Purpose Load shedding and grid instability continue to pose a significant challenge for commercial buildings in West Africa. Various artificial intelligence–Heating, Ventilation and Air Conditioning (AI–HVAC) system algorithms show promise in improving energy efficiency across different models. However, its performance under load-shedding conditions in shopping malls remains understudied. This study assesses the resilience of AI-controlled systems under load-shedding conditions in shopping malls in Ghana. Design/methodology/approach A mixed quasi-experimental design was employed, integrating sensor data with simulation models and conducting interviews with HVAC professionals in Ghana’s shopping malls. AI-based control strategies, such as Model Predictive Control (MPC), Data-enabled Predictive Control (DeePC) and Reinforcement Learning (RL), were tested across the malls to assess their response times, thermal comfort and energy consumption. Findings The study found that RL achieved the lowest response latency, the highest energy consumption, the highest thermal comfort and the highest uptime (95.4%) compared with MPC and DeePC. Furthermore, DeePC established moderate performance across the indicators, while MPC reported the lowest values. Qualitative results indicate limited awareness of AI-based systems but a strong willingness to adopt them, given their expected benefits. Practical implications The RL–HVAC systems offer a viable solution for enhancing energy resilience during load shedding in shopping malls. Although beneficial, this requires shopping management readiness and professional training. Originality/value This critical performance of RL, along with other AI-based algorithms, in AI-controlled HVAC systems under unstable power in urban areas represents a new direction compared with MPC and DeePC functionalities in energy simulations in cold-climate regions.

Abstract The CO2/R1270 mixture is recognized for its environmental compatibility, with system pressure reduction and energy efficiency enhancement being simultaneously achieved. A novel CO2/R1270 heat pump system with internal heat exchanger (IHX) for electric vehicles is proposed. Comprehensive evaluation models incorporating economic and environmental metrics were developed, with comparative analysis conducted against positive temperature coefficient (PTC) heating systems. Performance analysis across three climatic zones (Harbin, Tianjin, Guangzhou) was systematically performed to assess geographical adaptability. The results demonstrate that Guangzhou's annual cooling energy consumption (253.8 kWh) was 2.39 times higher than Tianjin's, while its heating demand represented only 10.1% of Tianjin's. A latitudinal dependence was observed, with heating energy decreasing and cooling demand increasing proportionally to latitude reduction. The PTC system exhibited 80.74%, 80.65%, 80.7% and 82.13% higher emissions of PM10, PM2.5, SO2, and NOx respectively compared to the heat pump. The Total Equivalent Warming Impact (TEWI) was quantified to be fivefold greater in PTC systems. Superior economic performance was demonstrated by the cabin evaporator, while the compressor was identified as requiring cost-reduction optimization due to high capital investment. Additional improvement potential was recognized in the heat exchanger and gas cooler configurations.

This study presents a comprehensive thermal analysis, design, and optimization framework for electrothermal heating systems integrated into composite wing structures. Thermal behavior is first investigated using finite volume simulations conducted with a commercial solver. An in-house thermal solver is then developed based on the governing heat transfer equations and a second-order finite difference discretization scheme. The in-house solver is validated against the commercial solver, showing a maximum deviation of less than 1%. The validated solver is subsequently coupled with a genetic algorithm to perform multi-objective optimization of the electrothermal heating system. A novel correlation for the convection heat transfer coefficient over airfoil surfaces is developed based on extensive turbulent flow simulations and a genetic algorithm. The developed correlation equation has significantly lower percent relative error (from 34% to 6%) compared to flat plate correlations. The developed convection coefficient is incorporated into the optimization process. Key design variables, including heat generation intensity, heater strip dimensions, and the thermal conductivity of composite and surface protection materials, are included in the optimization process. An original objective function is formulated to simultaneously minimize electrical power consumption, prevent ice formation on the external surface, and limit internal temperatures to safe operating ranges for composite materials. The optimized design is evaluated under both spatially varying and constant convection heat transfer coefficients to assess the impact of convection modeling assumptions. The proposed methodology provides a unified and extensible framework for the optimal design of electrothermal ice protection systems and can be readily extended to three-dimensional composite wing configurations.

The maximum efficiency of extracting work from thermal radiation energy has been intensely studied. However, a large part of the world's energy resources is actually used for heating rather than work production. Therefore, finding the most effective way of heating by using radiation energy is another problem of great practical interest, not often studied. Here, it is demonstrated that such a way involves heat extractors. A general broadband theory based on the first and second laws of thermodynamics and the model of deformed blackbody radiation is developed for radiation-driven heating systems. Particular cases are considered under the assumption of local thermal equilibrium. Application to solar radiation heating shows that the photothermal heating efficiency may be improved. During a winter clear sky day, solar radiation-driven heat extractors may provide, in the ideal case, several times more heat per unit collection surface area than traditional solar heating. When constructed with current technology, heat extractors with evacuated tube solar collectors oriented toward the Sun under low-concentrated radiation may provide between 106% and 118% more heat per unit collection surface area than traditional solar heating. For an improved (mature) heat extractor technology, this range of values increases to about 130% to 337%, depending on ambient temperature. This makes the problem of radiation heating efficiency important from a practical point of view.

Accelerating the low-carbon transition of an urban centralized heating system is a key concern for policymakers. We propose a novel equilibrium analysis framework to assess the feasibility of implementing ETS in China's central heating sector. The results demonstrate that implementing an emission trading scheme (ETS) within the central heating sector can accelerate decarbonization process by shifting the focus of the current Clean Heating Campaign from gas boilers to industrial surplus heat and geothermal energy, aligning with China's goal of reaching 25% nonfossil energy by 2030. It can provide a more cost-effective and sustainable decarbonization pathway in which a 1% annual reduction in carbon quotas leads to emissions peak at 2033, as well as it is expected to generate significant co-benefits by reducing heating-related air pollution. A well-designed subsidy reallocation and phase-out strategy can enable the ETS to drive decarbonization and alleviate fiscal pressures. This combination of ETS and subsidies ensures a smooth transition to low-carbon heating in the short term and is sustainable in the long run through endogenous technological advancement and market self-regulation.

To address the issue of energy conservation of high-pressure heater systems in feedwater temperature elevating, this paper proposes an advanced control strategy based on a self-disturbance-compensating generalized predictive control (GPC) algorithm. Combined with the control of high-pressure heater water level, the feedwater temperature is controlled. Aiming at the high inertia and significant delay in high-pressure heater systems, a GPC algorithm is introduced to effectively compensate for system dynamic lag. Concurrently, to tackle multi-source and unmeasurable disturbances during high-pressure heater operation, an extended state observer is presented for their real-time observation and compensation. This significantly enhances the control system’s disturbance rejection capability, while maximizing the heat transfer efficiency of the high-pressure heater and reducing irreversible losses in the thermal system. Simulation experiment results demonstrate that the proposed method achieves superior stability and control performance compared to relevant control methods for feedwater temperature regulation, offering a solution to enhance the thermal economy of the power plant.

An integrated system for simultaneous heating and dehumidification in dynamic tobacco drying using data center waste heat

Decentralized federated learning for coordinated dispatch of integrated energy and district heating systems: A fog-based multi-agent approach with homomorphic encryption

With the aim of mitigating the impact of wind power integration and source-load-side uncertainties on an integrated energy system, we initially employed the Monte Carlo simulation in this study to randomly generate multiple wind power output/load scenarios in accordance with probability distribution functions. Additionally, we proposed a two-stage optimization method. In the first stage of our study, an enhanced African vulture optimization algorithm was applied to perform multi-objective optimization targeting fuel cost and carbon emissions across various scenarios, thereby solving the Pareto frontier to obtain multiple candidate solutions. In the study’s second stage, comprehensively considering fuel cost, carbon emission, and wind power penetration rate, evidential reasoning was utilized to determine the optimal operation strategy among the candidates. Finally, a combined heat and power system composed of the IEEE 30-bus system and a 32-node heating network was simulated. The results demonstrate that this decision-making approach can effectively reflect the merits of candidate solutions, thus validating the feasibility of the designed research methodology.

Operational strategy and impact analysis of single train isolation in high pressure heater system for generation III pressurized water reactors

Adjustment of heating curve in space heating system to real energy needs as easily applicable and effective measure to increase energy efficiency in existing buildings

Thermal characteristics and structural configuration of solar water curtain heating system for solar greenhouse

Day ahead market clearing model for low-temperature district heating systems based on urban waste heat

Field study of sustainable space heating systems coupled with thermal energy storage for thermal comfort

Novel method for data center placement using multiobjective optimization with thermohydraulic models of existing district heating systems

Interpretable multi-task dual-attention model for forecasting heating load and supply water temperature in district heating systems

This article compares the hypocaust with two similar heating systems from different eras and regions: the Chinese kang and the Hispanic glorias. The main interest of this study lies in the fact that the kang and the glorias are still in use nowadays and so are the subject of more advanced technical studies than has been possible for the hypocaust. This article therefore lists the likenesses but also the differences between the different systems while placing particular emphasis on the functional elements of the kang and the glorias that may enlighten the working of the hypocaust. By undertaking this comparative study, we hope to enrich our reflection of new bibliographical references and research criteria that may have gone unnoticed until now.

Quantification and diagnostics of Corrosion-driven energy degradation in closed loop hydronic heating systems

A GIS-based thermal mapping and forecasting approach to decarbonize residential heating systems based on metals: A city-level case study.

Energy structure analysis of the process heating system in crude glycerin refinery using a physics-guided dual-region echo state network for multirate steam modeling