These advancements offer many exciting opportunities such as the availability of solar, wind, hydro, and other forms of energy to organisations and homes. We hereon will use the term “smart energy systems” for “smart grid” as a broader term that incorporates smart grids, electrical power systems, and related business and other developments. Smart grids continue to transform the energy sector with emerging technologies, renewable energy sources, decentralisation, decarbonisation, and others. Since power systems traditionally comprised large regional and national grids, monitoring the electrical systems of those grids and long distribution lines has been challenging causing many major electrical system failures, human lives, and hefty economic losses. Traditional electrical power grids have long suffered from operational unreliability, instability, inflexibility, and inefficiency. Energy availability enabled modern technological advancements including the ubiquity of computing and power (e.g., batteries), and transformed us into smart societies. A look at the global past and current conflicts reveal that energy has been central to many of them involving oil, natural gas, battery minerals, among others. This paper deepens our knowledge of AI governance in energy and is expected to help governments, industry, academics, energy prosumers, and other stakeholders to understand the landscape of AI in the energy sector, leading to better design, operations, utilisation, and risk management of energy systems.Įnergy has fundamentally shaped the geopolitics of our world and transformed our lives in the last century ( Vakulchuk et al., 2020 Blondeel et al., 2021). The findings show that research on AI explainability in energy systems is segmented and narrowly focussed on a few AI traits and energy system problems. The methodology for discovering parameters or themes is based on “deep journalism,” our data-driven deep learning-based big data analytics approach to automatically discover and analyse cross-sectional multi-perspective information to enable better decision-making and develop better instruments for governance. We collect 3,568 relevant papers from the Scopus database, automatically discover 15 parameters or themes for AI governance in energy and elaborate the research landscape by reviewing over 150 papers and providing temporal progressions of the research. This paper provides a review of AI explainability and governance in smart energy systems. However, the lack of explainability and governability of AI is a major concern for stakeholders hindering a fast uptake of AI in the energy sector. Artificial intelligence (AI) is being applied to smart energy systems to process massive and complex data in this sector and make smart and timely decisions. Smart grids (or smart energy systems) continue to transform the energy sector with emerging technologies, renewable energy sources, and other trends.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |