ENERGY EFFICIENCY AND DIGITALIZATION: CHALLENGES AND OPPORTUNITIES FOR UKRAINE'S CONSTRUCTION INDUSTRY IN THE CONTEXT OF ENERGY SHORTAGES DOI

S. Pimenow

THEORETICAL AND APPLIED ISSUES OF ECONOMICS, Год журнала: 2024, Номер 49, С. 150 - 166

Опубликована: Янв. 1, 2024

Against the backdrop of global challenges such as geopolitical instability, environmental threats, and social crises, Ukraine's energy system has come under unprecedented pressure, requiring tactical responses to destruction infrastructure well long-term strategic solutions ensure its resilience efficiency. Currently, state efforts focused on operational measures, including restoration damaged power plants, support for decentralized sources, mobilizing foreign aid meet seasonal demands. However, despite existing national programs, National Energy Efficiency Plan, several unresolved aspects require further detailing adaptation current conditions. Specifically, there is a lack concrete steps integrating sources into building projects, flexible mechanisms operate during disruptions, incentives widespread use green technologies in large-scale construction. This research aims analyze opportunities related enhancing efficiency construction sector through innovative artificial intelligence (AI), machine learning (ML), digital twins, eco-friendly materials. The study utilizes methods content analysis, comparative situational expert evaluation develop practical recommendations both companies government bodies. results indicate that autonomy resilience, particularly twins IoT, are most effective wartime. Larger-scale solutions, smart energy-efficient buildings, investment they may be implemented post-war period. introduction AI ML not only improves but also helps reduce carbon footprint, which positively affects at environment aids adapting climate change.

Язык: Английский

Challenges of Artificial Intelligence Development in the Context of Energy Consumption and Impact on Climate Change DOI Creative Commons
Sergiusz Pimenow, Olena Pimenowa, Piotr Prus

и другие.

Energies, Год журнала: 2024, Номер 17(23), С. 5965 - 5965

Опубликована: Ноя. 27, 2024

With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) machine learning (ML) has emerged as a crucial tool for enhancing efficiency mitigating impacts change. However, their implementation dual character: on one hand, AI facilitates sustainable solutions, including optimization, renewable integration carbon reduction; other training operation large language models (LLMs) entail significant potentially undermining neutrality efforts. Key findings include an analysis 237 scientific publications from 2010 to 2024, which highlights advancements obstacles adoption across sectors, such construction, transportation, industry, households. The review showed that interest in use ML grown significantly: over 60% documents have been published last two years, with topics construction forecasting attracting most interest. Most articles are by researchers China, India, UK USA, (28–33 articles). This is more than twice number around rest world; 58% research concentrated three areas: engineering, computer science energy. In conclusion, also identifies areas further aimed at minimizing negative maximizing its contribution development, development energy-efficient architectures new methods management.

Язык: Английский

Процитировано

13

Smart Building Transferable Energy Scheduling Employing Reward Shaping Deep Reinforcement Learning with Demand Side Energy Management DOI

Siva Subramanian Kumaresan,

Pandia Rajan Jeyaraj

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112316 - 112316

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

The G.A.R.D.E.N framework for parametric design: a literature review DOI
Feng Qiu, Xi Chen, Ling Ma

и другие.

Architectural Engineering and Design Management, Год журнала: 2025, Номер unknown, С. 1 - 28

Опубликована: Май 19, 2025

Язык: Английский

Процитировано

0

Python-driven sensitivity analysis of geometric parameters: Evaluating the impact of geometric variations on environmental performance of large office in Boston DOI Creative Commons
Zinat Javanmard, Consuelo Nava

Green Technologies and Sustainability, Год журнала: 2025, Номер unknown, С. 100222 - 100222

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

ENERGY EFFICIENCY AND DIGITALIZATION: CHALLENGES AND OPPORTUNITIES FOR UKRAINE'S CONSTRUCTION INDUSTRY IN THE CONTEXT OF ENERGY SHORTAGES DOI

S. Pimenow

THEORETICAL AND APPLIED ISSUES OF ECONOMICS, Год журнала: 2024, Номер 49, С. 150 - 166

Опубликована: Янв. 1, 2024

Against the backdrop of global challenges such as geopolitical instability, environmental threats, and social crises, Ukraine's energy system has come under unprecedented pressure, requiring tactical responses to destruction infrastructure well long-term strategic solutions ensure its resilience efficiency. Currently, state efforts focused on operational measures, including restoration damaged power plants, support for decentralized sources, mobilizing foreign aid meet seasonal demands. However, despite existing national programs, National Energy Efficiency Plan, several unresolved aspects require further detailing adaptation current conditions. Specifically, there is a lack concrete steps integrating sources into building projects, flexible mechanisms operate during disruptions, incentives widespread use green technologies in large-scale construction. This research aims analyze opportunities related enhancing efficiency construction sector through innovative artificial intelligence (AI), machine learning (ML), digital twins, eco-friendly materials. The study utilizes methods content analysis, comparative situational expert evaluation develop practical recommendations both companies government bodies. results indicate that autonomy resilience, particularly twins IoT, are most effective wartime. Larger-scale solutions, smart energy-efficient buildings, investment they may be implemented post-war period. introduction AI ML not only improves but also helps reduce carbon footprint, which positively affects at environment aids adapting climate change.

Язык: Английский

Процитировано

1