The Future Design of Smart Energy Systems with Energy Flexumers: A Constructive Literature Review

The ultimate goal of energy education is to cultivate citizens with energy literacy, which in turn influences the energy preferences of the general public. Various aspects, such as teaching, practice, publicity, and participation, all profoundly impact the formation of energy literacy. This study reviews the role of energy education in educational policy-making, the operation of educational systems, the design of innovative energy industry environments, and public participation. Through a systematic review, this study integrates empirical research across various contexts and environments. The relevant topics of empirical research include ‘energy education’, ‘energy literacy’, ‘energy preferences’, ‘energy education policy’, ‘operation of energy education systems’, ‘creation of a renewable energy industry environment’, and ‘public participation’. These studies indicate that energy education can enhance participants’ awareness of energy through knowledge transfer, enabling them to adopt more effective energy solutions and cultivate citizens with energy literacy. Energy education not only shapes the public’s energy literacy but also further influences energy preferences, which in turn can have profound effects on social interactions, market outcomes, and political and social systems. Finally, from the perspectives of ‘educational shaping’ and ‘cultural shaping’, the research explores the impact of energy education on the energy environment and people’s values. The findings reveal that society gradually forms a consensus on energy through long-term interactions, establishing a unique energy culture that subsequently influences the direction and implementation of national energy policies. There exist interactive cycles between energy education and energy policy: energy education influences public energy preferences, while energy culture, in turn, affects policy formulation.

Interactive Cycles between Energy Education and Energy Preferences: A Literature Review on Empirical Evidence

Hu,

Yang

2024

Intelligent Energy Management Systems in Industry 5.0: Cybersecurity Applications in Examples

Wyrzykowska,

Szczepaniuk,

Szczepaniuk

et al. 2024

The article examines modern approaches to energy management in the context of the development of Industry 5.0 with a particular focus on cybersecurity. Key tenets of Industry 5.0 are discussed, including the integration of advanced technologies with intelligent energy management systems (IEMSs) and the growing need to protect data in the face of increasing cyber threats. The challenges faced by small and medium-sized enterprises (SMEs) using solutions based on renewable energy sources, such as photovoltaic farms, are also analyzed. The article presents examples of IEMS applications and discusses methods for securing these systems, offering an overview of cyber threat protection tools in the context of modern energy management. The analysis carried out provided information that will help businesses make rational decisions and contribute to shaping the state’s macroeconomic policy on cybersecurity and energy savings. The results of this research can also help develop more effective strategies for managing technology and IT infrastructure, which is crucial in the digital age of Industry 5.0.

The Emerging Role of Artificial Intelligence in Enhancing Energy Efficiency and Reducing GHG Emissions in Transport Systems

Miller,

Durlik,

Kostecka

et al. 2024

The global transport sector, a significant contributor to energy consumption and greenhouse gas (GHG) emissions, requires innovative solutions to meet sustainability goals. Artificial intelligence (AI) has emerged as a transformative technology, offering opportunities to enhance energy efficiency and reduce GHG emissions in transport systems. This study provides a comprehensive review of AI’s role in optimizing vehicle energy management, traffic flow, and alternative fuel technologies, such as hydrogen fuel cells and biofuels. It explores AI’s potential to drive advancements in electric and autonomous vehicles, shared mobility, and smart transportation systems. The economic analysis demonstrates the viability of AI-enhanced transport, considering Total Cost of Ownership (TCO) and cost-benefit outcomes. However, challenges such as data quality, computational demands, system integration, and ethical concerns must be addressed to fully harness AI’s potential. The study also highlights the policy implications of AI adoption, underscoring the need for supportive regulatory frameworks and energy policies that promote innovation while ensuring safety and fairness.