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Reviewing 40 years of artificial intelligence applied to power systems-A taxonomic perspective

Energy and AI 2024年第1期15卷 136-150页

作者： f.heymann H.Quest T.Lopez Garcia C.Ballif M.Galus Swiss federal Office for Energy(SfOE) Section Geoinformation and Digital InnovationIttigenSwitzerland Ecole Polytechnique fédérale de Lausanne(EPfL) Photovoltaics and Thin-Film Electronics Laboratory(PV-LAB)Institute of Electrical and Micro Engineering(IEM)NeuchâtelSwitzerland 3S Swiss Solar Solutions AG ThunSwitzerland Swiss Center for Electronics and Microtechnology(CSEM) Sustainable Energy CenterNeuchâtelSwitzerland Digital Energy and Electric Power Lucerne University of Applied Sciences and ArtsLucerneSwitzerland

Artificial intelligence(AI)as a multi-purpose technology is gaining increased attention and is now widely used across all sectors of the *** growing complexity of planning and operating power systems makes AI extremely valuable for the power *** now,there has been a lack of clarity regarding the specific points along the power system supply chain where AI applications demonstrate significant value,as well as which AI domains are best suited for such *** study employs an AI taxonomy and automated web search to qualitatively and quantitatively unveil the biggest potentials of AI in the power *** analysis,based on a review of 258’919 publications between 1982 and 2022,reveals where AI applications are particularly *** consider six AI domains(reasoning,planning,learning,communication,perception,integration&interaction)and 19 use cases from the power supply chain(i.e.,generation,transmission networks,distribution networks,isolated grids/microgrids,market operations and retail).Our findings indicate that,as of now,the focus is predominantly on AI applications in power retail(55%),transmission(14%)and generation(13%).Most analyzed works describe applications built on algorithms of the AI domains“learning”(45%)and“planning”(14%).Results also suggest that the current definition of AI domains is ambiguous,and they highlight missing information on the actual use and successful implementation of AI in power system use cases.

关键词： Artificial intelligence Power systems Electricity Taxonomy Policy

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Barmag:用于生产特种纱线的新型空气变形机

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国际纺织导报 2004年第S1期32卷 62-63页

作者： f.heymann 高阔 Barmag公司德国

介绍了由Barmag公司研制的CATY新型空气变形机,可用于生产市场前景广泛的特种纱线。

关键词： ATY 变形机特种纱线

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Scarcity events analysis in adequacy studies using CN2 rule mining

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Energy and AI 2022年第2期8卷 116-123页

作者： fabian heymann Ricardo Bessa Mario Liebensteiner Konstantinos Parginos Juan Carlos Martin Hinojar Pablo Duenas Center for Power and Energy Systems INESC TEC Porto Portugal School of Business Economics and Society Friedrich-Alexander-Universitat Erlangen-Nuremberg NurembergGermany System Development ENTSO-E Brussels Belgium MIT Energy Initiative Massachusetts Institute of Technology Cambridge(MA) United States PERSEE Mines ParisTech

Dealing with scarcity events is nowadays gaining relevance in electricity market studies, as traditionally predictable generation and consumption patterns are fading. Policymakers and system planners use therefore adequacy studies to a) understand if the current market design will attract sufficient generation capacity to meet electricity demand in the future and b) to comprehend what drives system inadequacy or resource scarcity when future scenarios lack adequate capacity. This work addressed the latter and showcases a first in-its-kind rulebased methodology that filters scarcity events from a large set of electricity market simulations. In this proof-of-concept, a rule-mining algorithm is applied to outputs from ENTSO-E’s Pan-European electricity market model, which is run for 700 model scenarios, each covering 8760 time steps. The developed methodology shows how to unveil potential reasons behind scarcity events in an automated, interpretable, and scalable manner.

关键词： Electricity markets Data mining Security of supply Renewable energy Interpretability

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A 3D indicator for guiding AI applications in the energy sector

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Energy and AI 2022年第3期9卷 65-77页

作者： Hugo Quest Marine Cauz fabian heymann Christian Rod Lionel Perret Christophe Ballif Alessandro Virtuani Nicolas Wyrsch École Polytechnique fédérale de Lausanne(EPfL) Institute of Electrical and Micro Engineering(IEM)Photovoltaics and Thin-Film Electronics Laboratory(PV-LAB)NeuchâtelSwitzerland S Swiss Solar Solutions AG ThunSwitzerland Planair SA Yverdon-les-BainsSwitzerland Swiss federal Office for Energy(SfOE) Digital Innovation OfficeIttigenSwitzerland Swiss Center for Electronics and Microtechnology(CSEM) Sustainable Energy CenterNeuchâtelSwitzerland

The utilisation of Artificial Intelligence (AI) applications in the energy sector is gaining momentum, withincreasingly intensive search for suitable, high-quality and trustworthy solutions that displayed promisingresults in research. The growing interest comes from decision makers of both the industry and policydomains, searching for applications to increase companies’ profitability, raise efficiency and facilitate theenergy transition. This paper aims to provide a novel three-dimensional (3D) indicator for AI applicationsin the energy sector, based on their respective maturity level, regulatory risks and potential benefits. Casestudies are used to exemplify the application of the 3D indicator, showcasing how the developed frameworkcan be used to filter promising AI applications eligible for governmental funding or business *** addition, the 3D indicator is used to rank AI applications considering different stakeholder preferences(risk-avoidance, profit-seeking, balanced). These results allow AI applications to be better categorised in theface of rapidly emerging national and intergovernmental AI strategies and regulations that constrain the useof AI applications in critical infrastructures.

关键词： Artificial intelligence Digitalisation AI application Big data AI policy Energy sector

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Early dynamic transcriptomic changes during preoperative radiotherapy in patients with rectal cancer: A feasibility study

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World Journal of Gastroenterology 2013年第21期19卷 3249-3254页

作者： Stephane Supiot Wilfried Gouraud Loc Campion Pascal Jezéquel Bruno Buecher Josiane Charrier Marie-francoise heymann Marc-Andre Mahé Emmanuel Rio Michel Chérel Department of Radiation Oncology Institut de Cancérologie de l'Ouest René Gauducheau44800 Nantes-St-HerblainFrance INSERM U892 Centre de Recherche en Cancérologie Nantes-AngersUniversity of Nantes44000 NantesFrance Centre Hospitalier Universitaire 44000 NantesFrance Department of Nuclear Medicine Institut de Cancérologie de l'Ouest René Gauducheau44800 Nantes-Saint HerblainFrance

AIM: To develop novel biomarkers of rectal radiotherapy, we measured gene expression profiles on biopsies taken before and during preoperative radiotherapy. METHODS: Six patients presenting with a locally advanced rectal cancer (T>T2, N0/Nx, M0) eligible for preoperative radiotherapy (45 Gy in 25 fractions) were selected in a pilot study. Six tumor and 3 normal tissues biopsies were taken before and during radiotherapy,after a dose of 7.2 Gy at a median time of 1 h following irradiation (0:27-2:12). Tumor or normal tissue purity was assessed by a pathologist prior to RNA extraction. Mean RNA content was 23 μg/biopsy (14-37) before radiotherapy and 22.7 μg/biopsy (12-35) during radiotherapy. After RNA amplification, biopsies were analysed with 54K HG-U133A Plus 2.0 Affymetrix expression micro-arrays. Data were normalized according to MAS5 algorithm. A gene expression ratio was calculated as: (gene expression during radiotherapy-gene expression before radiotherapy)/gene expression before radiotherapy. Were selected genes that showed a ratio higher than ± 0.5 in all 6 patients. RESULTS: Microarray analysis showed that preoperative radiotherapy significantly up-regulated 31 genes and down-regulated 6 genes. According to the Gene Ontology project classification, these genes are involved in protein metabolism (ADAMDEC1 ; AKAP7 ; CAPN5 ; CLIC5 ; CPE ; CREB3L1 ; NEDD4L ; RAB27A), ion transport (AKAP7 ; ATP2A3 ; CCL28 ; CLIC5 ; f2RL2 ; NEDD4L ; SLC6A8), transcription (AKAP7 ; CREB3L1 ; ISX ; PAB-PC1L ; TXNIP), signal transduction (CAPN5 ; f2RL2 ; RA- B27A ; TNfRSf11A), cell adhesion (ADAMDEC1 ; PXDN ; SPON1 ; S100A2), immune response (CCL28 ; PXDN ; TNfRSf11A) and apoptosis (ITM2C ; PDCD4 ; PVT1). Up-regulation of 3 genes (CCL28 ; CLIC5 ; PDCD4) was detected by 2 different probes and up-regulation of 2 genes (RAB27A ; TXNIP) by 3 probes. CONCLUSION: Micro-arrays can efficiently assess early transcriptomic changes during preoperative radiotherapy for rectal cancer, and may he

关键词： CCL28 CLIC5 PDCD4 RAB27A TXNIP Protein metabolism Cell adhesion Cell migration SPON1 Carboxypeptidase E

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