Abstract
Current study results on artificial intelligence have been published. According to news reporting originating from Falun, Sweden, by NewsRx correspondents, research stated, “The concept of a Positive Energy District (PED) has become a vital component of the efforts to accelerate the transition to zero carbon emissions and climate-neutral living environments. Research is shifting its focus from energyefficient single buildings to districts, where the aim is to achieve a positive energy balance across a given time period.” Funders for this research include Joint Programming Initiative (Jpi) Urban Europe; Vinnova; The Scientific And Technological Research Center of Turkey; Swedish Energy Agency. Our news editors obtained a quote from the research from Dalarna University: “Various innovation projects, programs, and activities have produced abundant insights into how to implement and operate PEDs. However, there is still no agreed way of determining what constitutes a PED for the purpose of identifying and evaluating its various elements. This paper thus sets out to create a process for characterizing PEDs. First, nineteen different elements of a PED were identified. Then, two AI techniques, machine learning (ML) and natural language processing (NLP), were introduced and examined to determine their potential for modeling, extracting, and mapping the elements of a PED. Lastly, state-of-the-art research papers were reviewed to identify any contribution they can make to the determination of the effectiveness of the ML and NLP models. The results suggest that both ML and NLP possess significant potential for modeling most of the identified elements in various areas, such as optimization, control, design, and stakeholder mapping. This potential is realized through the utilization of vast amounts of data, enabling these models to generate accurate and useful insights for PED planning and implementation.”
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Mdpi