Scientific publications
SCIENTIFIC PUBLICATIONS AND CONFERENCE PAPERS
Find all the scientific publications produced by WeForming partners, presenting the latest scientific findings of the project.
SCIENTIFIC PUBLICATION
Authors
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Abstract
Carnot Batteries (CBs) are a promising option for energy storage, acting as a buffer for the variability from renewables and enabling multi-energy integration and dispatch, converting electricity to heat and back to electricity. Although techno-economic studies report promising costs and high feasibility, especially when components from both cycles are shared in long-term storage, there are few prototypes, and the technology readiness level remains near 4. This paper presents a reversible Rankine-based CB designed for integration with an abandoned flooded mine. The system is under construction, being the largest machine of its type. A physics-based model was developed and validated against manufacturer data to assess performance under realistic constraints. The key focus is the role of auxiliaries and temperature-glide control. By actively modulating secondary-loop pump rotational speed, the Organic Rankine Cycle (ORC) achieves up to a 36 % increase in efficiency and the Heat Pump (HP) mode up to 20 % increase in relative efficiency to a constant-glide strategy. Highlighting that no single pair of glide settings is optimal across the full operating envelope, underscoring the need for adaptive control. Neglecting auxiliaries leads to substantial errors: a relative difference of 24 % in round-trip efficiency (RTE) can be achieved when auxiliaries are omitted, resulting in unrealistic performance values and, consequently, an unrealistic feasibility. With auxiliaries and constraints included, the modelled charge–discharge RTE ranges from 22.8 % to 34.7 %, lower than conventional storage but consistent with reported limits for CB technology. However, CBs can also supply industrial heat, reject heat to district heating networks, and/or deliver cooling, making RTE efficiency an incomplete metric for this technology. The analysis indicates that efficiency depends more on operating conditions than on component selection. This highlights that, for CBs connected to low-temperature storage, auxiliary components are decisive for performance. Achieving high efficiency requires water pumps with high part-load efficiency (including both pump and motor), refrigerant pumps capable of high efficiency at low net positive suction head, and the deployment of active control laws governing charge management and pump operation.
Published inApplied Energy Volume 404
Authors
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Abstract
Recently, there has been a surge of interest in novel concepts for jointly operating devices in urban areas in clusters, motivated by their potential to support decarbonization, enhance power system flexibility, and promote energy justice. Such clusters encompass multiple devices or buildings but operate on a smaller scale than cities. Examples include Renewable Energy Communities and Positive Energy Districts. These Novel District Concepts (NDCs) integrate interdisciplinary urban planning and social sciences terminology into the energy domain. However, these concepts’ precise definitions and practical implementation lack consistency, leading to conceptual ambiguities in the literature. The present paper reviews clustering approaches from both the energy domain and the urban planning and social sciences disciplines to analyze rules for defining device clusters. The findings reveal that while numerous papers claim novelty using Novel District Concepts terminology, many rely on established energy-domain methodologies, such as clustering techniques structured around electricity grid hierarchies. In contrast, clustering approaches from urban planning and social sciences, which employ spatial and social criteria, remain underutilized and lack systematic evaluation for energy system applications. The present paper’s key contribution lies in systematically identifying and differentiating clustering rules, establishing a robust foundation for subsequent cluster-based research, and ensuring methodological consistency. By integrating concepts from urban planning and social sciences with established energy-domain approaches, this paper delineates clear boundaries and grounds them contextually. The present paper’s structured methodology provides a comprehensive workflow for distinguishing diverse clustering rules, mitigating the risk of misapplied terminology, and facilitating future evaluations of their applicability to specific energy-system tasks.
Published in Energy Reports Volume 14
Authors
, ,
Abstract
To empower the citizens’ engagement in the low-carbon transition, European directives highlight the importance of the local energy-sharing concept. This can be achieved with renewable energy communities (REC), citizen energy communities (CEC), collective self-consumption (CSC), peer-to-peer trading, energy cooperatives, etc. To investigate the potential benefits of local energy sharing in Croatia, this research focused on financial analyses and return of investment calculation for local photovoltaic (PV) systems based on real load and PV measurement data. Due to a limited number of energy community projects in Croatia and poorly defined regulations, the goal was to provide insight into different types of possible community trading approaches: household collective-self consumption with joint investment in PV, an energy community with only business customers, and a household-business customer energy community. Comprehensive financial analyses are based on the existing regulatory framework in Croatia with two different net-metering approaches for final customers with the onsite PV generation. The results suggest the selection of the most beneficial net-metering approach for different types of communities: monthly net metering is more beneficial for household CSC and energy communities with only business customers, while 15 min net metering results in lower costs and shorter return of investment period for a household-business customer energy community. Moreover, CSC analyses are made based on static, annual, and monthly keys of repartition (KoR) for energy sharing. Analyses show that electricity bills differ under the proposed KoR due to diverse consumption profiles. Consumers with high monthly consumption have the highest electricity bill with static KoR due to equal distribution of produced energy between all community members, while with annual or monthly KoR their electricity bill significantly decreases because they are allocated more PV production. Several settlement options are proposed highlighting the need for more detailed regulation and suggesting some regulation changes that will lead to higher acceptance of energy communities and joint local investments, such as the deduction of RES incentives for shared energy. Furthermore, the analyses suggest that regulation should define how excess PV production is shared and renumerated after the application of KoR in the second stage. Even though the analyses demonstrate the Croatian case study, the results and conclusions can easily be translated to any European country without a clear and detailed regulatory framework for energy communities.
Published in Energy Volume 338, 30 November 2025
Authors
Tomislav Antić, Andrew Keane, Tomislav Capuder
Abstract
Hosting capacity (HC) and dynamic operating envelopes (DOEs), defined as dynamic, time-varying HC, are calculated using three-phase optimal power flow (OPF) formulations. Due to the computational complexity of such optimisation problems, HC and DOE are often calculated by introducing certain assumptions and approximations, including the linearised OPF formulation, which we implement in the Python-based tool ppOPF. Furthermore, we investigate how assumptions of the distributed energy resource (DER) connection phase impact the objective function value and computational time in calculating HC and DOE in distribution networks of different sizes. The results are not unambiguous and show that it is not possible to determine the optimal connection phase without introducing binary variables since, no matter the case study, the highest objective function values are calculated with mixed integer OPF formulations. The difference is especially visible in a real-world low-voltage network in which the difference between different scenarios is up to 14 MW in a single day. However, binary variables make the problem computationally complex and increase computational time to several hours in the DOE calculation, even when the optimality gap different from zero is set.
Published in Sustainable Energy, Grids and Networks journal
Authors
Nikolina Čović, Jochen L. Cremer, Hrvoje Pandžić
Abstract
Accelerated development of demand response service provision by the residential sector is crucial for reducing carbon-emissions in the power sector. Along with the infrastructure advancement, encouraging the end users to participate is crucial. End users highly value their privacy and control, and want to be included in the service design and decision-making process when creating the daily appliance operation schedules. Furthermore, unless they are financially or environmentally motivated, they are generally not prepared to sacrifice their comfort to help balance the power system. In this paper, we present an inverse-reinforcement-learning-based model that helps create the end users’ daily appliance schedules without asking them to explicitly state their needs and wishes. By using their past consumption data, the end consumers will implicitly participate in the creation of those decisions and will thus be motivated to continue participating in the provision of demand response services.
Published in Electric Power Systems Research journal
Authors
Angel Paredes, Jean-Francois Toubeau, Jose A. Aguado, Francois Vallee
Abstract
Battery Energy Storage Systems (BESSs) are particularly well-suited to deepen the decarbonisation of reserve markets, traditionally dominated by non-renewable generators. BESSs operators often rely on Predict-Then-Optimise (PTO) methods to participate in these markets, which focus on forecasting market conditions without directly considering the impact of subsequent decisions while training. Recently, learning models have evolved to incorporate decision outcomes during training, known as Decision Focused Learning (DFL) methodologies, which have the potential to increase market benefits. This paper introduces a DFL approach that integrates the decision-making process of BESSs when participating in reserve markets into the training of their predictive models. By expressing the optimization problem as a primal-dual mapping using the Karush–Kuhn–Tucker (KKT) conditions, the proposed DFL method enables the regressor to learn from the BESS’s decisions, refining its predictions based on observed outcomes, improving decision accuracy and market performance. Results show that the proposed DFL approach outperforms traditional PTO methods, with up to a 9.5% increase in profits for a case study based on the Belgian secondary reserve market, highlighting its effectiveness in managing the complexities of dynamic market conditions.
Authors
Johannes Galenzowski, Simon Waczowicz, Hüseyin Çakmak, Erfan Tajalli-Ardekani, Sebastian Beichter, Ömer Ekin, Ralf Mikut, Veit Hagenmeyer
Abstract
Recently, there has been a surge of interest in novel concepts for jointly operating devices in urban areas in clusters, motivated by their potential to support decarbonization, enhance power system flexibility, and promote energy justice. Such clusters encompass multiple devices or buildings but operate on a smaller scale than cities. Examples include Renewable Energy Communities and Positive Energy Districts. These Novel District Concepts (NDCs) integrate interdisciplinary urban planning and social sciences terminology into the energy domain. However, these concept’s precise definitions and practical implementation lack consistency, leading to conceptual ambiguities in the literature.
CONFERENCE PAPERS
Authors
Ángel Paredes and José A. Aguado (UMA)
Abstract
grid. Current business models for buildings often fail to address the role of buildings as flexibility providers to the grid
and other consumers. This paper presents the Performance-Linked Energy Storage Intelligence (PLESI) business model,
leveraging intelligent Grid-Forming Buildings (iGFBs) to improve energy management and economic performance.
We develop a mathematical model that incorporates flexible loads, renewable generation, thermal building loads, and
Battery Energy Storage Systems (BESS). Sensitivity analyses show that the internal rate of return increases with the
peak load-to-BESS power ratio. Besides, economies of scale arise when increasing the number of end-users, resulting in
savings up to 45% for optimal configurations.
Authors
Tomislav Antić, Tomislav Capuder
Abstract
Installing distributed energy resources (DERs) in low voltage networks is limited by distribution grid codes, often defining a conservative connection power threshold, especially in the case of a single-phase connection or by the network’s technical constraints. Calculating the maximum installed power in that way is called hosting capacity (HC). Traditional HC calculation presents an assessment of static connection limits, determined by the lowest or highest electricity demand, depending on whether export or import limits are calculated. In this paper, we calculate the available range of aggregated active power of DERs based on worst-case and base-case demand scenarios. The results suggest the potential grid code redefinition since the analysed network can accommodate additional DERs in the range of 300 and 500 kW, compared to the current grid code limits. When observing only the grid code limitations in the import limits analysis, the results show an unrealistically high integration of more than 750 kW DERs, which is even higher than the best-case scenario. In the worst-case scenario, no additional DERs can be installed due to the initial violation of the network’s constraints. Dynamic export and import limits are in the theoretical range of values, showing the benefit of the concept.
Presented at CIRED 2024 Vienna Workshop
Authors
Tomislav Antić, Tomislav Capuder
Abstract
In this paper, we analyse the potential of demand-side flexibility and the importance of considering higher-order harmonics in calculating distributed energy resources (DERs) hosting capacity in low voltage (LV) distribution networks. We step aside from traditional calculations, in which hosting capacity (HC) is assessed based on the worst-case scenario and calculate dynamic export and import limits, based on near real-time electricity consumption estimates. In the scenario without modelling higher-order harmonics, the results show that upward flexibility contributes to the increase of installed distributed generators since aggregated active power increases between 0.05 and 38%, depending on the case study. When import limits are calculated, dynamic HC (DHC) also increases due to the demand-side flexibility potential, with the impact even more significant than in the case of export. Introducing higher-order harmonics in the model leads to decreased DHC in the scenario in which export limits are calculated. The decrease happens not only because of the total harmonic distortion (THD) constraint but also due to the contribution of the higher-order harmonics to the root-mean-square (RMS) voltage value. When calculating dynamic import limits, harmonic voltages increase the RMS voltage magnitude and, that way, free up additional space for the DERs installation.
Presented at CIRED 2024 Vienna Workshop
Authors
Aitor Cendoya, Frederic Ransy, Vincent Lemort, Andres Hernandez, Pierre Dewallef, Pierre-Henri Gresse, Jacques Windeshausen
Abstract
Nowadays, most countries are striving to transition their energy matrices towards renewable sources. To achieve this goal, energy storage systems play a crucial role in compensating for the inherent intermittency ofrenewable sources. Buildings are among the largest consumers of primary energy, due to their heating demands. Consequently, integrating renewable energies into buildings is essential. This paper presents a pioneering approach that integrates renewable energy sources with a multi-energy system. This system powers a Heat Pump (HP) responsible for heating an abandoned mine flooded with water, producing electricity via a Carnot Battery (CB), and distributing heating and cooling through a district heating network (DHN).This study is conducted in a real case of an abandoned slate mine in Martelange, Belgium, where three different size caverns are employed to store energy: 800, 6840, and 80000 m cubed for hot (90 C) medium (50 C) and cold (5 C) water temperature, respectively. The system combines photovoltaic panels, an electrical battery, heat pumps, electrical resistance, and an Organic Rankine Cycle. This study highlights the potential of reusing abandoned mines as energy storage systems, which can benefit adjacent communities by integrating diverse energy demands within a single system. This generates new perspectives for investors and residents, enabling the possibility of connecting the system to the grid for energy arbitrage and balancing services.
Published in Purdue
Authors
David Wölfle, Hartmut Schmeck
Abstract
Energy management, in sense of computing optimized operation schedules for devices, will likely play a vital role in future carbon neutral energy systems, as it allows unlocking energy efficiency and flexibility potentials. However, energy management systems need to be applied at large scales to realize the desired effect, which clearly requires minimization of costs for setup and operation of the individual applications. In order to push the latter forward, we promote an approach to split the complex optimization algorithms employed by energy management systems into standardized components, which can be provided as a service with marginal costs at scale. In this work we contribute a practical example how such services can be implemented utilizing the Energy Service Generics framework, a software explicitly designed to allow scientists and practitioners to derive fully functional web services from forecasting or optimization algorithms. To this end the implementation of typical components of forecasting or optimization services for energy management applications is discussed based on functional source code listings of a simple photovoltaic (PV) power generation forecast service.
Published in ACM SIGEnergy Energy Informatics Review
Authors
Ángel Paredes, José A. Aguado, Philipp Fisch, Patrick Witte, Sebastian Theissen, Pedro Rodríguez
Abstract
The ever-increasing need for climate action motivates the development of new and flexible energy solutions that adapts to society’s modern energy requirements. The i-STENTORE project aims to pioneer innovative solutions for the widespread deployment of hybrid energy storage systems. This paper investigates the simultaneous provision of flexibility services and hydrogen production within a real-world Luxembourgish hybrid energy system demonstrator, using multi-objective optimisation. While previous research has focused on either flexibility services or hydrogen production individually, this study fills the gap of a comparative analysis of different scenarios that consider trade-offs between these two objectives. The research provides operational insights into strategies for maximising economic viability and sustainability by analysing aspects such as the levelised cost of hydrogen, energy, degradation, and the impact of the battery size. The results show the potential of this demonstrator to provide flexibility to the system without significantly impacting in the hydrogen production.
Published in 2024 IEEE 15th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
Authors
Ángel Paredes, José A. Aguado
Abstract
Addressing the imperative for climate action requires adaptable energy solutions. Leveraging distributed technology like Virtual Energy Storage Systems (VESSs), the i-STENTORE project aims to pioneer innovative solutions for the widespread deployment of energy storage systems. This paper explores the potential of VESSs to increase the revenue of different distributed renewable technologies in the Iberian Wholesale and manual Frequency Restoration Reserve (mFRR) markets. Research up to date has focused on several market integration aspect of VESSs, yet considering the intricancies of the Iberian market of these technologies remains unexplored. The research aims to provide real-world insights into the potential of VESSs to increase the revenue of these technologies by stacking different services in the Iberian market. The results will show the potential of this demonstrator to increase profits using the concept of VESS and several storage technologies into the Iberian market.
Published in 2024 IEEE 15th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
Authors
Aitor Cendoya F. University of Liège
