Abstract

To address the modeling of integrated energy system equipment oriented towards dispatch optimization, a hybrid mechanism-data-driven dynamic modeling approach is proposed. This method employs a transfer function model to characterize the dynamic behavior of the equipment and a Multilayer Perceptron (MLP) to model the nonlinear residuals of the transfer function model. To evaluate the model performance, a water-source heat pump was modeled and comparisons were made among the first-principles model, the transfer function model, the NARX model, and the hybrid model. The results show that the simulation time of the hybrid model is comparable to that of the transfer function model, with reductions of 85.72% and 95.56% compared to the first-principles model and the NARX model, respectively. In terms of simulation accuracy of heat power and electrical power, the hybrid model is comparable to the NARX model, with improvements of 50.76% and 89.30% compared to the transfer function model. The proposed hybrid modeling approach achieves model light-weighting while maintaining accuracy, thereby better supporting the dispatch optimization of integrated energy systems.

Abstract

To achieve large temperature range refrigeration under high sink temperatures, this paper proposes an auto-cascade refrigeration (ACR) system using R123/R134a as the mixed refrigerant and conducts simulation studies. Based on Aspen Plus simulation model, the performance optimization of the auto-cascade refrigeration system under both high heat sink temperature and low heat sink temperature are investigated. Under high heat sink temperature, system performance is evaluated across R134a mass fractions of 0.24-0.34, revealing optimal COP values at 0.28-0.29 mass fraction. The evaporator-condenser analysis demonstrates that increasing heat transfer area beyond 1.32 m² yields diminishing returns in energy efficiency improvement. For low heat sink temperature, simulation results show an inverse relationship between R134a mass fraction (0.25-0.33) and system COP, with higher fractions increasing post-condensation stream dryness. Notably, when the heat sink temperature decreases from high to low, switching to single-stage vapor compression mode by closing valve VAL1 results in significantly enhanced COP compared to auto-cascade operation, demonstrating the system’s operational flexibility.

Abstract

In order to improve the energy efficiency and economy of geothermal cascade utilization system, this paper proposes a two-stage heat pump / thermosyphon system (THPTS), which optimizes the cascade utilization of geothermal energy by combining heat pump and thermosyphon technology. Based on TRNSYS software, the simulation models of traditional two-stage heat pump system (THPS) and THPTS are built, and their performances in geothermal heating are compared and analyzed. Taking an office building in Beijing as an example, the hourly load of the building is simulated, and the system operation strategy is designed: when the heat load is lower than the threshold, the thermosyphon mode is used for direct heat transfer; conversely, switch to heat pump mode. The results show that THPTS can maintain the heat extraction efficiency at 59.74 %, and the total power consumption in the heating season is 6.13 % lower than that of THPS, and the energy saving effect is obvious. This study provides an innovative solution for the efficient utilization of geothermal resources.

Abstract

In the context of the rapid development of smart cities and intelligent transportation systems, the energy management efficiency of new energy vehicles has become a critical factor in achieving carbon peak and carbon neutrality targets. Among these, the accuracy of power prediction significantly impacts the rationality of energy allocation and overall vehicle response performance. This paper systematically investigates two representative power prediction paths: the direct method, which predicts future power directly, and the indirect method, which first predicts vehicle speed and then computes power using a dynamic model. To evaluate their applicability in real traffic environments, operating conditions are categorized into high-speed, medium-speed, and low-speed scenarios, and performance is compared under different prediction time windows (1s, 3s, and 5s), with MAE and RMSE as the primary evaluation metrics. The results indicate that under varying average speeds, each prediction path has its own advantages and disadvantages. Furthermore, this paper highlights the complementarity of the two methods. The findings can provide a reference for optimizing predictive energy management strategies in intelligent new energy vehicles, thereby promoting further improvements in vehicle operation efficiency within intelligent transportation systems.

Abstract

The growing integration of renewable energy into the energy mix, coupled with the rapid emergence of diverse new market participants, has intensified challenges related to power system balancing. Consequently, research on balanced operational frameworks for modern power systems carries significant theoretical and practical relevance. This study first examines international balancing mechanisms, with a focused analysis of Germany’s Balancing Settlement Unit model. Subsequently, an operational framework designating VPPs as regional balancing responsibility entities is proposed, accompanied by the formulation of corresponding model optimization strategies. A case study of a representative region is then conducted, validating the proposed model against empirical power generation and consumption deviation data. Findings indicate that this operational framework offers valuable insights for the design of China‘s power balancing mechanisms. The paper concludes by presenting pertinent research outcomes.

Abstract

The liquid-phase density of phase change material (PCM) is a key thermophysical property to analyze the heat transfer properties of phase change process and the evolution process of phase-change interface. Six sugar alcohol PCMs, which are widely used for medium-temperature heat storage, are selected. Their liquid-phase density data in wide temperature ranges is measured by a thermostatic liquid-phase density measurement instrument. Results show that the variation of liquid-phase density can reach up to 2.43% as the temperature changes by 30°C for six sugar alcohol PCMs. The maximal difference in liquid-phase density of different sugar alcohol PCMs can reach up to 4.62% at the same temperature. Furthermore, the specialized high-precision prediction models of liquid-phase density are constructed for six sugar alcohol PCMs, respectively. A general prediction model of liquid-phase density is also constructed, which is suitable for all the sugar alcohol PCMs. The root mean square relative error of all the specialized prediction models are less than 0.15%, and that of the general prediction model is less than 0.25%.

Abstract

The virtual energy storage (VES) characteristics inherent to buildings are the primary contributor to the nonlinear behavior of heating, ventilation, and air conditioning (HVAC) loads. Investigating strategies between VES and HVAC operations in demand-side management remains a critical research focus. This review addresses the integration of VES into optimized regulation frameworks for building HVAC systems. First, two prevalent VES modeling approaches are discussed: physics-based methods, which utilize heat balance equations, and data-driven techniques, which excel in representing the nonlinear dynamics and coupled interactions of VES. Second, a systematic analysis of quantitative VES metrics, including the three primary categories of evaluation parameters, such as differential power and time, is provided. The paper critically evaluates current research on VES-integrated HVAC operational strategies. Results indicate that while model predictive control achieves high reliability, its practicality is limited by its reliance on a priori expertise. Conversely, model-free predictive control demonstrates superior adaptability to VES nonlinearity. Finally, the paper identifies future research directions and proposes a technical framework to address existing challenges, offering insights for enhancing the operational efficiency of VES-integrated HVAC systems.

Abstract

Carbon emissions are a key driver of global climate change, and their accurate characterization and prediction are essential for promoting regional sustainable development. This study develops a novel carbon emission modeling framework that integrates interpretable machine learning with land use data, without dependence on socio-economic indicators. This allows for emission prediction beyond the decoupling stage and captures spatial distribution patterns with high accuracy and interpretability. The Yangtze River Delta region is used as a case study. By combining Geographic Information System-based kernel density analysis for land-use refinement with an optimized Extra Trees Regression model, the approach achieves high predictive performance (R² = 0.86 for testing set). Model interpretability is enhanced using Shapley Additive exPlanations, which reveal nonlinear effects of various land types on emissions. Future land use scenarios are simulated using the Optimized Land Expansion Analysis Strategy and a Cellular Automaton based on Multiple Random Seeds, achieving overall accuracy above 85%. Projections estimate total carbon emissions in the Yangtze River Delta will reach 1,581 million tons by 2030, with Shanghai and Suzhou contributing 224 and 172 million tons, respectively. County-level emissions are further examined using spatial econometric models, which identify a significant clustering pattern (Moran’s / = 0.61). As industrial land becomes more dispersed, emission hotspots shift toward regional centers.

Abstract

To address the challenge of high heat flux chip cooling, this study proposes a novel liquid-cooled heat sink that integrates topology optimization with microchannel design. The novel proposal combines the superior flow characteristics of straight microchannels with the enhanced heat dissipation performance of topologically optimized structures. Firstly, a multi-objective topology optimization framework is developed to simultaneously minimize the average temperature and power dissipation of the cold plate, achieving a balance between thermal and hydraulic performance. Secondly, a three-dimensional numerical model is constructed based on the results of two-dimensional topology optimization, and its accuracy is validated. Finally, the performance of the proposed scheme was compared with that of the straight microchannel and separate topology optimization design. The results show that the proposed structure reduces the maximum chip temperature by 4.28 K and the pressure drop by 319.42 Pa compared with the straight microchannel, while also improving temperature uniformity. These findings demonstrate the effectiveness of the integrated scheme for designing high-performance cold plates tailored to the thermal management needs of electronic devices.

Abstract

Chemical looping combustion technology enables low-energy CO2 capture and is a promising low-carbon utilization approach for fossil fuels. As a solid-phase reactant, the oxygen carrier must undergo repeated involvement in the chemical looping process. In contrast to conventional approaches based on circulating fluidized beds or moving beds, this study proposes a simulated moving bed (SMB) reactor using multiple fixed beds arranged in both series and parallel configurations. By implementing a programmed gas?switching strategy, the reactor achieves the approximation of a steady-state moving bed process through inherently unsteady fixed-bed operations. By controlling gas inlet positions, the system can flexibly operate under either co-current or counter-current flow conditions. This novel reactor design features a simplified structure and mitigates the stringent requirements for mechanical strength and wear resistance of oxygen carrier materials typically associated with conventional moving bed reactors, while retaining the advantages of high fuel conversion efficiency and oxygen carrier utilization rate inherent to moving bed systems. We experimentally investigatefundamental reactor characteristics in the reduction stage of the chemical looping combustion process, including the weight hourly space velocity (WHSV) and the corresponding number of fixed-bed reactors in series. The optimal WHSV was determined to be 0.036h-1 for 1073K and three reactors, under which the methane conversion and CO2 selectivity reached 99.23% and 94.99%, respectively. Based on the identified optimal operating conditions, we introduce a gas?switching strategy for the novel SMB reactor. Experimental results demonstrated that the proposed novel chemical looping combustion method exhibits favorable performance and stability, offering a new pathway for the low-carbon utilization of fossil fuels through chemical looping technologies.