Call for Contributions on Springer Book "Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications"

3 Mai 2019

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Catégorie : Ouvrages

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Dear colleagues,

We are editing a Springer book on “Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications”. Based on your expertise and research domain, we would like to invite you to contribute to this book.

The contributed chapters can be theoretical, application-oriented, or combine theory and application in discussing challenges, emerging trends, and future directions. They can also comprise a comprehensive joint picture of your past works, coined into a „red story line“. Both a review paper, allowing to describe, discuss, compare (advantages, drawbacks) etc., of methods and tools related to one or more of energy transition domains such as Renewable energy management and penetration, Power Stability and Energy Markets, Distributed renewable resources and storage systems, Optimizing household, intelligent control systems etc., or a contribution paper with recent results are welcome. Please see the attached document for more details about the context and topics of this book.

If you are interested to contribute, please provide a potential title, list of authors, and a brief abstract of your contribution in PDF format and submit it online via the Easychair submission interface (https://easychair.org/conferences/?conf=aiset2019). We appreciate very much if you can inform us of your willing to contribute to this book as soon as possible by sending an email to moamar.sayed-mouchaweh@mines-douai.fr

If you have any question, please do not hesitate to contact us.


Best regards

 

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Call for Contributions on Springer Book:

 

Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications

 

 

Aims and scope

 

Smart grid (SG) is an electric system that includes heterogeneous and distributed electricity generation, transmission, distribution, and consumption components. It is the next generation of power grid able to manage electricity demand (consumption/generation/distribution) in sustainable, reliable and economic manner through the penetration of renewable energies (solar, wind, etc.). Therefore, SG includes also an intelligent layer that analyzes the data produced by the consumers as well as by the production side in order to optimize the consumption and the production according to weather conditions and the consumer profile and habits. Moreover, it can enhance the use of green energy through the penetration of renewable energy and the demand response. SG is the future power system within the context of energy transition with two way flow of power and data between suppliers and consumers (micro-grids). It presents several research problems and challenges that need to be addressed in order to enhance the energy efficiency of traditional/renewable power generators through user participation, to facilitate the penetration (integration) of distributed/centralized renewable energy systems into electric grids, to reduce the peak load by the use of efficient demand response strategies, to balance and optimize generation and consumption, to reinforce the grid protection (grid resilience, fault diagnosis and prognosis, grid self-healing and recovery, etc.) as well as cyber security and privacy issues etc.

This book gathers advanced methods and tools based on the use of Artificial Intelligence (AI) techniques in order to address and solve these challenges and problems. The collected methods and tools will cover all the value chain from data acquisition and treatment to decision delivery visualization and explication by passing by learning and inference engine. In addition, the collected contributions will be selected according to the system scale, the built decision support system (passive and active), the used features and type of data, and the level of intrusiveness in order to explore their advantages and drawbacks according to the application conditions and constraints within the context of energy transition.

It is thus intended to comprise the following parts in order to cover the complete methodological and technical chain ifor a scalable energy transition (for assuring the objectives mentioned above):

 

• Part I: Artificial Intelligence for Smart Energy Management

• Part II: Artificial Intelligence for Cyber Security and Privacy

• Part III: Artificial Intelligence for Mobility and Electrical Vehicles

• Part IV: Artificial Intelligence for Micro Grid Operations and Dynamic Pricing Revenue Management

• Part V: Artificial Intelligence for Renewable Energy Penetration and management

 

We seek chapters that describe different paradigms as well as recent advances in methods and techniques in the field of Smart Energy Management within the context of Energy Transition. Chapters can be theoretical, application-oriented, or combine theory and application in discussing challenges, emerging trends, and future directions. They can also comprise a comprehensive joint picture of your past works, coined into a “storyline“.

 

Please submit a tentative title, names and affiliation of authors and a brief abstract with keywords of your proposed contribution in PDF format via the Easychair submission interface (https://easychair.org/conferences/?conf=aiset2019 ).

 

This Springer edited book solicits contributed chapters including but not limited to the following topics:

 

• Demand side management

• Renewable energy management and penetration

• Active Demand Response

• Integration of Wind and solar power into the grid

• Distributed renewable energy management, storage and integration into smart grids

• Wind turbines (offshore/onshore/floating) monitoring and management

• Solar plant monitoring and management

• Optimizing household and Intelligent control systems

• Micro grids operation

• Predictive asset management

• Load Disaggregation from smart metering data

• Non-Intrusive Load Monitoring (NILM)

• Building energy efficiency

• Power Stability and Energy Markets

• Grid Flexibility

• Smart cities within energy transition

• Blockchain/big data techniques for energy and power systems and networks

• Decision Support Systems for Predictive Maintenance

• Data visualization for Prescriptive Maintenance

• …

 

 

Key dates

Abstract Deadline: As soon as possible but before June 1st, 2019
Notification to submit full chapter: Two days after the abstract submission
Chapter submission deadline: August 5th, 2019
Notification of decision: October 15th, 2019
Camera-ready submission deadline: November 30th, 2019
Book delivery expected date: December 15th, 2019