Empowering power distribution: Unleashing the synergy of IoT and cloud computing for sustainable and efficient energy systems

Results in Engineering 21 (2024) 101949 Available online 27 February 2024 2590-1230/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Review article Empowering power distribution: Unleashing the synergy of IoT and cloud computing for sustainable and efficient energy systems Arul Rajagopalan a , Dhivya Swaminathan b , Mohit Bajaj c , d , e , f , * , Issam Damaj g , Rajkumar Singh Rathore g , ** , Arvind R. Singh h , *** , Vojtech Blazek i , Lukas Prokop i a Centre for Smart Grid Technologies, School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India b School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India c Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India d Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan e Graphic Era Hill University, Dehradun, 248002, India f Applied Science Research Center, Applied Science Private University, Amman, 11937, Jordan g Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, CF5 2YB, United Kingdom h Department of Electrical Engineering, School of Physics and Electronic Engineering, Hanjiang Normal University, Hubei Shiyan, 442000, PR China i ENET Centre, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic ARTICLE INFO Keywords: Cloud computing Cloud of things Internet of things Power systems Renewable energy ABSTRACT This article gives an in-depth review of the integration of the Internet of Things (IoT) and cloud computing in power systems (PS), to improve power distribution sustainability and efficiency. IoT provides seamless communication throughout the electrical grid by leveraging modern Information and Communication Technology (ICT) and embedded technologies, ushering in an information revolution. The Internet of Energy (IoE) emphasizes the convergence of ICT and energy generation, highlighting IoT’s disruptive potential in the electric power industry. Cloud computing, on the other hand, effectively handles data processing, storage, and computational resources. Cloud of Things (CoT), the merging of IoT with cloud computing, provides huge processing capabilities and quick access to computer resources, enabling novel applications and analytics in power distribution. The influence of IoT and cloud-based applications in the distributed generation and renewable energy industries is demonstrated via case studies and real-world scenarios. The introduction of new parameters and optimization strategies highlights the potential for future developments in power technology. To achieve smooth integration and effective resource utilization, proposals for additional research in electric cars and grid-to-vehicle technologies have been made. The integration of CoT into PS has an enormous influence, opening the door for increased efficiency, sustainability, and reliability in the energy sector, as shown by the study’s overall findings. Future generations will advance thanks to the CoT, which presents exciting potential for a more eco-friendly and technologically sophisticated energy landscape. 1. Introduction The Internet of Things (IoT) is an artificial network that connects many objects and elements of a system by using contemporary Information and Communication Technology (ICT) and fundamental embedded systems, such as democratized detectors, gauges, and controllers. In their constant quest for sustainable and efficient distribution of energy, researchers are going on a revolutionary journey by investigating the integration of cutting-edge technology. The Internet of Things and cloud computing are at the vanguard of this revolutionary development, both of which hold the key to unleashing tremendous potential in the power systems (PS) area. In this article, we begin with a * Corresponding author. Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India. ** Corresponding author. *** Corresponding author. E-mail addresses: [email protected] (A. Rajagopalan), [email protected] (D. Swaminathan), [email protected] (M. Bajaj), IDamaj@ cardiffmet.ac.uk (I. Damaj), [email protected] (R.S. Rathore), [email protected] (A.R. Singh), [email protected] (V. Blazek), lukas. [email protected] (L. Prokop). Contents lists available at ScienceDirect Results in Engineering journal homepage: www.sciencedirect.com/journal/results-in-engineering https://doi.org/10.1016/j.rineng.2024.101949 Received 15 January 2024; Received in revised form 15 February 2024; Accepted 25 February 2024 Results in Engineering 21 (2024) 101949 2 detailed investigation of the subtle interplay between IoT and cloud computing architecture, providing light on their cumulative significance in changing the prospects of power distribution. In this respect, it is referred to as the information revolution in this century. An improvement to the IoT called the Internet of Energy focuses on fusing ICT with energy generation [1]. The term "IoT" has gained popularity recently; it describes a network in which physical data and development software are exchanged between items through the Internet. Every time the concept of the Internet of Things is proposed, corporations and governments are immediately interested, which promotes research and development. Due to the widespread promotion of demand and research, it expanded quickly over the world [2]. The IoT, defined by its seamless interconnectedness of various elements inside the electrical system, is the beacon of an information revolution. IoT surpasses conventional electrical networks by leveraging modern Information and Communication Technology and embedded systems to imagine a dynamic, self-aware network of intelligent devices and assets. The Internet of Energy idea amplifies the revolutionary power of ICT by fusing it with energy generation, resulting in an ecosystem where efficiency, flexibility, and sustainability converge. Automation and intelligence in several facets of the electrical business are now closer to reality due to IoT in PS. In reality, the creation of this idea is what spurs the advancement of the smart grid’s (SG) capabilities as well as those of related ideas like the smart city, smart house, linked automobile, etc [3]. IoT is a network of interconnected computing devices and infrastructure that allows for the collection, analysis, and dissemination of data from disparate sources. IoT devices share the data they collect from sensors by connecting to an IoT network or another edge device, which then either sends the data to the cloud for analysis or does the analysis locally. Cloud computing develops as an influential trend, providing PS scientists with unparalleled data processing, storage, and computational capabilities. As IoT creates a deluge of real-time data, cloud computing provides a robust and scalable architecture that not only collects but also unleashes this torrent of information for informed decision-making. The combination of IoT with cloud computing, referred to as CloudIoT or Cloud of Things, is an empowered paradigm that offers up an ocean of opportunities for creative applications, predictive analytics, and optimized energy management in power distribution studies. At times, these devices exchange information with one another and take appropriate action based on that data. Although humans are involved in the process because they must line up the devices, give them instructions, and collect the data, the machines do most of the work themselves. We highlight the far-reaching influence of IoT and cloud-based solutions in the fields of distributed generation and renewable energy through an interactive look into real-time applications. From supporting SG with autonomous control systems to revolutionized smart cities through interconnected technologies such as home automation and smart transportation, the convergence of IoT and cloud computing offers a compelling vision for a truly interconnected and intelligent power ecosystem. The goal of IoT in power networks is to facilitate information sharing by enabling communication across all PS items, parts, and subsystems [4]. For users of PS, this concept’s implementation creates difficulties in addition to its numerous advantages and uses. Communication, storage capacity, and processing power will be the main obstacles in this field, especially when a big stream of data is continuously being produced and the controllers must cope with such a sizable data set [5]. The difficulties posed by IoT are handled via cloud computing. Delivering hosted services through the internet is referred to as "cloud computing" in general. Infrastructure as a Service (IaaS), Platform as a Service (PaaS) [6], and Software as a Service (SaaS) are the three primary categories or kinds of cloud computing under which these services fall. The first method for gaining rapid access to massive computing resources through the Internet was cloud-based computing, which enables access to massive data handling and computational tasks in PS. The IoT and cloud computing are two distinct technologies that are currently part of our daily lives. It is anticipated that they will be extensively accepted and used, making them crucial components of the Digital Revolution. A novel approach that combines IoT with the cloud is anticipated to be significant and open up a large variety of application possibilities. By offering endless processing and storage capacity, this technology has addressed numerous issues related to the integration of IoT in PS. However, it is clear that cloud services technology has advanced more often than IoT, and so many IoT-related problems have been at least partially fixed. Since the cloud and the Internet of Things are compatible technologies, there is a phased rollout in the PS that has been anticipated to be combined. This new design is known as CloudIoT, commonly referred to as the Cloud of Things [7]. The major perspective of this article is to outline the characteristics of IoT and cloud-based computing in Power Distribution research. This article tries to not only clarify the present but also to imagine the range of possibilities as we travel towards the future of PS. The key roles and responsibilities served by IoT are listed as follows: power quality studies, renewable energy integration, SG communication, power monitoring and energy management studies. At the same time, Cloud computing categorized its purpose in SG operation, energy management and state estimation studies. It could drive the power sector to previously unattainable levels of efficiency, sustainability, and dependability by introducing fresh criteria and optimization approaches. In addition, we suggest future research directions with a focus on grid-to-vehicle technology and electric vehicle integration to promote efficient resource management and utilization of energy. The research objectives are summarized as follows: 1. Analyze the evolution of IoT by investigating its architecture and examining IoT security issues. 2. Explore the evolution of cloud computing by reviewing cloud computing deployment models. 3. Assess applications of IoT in PS studies by evaluating IoT-based power quality studies, renewable energy integration, SG communication, power monitoring, and energy management. 4. Evaluate applications of cloud computing in PS studies by examining cloud computing-based SG operation, energy management, and power system state estimation. 5. Conclude and propose future research directions in the context of IoT and cloud computing in PS. For this article, a survey protocol was utilized, focusing on an array of prominent academic databases. The search strategy was meticulously designed around a set of targeted keywords relevant to the study. These keywords included terms such as ’Internet of Things’, ’Cloud Computing’, ’Power Systems’, ’Renewable Energy’, ’Cloud of Things’, ’IoT Security’, ’Data Processing’, ’Smart Grid’, and ’Energy Management’. Each term was explored individually and in various combinations to ensure a thorough and wide-ranging literature coverage. The selection criteria for the papers included in this survey were primarily based on the relevance to the predefined objectives, the novelty of the methodology, the breadth and depth of coverage, and the significance of contributions to the field. Special emphasis was placed on research published mainly in the last seven years. From this point on, it is organized as follows. Section 2 masteries the reader with the IoT evolution. While Section 3 depicts the progress of cloud computing, IoT and cloud-based applications in Power distribution research are discussed in Sections 4 and 5, respectively. Conclusion and suggestions for further study are provided in Section 6. 2. Evolution of IoT The IoT is a set of various connected devices, utilities, humans, also technologies that can interlink, and segment data, and evidence to realize a common objective in many areas and software. Conveyance, agricultural production, Medicare, energy production, and distribution A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 3 are just a few of the Orders to synchronize dimensions. Several important elements have contributed to the development of the IoT. The integration of smart features into a variety of products has been made possible by advancements in microelectronics and the miniaturization of sensors and processors. As a result, these gadgets can now collect data and communicate it over the internet. The widespread use of smartphones and the proliferation of wireless networks have created the framework required for seamless device-to-cloud connection, enabling vast data collection and analysis. The objective of the IoT is to have variations in the way to live currently by authorized embedded systems to execute regular tasks and Smart institutions, new technologies, smart conveyance and organization, and so on ensure all examples of smart technologies [8]. IoT devices are application-centric entities. They can only be utilized for the purpose for which they were designed. For instance, IoT devices designed for smart homes cannot be used for other business, industrial, or medical purposes. The power requirements, form factors, and user interface designs of IoT devices vary depending on the application; on the other hand, the underlying component technologies and IoT sensors could be similar. Since it introduces sub-optimality, a generic device design is avoided [9]. 2.1. Youth opportunities and prospects The Internet of Things (IoT) provides numerous business opportunities, allowing organizations to make new business strategies and techniques to incorporate the concept. Not only business occasions, but also effective and resourceful current research are required for multidisciplinary academic learners as shown in Fig. 1 (a). As a result, it encompasses business studies, technical skills, science, and social sciences. Also, as shown in Fig. 1 (b), the internet of Things alters the universe into a smart world with its improved and economical operation, in which all activities are easy to access in less effort and time [10, 11]. 2.2. IoT architecture Each layer in the Internet of Things is described by the features it executes and the devices it employs. In the IoT, there are different viewpoints on the layer. However, many investigators consider the three levels of the IoT: perception, network, and application [12]. Each layer of the Internet of Things has its own set of safety considerations. Fig. 1 (b) depicts the IoT’s basic analytical design in terms of the devices and systems that each layer incorporated in it [13]. 2.2.1. Perception layer In IoT, it remains also discussed as the Sensors layer. The objective of this layer is to collect data from the atmosphere using sensors and gadgets such as laptops, smart meters, etc. Before transmitting data to the network layer, this layer discovers, collects, and processes it. This layer also changes IoT node joint efforts in indigenous and short-range systems [14]. 2.2.2. Network layer The network layer of the Internet of Things is responsible for data directing and communication to various youth centres and equipment. Cloud-based computing systems, Internet gateways, switching, and routing strategies, and other technologies in this layer use cutting-edge innovations like WiFi, LTE, Bluetooth, 3G, and Zigbee. By combining, filtering, and transmission of data to and from sensor data, network interfaces act as a mediator among different IoT devices as given in Fig. 2 [13]. 2.2.3. Application layer The data’s validity, integrity, and anonymity are all guaranteed by the application layer. Therefore, the goal of IoT or the emergence of a network grid is accomplished at this layer. 2.3. IoT security issues Various security issues are related to IoT whose description is being given in subsequent sections. 2.3.1. Confidentiality It is significant to guarantee that data is safe and accessible only to authenticate personnel. A user on the Internet of Things can be a person, a computer, or a service, as well as internal artefacts (strategies that are connected to the network) and outside substances (strategies that are not connected to the network). It is critical, for instance, to ensure that detectors do not expose information collected to nearby nodes. 2.3.2. Integrity Because the Internet of Things relies on data being exchanged between such a variety of devices, data accuracy is critical as depicted in Fig. 3. However, end-to-end safety in Communication protocols can be used to enforce the integrity feature. Since the quality base nature of short computing authority of IoT nodes, data traffic is handled using Fig. 1. (a) IoT assistances as the cutting-edge equipment; (b) IoT-based smart applications. A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 4 firewalls and procedures, but this does not assure security at the endpoints [15]. 2.3.3. Availability The goal of the Internet of Things is to attach as many smart devices. Therefore, users of the Internet of Things should have access to all data at all times. However, data is not the only element used in the IoT; to meet IoT perceptions, products and applications must be attainable and available when needed promptly [16]. 2.3.4. Authentication Each IoT object is necessary to be able to recognize and verify other IoT objects. However, because of the evolution of the IoT, this process can be difficult; many objects are involved (devices, individuals, facilities, service workers, and processing units), and artefacts may be essential to communicate with others for the first time [17]. 3. Evolution of cloud computing Cloud-based Computing is popular equipment that provides facilities for both private and public such as easy access to data, applications, and files over the internet and accessible computing services online rather than nearby stored documents on employers’ computers and phones. It is too recognized to provide active services [18] to clients such as [19] affordable, flexible alternatives [20]. It is a product that benefits businesses all over the world by lowering hardware expenses. The skill is based on the Compensation model, and many of its services can be found in well-known technology businesses such as Google, Microsoft, IBM, and others. Compared to a regulated service, more often known as contributions, this model allows clients to buy the services they desire based on their needs. In the ‘Software as a Service’ (SaaS) distribution model, this type of approach is commonly utilized [21]. Computing is quickly becoming one of the most popular topics in the field of information technology. Large corporations and small and medium-sized firms aim to adopt cost-effective computer resources for their enterprise applications, i.e., by incorporating the cloud computing idea into their ecosystem. It’s a novel way of offering virtualization techniques. It is a collection of IT services provided to a client on a licensed basis across networks with the capacity to grow up or down their service requirements. Typically, a third-party supplier who owns the equipment delivers Cloud Services. Customers may use the cloud to demand services, apps, and services and store large amounts of data from many locations. It has the potential to eliminate the need for the business to build up a high-cost computing infrastructure to leverage ITbased software and products. It claims to deliver a flexible IT infrastructure that can be accessed via the internet from mobile devices. This would allow the capability and abilities to exist and new programs to be multiplied many times. This new computing economic model has taken root and is drawing significant worldwide investments. Due to the efficiency of services given by the pay-per-use uniform grid on assets such as power consumption utilized, transactions carried out, broadband used, data moved, or storage space, many sectors such as finance, health, and academia are shifting to the cloud. Due to the potential advantages of cloud computing, enterprises are apprehensive about using it owing to security concerns and obstacles. Security is a vital part of cloud computing, with several concerns and problems associated with it. Both the cloud provider and the cloud service customer must ensure that the cloud is secure from any external threats. There was also a chance that a malicious user could acquire the cloud by simulating a genuine user, contaminating the whole cloud and affecting a large number of customers who share the infected cloud. This study article explains what a public cloud is, the many cloud architectures, and the factors that influence data protection. The cloud computing model is provided in Fig. 4 below. Cloud computing enables internet users to immediately access up and down, providing greater validity, rapid response time, and adaptability to accommodate traffic variations and requirements. It also supports multi-tenancy, with machines designed in such a way that they’ll be aggregated and accessed by a large number of companies or consumers [22]. Cloud suppliers can use computing power to turn a single system into many virtual machines, removing the need for customer communication in subjective [23]. This optimizes integrated demand while also allowing clients to benefit from scale economies. Fig. 2. Layers of IoT architecture. Fig. 3. Security issues in IoT. A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 5 Cloud computing involves a significant amount of data transfer. These include vendor-to-user communications, customer broadcasts, and user-to-third-party communications. Encrypted is perhaps the most straightforward approach to ensuring that all data transmissions are safe and that the data reaches its desired target without being tampered with. Data security is provided by monitoring and restricting access to data via security protocols, levels, and identity management. There are two parts of a standard Cloud Computing environment: the front and the back end. The front end is on the customer’s side, and it can be accessed via the Internet. On the other hand, the back end is disturbed by cloud services [19]. Cloud Computing Architecture is shown in Fig. 5. 3.1. Deployment models Some clients have access to the public cloud, which a 3rd person operates. During the same period, different businesses could use the technology supplied. Clients can constantly supply services from the service provider via the Internet. Waste of assets is reduced because customers pay for the services they receive. Cloud services are solely offered to a single client and maintained by the company or a third-party service provider [24]. This is a proprietary network that employs the idea of system emulation. Eucalyptus Systems [25] is one of the greatest instances of a private cloud. Equipment used by various organizations for a common goal is maintained either by individuals or by a third-party network operator. Facebook is an example of a Community Cloud. A combination of various cloud deployment models that are coupled in such a way that data is transferred from them without interfering with one another. Amazon is an example of a Hybrid Cloud. Additionally, cloud computing offers services and opens up new application categories that were previously unattainable. Some examples are (a) location-, environment-, and context-aware mobile interactive applications that react in real time to data from human users, sensors (such as stress and humidity sensors inside shipping containers), or even independent information services (like global weather data); (b) parallel batch processing, which enables users to leverage massive processing power to analyze terabytes of data for comparatively short periods of time, while programming abstractions like Google’s Map or its open source make the intricate process of parallel running an application across dozens of servers transparent to programmers [26]. 4. Applications of IoT in power system studies As an empirical study, we have predicted the rise in the proportion of IoT sensor devices based on the different datasets prevailing from the International Data Company (IDC) [27]. During 2015-16, a 2.27 % rise in the interconnection of sensor devices attained a peak of 11.01 % rise that occurred in 2023-24 as plotted in Fig. 6. The role of IoT in different PS studies has been listed in subsequent sections. 4.1. IoT-based power quality studies Authors [28] proposed ‘k’ mapping as a successful technique for quickly activating the knowledge of a system in a smart network using IoT innovation. This research proposes an acceptable technique for enterprise power flow controllers for grid-connected systems to recover their strength and block organization in a grid by analyzing power flow between the multi-lines. IPFC integrates a collection of paying FACTS devices and makes use of their capabilities. This article examines the use of IoT in a web-based, globally collected grid-connected PS utilizing IoT, with an emphasis on the standard for the advancement of the dazzling matrix. The results were compared to those obtained using more traditional methods and the reduced time needed for the movements to settle after pay has decreased, as exemplified by the reaction. In this way, constant observation and early warning of disaster can be accepted, allowing the power framework to sufficiently reject or mitigate the harm caused by considerable cataclysmic events. The cost of our electricity broadcast line observing outline should decrease in the future, and the Fig. 4. Overview of cloud computing. Fig. 5. Cloud computing architecture. A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 6 accuracy of our framework should be improved as well. 4.2. IoT-based renewable energy integration Authors [29] defined a method for analyzing citywide solar power services for a remote base IV tracing system. The development and execution of a remote base, observing system that allows investors to accurately measure the appearances and performance of solar sections under controlled circumstances were presented in this paper. The system also includes data storage and management infrastructure, as well as integration with different analysis engines. While the system can work independently, it was built with decentralized systems in mind and can successfully be implemented with other youth-based remote solar observing strategies. To analyze the effects of soiling on solar output power, the research conceptual test facility was employed, and the efficacy of PV assortments was evaluated for two months. A comparison of the goods from the two sites after two months in summer weather with a typical daily temperature of 45 ◦C demonstrates a soiling reduction of up to 40%. It is mandated to improve solar panel washing to decrease cleaning costs and increase power output by conducting thorough data analysis. This is an important step toward implementing solar power in areas where soiling is a major barrier. However, the system’s application is not restricted to the use case presented here. The software’s layout, which follows the IoT paradigm, allows it to represent a range of circumstances and use cases with minimal infrastructure changes. If anything, depending on the use case, control devices or software applications can be properly installed. Instead of relying on computer models, the ability to study levels in different configurations in a real-life setting could provide a more accurate representation of the facility’s actual performance. 4.3. IoT-based smart grid communication A flexible power scheme for solar-powered IoT sensors was presented [30]. Developers’ current design approach for long-lasting energy from the smart sun sensor in this paper. The quality characteristics of storage volume and solar cell region for five years of continuous procedure were calculated using innovative insight. The device can adjust its electricity consumption based on the available power. The battery public of responsibility and the average solar activity accessible to the device in the previous 24 h are used to determine the power generated. To compensate for the lower amount of information conducted per hour, the device’s power consumption is reduced. In both cases, adaptive power can aid in the reduction of PS sizing. The flexible power to SOC state reduces the battery constraint while allowing for a smaller solar cell area. Evolutionary power consumption in response to solar activity, on the other hand, has a greater impact on the required power consumption while maintaining the average transmission rate. In practice, integrating adaptive power necessitates electronic circuits and computing power considerations. Understanding the impact of different methods on a power layout can aid in the development of a better solution for a particular smart sensor. As a result, designing an adaptable and flexible solar-powered system requires knowledge of the system’s application and efficiency constraints. In Ref. [31], they were assigned to develop and implement an extraordinary precision, elevated, low power, and versatile influence system of measurement that could be used in various applications. A voltage trying to regulate, regulator loop, zero offset speakers, highly accurate equivalent to digital adapters, and the reference voltage are all part of the proposed system. Simulations and experimental measurements are used to validate the proposed circuit’s proper operation. The system architecture has a maximum sampling rate of 5 MHz, 0.16 % load guideline error, and 0.32 % correlation mistake. The implemented system is expected to provide accurate guidance for IoT device power behaviour, which can be used for system efficiency improvement as well as personality testing. It is worth emphasizing that, in contrast to other authority amount solutions and yields on the market, the power generation measurement system is intended for smart energy networks. To reduce IoT network power requirements, it has the desired precision of capacity, rapidity, usability, and reliability. Integration of the items in the research circuit is also economically viable due to the large number of IoT devices. SG Power Transmission was presented [32]. The use of the Internet of Things equipment on the power grid is an effective technique for speeding up the modernization of the power grid system, as well as for efficient power grid architecture design. One of the essential IoT application fields is disaster prevention and the decrease of power transmission lines. Innovative IoT sensing and social networks can accurately prevent or reduce transmission line damage from natural disasters, improve power transmission accuracy, and reduce economic loss. This paper discussed using it in an online observing program for power broadcast lines, focusing on SG design and maintenance characteristics. The cost of our power broadcast line monitoring organization needs to be minimized in the future, and the system’s consistency needs to be improved. Authors [33] collaborated on a smart farm irrigation system powered by IoT and solar power. The construction of an IoT-based solar power framework for smart irrigation is critical for locations throughout the world that face water shortages and power constraints. The suggested system focuses on a specific board system-on-a-chip console (hence referred to as the controller) with a built-in Wi-Fi connection and influences to a solar cell to deliver efficient management influence. The control system examines the field for moisture, temperature, and detectors before sending suitable actuation knowledge signals to the irrigation equipment. The controller also attempts to concentrate on the alternate water Fig. 6. Comparative assessment of IoT sensor devices interconnection for last 9 years. A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 7 level, which is required to protect the pump motors from overheating owing to low water levels in the well. Federal control, mobile observation, switch, and fuzzy-based control are the three modes of operation of the suggested model. An example was deliberate, built, and evaluated in verifying the proposed system. For industrial drive applications [34], proposed that an IoT is a cloud intelligent voltage stability observing system. To keep the procedure going properly, industries are increasingly using IoT-based power feature monitoring equipment. As a result, the paper developed an automated power quality method that manages the power quality dynamic features logging with preand post-values to make the data combination system more efficient. The offered system logs the drive’s electrical measures as well as voltage stability event data in the Firebase cloud, reducing the amount of space required and saving time when evaluating power quality occurrences. Furthermore, end-users could choose the power quality requirements. Overall, the implemented application is faster, more cost-effective, more accurate, and simpler to use, and it can be applied to a variety of real-time applications. In the future, the researchers will create a smarter IoT device from two viewpoints. Techniques must be automatic to quantify the system’s harmonics at the measuring point. Authors must consider using ML to utilize all of the evidence gathered from IoT power superiority technology to monitor possible problems and anomalous behaviour on the cloudy side. Finally, the proposed model will be a plugand-play scheme or a standardized device that can incorporate with any current system and begin monitoring operations. Power-system protection device [35] was suggested based on Internet-of-Things techniques that could be incorporated into intelligent devices. The detection system protects electrical customers linked to the community power grid by cutting off power in case of several faults, including short circuits, overcurrent, escape of the current, and electrical arc. The design, application, and useable validation of an efficient energy safety device with IoT-based assistance for incorporating intelligent devices such as Smart Homes and Smart Cities were discussed. The designed methodology refers to new functions of a power switch by offering security toward extra faults and fetching smart in the context that each detection system interconnects with a Web server via a concentrator-type architectural design. The system also has a Web-based configuration for an observing system of effective devices, as well as actual event notification via g-mail and SMS. IoT was proposed to monitor power broadcast and delivery for the SG. The basic Internet of Things design for power transmission and transfer observing is described in this paper. When creating a WSNbased IoT, it’s important to think about detector requirements as well as interface design that’s appropriate for a specific local power transmission system. Consequently, for distant monitoring and developing nations such as Indonesia, wireless transmission is used. To address the fundamental needs for data sources, real-time monitoring, and long-distance monitoring, GPRS is recommended. Using IoT technology, power broadcast and delivery constraints may be clearly shown on a PC or even a smartphone. The authors want to focus their future work on building enterprise-to-trial devices for power distribution systems that may be useful to Indonesia. Within the field of Energy Informatics, the essential part of Smart Dynamism and Power Schemes Demonstrating were defined [36]. The ultimate goal is to determine how the smart energy and Power Structures Molding themes may be applied to address challenges. To begin, the paper will explore how and where the topic of Smart Energy [37] and PS Modelling fits within the larger topic of energy informatics. The role of smart energy and PS modelling within the broader Energy Information systems area is then acknowledged, with explanations of the main connections between fundamental subjects, specific fields of study, qualitative and quantitative data, and IoT, to perform specific assessments for current and future PS. Furthermore, additional work will be carried out to establish a suitable vision for energy informatics academic courses based on the major challenges and interconnections found in this study. 4.4. IoT-based power monitoring In [38], the authors presented a systematic and comprehensive review of current ML methods and their possible applications in combined PS. In the framework of AI, machine learning presents a potential solution for constructing well-organized and correct data-driven defensive measures to deal with developing effective and switch issues in PS. Machine learning has the primary benefit of being able to process information on a larger scale and with more dimensions in a complex system. Furthermore, machine learning techniques rely heavily on historical datasets and quality training, which are typically unaffected by dynamic simulation and specifications. Machine learning techniques would have quick responses and important flexibility in various circumstances if efficient learning datasets were provided. This paper presented a thorough and systematic review of current ML methods in a wide range of youth-integrated PS. Authors [39] execute a review of the previous works on its use in energy systems in general and SG in specific. We also go over some of the IoT skills, such as cloud technology and various data analysis systems. They also look at some of the difficulties of deploying it in the energy sector, such as security and privacy, as well as some alternatives, such as blockchain technology. This survey gives energy policymakers, economic experts, and managers an overview in PS enhancement. The authors categorize various IoT use cases in each segment of the energy supply chain, from source to energy grids to end-user sectors. The benefits of its-based energy management to increase energy efficiency and integrate renewable energy are mentioned, and the results are summarized. The authors discuss some of the difficulties of using it in the energy sector, such as object identification, large information management, network connections and uncertainty, subsystem integration, privacy and security, the electricity consumption of IoT systems, optimization, and architecture. 4.5. IoT-based energy management For demand reduction [40], they suggested a fog-based PS. In a youth-based system, this paper suggests a multi-negotiator approach for a smart energy society. The competitive atmosphere in human civilizations has inspired this author to offer an Agent Negotiation system for source reduction. The IoT system’s agents haggle with the metering agent to accept a plan that reduces peak-hour use. Negotiations are conducted with hundreds of thousands of institutions, allowing benefits to manage supply and demand in general [41]. Customers receive good pricing based on the strategies that have been agreed upon. Installation of power line sensors to collect data on voltage, active power, and other electrical limitations might be added to the project in the future. This will make it easier to monitor the quality of power provided to houses. The data from the satellites and associated intelligent devices may be utilized to track the transformer’s health. It is possible to monitor the entire grid and use cutting-edge MLA such as deep learning to assess the probability of blackouts or outages. Its Architecture for SG was presented by Ref. [42]. The execution of the IoT in various parts of insolent grids was examined in this work. The application of the Internet of Things in various parts of SG was examined in this work. The research was divided into three sections. The implications of it in the generation layer were discussed in the first section. The importance of new technology in wind and solar alternative fuels, as well as thermal plants and power storage infrastructure, was thoroughly explained in this layer. The transmission layer is addressed in the second part. Its integration in this layer enhances line reliability, resulting in better power grid monitoring. Automatic IoT controllers result in more successful utilization as well as better congestion management in emergencies. Finally, the distribution level was treated within the third layer. In addition to industrial digital technology, the role of youth ineffective distribution systems, microgrids, smart cities, intelligent cities, and smart homes were evaluated in this section. Home automation is the future of energy management in smart A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 8 buildings. Domotics, as a subfield of mechatronics, deals with home automation that allow one to regulate the lights, air conditioning, appliances, security, and theatre [43]. Devices on domestic zone become an essential part of the IoT when they are connected to the Internet. Automation, including automated control and decision-making, is another advancement in the SG. The terms "unmanned aerial vehicles" (UAV) and "unmanned grounded vehicles" (UGV) refer to robotic systems. UAVs and UGVs are basically utilized on the ground to further automate the current PS when they have an internet connection, making them IoT. It could be used to identify and locate faults in the PS. The literature has a few examples of how to integrate IoT technologies and mechanisms into the automation of SG. A solar power plant’s maximum power point tracking system based on the IoT has been visualized [44]. The scientists have looked into power transmission line fault diagnosis [45]. An Arduino platform IoT concept for a small virtual power plant is depicted. Through an examination of the relationships between various virtual power networks and highor medium-voltage networks, the relationship between IoT and microgrid economics is further explored [46]. Furthermore, intelligent algorithms like ramping behavior analysis can be used to better integrate price-based demand response with system control. 5. Applications of cloud computing in power system studies The roles of cloud computing in different PS studies have been listed in subsequent sections. 5.1. Cloud computing-based smart grid operation SG Incorporation was performed using Cloud-Based Systems and Decentralized Platforms [47]. This research discusses critical issues that must be talked about in instruction to guarantee the security of decentralized cloud energy schemes. The paper also examines how cloud computing and blockchain can help Ghana improve its inefficient distribution and transmission networks. Following that, a strategy for the democratization of Ghana’s grid network is being developed. A blockchain and SDN-based architecture have been proposed to address the probable issues of integrating a legacy network with a processer cloud [48]. Taking care of these issues ensures that the SG in the cloud is safe and operates efficiently. Incorporating its SDNs, and Blockchain into DERs could help ensure that enough electricity is generated to meet available at any given time. Task scheduler [49] plans to enhance cloud system performance. By decreasing the task-to-come time, time of execution, and energy ingestion, the task development procedure aims to improve the efficiency of real-time applications and services. The proposed method is based on an artificial neural network (ANN)-based system with a genetic algorithm (GA)-based preparation model. According to the findings, the proposed GA-ANN model outperforms existing techniques in terms of power consumption, total achievement time (ms), average start time (ms), and average completion time (ms). The GA-ANN model used in this study is based on real-time user needs gathered from workload traces and produced data sets. The suggested framework reduces power consumption by 13%, reduces development time by 77.14%, and reduces implementation times by 36%. As a result, when compared with existing systems, the proposed GA-ANN method outperforms them. The cloud-based moderate PS simulator [50] was implemented. Cloud PSS, an elevated PS emulator, is described. Cloud PSS provides a high-efficiency, simple-to-use, and low-cost alternative for modelling large-scale PS and multi-scenario upgrades to the planned open cloud service integrated system, the intuitive code generator, and the various distributed processing approaches. It’s worth noting that the automated software generator’s framework and methods aren’t limited to simulations. Hybrid-cloud-based data processing in SG was suggested [51]. The technique indicated that a significant and productive wireless sensor network be built to supervise the numerous significant extent parameters in the PS. SG architectural design, monitoring and individual possesses to improve the performance for validating numerous demanding applications and trying to build a high-reliability, high-performance wireless sensor network for observing the power grid’s numerous significant measurement parameters. Renewable energy is illustrated by integrating accessible renewable energy sources (solar, biomass, or wave energy) into the electricity network and increasing storage capacity by participating in data processing hardware-based devices to the private cloud that can be used in power grid data processing and forecasting. PS evaluation and control, which entails enhancing power grid stability to deal with rapid changes in energy grid flow. Using data analysis hardware, improve adaptive security, transient stability switching, energy control, and capacity analysis. 5.2. Cloud computing-based energy management Load-balancing methods in a cloud computing system were studied [52]. Researchers could use this review paper to create optimized and efficient scheduling algorithms for cloud environments. Because it included an understanding of current and available load-balancing techniques, this study will aid researchers in identifying research issues related to load balancing, particularly in terms of reducing response time and avoiding server faults. Researchers can continue to examine ways to build strategies that are more dynamic and intelligent, as well as focus on fault tolerance concerns, to improve the performance of cloud services. Researchers will evaluate the environment and perceptive methodologies in the future, such as the use of machine learning or classification models. In Ref. [53], the authors suggested a cloud-based economic delivery model for SG. They proposed an intelligent grid, cloud economic power dispatch model. We presented an overview of current work that blends cloud computing into the established SG architectural design to develop a trustworthy and energy-efficient [54] distribution system in this research. Various topics of SG power management were debated. We identified several critical technical problems and suggested several areas for future research for cloud-based SG. This design provides additional memory for evaluating computing mechanisms for electricity management and cost-cutting. A novel way to provide low-cost cloud-based power for SG applications has been presented. According to the findings of this survey, the use of cloud computing in SG is expected to be helpful for further enhancing SG architectural design in areas such as cost monitoring, computer technology, and power organization. 5.3. Cloud computing-based power system state estimation A cloud-hosted virtualized explanation [55] has been done for additional generation messages based on PMU capabilities. Not only can the technique execute economic load dispatch to keep the system balanced, but it can also share emergency response information such as control signals, system balancing performance indicators, and operator rebuttals in a timely, precise, and secure manner. With the aid of this cloud-based technology, developing human mistakes produced by phone calls utilized for manual, verbal deployment may be avoided. Each procedure activity carried out on the platform is recorded in a database using a standard data format, making auditing and authority monitoring much simpler. This work also included the integration, and cybersecurity method that included data protection, access control, key rotation, and access authorization to meet critical organization specifications for the influence grid. It offers guidance for further grid operators trying to acquire their cloud storage. Overall experience in developing and implementing the first manufacturing cloud-based PS simulation framework was discussed [56]. The platform was built with an open architecture in mind. It can support a variety of resource management and work balancing tools, as well as various system simulation programs. The cloud-computing A. Rajagopalan et al. Results in Engineering 21 (2024) 101949 9 interface meets the requirements of existing cyber safety and data privacy necessities thanks to carefully deploying cyber security strategies that are exactly equivalent to establishing evidence infrastructure and services. The power production industry has struggled to implement cloud-based facilities, but as values strive to remain adaptable in the face of ever-changing technology, this framework is fast transforming. Discussions on architecture, enterprise, secure and resilient, computational display, cost savings, and difficulties will help all utilities that have been constrained by the ever-increasing need for sophisticated computing features in power scheme offline planning training. Based on the CHAIN framework [57] a cloud battery management system. Developers proposed a cloud-to-things outline with four systems: end, edge, cloud, and knowledge by merging digital twins with deep learning approaches, difficult identification, estimate, and optimum control functions [58, 59]. We also used an example to demonstrate a successful direction. Using the cyber hierarchy and interactional network architecture, an end power cloud architecture design for a cloud-based BMS with multi-scale centralized data analysis was constructed as tabulated in Table 1. The current proposed structure is based on the CHAIN outline and has extremely large potential for improving battery and management system performance in a smart and maintainable manner [60,61]. The primary goal of power automation system (PAS) was to offer an intelligent and self-sufficient monitoring solution through the use of affordable hardware and lightweight software. Deep ensemble models were employed by the PAS for PV system power forecast and fault detection. The following steps served as the foundation for the PAS fault diagnostics. First, by examining Current–Voltage (I–V) characteristics in a number of faulty and normal occurrences, the key aspects were identified. For comprehensive PV plant monitoring, including data collection, storing, preand post-processing, fault and failure diagnosis, performance and energy yield assessment, and output power projection, PAS offers an interoperable, scalable, and reproducible system. IoT applications can be utilized for user access and data transfer, while cloud servers can handle system processing. Remote locations might make advantage of this monitoring service [66]. The Internet of Things (IoT) platform is used by PAS to handle data and facilitate communication and interoperability between its various components and devices. Additionally, PAS comes with a personal cloud server for processing and archiving the PV system data that is collected. Additionally, the information is displayed to numerous users via an open-source, lightweight web monitor system that is part of the PAS. The monitoring and evaluation tasks covered in this study were composed of a series of independent steps; nevertheless, tasks may also be considered non-independent, or as a work flow in which dependent activities cannot be finished concurrently. This raises questions for future research. To enable quicker handling, some data with a high emergency level can be assigned a priority level. Several guidelines can be devised for data transfer. However, parameters such as energy, cost, demand prediction etc., might be included to identify where tasks should be performed. In subsequent study, we intend to precisely diagnose all electrical failures in PV arrays, including bypass diode problems, line-ground issues, shading, etc. The Deep learning algorithms can be challenging to select ensemble learning models. Thus, the optimization techniques could be incorporated. To increase the precision of power forecasting, we would also employ several loss functions. 6. Conclusion & future work This comprehensive review has shed light on the transformational possibilities of combining IoT and cloud computing in power distribution systems. The convergence of these cutting-edge technologies provides exceptional prospects to improve the power industry’s efficiency, sustainability, and dependability. IoT lays the groundwork for an information revolution by seamlessly integrating disparate parts inside the electrical grid, enabling a dynamic network of intelligent devices and assets. Furthermore, the Internet of Energy (IoE) accelerates this revolution by imagining a future in which ICT and energy generation merge to produce an adaptive and self-aware power ecosystem. Cloud computing arises as a major changer, supplying the infrastructure required to manage the massive volume of real-time data created by IoT devices. Cloud computing provides effective utilization of this information for informed decision-making by providing robust data processing, storage capabilities, and scalable resources. The combination of IoT with cloud computing, known as CloudIoT or Cloud of Things, Table 1 Comparative analysis of IoT and cloud computing. Reference IoT Cloud Contribution [28] YES NO To enhance the accuracy of a grid-associated PS using an interline power flow organizer. [29] YES NO IoT-based isolated IV tracing scheme for the study of citywide solar power Services. [32] YES NO Submission of IoT in SG Power Broadcast [33] YES NO Internet of Things solar energy mechanical smart farm irrigation scheme. [34] YES NO For manufacturing drive applications, it entrenched cloud-based intelligent power feature observing system is distinct. [35] YES NO With it, the PS security device provided support for combinations in smart environments. [39] YES NO IoE interpretation is highlighted [40] YES NO Agent involvement in a control delivery scheme based on IoT-Fog for demand reduction. [49] NO YES Power well-organized resource provisioning for cloud organization using bio-stimulated ANN model [50] NO YES High-performance power scheme emulator based on cloud computing [51] NO YES Hybrid cloud-based data handling for SG power scheme verification. [53] NO YES An application survey on cloud computing for a dynamic organization in SG [55] NO YES Dispatch without the need for a server for cloud-based power grid substitution generation [58] YES YES To better implement assets in some cloud-based healthcare schemes, identify three fundamental factors. Look over some papers that show how fog computing is being used in the healthcare IoT network. Demonstrating the shortcomings of modern techniques, systems, and structures. [59] YES NO Integrate it into the e-health environment in a systematic way (hardware and software). Demonstrate the difficulties and potential of it in ehealth. Make a list of IoT device and network security issues. [60] YES YES Examine the role of cloud-based architecture in health care. Discuss critical IoT difficulties and problems in health care. [61] NO YES Suggest a fog computing-based structure for responding to mobile healthcare professionals more quickly. Create a prototype using the research models (the response time is reduced by four times) [62] NO YES SG Integration Using Cloud-Based Schemes and Distributed Platforms Conducts grid network research and forecasting in Ghana. [63] YES NO Focus on various sensor types and communication methods. Establish a methodology that can be used in a variety of generation-based applications. [64] YES NO Disambiguation and inquiry directions for IoT, fog, mobile edge, and edge developing calculating instances [65] NO YES Examine the numerous advantages and disadvantages of using fog computing in healthcare. For real-time applications, introduce a three-layer healthcare architectural design. A. Rajagopalan et al.