Impacts of digitalization on smart grids, renewable energy, and demand response: An updated review of current applications

• Different digitalization techniques in the energy sector is briefly outlined • Impacts of digitalization in smart grids is critically analyzed. • Integration of the renewable energy sources are given priority during the selection of digitalization methods. • Maximum energy efficiency attainment using demand response is ensured in the processes. Decarbonization, decentralization, and digitalization are essential for advanced energy systems (AES), which encompass smart grids, renewable energy integration, and demand response initiatives. Digitalization is a significant trend that transforms societal, economic, and environmental processes globally. This shift moves us from traditional power grids to decentralized, intelligent networks that enhance efficiency, reliability, and sustainability. By integrating data and connectivity, these technologies optimize energy production, distribution, and consumption. This article presents a comprehensive literature review of four closely related emerging technologies: Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, and Digital Twin (DT) in AES. Our findings from the previous works indicate that AI significantly improves Demand Response strategies by enhancing the prediction, optimization, and management of energy consumption. Techniques like linear regression effectively predict power demand and aggregated loads, while more complex methods such as Support Vector Regression (SVR) and reinforcement learning (RL) optimize appliance scheduling and load forecasting. The integration of IoT technologies into Energy Management Systems (EMS) further enhances efficiency and sustainability through real-time monitoring and automated control. Additionally, DT technology aids in simulating energy scenarios and optimizing consumption in both residential and commercial smart grids. Our findings also emphasize blockchain’s role in creating decentralized energy trading platforms, facilitating peer-to-peer transactions, and enhancing trust through smart contracts. The insights gained from this review highlight the essential role of these emerging technologies in supporting decentralized, intelligent energy networks, offering valuable strategies for stakeholders to navigate the complexities of the evolving digital energy landscape.

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Publication Details

Journal
Energy Conversion and Management X
Published
2024-10-01
DOI
https://doi.org/10.1016/j.ecmx.2024.100790
Citations
81
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
16.90
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article

Impacts of digitalization on smart grids, renewable energy, and demand response: An updated review of current applications

Mahmudul Hasan, Mou Mahmood, Prangon Chowdhury, Nahid-Ur-Rahman Chowdhury et al.
81 citations
Energy Conversion and Management X
Smart Grid Energy Management
16.90
article

Impacts of digitalization on smart grids, renewable energy, and demand response: An updated review of current applications

Mahmudul Hasan, Mou Mahmood, Prangon Chowdhury, Nahid-Ur-Rahman Chowdhury, Rahbaar Yeassin, Tanvir Ahmad
article en
81 citations

Abstract

• Different digitalization techniques in the energy sector is briefly outlined • Impacts of digitalization in smart grids is critically analyzed. • Integration of the renewable energy sources are given priority during the selection of digitalization methods. • Maximum energy efficiency attainment using demand response is ensured in the processes. Decarbonization, decentralization, and digitalization are essential for advanced energy systems (AES), which encompass smart grids, renewable energy integration, and demand response initiatives. Digitalization is a significant trend that transforms societal, economic, and environmental processes globally. This shift moves us from traditional power grids to decentralized, intelligent networks that enhance efficiency, reliability, and sustainability. By integrating data and connectivity, these technologies optimize energy production, distribution, and consumption. This article presents a comprehensive literature review of four closely related emerging technologies: Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, and Digital Twin (DT) in AES. Our findings from the previous works indicate that AI significantly improves Demand Response strategies by enhancing the prediction, optimization, and management of energy consumption. Techniques like linear regression effectively predict power demand and aggregated loads, while more complex methods such as Support Vector Regression (SVR) and reinforcement learning (RL) optimize appliance scheduling and load forecasting. The integration of IoT technologies into Energy Management Systems (EMS) further enhances efficiency and sustainability through real-time monitoring and automated control. Additionally, DT technology aids in simulating energy scenarios and optimizing consumption in both residential and commercial smart grids. Our findings also emphasize blockchain’s role in creating decentralized energy trading platforms, facilitating peer-to-peer transactions, and enhancing trust through smart contracts. The insights gained from this review highlight the essential role of these emerging technologies in supporting decentralized, intelligent energy networks, offering valuable strategies for stakeholders to navigate the complexities of the evolving digital energy landscape.

Energy Conversion and Management XVol. 24
Ahsanullah University of Science and Technology (BD), Southeast University (BD), Northern University Bangladesh (BD)
Affordable and clean energy
Openalex Percentile: Top 0%
Smart Grid Energy Management
16.90
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