Complex energy monitoring and control systems have been widely studied as the related topics include different approaches, advanced sensors, and technologies applied to a strongly varying amount of application fields. This paper is a systematic review of what has been done regarding energy metering system issues about (i) sensors, (ii) the choice of their technology and their characterization depending on the application fields, (iii) advanced measurement approaches and methodologies, and (iv) the setup of energy Key Performance Indicators (KPIs). The paper provides models about KPI estimation, by highlighting design criteria of complex energy networks. The proposed study is carried out to give useful elements to build models and to simulate in detail energy systems for performance prediction purposes. Some examples of energy complex KPIs based on the integration of the Artificial Intelligence (AI) concept and on basic KPIs or variables are provided in order to define innovative formulation criteria depending on the application field. The proposed examples highlight how modeling a complex KPI as a function of basic variables or KPIs is possible, by means of graph models of architectures.
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http://dx.doi.org/10.3390/s22134929 | DOI Listing |
Photosynth Res
January 2025
Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia, 119991.
The femtosecond dynamics of energy transfer from light-excited spirilloxanthin (Spx) to bacteriochlorophyll (BChl) a in the reaction centers (RCs) of purple photosynthetic bacteria Rhodospirillum rubrum was studied. According to crio-electron microscopy data, Spx is located near accessory BChl a in the B-branch of cofactors. Spx was excited by 25 fs laser pulses at 490 nm, and difference absorption spectra were recorded in the range 500-700 nm.
View Article and Find Full Text PDFAir conditioning systems are widely used to provide thermal comfort in hot and humid regions, but they also consume a large amount of energy. Therefore, accurate and reliable load demand forecasting is essential for energy management and optimization in air conditioning systems. Within the current paper, a novel model on the basis of machine learning has been presented for dynamic optimal load demand forecasting in air conditioning systems.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia.
Polycyclic aromatic compounds (PACs) are pervasive environmental contaminants derived from diverse sources including pyrogenic (e.g., combustion processes), petrogenic (e.
View Article and Find Full Text PDFNat Commun
January 2025
MOE Key Laboratory of Bio-Intelligent Manufacturing, School of Bioengineering, Dalian University of Technology, Dalian, China.
Visualizing mechanical stress distribution in soft and live biomaterials is essential for understanding biological processes and improving material design. However, it remains challenging due to their complexity, dynamic nature, and sensitivity requirements, necessitating innovative techniques. Since polysaccharides are common in various biomaterials, a biosensor integrating a Förster resonance energy transfer (FRET)-based tension sensor module and carbohydrate-binding modules (FTSM-CBM) has been designed for real-time monitoring of the stress distribution of these biomaterials.
View Article and Find Full Text PDFNat Commun
January 2025
Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute & Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China.
The unsatisfactory ionic conductivity of solid polymer electrolytes hinders their practical use as substitutes for liquid electrolytes to address safety concerns. Although various plasticizers have been introduced to improve lithium-ion conduction kinetics, the lack of microenvironment understanding impedes the rational design of high-performance polymer electrolytes. Here, we design a class of Hofmann complexes that offer continuous two-dimensional lithium-ion conduction channels with functional ligands, creating highly conductive electrolytes.
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