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Thermal insulation coating (TIC) is beneficial for reducing building energy consumption. In this work, a joint optimization and analysis approach for multi-parameters of TIC was proposed to determine its optimization trend, importance order of parameter and available parameter combinations. Its radiation characteristics and thermal resistance were comprehensively considered. Based on the approach, TIC was evaluated from energy saving rate of cooling (ESR cool), heating (ESR heat), and total energy consumption (ESR total) in two climates: hot summer cold winter (Shanghai), and hot summer warm winter (Guangzhou). Results indicated that constantly positive ESR cool was only achieved by optimizing solar absorptivity, while constantly positive ESR heat can be obtained by optimizing different parameters. To guarantee positive ESR total , thermal resistance should exceed 0.11 m2·K·W−1 or solar absorptivity should be between 0.2 and 0.6 in Shanghai, while solar absorptivity should be between 0.1 and 0.3 in Guangzhou. For these two cities, the most important parameter was thermal resistance or solar absorptivity. The optimal TIC for Shanghai was "high thermal resistance + low solar absorptivity + low emissivity", while high emissivity was suitable for Guangzhou. By utilizing the approach and results, energy-saving effect of TIC can be optimized during material design, and influence of material aging can be predicted. • A joint optimization and analysis approach for multi-parameters of TIC is proposed. • Optimization and deterioration impact of TIC multiple parameters is evaluated. • Parameter combination law for positive or negative energy saving rate is obtained. • Importance order of parameter is used for optimization design and material aging. • Effect of energy consumption caused by material aging consequences is predicted. [ABSTRACT FROM AUTHOR]

Most existing material design studies assume that radiative cooling (RC) windows should be ideal radiators with high emissivity (ε λ ∼ 1) in wide infrared band (IR, 2.5–20 μm). However, whether this assumption is universal has not been tested. Different from previous studies based on experiments and steady-state theoretical calculation models, a transient building heat transfer model with facade windows verified by experiments is used to explore the optimal design of IR emissivity of RC windows. Results show that the RC effect of windows is not always improved as traditionally expected with the increase of emissivity ( ε ‾ NAW) in the infrared " non-atmospheric window (NAW) " band. In fact, the adjustment trend of ε ‾ NAW for the RC effect of windows is reversed. Smaller ε ‾ NAW can weaken the heat flow into the room and prolong the time that windows become " coolers ". A wider range of window-to-wall ratios are also studied, and it is found that the design of selective high emissivity ( ε ‾ NAW ∼0) is more conducive to the RC of windows. It is proved that the current default design of the RC window emissivity in IR band is non-universal, and new laws found provide an enlightening guide for the material development of RC windows. • A reversal trend of RC regulation of window emissivity outside the AW is revealed. • Smaller window emissivity outside the AW extends the time windows become coolers. • Designs with selective high emissivity may be more favorable for the RC of windows. • The default "broadband, high emissivity" of RC windows in IR band is not universal. [ABSTRACT FROM AUTHOR]

To improve the comprehensive utilization efficiency of energy, a multi-objective optimization control strategy applied to the energy hub (EH) within the system is proposed to address the electrical and thermal load distribution of the integrated energy system (IES) and the low-carbon economic operation. First, a model of the electrical and thermal energy outputs is established based on the characteristics of the IES network and the multidimensional "load parameter" evolution law. Moreover, a distributed control strategy is proposed that utilizes the information interaction between neighboring EHs to accurately share the electrical and thermal loads, which reduces the communication burden of the system while avoiding overloads. Furthermore, to coordinate the optimal operation of the devices within the hub, based on the energy conversion characteristics of the EH, a multi-objective optimization model is proposed that considers low-carbon and economic aspects to realize efficient energy use. Simulation results show that the proposed strategy effectively improves the robustness of the system while realizing proportional load distribution and low-carbon economic operation. Under the same load, when focusing on system economics, the operating cost is 2.182/¥ lower than when focusing on low-carbon systems, but carbon emission is 1.6753/kg CO 2 higher. [Display omitted] • A novel energy hub management for integrated energy systems was proposed. • A multi-objective optimization control strategy was proposed. • The proposed strategy could be accurately shared electrical and thermal loads. • Optimized operation of devices within the Energy hub was achieved. • Simulation results were implemented to verify the effectiveness of the strategy. [ABSTRACT FROM AUTHOR]

The hump characteristic is one of the unique hydraulic instability of the large vertical volute centrifugal pump (LVVCP) under part-load conditions, which is extremely detrimental to the safe and stable unit operation. To suppress the hump characteristic of LVVCP, a passive suppression method with a combined diffuser vane structure is proposed in this paper. This diffuser vane structure consists of a combination of large and small hydrofoil vanes, with the special 6 small hydrofoil vane B are arranged within 150° range of the small volute section side. To investigate the key reasons for suppression, detached eddy simulations are performed for LVVCP with original diffuser vane (Diffuser A) and combined diffuser vane (Diffuser B), and the energy loss and flow patterns are analyzed. The hump region of LVVCP with Diffuser B is narrower, the positive slope of Q - H curve is decreased and the hump margin is increased. The reduced conversion of kinetic energy to turbulent kinetic energy and the decreased Reynolds stress diffusion loss in the Diffuser B and volute are main reasons for the hump characteristic suppression. The energy loss in the volute small section side region and its corresponding diffuser region increases significantly under hump conditions, and Diffuser B can obviously reduce the energy loss in these regions. The flow pattern analysis in the diffuser shows that the weakened rotating stall in Diffuser B leads to a more regular Q m variation with time in D1∼D6. The reduced chord length and thickness of vane B results in a significant decrease of pressure surface separation vortex (PSV) and suction surface separation vortex (SSV) scales and a weakened vortex merging phenomenon, which causes a considerable drop of Δ S PRO in the Diffuser B. The Diffuser B provides a more uniform α distribution to the volute inlet, and decreases the vortex scale and vortex-induced energy loss on the volute small section side. • A passive suppression method is proposed for the hump characteristic: combined diffuser vane arrangement strategy. • A combined energy loss evaluation methodology with entropy production theory and energy balance equations is applied. • The entropy production and Omega vortex identification technology are combined to analyze the flow pattern on the hump characteristic suppression. • The smaller chord length and thickness of vane B can alleviate flow separations and vortices merging in the diffuser and provide better inlet conditions for the volute. [ABSTRACT FROM AUTHOR]

Piezoelectric energy harvesters (PEH) are widely used to collect piezoelectric energy. However, adapting to different engineering application environments is difficult for traditional PEHs. To improve the engineering application value of PEH, a hanger piezoelectric energy harvester (HPEH) based on low frequency vibration of hanger is proposed in this paper. A dynamic electromechanical coupling model was established for hanger structure, and the effects of the external load resistance, the polyvinylidene fluoride (PVDF) piezoelectric film installation location, the stability of the PVDF piezoelectric film with different winding methods, and the external excitation amplitude on the energy output performance of the HPEH were studied. Results indicate that the optimal load resistance of the HPEH studied in this paper is 1.0 MΩ; the PVDF piezoelectric film location has a significant impact on the performance of the HPEH, and the output power is highest at hanger L c/4; the PVDF piezoelectric films during ring winding is better than those in spiral winding for the same external cycle excitation; in the external excitation amplitude range of 2 d –6 d (d : hanger diameter), appropriately increasing the external excitation amplitude is conducive to improving the output voltage of the HPEH, with the root mean square voltage increasing by 95.11 % at external excitation amplitude A = 6 d compared with that at the initial excitation amplitude. It provides an innovative solution for the field of cable structures and new energy sources, and the further research and application of this technology is expected to have a profound impact in the field of energy sustainability and engineering technology. • This paper proposes a novel hanger piezoelectric energy harvester. • The key parameters affecting the energy harvesting performance are analyzed. • The engineering application value is increased compare with conventional harvesters. • It is suitable for low-frequency vibrations of cable structures. • It provides a new idea for energy harvesting of cable structures. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) has been widely studied in the energy management of hybrid electric vehicles (HEVs) for its remarkable energy efficiency improvement compared to conventional methods. However, how to alleviate the time consumption of training a stable reinforcement learning agent still needs to be solved in real-world implementation. This study presents a human expert knowledge encoded 'warm start' method with the flexibility to change the neural network architecture. The expert knowledge is encoded in a decision tree which then initializes the weights and bias of the DRL neural network. Compared with another fixed architecture warm start method, the proposed FlexNet exhibits improved learning speed by 60.8 % and 88.8 % in action space 50 and 100, respectively. The energy consumption by the proposed FlexNet EMS method is 12.2 % and 6.4 % better than rule-based and equivalent consumption minimization strategy, respectively. This proposed warm start method can reduce learning time and increase energy efficiency in various energy management applications. • Expert knowledge is encoded in a decision tree to warm-start reinforcement learning. • The expert knowledge encode process allows flexible neural network architecture (FlexNet). • The proposed FlexNet reduces learning time by 60–80 % compared with existing method. • The proposed FlexNet reduces energy consumption compared with baseline methods. [ABSTRACT FROM AUTHOR]