To unlock emissions reduction alongside demand-side flexibility in industry, steam-generating heat pumps must ensure a continuous and steady steam supply to users during power modulation events. This study aims to understand and characterise the steam supply dynamics and off-design performance of various heat pump control strategies that could be used to enact demand-side flexibility. Dynamic simulations of a 5 MWth steam-generating heat pump reveal a significantly different power modulation range, system efficiency impact and delivered steam fluctuations of the tested control strategies. Coupling a downstream steam accumulator is shown to enable demand‑response without compromising the continuity of steam. New accumulator design charts and sizing correction factors are derived to ensure this is the case, which traditional steady‑state analyses fail to do. Through a combination of control strategies, an overall 48 to 164 % power modulation range could be spanned by the heat pump. Variable rotational speed control enables turndown to 48 % power absorption and up to 11 % higher COP compared to rated conditions, and variable inlet guide vanes yield up to 164 % power absorption with COP reductions below 13 % from rated values. Development of compressor technology with improved surge and choke characteristics, as well as co-design of steam-generating heat pumps and thermal storage, are follow-up research directions towards promoting flexibility from the integrated system considered.

This work explores and compares control strategies to enable off-design operation of grid-scale pumped thermal energy storage (PTES) systems. Four relevant control strategies are identified to provide this kind of operational flexibility: inventory control, variable speed operation, flow control with bypass valves, and variable turbomachine geometry. These are applied to a comprehensive system model of a 100MW, 10h commercial PTES concept. The system model is characterised by a dynamic consideration of the thermal reservoirs, off-design performance models for all components and a more detailed description of electrical components. Each control strategy’s operating range and its impact on component performance, system performance, and electrical energy capacity are quantified. The findings indicate that none of the strategies cover the entire operating range. Inventory control is confirmed as the most promising strategy, covering 61.4% of the theoretical nominal operating range, without significant performance loss. Variable speed covers 38.6% of the nominal operating range and shows performance drops in off-design. Bypassing the turbine enables limited flexibility on the charging side and covers the lowest operating range (22.1%). Bypass control can only modulate the discharging power by incurring high losses. Variable compressor inlet guide vanes have a similar effect to variable speed, covering 30.7% of the operating range, but at a much lower cost. Variable speed, turbine bypass, and variable compressor inlet guide vanes significantly alter the cycle’s specific work; this, in turn, causes temperature fluctuations in the liquid storage tanks. Temperature fluctuations in one cycle can affect subsequent cycles, making those control options less attractive as stand-alone options.

Accurate state of charge (SoC) estimation in latent thermal energy storage (latent TES) systems is critical for optimizing renewable energy integration and ensuring efficient energy storage operation. Traditional physics-based methods, though accurate, were computationally intensive and required complex parameter calibration, limiting their applicability for real-time applications. This study introduced an artificial intelligence (AI) framework for real-time SoC estimation in shell-and-tube latent TES systems, integrating long short-term memory recurrent neural networks (LSTM-RNN) and extreme gradient boosting (XGBoost) through an optimised weighted ensemble (0.3 LSTM-RNN, 0.7 XGBoost), with weights determined using grid search. The framework was trained and validated on 605 charging and discharging profiles from a previously experimentally validated model, significantly expanding prior studies. The dataset covered a broad range of operating conditions, including charging (140-150 degrees C) and discharging (100-110 degrees C) cycles with mass flow rates between 0.8 and 1.2 kg/s. The ensemble model achieved superior accuracy (RMSE: 1.7%, MAE: 0.9%, R-2 >99.7% for charging; RMSE: 1.4%, MAE: 0.8%, R-2 >99.8% for discharging) compared to individual LSTM-RNN and XGBoost models, while reducing computational costs by 80%, enabling inference within 2.6 ms per sample. This significant reduction in computational requirements transforms SoC estimation from a computational bottleneck into an enabling technology for real-time control integration, allowing direct deployment in industrial control systems where traditional physics-based methods remain impractical due to their computational demands.

The large-scale integration of renewable electricity is reshaping global energy systems, accelerating the transition away from fossil fuels while introducing challenges linked to variability and system balancing. Addressing these challenges requires advanced energy conversion and storage technologies that can balance supply and demand across multiple energy vectors. This paper reviews the role of thermo-mechanical energy storage (TMES) in enabling sector coupling (SC) - the coordinated integration of electricity, heating, and cooling—as a strategy to improve system flexibility and efficiency. In addition to TMES, partial configurations such as high-temperature heat pumps and organic Rankine cycles coupled with thermal energy storage (TES) are examined. Integrated systems are categorized based on their charging, storage, and discharging components, and their applicability across various temperature ranges and end-use sectors is discussed. The review finds that power-to-heat solutions, exceptionally resistive heating combined with TES, are the most mature, with several commercial-scale deployments already operating in industrial and district heating contexts. By contrast, power-to-heat-to-power and heat-to-power technologies remain at the prototype or demonstration stage, but offer strong potential for multi-energy provision and increased system flexibility. Research gaps are identified in underexplored areas, such as cold integration, simultaneous cogeneration, and applications requiring extremely high or extremely low temperatures. Beyond the technology overview, the paper introduces a novel Key Performance Indicator (KPI) framework to evaluate the effectiveness of TMES for SC. Unlike traditional round-trip efficiency, which overlooks non-electric outputs, the proposed KPI framework accounts for heating and cooling services, enabling fairer comparison with conventional benchmarks such as combined heat and power units, electrochemical batteries, or stand-alone heat pumps. Results show that while TMES underperform against Li-ion batteries in civil applications, they outperform fossil-based CHP plants in industrial contexts, highlighting their competitive advantage in large-scale, multi-vector energy hubs. By combining technology categorization with a new performance assessment tool, this work aims to support future research, demonstration, and deployment of integrated energy conversion and storage solutions in both civil and industrial sectors.

Decarbonising the civil heating sector increasingly relies on the electrification of thermal systems, primarily through the use of heat pumps. The increased use of electricity as the unique energy carrier stresses the power grid, leading to increasing demand for thermal energy storage. Demand-Side Management strategies reduce the mismatch between energy availability and demand. In this paper, the influence of operation scheduling (duration of load shifting and intra-operation break) and borehole charge through waste heat on Ground-Source Heat Pump performance as dispatchable thermal loads are investigated via a numerical model. Results show the DSM strategies both provide flexibility services at intra-day frequencies and enhancement of the performance in terms of electricity consumption and ground temperature stability at the expense of increased storage volumes requirement to ensure self-consumption capacity.

Steam networks are widely used for industrial heat supply. High-temperature heat pumps (HTHPs) are an increasingly attractive low-emission solution to traditional steam generation, which could also improve the operational efficiency and energy demand flexibility of industrial processes. This work characterises 4-bar steam supply via HTHPs and aims to assess how variations in power input that result from flexible HTHP operation may affect steam flow and temperature, both with and without a downstream steam accumulator (SA). First, steady-state modelling is used for system design. Then, dynamic component models are developed and used to simulate the system response to HTHP power input variations. The performance of different SA integration layouts and sizes is evaluated. Results demonstrate that steam supply fluctuations closely follow changes in HTHP operation. A downstream SA is shown to mitigate these variations to an extent that depends on its capacity. Practical SA sizing recommendations are derived, which allow for the containment of steam supply fluctuations within acceptability. By providing a basis for evaluating the financial viability of flexible HTHP operation for steam provision, the results support clean technology’s development and uptake in industrial steam and district heating networks.

This work investigates new enhancement pathways for thermochemical energy storage reactors by the concurrent intensification of heat and mass transfer. The heat transfer from the reactive bed is maximized through the generation of optimal fin designs, while enhanced reactant transfer is ensured by the optimal design of flow channels. Three optimization routes are thus proposed and investigated: (i) heat transfer maximization, (ii) mass transfer maximization, and (iii) concurrent heat and mass transfer maximization. Topology optimization is adopted as systematic design tool to explore each of these strategies. The results highlight the most suitable optimization route to depend on the reactive bed properties and operating conditions, with the concurrent heat and mass transfer intensification route recommended in the instance of poor reactive bed permeability and low-pressure regimes, for which final reaction advancement increases up to 70.5% were predicted compared to designs optimized for heat transfer solely. Ultimately, the design approach and results presented in this work establish new enhancement pathways for the effective configuration of thermochemical energy storage reactors, significantly contributing to the advancement of core knowledge in optimizing their performance.

This research investigates the novel concept of pillow plate latent heat thermal energy storage (PP-LHTES) for storing process heat and/or waste heat at medium temperature, up to around 200 degrees C, and with a focus on mobile TES applications, such those in the maritime sector. The work introduces a novel methodology that combines computational fluid dynamics (CFD) with reduced-order modelling (ROM) techniques to evaluate the thermoeconomic performance of PP-LHTES at the prototype scale (similar to 102 kWh) and predict its potential at full scale (similar to MWh). These are the key aspects of novelty of the research. The study focuses on the impact of key technical factors, including the selection and thermophysical properties of the phase change material (PCM), its melting temperature and latent heat of fusion, the operating temperature, and the flow rate of the heat transfer fluid. Furthermore, the cost-effectiveness of PP-LHTES was examined by evaluating nine design parameters, such as the number of pillow plates and the cost per unit of PCM. Findings indicate that PP-LHTES appear to have a competitive advantage in volumetric energy storage density at the system level (similar to 89 kWh/m(3)), making it more compact than other LHTES solutions (similar to 53 kWh/m(3)) with a similar specific capital cost (similar to 200 (sic)/kWh). The PP-LHTES module weighs 500 kg, occupies 0.25 m(3), and provides an energy storage capacity of 17 to 22 kWh. The scalability of the design is investigated and results emphasize the its versatility. The mass-averaged volumetric energy storage density is comparable to existing LHTES systems (similar to 50 kWh/t). This is due to the distinctive design of pillow plate heat exchangers, which integrate heat transfer fluid channels and extended heat transfer surfaces into a compact structure. This design increases energy density at the system level, reduces the overall footprint, and enhances the feasibility of deploying TES devices in end-user applications.

This paper investigates the novel class of pillow-plate latent heat thermal energy storage (PP-LHTES) systems based on the combined use of phase change materials (PCM) of pillow plate heat exchanger technology. Despite recent studies highlighting the promising thermal and economic performance of PP-LHTES systems, their investigation remains limited. In particular, there is a lack of comprehensive thermo-economic analyses to support informed decision-making, especially during the design phase. To address this gap, this paper systematically explores the thermo-fluid and economic performance of PP-LHTES systems by analyzing their design space. An innovative procedure for the optimal design of these devices was developed. The proposed methodology consists of two models: a 1D analytical discretized stationary model, called the design model, and a 1D analytical discretized dynamic model, named the dynamic model. The former is used to determine the design parameters and costs, while the latter is used to validate the designed system under dynamic conditions. The two models are validated against relevant experimental studies taken from the literature and show good performances with errors in the order of 10 % for the design model and 2 % for the dynamic model. A total of 27 configurations were evaluated for potential industrial applications, considering energy storage capacities between 5 and 25 MWh and heat transfer rates ranging from 1 to 5 MW. Representative case studies and operating maps highlight the effects of inlet and outlet temperatures and PCM properties on performance. The layer thickness of the storage material and the channel length depend on discharge time, while the channel count remains constant at a fixed heat transfer rate. The heat exchange area, however, varies with energy storage capacity and heat transfer rate. Additionally, cost maps are systematically examined in terms of energy capacity cost ($/kWh) and power capacity cost ($/kW), highlighting the critical relationship between key PP-LHTES design parameters and the overall cost-competitiveness of the technology. Systems designed for higher temperature differentials (Delta T) demonstrated superior thermal and economic performance, reducing the required heat exchange area and lowering both energy and power capacity costs. An exemplar case study is developed, starting from a reference case in the literature, to illustrate the effectiveness of the proposed methodology. This case study outlines the process of gathering input parameters and demonstrates how the outputs of the two models should be processed to achieve the final design. Ultimately, PP-LHTES emerges as a promising and viable solution for industrial applications at the medium and large scales, with energy capacity costs ranging from 30 to $90 per kWh.

This review investigates the role of artificial intelligence in predicting the state of charge for thermal energy storage devices. Traditional estimation methods often struggled with complex dynamics and large-scale data, showing accuracy limitations of 5–10 % under dynamic conditions. Artificial intelligence significantly improved accuracy, efficiency, and scalability, achieving 98 % prediction accuracy in electrical storage, a 30 % efficiency gain in thermal energy storage, a 77 % reduction in power fluctuations for mechanical storage, and a 40 % efficiency boost in chemical storage. The review analysed various artificial intelligence methodologies applied to thermal energy storage, including neural networks, support vector machines, reinforcement learning, and hybrid models, which reduced computational time by up to 60 %. Integrating artificial intelligence with the internet of things and big data enabled real-time analysis of thermal energy storage systems, reducing monitoring latency by 70 %. However, challenges persisted regarding data integrity, integration costs, and ethical concerns. The study also revealed implementation gaps within thermal storage technologies, with artificial intelligence adoption at 15 % in latent thermal energy storage compared to other energy systems like electrical storage where adoption reaches 85 %. Future research should focus on explainable artificial intelligence models, robust data quality frameworks, and standardized integration protocols, specifically tailored for the unique challenges of thermal energy storage including sensible, latent, and thermochemical systems. This review highlights the transformative impact of artificial intelligence on state of charge estimation in thermal energy storage systems, paving the way for more efficient and reliable energy management strategies.

This study focusing on Pumped Thermal Energy Storage (PTES), specifically Thermally Integrated PTES (TI-PTES) as attractive and novel solution centred around combination of power-to-heat-to-power and thermal energy storage. The research and novelty of the work lies in the proposal and application systematic framework for early-stage design decisions regarding key design parameters of TI-PTES system. In particular the work specializes on TI-PTES comprising a Heat Pump (HP) with an Electric Heater (EH) for power-to-heat and an Organic Rankine Cycle (ORC) as the Heat- to-Power technology to maximize economic and environmental benefits. Both the cycles consider R1233zd(E) as working fluid with attractive future applicability and operating temperatures up to similar to 210 degrees C - hence within reach of combination of HP with EH and, on discharge, of ORC. Thus the timelines and technological relevance of the present work. However, the development and deployment of a competitive such TI-PTES solutions necessitates combined decisions regarding the technical design parameters across all key sub-systems (HTHP, EH, ORC, TES) as well as regarding the economic competitiveness of TI-PTES system as a whole. Little work has been done in this area; therefore, this paper proposes and applies a techno-economic decision-making framework to guide the TI-PTES selection toward feasible applications. The proposed framework is deliberately aimed at supporting early-stage design decision and exploration of effect of key HP, ORC, TES parameters prior to detailed thermodynamic analysis. Hence the novelty of this work compared with existing literature. The proposed framework is implemented and tested to investigate a case study of 5MW/20MWh TI-PTES system which could find application in industrial energy parks that might be in need of both energy flexibility (energy storage) and energy efficiency (waste heat upgrade/recovery) simultaneously (EES) software. The results indicate that the TI-PTES baseline case achieves a Round Trip Efficiency (RTE) of around 44%. Furthermore, the findings highlight that minimizing the temperature lift during the charge cycle while maximizing difference between hot and cold reservoirs during the discharge cycle significantly increases the RTE. Additionally, the performance of turbomachinery in the HP and ORC is crucial for overall system efficiency and economic viability. Instead, The uses of the EH permits to achieve higher temperature of the stored heat, in comparison with the only use of the HP, the latter assumed to operate up to 130 degrees C. Ultimately the results support that the proposed TI-PTES configuration appears to be an interesting option for those applications that require electricity and thermal energy at medium temperatures. From economic stand point, The Levelized Cost of Energy results to be around 0.14 _/kWh, considering 20 years of life span of the system. In summary, the study emphasizes the importance of a multi- criteria selection of TI-PTES technological parameters to meet industrial thermal and electrical demands and achieve economic profitability. Furthermore, this study contributes to systematic decision-making in the rational design and deployment of TI-PTES, aiming to maximize decarbonization benefits in industrial sectors and enhance the potential and viability of such integrated systems.

This study addresses the need for heat transfer intensification in closed thermochemical energy storage reactors using topology optimization as a design approach. We introduce a novel topology optimization framework to simultaneously optimize fins geometry and amount of enhancer material while meeting specific discharge time, bed size, and bed porosity requirements. The proposed topology optimization framework is thoroughly tested by optimally designing innovative fin structures in a reference thermochemical storage reactor aimed at heat storage in industrial applications and operated with Strontium Bromide in the range 150-250 degrees C. The generated designs show performance improvement up to +286% compared to state-of-the-art designs. Our findings also indicate that the optimal amount of enhancer material varies significantly; large bed sizes with high packing factors maximize reactor energy density while highly packed reactive beds provide a larger amount of energy in fixed discharge times compared to less packed reactive beds. Finally, the benefits and limitations of the proposed topological optimization approach, as well as the extent to which the optimal designs found are generally applicable are thoroughly discussed to provide guidelines for configuring high-performing closed system thermochemical energy storage reactors.

The growing intensity of international commerce and the high share of total global greenhouse gas emissions by the maritime sector have motivated the implementation of regulations by the International Maritime Organisation to curtail vessel emissions. In this context, waste heat recovery (WHR) is an effective way to improve ship energy efficiency, lower amounts of wasted energy rejection to the environment, and therefore ultimately curb green-house gas emissions. Presently, there exists a heterogeneity within the body of literature concerning WHR technologies for on-board applications, study scope and results, complicating the interpretation and cross comparison of the outcomes. Sporadic attempts have been made to review and systematise this landscape, leaving some key areas uncovered. Therefore, the present article aims at filling these gaps by providing and holistic review of WHR technologies development and on-board applications. Further, the energy systems and available waste heat characteristics in large vessel types are overviewed, before both existing and developmental on-board waste heat recovery technologies for maritime applications are reviewed. Emphasis is placed on the performance of these technologies within the broader on-board energy system. Common key performance indicators are drawn from existing systems, experimental prototypes, and simulations, to quantitatively compare the different technologies. This review indicates that a wide range of technological options for embedding waste heat recovery in on-board energy systems are emerging. In particular, traditional turbocompounding is already fully implemented within the marine waste heat recovery (WHR) context. Conversely, ORC systems and absorption refrigeration systems have not yet been suitably adapted for marine applications due to a lack of research and prototypes, despite their deployment in conventional WHR contexts. Other technologies, such as thermal energy storage devices, hybrid refrigeration systems, isobaric expansion engines, Kalina Cycles, and adsorption desalination and cooling systems, are still at the research and development stage, while thermo-electric generation systems continue to incur high deployment costs. The development of research on these innovative technologies, the reduction of their cost and their synergistic integration could lead to significant improvements inengine fuel efficiency and emissions reduction, especially when coupled with existing waste heat recovery measures.

This paper investigates waste heat (WH) valorisation on maritime vessels from a systemic perspective. It aims to demonstrate how a set of innovative waste heat recovery (WHR) technologies can synergistically work together to valorise waste heat in multiple ways. It proposes and develops a dedicated techno-economic analysis framework and model, surpassing previous literature that focused on individual technologies or specific combinations. Employing a Mixed Integer Linear Programming (MILP) approach, this study evaluates the dynamic and flexible operation of the WHR system throughout the round-trip journey of a vessel. Identifying the most profitable WHR system layout, determining the capacity of technologies, optimising the interconnections between technologies, and establishing strategic WH dispatching are all among the key objectives of the study. An average-scale vessel with a 36 MW diesel engine, is selected for this study which involves a 17-day journey with multiple stops in Northern Europe. The vessel adequately represents the complexity of onboard energy systems in terms of types and variability of demands, as well as WH availability. The proposed WHR system, which is tailored for the selected vessel, integrates three active technologies: an isobaric expansion engine (IEE) to contribute to mechanical power demand, a sorption system for providing cooling, and an advanced Organic Rankine Cycle (ORC) for trigeneration of power, heating, and cooling. All technologies are supported by the passive WHR technology of Thermal Energy Storage (TES). The results show that deployment of the optimised WHR system onboard the selected vessel enhances energy efficiency by 5 to 7.5 percentage points and reduces fuel consumption by 13%. The study also explores economic key performance indicators (KPIs), such as the Internal Rate of Return (IRR) which is found at about 15%, clearly evidencing a compelling solution to ship owners. Additionally, the discussion includes a detailed analysis of the contribution of individual technologies in covering onboard demands, as well as their synergistic interactions. This work clarifies the role, value, and benefit of WHR technologies onboard, advancing the understanding from individual WH recovery interventions to a system-level approach. This is especially valuable in practice, considering its adaptability across various vessel types within the global fleet.

Reactive metals are emerging as potential zero-carbon energy carriers. The recent increase in fundamental knowledge on this topic calls for an assessment of the actual potential of the different metals proposed to fulfil this role on a commercial scale. In the present study, a Multi-Criteria Decision Analysis (MCDA) is performed for iron, aluminium, magnesium and silicon. The nine Selection Criteria (SC) cover the entire metal energy cycle and allow for a practical comparison of the metal candidates. A particular attention was given to the technology readiness of the key processes (energy charge through metal oxide reduction, and energy discharge through metal-air combustion). The study suggests that despite better intrinsic characteristics of the other metals, the much greater availability of iron makes it the most suitable to become a global zero-carbon energy carrier on a short term, especially for stationary applications. For mobile applications however, the energy densities of aluminium make it a better alternative. Our review gives a practical overview of the current knowledge on the metals cycles, and discusses current major roadblocks, such as nanoparticle emissions during combustion, that should be the focus of future research.