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The smart grid is not a monolithic system, but rather is a collection of several renewable energy resources and enabling technologies in which, intelligent control is an integral part of its mechanism to improve the utilization of assets. The dynamic characteristics of a smart grid upgrade the conventional system requirements using advanced control strategies to provide continuous power to the load from intermittent renewable generation. The communication networks and control systems that enable the accommodation of distributed generation are crucial technologies in monitoring, protecting, and operating the smart grid in a centralized or decentralized manner. This paper improves the earlier published review articles by exploring the evolution of smart grids in light of renewable energy penetration with associated features. Then, the review gives an overview of notable research works in the literature aimed at developing the management and control of smart energy systems. The reader is provided with an indepth analysis of advanced cloud computing, the internet of things, and blockchain technology with real examples for the related renewable energy projects in smart cities. Furthermore, a special interest has been paid to quantify the performance of communication technologies along with the protocols through the conceptual investigation of real cases using the optimized network engineering tools. The outcomes of the presented review can assist researchers to understand the driving mechanism of smart grid as a route to intelligently utilize renewable energy storage. It is concluded that the amalgamation of blockchain and artificial intelligence for renewable energy management is the key area where the avenue is still open for future research studies.

The mitigation of uncertainty in the availability of power generation from microgrids to enable renewable resources to be dispatched is a daunting task for the individual operators. Installing energy storage systems may reduce the impact of renewable energy intermittency. However, a peculiarity in energy management can be arisen, particularly, when different energy providers manage these resources. Hence, an intelligent utilization approach should be devised to maximize the benefits of using battery energy storage, since the cost of this system is the most expensive part. This article proposes an effective power dispatch strategy for clustered microgrids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. The frequency-shift keying (FSK) technique has been adopted for transmitting the binary signal over the power line communication (PLC). A part of the algorithm is utilized to deal with the optimal scheduling control, whereas the other actuates the dynamic-demand-response-based photovoltaic power forecasting. The performance of the proposed approach with the formulated backup injection index has been validated using data collected from the practical network of "Bario, Sarawak." The presented results suggest that the implementation of the proposed strategy can improve the efficiency of the overall system, causing less operating cost and fast return. It was also found that the binary signal can be transferred with less distortion through PLC networks when using the FSK technique compared to other techniques.

The mitigation of uncertainty in the availability of power generation from microgrids to enable renewable resources to be dispatched is a daunting task for the individual operators. Installing energy storage systems may reduce the impact of renewable energy intermittency. However, a peculiarity in energy management can be arisen, particularly, when different energy providers manage these resources. Hence, an intelligent utilization approach should be devised to maximize the benefits of using battery energy storage, since the cost of this system is the most expensive part. This article proposes an effective power dispatch strategy for clustered microgrids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. The frequency-shift keying (FSK) technique has been adopted for transmitting the binary signal over the power line communication (PLC). A part of the algorithm is utilized to deal with the optimal scheduling control, whereas the other actuates the dynamic-demand-response-based photovoltaic power forecasting. The performance of the proposed approach with the formulated backup injection index has been validated using data collected from the practical network of "Bario, Sarawak." The presented results suggest that the implementation of the proposed strategy can improve the efficiency of the overall system, causing less operating cost and fast return. It was also found that the binary signal can be transferred with less distortion through PLC networks when using the FSK technique compared to other techniques.

The use of diesel generators as a backup to supply the load demand in Bario is costly and environmentally troublesome. On the other hand, utilizing natural resources that form islanded microgrids located in different areas can pose peculiar energy management issues, particularly, when different energy providers manage the renewable and nonrenewable small powerhouses. This paper proposes a framework focusing on the design of sustainable aggregate management system for minimizing the operating time of diesel generators, and thus, reducing the fuel cost and increasing the battery lifetime, while at the same time protecting the environment. Initially, the paper discusses the structure of the existing system. Further, an energy management approach is presented for maximizing the generated power from the available renewable resources at different hours. The presented results show that the proposed sustainable design can be an effective method for planning the development of electrification in the rural areas of Sarawak.