This paper presents a reinforcement learning (RL) approach for evaluating and controlling residential building flexibility in response to dynamic electricity pricing and intermit-tent grid requests. To address the challenge of sparse rewards and fluctuating states, a curriculum learning (CL) strategy is integrated with reward shaping, enabling a model-free RL agent to learn complex, multi-objective control behavior. A custom Gymnasium-EnergyPlus environment is developed to simulate thermal dynamics, price signals, and USEF-aligned flexibility requests. The agent is trained through a three-stage curriculum, progressing from comfort maintenance to cost minimization, and finally, to flexibility response. Results show that CL significantly improves training stability and responsiveness compared to a non-curriculum approach, with agents able to balance comfort, cost efficiency, and flexibility provision under varying conditions.

This study conducts a detailed techno-economic analysis of photovoltaic-thermal (PVT) collectors integrated with ground-source heat pumps (GSHPs) for land-constrained multi-family buildings in cold climates. Using dynamic TRNSYS simulations, the system is designed around an undersized borehole field and incorporates realistic electricity pricing models, including dynamic spot prices and capacity-based tariffs, and peak demand considerations. A stepwise analysis evaluates five PVT absorber types, array sizes, layouts, and control strategies. The most cost-effective design combines 60 m² of unglazed finned collectors, pre-borehole layout, and 80 l/h-m² fixed flow, achieving a seasonal performance factor above 2.7 and a minimum total life-cycle cost (TLCC) of €451 k€. Among all design variables, array size has the greatest impact on system performance and cost, with flow rate being the next most critical factor. Relative to a stand-alone GSHP, the hybrid system lowers peak electric load by 10 % and reduces total life-cycle cost by 4–23 % when benchmarked against alternative heating configurations including district heating, air-source heat pump, and PV-assisted GSHP. Scenario analyses show that electricity pricing structure and volatility significantly influence optimal collector sizing, with higher electricity prices favoring larger PVT array sizes. The results provide actionable design guidelines for researchers and practitioners seeking to improve performance and cost-effectiveness of heat pump systems, and to support their broader deployment in space- and grid-constrained urban environments.

The worldwide growth of 5G networks is increasing energy consumption in the technology sector, turning telecommunication base stations (TBS) into significant sources of low-temperature waste heat. This presents a major, yet largely untapped, opportunity to recover this energy, especially in cities where the heat could be recovered to produce domestic hot water (DHW). The primary challenge lies in upgrading this low-temperature (30–45 °C) heat to the 55–60 °C required for DHW systems. This paper presents the design, prototyping, and comprehensive experimental evaluation of a novel solution: a compact "heat pump door" designed for direct integration into TBS cabinets. The prototype employs a miniaturized vapor-compression cycle using the low-GWP natural refrigerant R600a (isobutane) with a charge under 150 g. A systematic experimental campaign was conducted in the laboratory with a dedicated test rig to quantify the system's performance under emulated real-world conditions. The results demonstrate the system's viability, successfully producing DHW at 55 °C with a heating COP of 3.1 and a heat recovery ratio (HRR) reaching up to 85%. A detailed experimental investigation has also been conducted into key parameters like compressor speed, fan power, and internal airflow management to evaluate the system's performance for evaluating the optimal operating strategies. This work provides the first experimental validation of novel miniaturized heat pump prototype. This technology offers a scalable solution through mass deployment across widespread TBS waste heat sources, contributing to the decarbonization of both the telecommunication and building sectors.

Industrial high temperature heat pump (IHTHP) offers an efficient solution for industrial thermal demands which account for a large proportion of total energy consumption. Since it is in early deployment, optimizing its utilization and improving its economic and environmental attractiveness are essential. To address these issues, pinch analysis, techno-economic analysis, environmental impact assessment, and sensitivity analysis are conducted. Results indicate that switching IHTHP from single heating to combined cooling and heating operating mode could improve the system's efficiency by 21.3 %, achieving considerable electricity savings at regional or national scale. Moderate carbon tax (CT) proves most effective in establishing the economic advantage of IHTHP with minimal additional improvements. Prioritizing promoting IHTHP in specific regions offers immediate economic benefit, due to existing favorable conditions about industrial resources, electricity price, and electricity CO2 emission in these areas. Reducing electricity emission or increasing unit efficiency would position IHTHP as the most environmentally-friendly choice. Without relying on national electricity emission reduction, establishing localized hybrid PV-grid system in industrial park with adequate PV share (RPV) provides a short-term realizable environmental advantage for IHTHP. Higher RPV, moderate CT, and subsidies may be required to ensure the economic competitiveness of this scheme. Finally, sensitivity analysis reveals that IHTHP's efficiency is most crucial for its economic advantage while the electricity cleanliness primarily determines its environmental benefit. This work proposes practical and short-term achievable strategies to enhance the competitiveness of IHTHP for broader application, supporting the sustainable transition of industry.

There has been an increase in solar photovoltaic/thermal (PVT) research in recent years, however, relatively little research has been dedicated to the design of PVT collectors as part of a heat pump system. This study aims to identify cost-effective design strategies for a PVT collector absorber to be integrated into a ground source heat pump (GSHP) circuit and enhance heat capture from the ambient air. The effect of geometry, material selection, fins, and forced convection on the overall U-value and thermal performance coefficients of the collector, are evaluated under steady state conditions using numerical modelling tool COMSOL Multiphysics. An annual mean fluid temperature profile is derived from a PVT + GSHP system simulation to calculate the annual thermal energy output, energy-to-mass and energy-to-cost ratios of the absorbers. Results show that the addition of fins and forced convection have the greatest influence on collector thermal performance, while material selection has a negligible impact. The corrugated, polycarbonate absorber with 10 mm fins, generates 55 % more thermal energy (1,464 kWhth/m2-yr) than the reference metallic sheet and tube collector at an energy-to-cost ratio 1/10th the reference, suggesting good market potential. An exergy analysis reveals that thermal exergy contributes 20 % to 50 % of the total exergy output, highlighting that low-temperature PVT designs exhibiting a smaller thermal share relative to electrical exergy compared to their higher temperature counterparts. This work's novelty and contribution comes from PVT design specifically for GSHP integration, examined at component and system levels, from both technical and economic perspectives.

The temperature difference between evaporating and condensing side of cascade high temperature heat pump (CHTHP) can be large. However, its heating coefficient of performance (COP) is not ideal due to the performance attenuation brought by large temperature lift. If both heating and cooling sides can be utilized, the whole COP will be greatly improved. In this work, a CHTHP prototype is established, along with three application scenarios, specifically dairy processing, liquor processing, and deep dehumidification, which simultaneously have cooling and heating demands consistent with the operating range of the unit. The experimental results indicate that the CHTHP prototype can supply cooling as low as 2 °C and heating up to 120 °C with comprehensive COP over 2.58, being more than 45.8 % higher than single heating system, showing impressive performance in combined cooling and heating (CCH) for industrial processes. Through the joint investigation of heat pump and application scenarios, it is revealed that the comprehensive performance of CHTHP can surpass conventional approach of using two separate heat pumps to provide cooling and heating respectively when the ratio of heating to cooling demand is high. In addition, the performance of CCH system can be further enhanced by optimizing corresponding process parameters in different scenarios. Based on the excellent performance of CHTHP in CCH and its practical industrial applications, this work will maximize the effectiveness of high temperature heat pump in the electrificaiton of industrial thermal energy consumption.

Energy communities are emerging as key enablers of the energy transition, facilitating greater electrification and providing essential flexibility services in urban energy systems. This study explores the economic performance of energy communities in Mediterranean cities, focusing on integrating solar generation with a battery energy storage system, electric vehicles, air-source heat pumps, and electric water heaters. Using a mathematical optimisation model applied to a case study in Catarroja, Spain, the research evaluates the techno-economic interactions of these technologies under different economic and regulatory conditions. The results highlight that combining solar generation with flexible technologies enhances economic viability. At the same time, the level of electrification plays a crucial role in determining the profitability of battery storage and photovoltaic systems. These findings underscore the importance of flexibility in designing and operating energy communities, offering valuable insights for policymakers and stakeholders aiming to optimise collective energy systems and support a sustainable transition.

PARMENIDES addresses challenges in the energy system by providing interoperable solutions that harness the potential of Hybrid Energy Storage Systems.A key innovation is the PARMENIDES Energy Community Ontology streamlining energy community operations through optimized energy flows and local energy maximization.The project introduces an Energy Management System for Hybrid Energy Storage Systems, utilizing ontology as a knowledge base and for extended information inference.Diverse PARMENIDES use cases cover scenarios ranging from passive energy community participation to fully automated optimization.These use cases vary in automation levels, optimization features, and flexibility strategies.The developed Information and Communication Technology architecture ensures interoperability, reliability, and security.Components include a Grid Capacity System, Grid Monitoring Devices and Smart Meters, an Information and Configuration System as a central repository for knowledge and data and an Energy Management System.Specific instantiations of the architecture will be implemented in the Austrian and Swedish pilots.

Indirect evaporative chiller (IEC) can produce chilled water below the wet-bulb temperature of outdoor air. To evaluate the potential of applying indirect evaporative chillers for covering the high indoor sensible cooling loads in commercial buildings of Northern European countries, a case study based on a real commercial building in Stockholm was carried out assuming renovation of the existing air-conditioning system by replacing district cooling with an indirect evaporative chiller as cooling source. Numerical models were built for the indirect evaporative chiller as well as for the entire space cooling system, and techno-economic performance evaluation as well as sensitivity analyses were conducted with a validated numerical model to comprehensively evaluate renovation benefits. The simulation results show that, an indirect evaporative chiller fulfilling 80 % of the total sensible cooling load of the design outdoor condition with a dry-bulb outdoor air temperature of 26 °C and a relative humidity of 45 %, can produce chilled water below the wet-bulb outdoor air temperature when the relative humidity is lower than 0.4 for hours in July of year 2015 and 2018. Sensitivity analyses show that reducing the supply air flow rate of the ventilation system from the default setpoint of 1.2 L/(m2·s) to the minimum hygienically required level of 0.35 L/(m2·s) would double the seasonal energy efficiency rating of the air-conditioning system from 6.3 to 12.8. Compared to the original district cooling-based system, the operational expenditure of the renovated system can be saved for optimally 54 k SEK, justifying a capital expenditure of 588 k SEK assuming operation of 15 years. The case study shows that indirect evaporative chiller can potentially be applied for commercial buildings under the and climatic and market context of Sweden, providing an alternative cooling solution for similar applications.

Modern heat pump systems often come equipped with sensors, enabling the collection of substantial operational data. However, many residential heat pumps installed in preceding decades lack pressure sensors, energy meters, or mass flow meters, primarily due to financial limitations. As a result of these incomplete measurements, the direct analysis of the heat pump system’s performance or the leveraging of the amassed data for inventive applications like prognosticating energy consumption, detecting and diagnosing faults, and implementing intelligent control becomes challenging.In existing literature, the focus of soft sensors in heat pump systems has been on estimating a single parameter. This approach, however, overlooks the reality that multiple parameters are often missing due to the lack of all-encompassing physical meters and sensors. Furthermore, current soft sensor models are typically developed using inputs such as compressor power consumption, pressures, evaporation, and condensation temperatures. These inputs, unfortunately, tend to be inaccessible within existing heat pump monitoring installations.In practice, it is a challenge to compensate for several critical measurements, encompassing mass flow rate, pressures, power consumption, and heating capacity, by using only commonly available sensors such as secondary loop temperatures and compressor frequency are available. Currently, there is a notable gap in research concerning this practical issue.To address the problems associated with inadequate measurements, this study presents the development and validation of soft sensors based on a data-driven approach, which can compensate for the parameters often unavailable with data collected from a limited number of commonly used sensors. Each component model employs a multivariate polynomial regression that calculates the evaporation temperature, condensation temperature, mass flow rate, and compressor power consumption, respectively. Subsequently, we present an integrated heat pump model that combines these component models into a comprehensive heat pump model.Finally, we validate the data-driven model against field test installations, demonstrating its accuracy with a relative root mean squared error (RRMSE) ranging from 10% to 20%.