CONF-MPCS 2025
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Title:

Leveraging EVs and Machine Learning for Sustainable Energy Demand Management

Date:

May 16th, 2025 (UTC +1)

Organizer:

Department of Computer and Information Sciences, University of Strathclyde

Symposium Chair:

Dr. Anil Fernando

Professor in University of Strathclyde

Personal Bio:

Dr. Anil Fernando received the B.Sc. (Hons.) degree (First Class) in electronics and telecommunication engineering from the University of Moratuwa, Sri Lanka, in 1995, and the M.Sc. in Communications (Distinction) from the Asian Institute of Technology, Bangkok, Thailand in 1997 and Ph.D. in Computer Science (Video Coding and Communications) from the University of Bristol, UK in 2001. He is a professor in Video Coding and Communications at the Department of Computer and Information Sciences, University of Strathclyde, UK. He leads the video coding and communication research team at Strathclyde. He has worked on major national and international multidisciplinary research projects and led most of them. He has published over 460 papers in international journals and conference proceedings and published a book on 3D video broadcasting. He has been working with all major EU broadcasters, BBC, and major European media companies/SMEs in the last decade in providing innovative media technologies for British and EU citizens. His main research interests are in Video coding and Communications, Machine Learning (ML) and Artificial Intelligence (AI), Semantic Communications, Quantum Communications, Signal Processing, Networking and Communications, Interactive Systems, Resource Optimizations in 6G, Distributed Technologies, Media Broadcasting and Quality of Experience (QoE).

Committee Members:

Lahiru Deshan, University of Strathclyde, UK, [email protected]

Piyumi Perera, University of Strathclyde, UK, [email protected]

Prabaji Dharmarathna, University of Strathclyde, UK, [email protected]

Call for Papers

Background:

The world's transition to renewable energy and a fully electric vehicle (EV) fleet by 2050 presents both opportunities and challenges in managing peak energy demand. Traditional methods, such as reliance on natural gas and centralized battery storage, are unsustainable due to high carbon emissions and inflexibility. EVs offer a decentralized energy storage solution, but their integration requires robust financial incentives to encourage participation. Current tariffs, like Economy 7, fail to address challenges such as battery depletion and limited off-peak recharge windows, discouraging EV users from contributing to grid stability.

This symposium proposes an innovative income model combining dynamic pricing, contribution bonuses, and battery health subsidies to incentivize EV users. By leveraging machine learning models, such as Bayesian probability frameworks, the model optimizes energy demand forecasting and user behavior. This approach not only enhances grid stability but also supports the net-zero goals by reducing reliance on fossil fuels. The symposium will explore how this model can transform peak demand management, creating a sustainable and scalable solution for the future.

Goal/Rationale:

We present a sustainable solution for managing peak energy demand considering the UK as an example by leveraging the growing electric vehicle (EV) fleet as a decentralized energy storage system. Our approach integrates machine learning models, such as Bayesian probability frameworks, to optimize EV energy supply during peak periods and recharging during off-peak hours. This strategy aims to reduce reliance on fossil fuels, enhance grid stability, and support the UK's net-zero goals. Central to this framework is an innovative income model designed to incentivize EV users to participate in energy trading. By incorporating dynamic pricing, contribution bonuses, and battery health subsidies, we ensure financial rewards for users while minimizing grid strain.

Real-time data on EV mobility, charging patterns, and grid demand will be analyzed to optimize energy distribution and maximize user participation. Additionally, predictive analytics will be used to forecast peak demand and adjust compensation rates, ensuring a balanced and efficient system. Through this symposium, we aim to bridge the gap between technical feasibility and real-world implementation, providing actionable insights for researchers, policymakers, and energy professionals. By aligning financial incentives with sustainability goals, our framework offers a scalable solution for managing peak energy demand. We highlight the environmental, economic, and societal benefits of this approach, paving the way for a sustainable energy future in the UK and beyond.

Topics:

The main topics of this symposium are listed below.

Computational Simulation

  • Adaptive Control and Non-Linear Control
  • Artificial Intelligence
  • Computational Intelligence
  • Design, Analysis and Applications of Optimisation Algorithms
  • Deterministic, Dynamic, Stochastic, Robust and Combinatorial Optimisation Models
  • High Performance Computing
  • Information Science
  • Intelligent Control, Neuro-control, Fuzzy Control
  • Machine Learning
  • Mathematical Modeling and Simulation
  • Nano- and Bio- Mechanics
  • Optimization Techniques
  • Robotics and Automation
  • Smart Structures and Health Monitoring
  • Soft Computing
  • Structural Optimization
  • Theoretical and Empirical Studies of Computational Methods, Models and Empirical Analysis

Meanwhile, submissions aligned with the overall conference theme are also welcome.

Mathematical Physics

  • Dynamical Systems
  • Equilibrium Statistical Mechanics
  • General Relativity
  • Integrable Systems
  • Many-body Quantum Systems and Condensed Matter Physics
  • Nonequilibrium Statistical Mechanics
  • Partial Differential Equations
  • Probability and Random Structures
  • Quantum Field Theory
  • Quantum Information
  • Quantum Mechanics and Spectral Theory
  • String Theory and Quantum Gravity

Applied Physics

  • Accelerator Physics
  • Accelerator Research and Development
  • Acoustics, Noise and Vibration
  • Applications of Particle Trapping
  • Biophysics, Medical Physics
  • Detectors and Data Handling
  • Engineering Physics
  • Instrumentation and Control Components
  • Magnetic Devices and Materials
  • Materials Physics
  • Mechanics, Rheology and Tribology
  • Nano and Metamaterials
  • Neuromorphic Computing
  • Nuclear Physics
  • Quantum Chromodynamics and Quantum Computers
  • Spin Dynamics
  • Statistical Mechanics
  • Stealth Technology
  • Storage Ring Physics
  • Systems and Automation Thermodynamics

Mathematics and Applied Mathematics

  • Algebra and Its Application
  • Applied Partial Differential Equations
  • Bayesian Inference
  • Control Theory
  • Discrete Applied Mathematics
  • Fluid Dynamics
  • Fuzzy Mathematics and Its Applications
  • Geometry
  • Image Processing
  • Integral Equations
  • Nonlinear Problems in Mechanics
  • Numerical Analysis
  • Optimization and Operational Research
  • Planning and Scheduling
  • Probability Theory
  • Regression Analysis Estimation Theory
  • Sampling Theory
  • Statistics
  • Stochastic Processes

Submission:

Prospective authors are kindly invited to submit full papers that include title, abstract, introduction, tables, figures, conclusion and references. It is unnecessary to submit an abstract in advance. Please submit your papers in English.

Each paper should be no less than 4 pages. One regular registration can cover a paper of 6 pages, and additional pages will be charged. Please format your paper well according to the conference template before submission. Paper Template Download

Please prepare your paper in both .doc/.docx and .pdf format and submit your full paper by email with both formats attached directly to [email protected]

Important Dates:

Process Date & Time
Submission Deadline May 9, 2025
Symposium Date May 16, 2025
Notification of Acceptance 7-20 workdays

Publication:

Accepted papers of the symposium will be published in Theoretical and Natural Science (TNS) (Print ISSN 2753-8818), and will be submitted to Conference Proceedings Citation Index (CPCI), Crossref, CNKI, Portico, Engineering Village (Inspec), Google Scholar, and other databases for indexing. The situation may be affected by factors among databases like processing time, workflow, policy, etc.

Publication info

Title: Theoretical and Natural Science (TNS)
Press: EWA Publishing, United Kingdom
ISSN: 2753-8818, 2753-8826 (electronic)

This symposium is organized by CONF-MPCS 2025 and it will independently proceed the submission and publication process.

* The papers will be exported to production and publication on a regular basis. Early-registered papers are expected to be published online earlier.

Ways to Participate

Venue:

Room LT507, Livingston Tower, Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK

Attend in Person:

If you want to attend the symposium on-site, please email [email protected]. The symposium seats are limited. Both contributors and non-contributors who wish to participate in the symposium in person need to apply to the symposium organizers.

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My scientific studies have afforded me great gratification; and I am convinced that it will not be long before the whole world acknowledges the results of my work.