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

Artificial intelligence(AI)as a multi-purpose technology is gaining increased attention and is now widely used across all sectors of the economy.The growing complexity of planning and operating power systems makes AI extremely valuable for the power industry.Until 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 applications.This study employs an AI taxonomy and automated web search to qualitatively and quantitatively unveil the biggest potentials of AI in the power industry.Our analysis,based on a review of 258’919 publications between 1982 and 2022,reveals where AI applications are particularly promising.We 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.

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

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 development.In 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.

Integrated silicon ohotonic MEMS

Silicon photonics has emerged as a mature technology that is expected to play a key role in critical emerging applications,including very high data rate optical communications,distance sensing for autonomous vehicles,photonic-accelerated computing,and quantum information processing.The success of silicon photonics has been enabled by the unique combination of performance,high yield,and high-volume capacity that can only be achieved by standardizing manufacturing technology.Today,standardized silicon photonics technology platforms implemented by foundries provide access to optimized library components,including low-loss optical routing,fast modulation,continuous tuning,high-speed germanium photodiodes,and high-effciency optical and electrical interfaces.However,silicon's relatively weak electro-optic effects result in modulators with a significant footprint and thermo-optic tuning devices that require high power consumption,which are substantial impediments for very large-scale integration in silicon photonics.Microelectromechanical systems(MEMS)technology can enhance silicon photonics with building blocks that are compact,low-loss,broadband,fast and require very low power consumption.Here,we introduce a silicon photonic MEMS platform consisting of high-performance nano-opto-electromechanical devices fully integrated alongside standard silicon photonics foundry components,with wafer-level sealing for long-term reliability,flip-chip bonding to redistribution interposers,and fibre-array attachment for high port count optical and electrical interfacing.Our experimental demonstration of fundamental silicon photonic MEMS circuit elements,including power couplers,phase shifters and wavelength-division multiplexing devices using standardized technology lifts previous impediments to enable scaling to very large photonic integrated circuits for applications in telecommunications,neuromorphic computing,sensing,programmable photonics,and quantum computing.