scholarly journals Accelerating Energy Transition to Green Electricity through Artificial Intelligence

2021 ◽  
Author(s):  
Hendro Wicaksono
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Power Generation ◽  
Demand Response ◽  
Energy Transition ◽  
Data Driven ◽  
Smart Metering ◽  
Green Electricity ◽  
Definition Of

The presentation focuses on the role of artificial intelligence in accelerating the transition to green electricity in Germany. It discusses the challenges in the transition towards green electricity in Germany and the role of digitalization through smart metering. One of the methods to adopt and disseminate the use of green electricity is demand response. The presentation explains the definition of demand response concept and gives an example of projects that applies neural network to forecast power generation and consumption to enable calculation of dynamic electricity price. Finally, the presentation explores the adoption of green electricity in broader contexts, e.g., cities and districts, through a data-driven smart energy platform.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Applications of AI in Financial System

2017 ◽  
pp. 101-109
Author(s):  
Santosh Kumar ◽  
Roopali Sharma
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Decision Analysis ◽  
Computer Science ◽  
Investment Decision ◽  
Analysis Tool ◽  
Changing Environment ◽  
Human Interference ◽  
Applications Of Ai

Role of computers are widely accepted and well known in the domain of Finance. Artificial Intelligence(AI) methods are extensively used in field of computer science for providing solution of unpredictable event in a frequent changing environment with utilization of neural network. Professionals are using AI framework into every field for reducing human interference to get better result from few decades. The main objective of the chapter is to point out the techniques of AI utilized in field of finance in broader perspective. The purpose of this chapter is to analyze the background of AI in finance and its role in Finance Market mainly as investment decision analysis tool.

scholarly journals Critical Care, Critical Data

2019 ◽  
Vol 10 ◽  
pp. 117959721985656 ◽  
Author(s):  
Christopher V Cosgriff ◽  
Leo Anthony Celi ◽  
David J Stone
Keyword(s):  
Artificial Intelligence ◽  
Critical Care ◽  
Clinical Data ◽  
Continuous Monitoring ◽  
Data Science ◽  
Clinical Decision ◽  
Critical Care Medicine ◽  
Data Driven ◽  
Critical Data

As big data, machine learning, and artificial intelligence continue to penetrate into and transform many facets of our lives, we are witnessing the emergence of these powerful technologies within health care. The use and growth of these technologies has been contingent on the availability of reliable and usable data, a particularly robust resource in critical care medicine where continuous monitoring forms a key component of the infrastructure of care. The response to this opportunity has included the development of open databases for research and other purposes; the development of a collaborative form of clinical data science intended to fully leverage these data resources, and the creation of data-driven applications for purposes such as clinical decision support. Most recently, data levels have reached the thresholds required for the development of robust artificial intelligence features for clinical purposes. The systematic capture and analysis of clinical data in both individuals and populations allows us to begin to move toward precision medicine in the intensive care unit (ICU). In this perspective review, we examine the fundamental role of data as we present the current progress that has been made toward an artificial intelligence (AI)-supported, data-driven precision critical care medicine.

scholarly journals Does Combined Heat and Power Play the Role of a Bridge in Energy Transition? Evidence from a Cross-Country Analysis

2019 ◽  
Vol 11 (4) ◽  
pp. 1035 ◽  
Author(s):  
Hyo-Jin Kim ◽  
Jeong-Joon Yu ◽  
Seung-Hoon Yoo
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Electricity Generation ◽  
Nuclear Power ◽  
Energy Transition ◽  
Parameter Estimate ◽  
Combined Heat And Power ◽  
Cross Country ◽  
The Impact

In an era of energy transition involving an increase in renewable energy and a reduction in coal-fired power generation and nuclear power generation, the role of combined heat and power (CHP) as a bridging energy is highly emphasized. This article attempts to look empirically into the impact of increasing the share of renewable energy in total electricity generation on CHP share in total electricity generation in a cross-country context. Data from 35 countries during the period 2009–2015 were used, and the least absolute deviations estimator was applied to obtain a more robust parameter estimate. The results showed that a 1%p increase in the share of renewable energy significantly increased the CHP share by 0.87%p. Therefore, the hypothesis that CHP serves as bridge energy in the process of energy transition was established.

scholarly journals Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 16
Author(s):  
Abdul Majeed ◽  
Seong Oun Hwang
Keyword(s):  
Artificial Intelligence ◽  
Personal Data ◽  
General Purpose ◽  
Data Driven ◽  
Healthcare Sector ◽  
Future Research ◽  
Recent Developments ◽  
Technological Developments ◽  
Novel Coronavirus

This paper presents the role of artificial intelligence (AI) and other latest technologies that were employed to fight the recent pandemic (i.e., novel coronavirus disease-2019 (COVID-19)). These technologies assisted the early detection/diagnosis, trends analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control, to name a few. The key-enablers of these technologies was data that was obtained from heterogeneous sources (i.e., social networks (SN), internet of (medical) things (IoT/IoMT), cellular networks, transport usage, epidemiological investigations, and other digital/sensing platforms). To this end, we provide an insightful overview of the role of data-driven analytics leveraging AI in the era of COVID-19. Specifically, we discuss major services that AI can provide in the context of COVID-19 pandemic based on six grounds, (i) AI role in seven different epidemic containment strategies (a.k.a non-pharmaceutical interventions (NPIs)), (ii) AI role in data life cycle phases employed to control pandemic via digital solutions, (iii) AI role in performing analytics on heterogeneous types of data stemming from the COVID-19 pandemic, (iv) AI role in the healthcare sector in the context of COVID-19 pandemic, (v) general-purpose applications of AI in COVID-19 era, and (vi) AI role in drug design and repurposing (e.g., iteratively aligning protein spikes and applying three/four-fold symmetry to yield a low-resolution candidate template) against COVID-19. Further, we discuss the challenges involved in applying AI to the available data and privacy issues that can arise from personal data transitioning into cyberspace. We also provide a concise overview of other latest technologies that were increasingly applied to limit the spread of the ongoing pandemic. Finally, we discuss the avenues of future research in the respective area. This insightful review aims to highlight existing AI-based technological developments and future research dynamics in this area.

scholarly journals Potential Renewable Hydrogen from Curtailed Electricity to Decarbonize ASEAN’s Emissions: Policy Implications

2020 ◽  
Vol 12 (24) ◽  
pp. 10560 ◽  
Author(s):  
Han Phoumin ◽  
Fukunari Kimura ◽  
Jun Arima
Keyword(s):  
Power Generation ◽  
Hydrogen Production ◽  
Large Scale ◽  
Fossil Fuels ◽  
Wind Farms ◽  
Energy Transition ◽  
Policy Implications ◽  
Policy Support ◽  
Renewable Hydrogen

The power generation mix of the Association of Southeast Asian Nations (ASEAN) is dominated by fossil fuels, which accounted for almost 80% in 2017 and are expected to account for 82% in 2050 if the region does not transition to cleaner energy systems. Solar and wind power are the most abundant energy resources but contribute negligibly to the power mix. Investors in solar or wind farms face high risks from electricity curtailment if surplus electricity is not used. Employing the policy scenario analysis of the energy outlook modelling results, this paper examines the potential scalability of renewable hydrogen production from curtailed electricity in scenarios of high share of variable renewable energy in the power generation mix. The study found that ASEAN has high potential in developing renewable hydrogen production from curtailed electricity. The study further found that the falling cost of renewable hydrogen production could be a game changer to upscaling the large-scale hydrogen production in ASEAN through policy support. The results implied a future role of renewable hydrogen in energy transition to decarbonize ASEAN’s emissions.

scholarly journals Integration of the Iberian Natural Gas Infrastructure into the European Energy Transition to Renewable Sources

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1492
Author(s):  
Pablo Fernández Fernández ◽  
Jose Pablo Paredes Sánchez ◽  
Jorge Xiberta Bernat
Keyword(s):  
Power Generation ◽  
Natural Gas ◽  
Equilibrium Model ◽  
Energy Transition ◽  
Spatial Equilibrium ◽  
Renewable Sources ◽  
Spatial Equilibrium Model ◽  
The Future ◽  
The Eu

The natural gas is broadly envisaged as a transition fuel in the energy decarbonisation. However, demand scenarios to 2050 differs largely depending on the share captured in the power generation and transport sectors. In such an uncertain context, an intertemporal spatial equilibrium model is implemented, to optimize the deployment of the future EU infrastructures over the period 2015-2050. The Iberian sub region is emphasized, so that the role of its regasification capacity and the interconnection with the rest of the EU is stated. As a result, additional investments on regasification plants are not required, provided that the EU- Iberian interconnection is properly expanded, in line with the planned project MIDCAT.

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