Using Blockchain and Artificial Intelligence in Energy Management as a Tool to Achieve Energy Efficiency

Kuzior, Aleksandra; Sira, Mariya; Brożek, Paulina

doi:10.34021/ve.2022.05.03(4)

Cited by 15 publications

(14 citation statements)

References 26 publications

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“…Blockchain can support decentralized energy management systems in construction projects, optimizing energy consumption, and enabling the integration of renewable energy sources. This reduces reliance on fossil fuels and promotes energy efficiency [64,65,66] Office services…”

Section: Supply Chain Managementmentioning

confidence: 99%

Potential of Advanced Technologies for Environmental Management Systems

Sira

2024

Management Systems in Production Engineering

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Environmental management systems (EMS) are essential in promoting sustainable practices and mitigating the adverse effects of human activities on the environment. As technology continues to advance, there is an increasing opportunity to utilize advanced technologies to improve environmental management systems. This article examines the potential of different advanced technologies, such as artificial intelligence (AI), blockchain, big data, and the Internet of Things (IoT), within the context of environmental management systems. This article intends to offer valuable insights to researchers, practitioners, and policymakers by examining the potential uses of AI, blockchain, big data, and IoT in environmental management systems. The goal is to demonstrate how these advanced technologies can be leveraged to enhance sustainability, boost environmental performance, and yield favourable environmental results across different sectors and industries.

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Section: Supply Chain Managementmentioning

confidence: 99%

Potential of Advanced Technologies for Environmental Management Systems

Sira

2024

Management Systems in Production Engineering

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“…Aguilar et al highlighted different approaches and strategies for using AI in building energy management, including how and when to use these approaches in smart buildings [40]. Kuzior et al [41] compared the use areas of blockchain and AI in the energy industry. They found blockchain's prominence in wholesale electricity distribution, peer-to-peer energy trading and electricity data management, while AI tools were used for energy management and energy efficiency in buildings.…”

Section: Analysis Of Relevant Reviewsmentioning

confidence: 99%

A Systematic Review on the Use of AI for Energy Efficiency and Indoor Environmental Quality in Buildings

Ogundiran,

Asadi,

Gameiro da Silva

2024

Sustainability

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Global warming, climate change and the energy crisis are trending topics around the world, especially within the energy sector. The rising cost of energy, greenhouse gas (GHG) emissions and global temperatures stem from the over-reliance on fossil fuel as the major energy resource. These challenges have highlighted the need for alternative energy resources and urgent intervention strategies like energy consumption reduction and improving energy efficiency. The heating, ventilation, and air-conditioning (HVAC) system in a building accounts for about 70% of energy consumption, and a decision to reduce energy consumption may impact the indoor environmental quality (IEQ) of the building. It is important to adequately balance the tradeoff between IEQ and energy management. Artificial intelligence (AI)-based solutions are being explored for improving building energy performance without compromising IEQ. This paper systematically reviews recent studies on AI and machine learning (ML) for building energy management and IEQ by exploring common use areas, the methods or algorithms applied and the results obtained. The overall purpose of this research is to add to the existing body of work and to highlight energy-related AI applications in buildings and the related gaps. The result shows five common application areas: thermal comfort and indoor air quality (IAQ) control; energy management and energy consumption prediction; indoor temperature prediction; anomaly detection; and HVAC controls. Gaps involving policy, real-life scenario applications, and insufficient study of the visual and acoustic comfort areas are also identified. Very few studies take into consideration the need to follow IEQ standards in the selection process and positioning of sensors in AI applications for IEQ in buildings. This study reveals a need for more systematically summarized research.

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“…At the same time, it appeared that green investments, consumption of renewable energy, and energy innovation neutralize environmental pollution [64]. A fairly new approach to achieving energy efficiency is using artificial intelligence and blockchain in energy management systems [65].…”

Section: Literature Reviewmentioning

confidence: 99%

Carbon Dioxide, Nitrous Oxide, and Methane: What Types of Greenhouse Gases Are Most Affected by Green Investments and Renewable Energy Development?

Kwilinski,

Dobrovolska,

Wołowiec

et al. 2024

Energies

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The article aims to analyze the impact of green investments and the development of renewable energy on greenhouse gas emissions based on 223 countries in 2011–2021. The information base is the International Renewable Energy Agency, Our World in Data, Climate Policy Initiative, and FTSE Russell. Correlation analysis was used to check the data multicollinearity, multivariate regression analysis with stepwise variable entry—to formalize functional relationships. All variables characterizing the dynamics of green investments and the development of alternative energy, the number of annual investments in off-grid renewable energy has the largest impact on the amount of CO2 and N2O. Thus, an annual investment increase of USD 1 million leads to a CO2 emission increase of 4.5 kt and an N2O emission increase of 0.272 kt. Simultaneously, the green economy’s market capitalization level has the largest impact on the amount of CH4. In this case, a capitalization increases of USD 1 trillion leads to a CH4 emission increase of 129.53 kt. The dynamics of renewable energy development have a statistically significant effect on only one of the three studied greenhouse gases—CO2 emissions. Here, 1 MW growth of an absolute increase in off-grid renewable energy capacity leads to a 1171.17 kt reduction of CO2 emissions. Checking input data for lags confirmed a time lag of one year between the level of green investments and the level of greenhouse gas emissions. That is, the impact of green investments on the level of greenhouse gas emissions is delayed by one year. The results of regression models taking into account lags confirmed that an increase in the level of green investments has a positive effect on reducing the level of greenhouse gas emissions (an increase in off-grid renewable energy annual investments of USD 1 million leads to a decrease in CO2 of 1.18 kt and N2O of 1.102 kt; the increase in green economy market capitalization of USD 1 trillion leads to a decrease in CH4 emissions of 0.64 kt).

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Using Blockchain and Artificial Intelligence in Energy Management as a Tool to Achieve Energy Efficiency

Cited by 15 publications

References 26 publications

Potential of Advanced Technologies for Environmental Management Systems

Potential of Advanced Technologies for Environmental Management Systems

A Systematic Review on the Use of AI for Energy Efficiency and Indoor Environmental Quality in Buildings

Carbon Dioxide, Nitrous Oxide, and Methane: What Types of Greenhouse Gases Are Most Affected by Green Investments and Renewable Energy Development?

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