences of occupants [19, 47, 48]. For example, if a room is unoccupied, the system can automatically adjust the temperature and lighting to save energy. Similarly, if a person prefers a certain lighting or temperature, the system can adjust accordingly to provide a more comfortable and personalized environment [19].

3.2. Tagging Things

Tagging things are used to identify and track physical objects or assets in an IoT system [49–52]. Radio-frequency identification (RFID) tagging is a type of IoT technology that can be used in SG systems to improve energy management and efficiency [50, 52]. RFID tags are small, wireless devices that can be attached to objects, enabling them to be identified and tracked using radio waves [49–52].

3.3. Thinking Things

Thinking things use smart meters on the devices at home and business to measure energy usage and provide real-time feedback to both the consumer and the utility company. This allows users to monitor and control their energy usage, giving them a greater understanding of their consumption patterns and helping them make more informed decisions to reduce waste and lower their energy bills [53, 55]. Smart sensors installed on power lines can detect faults and outages in real time, allowing for immediate response and faster restoration of power [53, 55]. They can also be used to monitor the condition of equipment such as transformers and predict when maintenance is needed, thereby reducing downtime and improving reliability [53].

3.4. Shrinking Things

Shrinking things refer to the miniaturization of IoT devices that can be embedded in a wide range of objects, from sensors to appliances, and enable them to communicate and exchange data with other devices and systems [58–60].

5.1. AMI

AMI is a critical component of modern SGs. It facilitates two-way communication between utilities and customers. It includes smart meters, communication networks, and data management systems. In Figure 6, the implementation of AMI has several advantages such as enhanced energy efficiency, improved reliability, and outage management; it enhances customer engagement and operational efficiency [72]. Nonetheless, while AMI offers numerous benefits in terms of energy efficiency, reliability, customer engagement, and operational efficiency, it also presents challenges related to costs, privacy, security, and technology integration. Utilities must carefully weigh these factors when considering the deployment of AMI as part of their SG strategy [73].

5.2. Data Distribution Service (DDS)

DDS is a middleware protocol and API standard for data-centric connectivity from the Object Management Group (OMG). It enables scalable, real-time, dependable, high-performance, and interoperable data exchanges between systems [74]. In the context of SGs, DDS offers several benefits such as scalability and flexibility, real-time data handling, reliability and robustness, and security. However, it also presents challenges such as complexity, cost, resource intensity, and potential interoperability issues. Utilities must carefully evaluate these factors to determine the suitability of DDS for their specific SG needs [75].

5.3. SCADA

SCADA systems play a pivotal role in the management and operation of SGs [76]. They are essential for monitoring, controlling, and automating processes within the grid, contributing to improved efficiency, reliability, and flexibility. However, SCADA systems also come with certain drawbacks such as cybersecurity vulnerabilities, high costs, complexity, and dependency concerns. Utilities must carefully consider these factors when implementing and maintaining SCADA systems to ensure they maximize benefits while mitigating potential drawbacks [77].

5.4. Potential Security Threats and Mitigation Strategies for IoT-Enabled SGs

The advent of the IoT has improved the power grid, ushering in the era of SGs. However, the increasing interconnectivity and digitalization of the power infrastructure have also introduced notable cybersecurity challenges [78]. Identifying and addressing these threats is crucial for maintaining the reliability, efficiency, and resilience of SG systems. One of the potential security threats in IoT-enabled SGs is the vulnerability of communication networks [79]. IoT devices, such as smart meters and sensors, with the power grid create a complex, interdependent system that is susceptible to cyberattacks. They are often the weakest link as a result of shortcomings in computational resources and inadequate security measures [80]. The vulnerability of these devices is high to physical tampering, malware infections, or exploitation of weak authentication protocols. Thus, the IoT devices that connect communication networks in order to control centers are prone to attacks that include eavesdropping, man-in-the-middle attacks, and data interception [81]. These vulnerabilities can be taken advantage of to manipulate data, and disrupt communications, or even launch distributed denial of service (DDoS) attacks [82]. Additionally, vulnerabilities at the system level may arise from insufficient access controls, outdated software, or improper configuration of grid management systems. Weaknesses from these allow unauthorized access to critical systems which may lead to potential obstruction or data breaches [83]. As a result, strong encryption standards like Advanced Encryption Standard (AES) and Transport Layer Security (TLS) should be implemented across IoT devices and communication channels for significant protection of data integrity [84]. Secure communication protocols are essential for preventing unauthorized access to data, ensuring that interception and manipulation are avoided, which is crucial for upholding the grid’s reliability and overall security [85].

Blockchain technology adoption also is being utilized as IoT security integration with cybersecurity frameworks in SGs. It gives a decentralized, tamper-resistant ledger for transactions and authentication of devices as shown in Figure 7 [86]. This can help mitigate the risk of data tampering and unauthorized access. In a nutshell, vulnerabilities such as limited capacity systems, implicit trust, and the lack of robust authentication mechanisms can be exploited by malicious actors to disrupt grid operations, compromise data integrity, and even trigger cascading failures [87]. Another threat is known as advanced persistent threat (APT); herein, SGs are also targeted by APTs. These attackers have the tendency to have long-term access to the network and collect relevant data and manipulate grid operations secretly [88]. These threats are particularly as a result of their ability to evade detection for extended periods, causing significant disruption to grid operations and leading to potential outages [89].

Interestingly, incorporating AI and machine learning (AI-driven threat detection) into these frameworks allows for real-time threat detection and response as they can analyze vast amounts of data to identify patterns indicative of APT security threats and respond more swiftly and accurately than traditional methods [90]. This is because even as traditional methods can be effective for threat detection, it can be limited in identifying new, unknown, or complex threats that have different patterns than the existing patterns [91]. In addition, Manipulation of Demand through IoT (MaDIoT) attacks is another potential threat to SGs. During this attack, IoT devices are manipulated to create demands that are artificial surges or reductions [92]. This can lead to blackouts or damage in equipment after it must have destabilized the grid. Attacks like this call for an importance of robust security measures at both the device and network levels. This also prompts to ensure that IoT security practices should comply with established industry standards such as NIST Cybersecurity Framework (NIST CSF) and ISO/IEC 27001 [93]. Conforming IoT security with these frameworks is crucial as it helps to maintain a consistent protection of critical infrastructure across the entire network [94].

Furthermore, the integration of IoT security into existing data governance policies ensures that all data, whether generated, transmitted, or stored by IoT devices, comply with relevant regulations, like GDPR, in order to protect user privacy and data integrity [95]. Overall, IoT security integration with existing cybersecurity frameworks is crucial for protecting SGs from the unique threats posed by IoT devices and networks [96]. Recent research and developments have presented several innovative solutions to address the evolving security challenges in SGs such as aforementioned blockchain technology and AI-driven threat detection [97]. Additionally, quantum-resistant cryptography, which is referred to as post-quantum cryptography, involves cryptographic algorithms designed to protect against potential threats posed by quantum computers [98]. In contrast to traditional computers that use bits as the smallest unit of information, quantum computers use qubits that can represent multiple states simultaneously due to quantum superposition. With the advent of quantum computing, traditional cryptographic methods may be outdated as researchers continue to develop quantum-resistant algorithms that can withstand attacks from quantum computers to ensure long-term security for SGs [99]. Zero trust architecture (ZTA): ZTA assumptions state that every network segment, device, and users could be compromised. It requires continuous verification and strict access controls to be effective in environments with a large number of IoT devices like SGs [100]. These recent solutions, when integrated with existing cybersecurity frameworks, can significantly enhance their resilience against both existing and emerging security threats [101]. More so, utilities can ensure the security, reliability, and resilience of IoT-enabled SGs when robust encryption, advanced threat detection, scalable data storage, and comprehensive incident response plans are implemented [102].

In addition, according to [103], utilizing cloud storage solutions can provide the scalability required to handle the massive data volumes generated by IoT devices as cloud storage offers flexible and on-demand resources, enabling efficient data storage and management. Reference [104] suggested that implementing distributed storage systems such as Hadoop and NoSQL databases can enhance scalability by distributing data across multiple nodes, ensuring high availability and fault tolerance. Utilizing machine learning algorithms for predictive analytics and anomaly detection can enhance the efficiency of data processing and provide valuable insights for grid management [105]. The use of big data analytics platforms can handle the large-scale data generated by IoT devices, enabling efficient processing and real-time analysis [106]. Notably, scalability and efficiency are critical challenges in data storage and exchange for IoT-based SGs. Addressing these challenges requires scalable storage solutions, optimized data transmission protocols, and advanced data analytics techniques [107]. By implementing these strategies, utilities can enhance the performance and reliability of IoT-enabled SGs, ensuring they can meet the growing demands of modern power systems [108].

Noteworthily, IoT has the potential to enhance the capabilities of technologies used in SG [109]. The extensive sensing and processing capabilities offered by the IoT can enhance various functions within the SG infrastructure, including processing, warning systems, self-healing mechanisms, disaster recovery protocols, and overall reliability [110]. The integration of IoT with SG has the potential to significantly propel the advancement of smart terminals, meters, sensors, information equipment, and communication devices utilized within the grid. By utilizing IoT, it is possible to achieve reliable data transmission in both wired and wireless communication infrastructures across various sections of the SG, including electricity generation, transmission lines, distribution, and consumption/utilization, as shown in Figure 8 [66, 111].

Currently, in this electricity generation, the IoT serves a multitude of purposes. It facilitates the monitoring of electricity generation across various types of power plants, including coal, wind, solar, and biomass facilities [112]. IoT enables tracking of gas emissions, management of energy storage systems, monitoring of energy consumption patterns, and prediction of the requisite power to meet consumer demand. Furthermore, IoT technologies can be leveraged to gather data on electricity consumption, aid in dispatching operations, monitor and safeguard transmission lines, substations, and towers, and manage and control equipment used within the electricity generation and distribution infrastructure [113]. To improve the reliability of transmission lines, wireless broadband communication technologies can be utilized for monitoring purposes. By deploying these technologies, it is possible to monitor transmission lines in real time, detect faults, and take corrective actions to eliminate them. On the customer side, IoT can be used in smart meters to track various parameters, support smarter energy use, enable communication between different networks, manage EV charging and discharging, and help improve energy efficiency and control power demand [114].

According to [115], a wide range of applications of IoT technology in various domains, including energy and power systems, were discussed. The potential advantages of using IoT technologies in the development of SGs, including enhancements in efficiency, reliability, and sustainability, were interestingly explored. The study provides a comprehensive overview of different aspects of SGs, such as electricity generation, transmission, distribution, and consumption/utilization, as shown in Figure 9 [116]. More so, the challenges that come with implementing IoT in SGs, such as ensuring data security and privacy, achieving standardization, and promoting interoperability, were also addressed [117]. IoT connectivity protocols can be categorized based on their key characteristics for various SG applications. For instance, the DDS protocol is suitable for controlling distributed systems, such as managing components of a smart wind farm, SCADA, and load balancing. On the other hand, the Message Queuing Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) protocols are more appropriate for data collection applications, such as gathering data from smart meters as shown in Figure 10 [118]. The Advanced Message Queuing Protocol (AMQP) protocol is commonly used for processing subscribers’ billing. Moreover, the Extensible Messaging and Presence Protocol (XMPP) and Representational State Transfer (REST) protocols are utilized in the Application Program Interfaces (APIs) of SG web-based programs, such as connecting with smart meters and remote controlling, for instance, lighting control [119]. The applications of each connectivity protocol in SG are illustrated in Figure 10.