Integrated Energy Systems Optimization

Latest papers

• Quantifying AI impact in energy transitions: The Energy Justice Impact Assessment (EJIA) framework

  Emily Bringmann, Florian Kutzner, Bianca Weber, Celina Kacperski · 25 September 2026

  Artificial intelligence is increasingly deployed across energy systems to optimize efficiency, balance supply and demand, and integrate renewable sources. These applications alter how energy systems function, changing how benefits and burdens are distributed, whose needs are represented in system de…

• How to build a campfire? Participatory modelling with justice

  Nynke van Uffelen, Sander ten Caat, Aarthi Sundaram, Annemiek de Looze, Marion Collewet, Eefje Cuppen, Igor Nikolic · 16 September 2026

  Energy transition decision-making is pervaded by deep uncertainties. Computational models are helpful in addressing such uncertainties, as they can give insight into techno-economic complexity. However, models alone are insufficient, as part of the uncertainties involve justice dilemmas.…

• Computing at Sea: Floating and Offshore Data Centres as a Pathway to Sustainable AI Infrastructure

  Cheng Siong Chin, Jianhua Zhang, M. Venkateshkumar · 14 September 2026

  The rapid expansion of artificial intelligence is transforming data centres into one of the world's fastest-growing sources of electricity demand. As AI systems scale in size and capability, the physical infrastructure supporting computation is approaching critical limits in energy availability, coo…

• AI for AI: Optimizing Additional Infrastructure Build-out to Power Artificial Intelligence Data Centers

  Alexander Crosier, Kyle Onghai, Ronnie Sircar · 9 September 2026

  The twenty-first century's transformative technology, artificial intelligence, is increasingly constrained by the twentieth century's transformative technology, the electricity grid. Rapid growth in electricity demand from data centers is leading to higher electricity prices, without a compensating …

• Improving Energy Efficiency of Oil Platforms Through Optimal Loading of Diesel Generators Using Machine Learning and Search Algorithms

  Khivishta Boodhoo, Josh Plumbly, Nicholas Watson · 25 August 2026

  Rising energy demand, fossil fuel depletion and climate change highlight the need for more efficient energy production and consumption. Offshore oil and gas platforms face challenges related to inefficient energy use, system failures, accessibility and environmental impact. Machine learning (ML) off…

• Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

  Jacopo Ghirri, Carlos Rodriguez-Pardo, Lara Aleluia Reis, Massimo Tavoni · 20 August 2026

  The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with this ambition remains uncertain. We apply deep learning to high-resolution socioeconomic and sectoral data across EU27 member states till 2023 to projec…

• XGBoost "is all you need": the case of forecasting transmitted heat energy in District Heating Systems

  Milan Zdravkovi\'c · 13 August 2026

  This paper presents a comparative study of two distinct approaches, XGBoost and Long-Short Term Memory (LSTM), for forecasting transmitted heat energy in District Heating Systems (DHS). The objective is to explore scenarios in which conventional ML algorithms demonstrate better performance over deep…

• Automated Extraction of Techno-Economic Data from 76,000 Energy System Studies

  Maxime Gorres, Jan Göpfert, Patrick Kuckertz, Noor Titan Putri Hartono, Heidi Heinrichs, Jochen Linßen, Iain Staffel, Jann Michael Weinand · 22 July 2026

  Energy system models guide societally important decisions, but their credibility rests on quantitative assumptions that are difficult to source and audit. Meta-analyses can improve transparency and modeling practices, but the rapid growth of publications makes manual information extraction increasin…

• A Phased Development Framework Enabling Islanded Operation of Sustainable AI Data Centers With Onsite Grid-Following and Grid-Forming Energy Architectures

  Soham Ghosh, Nabil Mohammed, Mohammad Ashraf Hossain Sadi · 21 July 2026

  As hyperscale and colocation AI data centers continue to expand, the electric grid is increasingly required to support large, concentrated loads, with individual facilities ranging from 500 MW to 2 GW. Current projections estimate that approximately 50 GW of AI data center capacity will require grid…

• A Statistical and Machine Learning Framework for Operational Threshold Detection and Deployable Dispatch Controller Development in Hydrogen Multi-Energy Systems

  Shadi Heenatigala, Hasanika Samarasinghe · 15 June 2026

  This study presents a statistical and machine learning framework for characterizing a hydrogen-based multi-energy system (H-MES) using one year of high-resolution operational data. Statistical analysis revealed a binary operation driven by renewable surplus, with solar irradiance explaining 45.7% of…

• Powering the Future of AI: Navigating the Trade-offs for Europe's Energy Transition and Net-Zero Goals

  Mohammad Hemmati, Gbemi Oluleye, Vassilis M. Charitopoulos · 9 June 2026

  The rapid expansion of AI globally has led to the proliferation of energy-intensive hyperscale data centres (DCs), making them as a structurally challenging component in power system planning and operation. Using a spatially explicit optimisation model of Europe across 21 AI growth scenarios, we sys…

• Powering the Future of AI: Navigating the Trade-offs for Europe's Energy Transition and Net-Zero Goals

  Mohammad Hemmati, Gbemi Oluleye, Vassilis M. Charitopoulos · 9 June 2026

  The rapid expansion of AI globally has led to the proliferation of energy-intensive hyperscale data centres (DCs), making them as a structurally challenging component in power system planning and operation. Using a spatially explicit optimisation model of Europe across 21 AI growth scenarios, we sys…

• Bridging the climate to energy data gap: simulated annealing for representative climate year selection

  Bram van Duinen, Karin van der Wiel, Jean Thorey, Laurens Stoop · 18 May 2026

  Energy system models are increasingly dependent on representative climate input. Yet, a fundamental mismatch persists between the hundreds of simulated years often used in climate science and the handful of years that computationally demanding power system models can process. Current practice, inclu…

• Enabling Predictive Maintenance in District Heating Substations: A Labelled Dataset and Fault Detection Evaluation Framework based on Service Data

  Cyriana M. A. Roelofs, Edison Guevara Bastidas, Thomas Hugo, Stefan Faulstich, Anna Cadenbach · 20 April 2026

  Early detection of faults in district heating substations is imperative to reduce return temperatures and enhance efficiency. However, progress in this domain has been hindered by the limited availability of public, labelled datasets. We present an open-source framework combining a service report va…

• End-to-End Learning-based Operation of Integrated Energy Systems for Buildings and Data Centers

  Zhenyu Pu, Yu Yang, Liang Yu, Xiaohong Guan · 17 April 2026

  Buildings and data centers (DCs) are energy-intensive sectors, playing a critical role to achieve the low-carbon and sustainable energy transition targets. To this end, integrated energy system (IES) that incorporates diverse renewables, energy generation, conversion, and storage technologies to ena…

• Virtual Smart Metering in District Heating Networks via Heterogeneous Spatial-Temporal Graph Neural Networks

  Keivan Faghih Niresi, Christian M{\o}ller Jensen, Carsten Skovmose Kalles{\o}e, Rafael Wisniewski, Olga Fink · 14 April 2026

  Intelligent operation of thermal energy networks aims to improve energy efficiency, reliability, and operational flexibility through data-driven control, predictive optimization, and early fault detection. Achieving these goals relies on sufficient observability, requiring continuous and well-distri…

• Exploring near-optimal energy systems with stakeholders: a novel approach for participatory modelling

  Oskar V{\aa}ger\"o, Koen van Greevenbroek, Aleksander Grochowicz, Maximilian Roithner · 14 April 2026

  Involving people in energy systems planning can increase the legitimacy and socio-political feasibility of energy transitions. Participatory research in energy modelling offers the opportunity to engage with stakeholders in a comprehensive way, but is limited by how results can be generated and pres…

• Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

  Danbo Chen, Zijun Zhou, Yongyang Cai, Jiahong Qin, Ani Katchova, Lei Chen · 9 April 2026

  The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure on electricity systems. This study introduces an AI-energy coupling framework that combines large language models (LLMs)-based analysis of corporate, …

• NeedForHeat DataGear: An Open Monitoring System to Accelerate the Residential Heating Transition

  Henri ter Hofte, Nick van Ravenzwaaij · 6 April 2026

  We introduce NeedForHeat DataGear: an open hardware and open software data collection system designed to accelerate the residential heating transition. NeedForHeat DataGear collects time series monitoring data in homes that have not yet undergone a heating transition, enabling assessment of real-lif…

• An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis

  Oluwamayowa O. Amusat, Luka Grbcic, Remi Patureau, M. Jibran S. Zuberi, Dan Gunter, Michael Wetter · 3 April 2026

  Designing reliable integrated energy systems for industrial processes requires optimization and verification models across multiple fidelities, from architecture-level sizing to high-fidelity dynamic operation. However, model mismatch across fidelities obscures the sources of performance loss and co…

• Optimal trajectory-guided stochastic co-optimization for e-fuel system design and real-time operation

  Jeongdong Kim, Minsu Kim, Jonggeol Na, Junghwan Kim · 5 March 2026

  E-fuels are promising long-term energy carriers supporting the net-zero transition. However, the large combinatorial design-operation spaces under renewable uncertainty make the use of mathematical programming impractical for co-optimizing e-fuel production systems. Here, we present MasCOR, a machin…

• Improving Spatial Allocation for Energy System Coupling with Graph Neural Networks

  Xuanhao Mu, Jakob Geiges, Nan Liu, Thorsten Schlachter, Veit Hagenmeyer · 27 February 2026

  In energy system analysis, coupling models with mismatched spatial resolutions is a significant challenge. A common solution is assigning weights to high-resolution geographic units for aggregation, but traditional models are limited by using only a single geospatial attribute. This paper presents a…

• Data-driven Bi-level Optimization of Thermal Power Systems with embedded Artificial Neural Networks

  Talha Ansar, Muhammad Mujtaba Abbas, Ramit Debnath, Vivek Dua, Waqar Muhammad Ashraf · 17 February 2026

  Industrial thermal power systems have coupled performance variables with hierarchical order of importance, making their simultaneous optimization computationally challenging or infeasible. This barrier limits the integrated and computationally scaleable operation optimization of industrial thermal p…

• Representation Learning Enhanced Deep Reinforcement Learning for Optimal Operation of Hydrogen-based Multi-Energy Systems

  Zhenyu Pu, Yu Yang, Lun Yang, Qing-Shan Jia, Xiaohong Guan, Costas J. Spanos · 3 February 2026

  Hydrogen-based multi-energy systems (HMES) have emerged as a promising low-carbon and energy-efficient solution, as it can enable the coordinated operation of electricity, heating and cooling supply and demand to enhance operational flexibility, improve overall energy efficiency, and increase the sh…

• Techno-economic optimization of a heat-pipe microreactor, part I: theory and cost optimization

  Paul Seurin, Dean Price, Luis Nunez · 19 December 2025

  Microreactors, particularly heat-pipe microreactors (HPMRs), are compact, transportable, self-regulated power systems well-suited for access-challenged remote areas where costly fossil fuels dominate. However, they suffer from diseconomies of scale, and their financial viability remains unconvincing…