The distribution network is a crucial component of the power system, with industrialization driving increased energy demand. Traditional power-generating techniques, such as thermal and hydroelectric are not enough to meet this demand, leading to the development of Distributed Generation (DG). DG requires an extensive re-evaluation of the current power system, as it modifies energy losses and line flows. Inadequate integration of DG can cause power outages, disruption of protection coordination, and lead to islanding. AI can help overcome this issue by determining the best system architecture. Researchers have been interested in the Artificial Immune System (AIS) algorithm, which has room for development and lacks a fixed template. In order to improve AIS, X3PAIS, a hybridization strategy that combines clonal selection with a three-parent crossover has been developed within the scope of the study. X3PAIS was pre-tested using applications in a planetary gear train, a wastewater treatment facility, and mathematical calculations, showcasing its robustness and versatility. In the context of power distribution, X3PAIS is used in the multiple DG architecture of the power distribution system, reducing power losses by placing DG units in the best locations and sizing them to match load profiles. The four DGs' experiment results show that X3PAIS can minimize power losses by more than 89 %. To optimize power losses in the power distribution system, X3PAIS may be improved with a three-parent multiple-point crossover operation.
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http://dx.doi.org/10.1016/j.heliyon.2024.e37332 | DOI Listing |
Research (Wash D C)
July 2022
Department of Physics, Xiamen University, Xiamen 361005, China.
How to achieve high thermoelectric figure of merit is still a scientific challenge. By solving the Boltzmann transport equation, thermoelectric properties can be written as integrals of a single function, the transport distribution function (TDF). In this work, the shape effects of transport distribution function in various typical functional forms on thermoelectric properties of materials are systematically investigated.
View Article and Find Full Text PDFACS Energy Lett
January 2025
Department of Chemistry and Centre for Processable Electronics, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, U.K.
Antisolvent treatment is used in the fabrication of perovskite films to control grain growth during spin coating. We study widely incorporated aromatic hydrocarbons and aprotic ethers, discussing the origin of their performance differences in 2D/3D Sn perovskite (PEAFASnI) solar cells. Among the antisolvents that we screen, diisopropyl ether yields the highest power conversion efficiency in solar cells.
View Article and Find Full Text PDFCureus
December 2024
General Orthopedics, Midwest Bone and Joint Center, Macon, USA.
Introduction: Tranexamic acid (TXA) is an antifibrinolytic drug commonly used in total knee arthroplasty (TKA). Intravenous (IV) and topical TXA therapy have been extensively studied and shown to reduce blood loss, length of hospital stay, and blood transfusion rates following TKA. Despite the extensive literature regarding IV and topical TXA in orthopedics, there is a current dearth of studies analyzing oral usage.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
Microsystems Group, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
The increasing demand for processing large volumes of data for machine learning (ML) models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising solution to address this gap by enabling distributed data storage and processing at the micro-architectural level, significantly reducing both latency and energy. In this article, we present In-Memory comPuting architecture based on Y-FlAsh technology for Coalesced Tsetlin machine inference (IMPACT), underpinned on a cutting-edge memory device, Y-Flash, fabricated on a 180 nm complementary metal oxide semiconductor (CMOS) process.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
Electrical and Computer Engineering Department, UCLA, Los Angeles, CA, USA.
Sensors for the perception of multimodal stimuli-ranging from the five senses humans possess and beyond-have reached an unprecedented level of sophistication and miniaturization, raising the prospect of making man-made large-scale complex systems that can rival nature a reality. Artificial intelligence (AI) at the edge aims to integrate such sensors with real-time cognitive abilities enabled by recent advances in AI. Such AI progress has only been achieved by using massive computing power which, however, would not be available in most distributed systems of interest.
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