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Abstract Recently, more and more absorption heat pumps have been applied in district heating systems, especially with industrial waste heat used as the driving heat source. This type of heat pumps utilizes flashing as an alternative to generators. The performance of a LiBr solution-based flashing process in an absorption heat pump is discussed in this paper. Flashing experiments were conducted in an absorption heat and mass transfer test bench. Observation results highlighted various types of flashing jets, i.e. the non-shattering jets, partially shattering jets, and completely shattering jets. Experimental results also showed that the initial superheat pressure significantly influenced transitions of the flow regimes. The whole spraying flash phenomenon is divided into three processes, and the flashing performance in each process was discussed. The flashing rate was simplified to be proportional to the superheat pressure in the first stage. And the mass transfer coefficients for the second stage were calculated, which is about 2 × 10−4–7 × 10−4 m/s. It is hoped that these results will help predict the flashing results of LiBr H2O solutions in future research.

The oxidation of coal in supercritical water was explored by using H2O2 as the oxidant. The sulfur-containing components in the effluents were identified. The experiments, which were conducted in a bench scale semi-continuous Supercritical Water Oxidation (SCWO) installation, indicated that the sulfur contained in coal could be gradually oxidized to sulfate in supercritical water medium. The main species containing sulfur in the effluents of coal SCWO were determined as sulfide, thiosulfate, sulfite and sulfate, in which thiosulfate and sulfate were predominant. The effects of the reaction temperature and time on the sulfur transformations during SCWO of coal were also investigated.

In combined electric and heat systems, selecting a suitable testbed for power flow analysis or economic dispatch is not easy: a large number of existing testbeds are not open-source, while others are difficult to be reused by other researchers due to the particularity of system scale, topology, and data. In this paper, we present three open-source testbeds with different scales based on practical combined electric and heat systems. To satisfy researchers' specific demands on the system topology and data, we also discuss how to modify testbeds based on existing topologies and data. Researchers can use the testbeds presented in this paper to test their innovative methods for power flow analysis and economic dispatch, and can also design their own testbeds based on the methodology in this paper, using published topologies and data.

Many-objective (four or more objectives) optimization problems pose a great challenge to the classical Pareto-dominance based multi-objective evolutionary algorithms (MOEAs), such as NSGA-II and SPEA2. This is mainly due to the fact that the selection pressure based on Pareto-dominance degrades severely with the number of objectives increasing. Very recently, a reference-point based NSGA-II, referred as NSGA-III, is suggested to deal with many-objective problems, where the maintenance of diversity among population members is aided by supplying and adaptively updating a number of well-spread reference points. However, NSGA-III still relies on Pareto-dominance to push the population towards Pareto front (PF), leaving room for the improvement of its convergence ability. In this paper, an improved NSGA-III procedure, called θ-NSGA-III, is proposed, aiming to better tradeoff the convergence and diversity in many-objective optimization. In θ-NSGA-III, the non-dominated sorting scheme based on the proposed θ-dominance is employed to rank solutions in the environmental selection phase, which ensures both convergence and diversity. Computational experiments have shown that θ-NSGA-III is significantly better than the original NSGA-III and MOEA/D on most instances no matter in convergence and overall performance.

Net anthropogenic emissions of carbon dioxide (CO2) must approach zero by mid-century (2050) in order to stabilize the global mean temperature at the level targeted by international efforts1-5. Yet continued expansion of fossil-fuel-burning energy infrastructure implies already 'committed' future CO2 emissions6-13. Here we use detailed datasets of existing fossil-fuel energy infrastructure in 2018 to estimate regional and sectoral patterns of committed CO2 emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of the associated infrastructure. We estimate that, if operated as historically, existing infrastructure will cumulatively emit about 658 gigatonnes of CO2 (with a range of 226 to 1,479 gigatonnes CO2, depending on the lifetimes and utilization rates assumed). More than half of these emissions are predicted to come from the electricity sector; infrastructure in China, the USA and the 28 member states of the European Union represents approximately 41 per cent, 9 per cent and 7 per cent of the total, respectively. If built, proposed power plants (planned, permitted or under construction) would emit roughly an extra 188 (range 37-427) gigatonnes CO2. Committed emissions from existing and proposed energy infrastructure (about 846 gigatonnes CO2) thus represent more than the entire carbon budget that remains if mean warming is to be limited to 1.5 degrees Celsius (°C) with a probability of 66 to 50 per cent (420-580 gigatonnes CO2)5, and perhaps two-thirds of the remaining carbon budget if mean warming is to be limited to less than 2 °C (1,170-1,500 gigatonnes CO2)5. The remaining carbon budget estimates are varied and nuanced14,15, and depend on the climate target and the availability of large-scale negative emissions16. Nevertheless, our estimates suggest that little or no new CO2-emitting infrastructure can be commissioned, and that existing infrastructure may need to be retired early (or be retrofitted with carbon capture and storage technology) in order to meet the Paris Agreement climate goals17. Given the asset value per tonne of committed emissions, we suggest that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternatives are available and affordable4,18.

This paper presents an improved gravitational search algorithm(IGSA) to solve the economic load dispatch(ELD) problem. In order to avoid the local optimum phenomenon, mutation processing is applied to the GSA. The IGSA is applied to solve the economic load dispatch problems with the valve point effects, which has 13 generators and a load demand of 2520 MW. Calculation results show that the algorithm in this paper can deal with the ELD problems with high stability.

The development of methane hydrate extraction technology remains constrained due to the limited physical understanding of hydrate dissociation dynamics. While recent breakthroughs in pore-scale visualization techniques offer intuitive insights into the dissociation process, obtaining a profound grasp of the underlying mechanisms necessitates more than mere experimental observations. In this research, we introduce a two-phase micro-continuum model that facilitates the numerical simulation of methane hydrate dissociation at both single- and multiscale levels. We employed this numerical model to simulate microfluidic experiments and determined the kinetic parameters of methane hydrate dissociation based on experimental data under various dissociation scenarios. The simulations, once calibrated, correspond closely to experimental results. By comprehensively comparing the simulated results with experimental data, the rate constant and the effective diffusion coefficient were reliably determined to be kd = 1.5 × 108 kmol2/(J·s·m2) and Dl = 0.8 × 10−7 m2/s, respectively. Notably, the multiscale model not only matches the precision of the single-scale model but also presents considerable promise for streamlining the simulation of hydrate dissociation across multiscale porous media. Moreover, we contrast hydrate dissociation under isothermal versus adiabatic conditions, wherein the dissociation rate is significantly reduced under adiabatic conditions due to the shifted thermodynamic condition. This comparison highlights the disparities between microfluidic experiments and real-world extraction environments.

Changes in climate patterns not only affect precipitation and precipitation patterns, but also cause the spatiotemporal redistribution of precipitation and runoff, affecting hydrogeneration in turn. Based on the coupling relationship between the Coupled Model Intercomparison Project 5 (CMIP5) climate change model and surface runoff in China, a database of China’s major hydropower stations was constructed in this study and the Water Evaluation and Planning model was applied to analyze the impacts of climate change on hydropower generation in China by region and basin under the Representative Concentration Pathway (RCP)4.5 and RCP8.5 scenarios. During the forecast period, national power generation compared with base year first decreased in the 2030s and then increased in the 2070s, while a risk of excessive hydropower generation was concentrated in the southwestern provinces, Yangtze River Basin, and giant hydropower stations. During the 2030s, hydropower generation may face a risk of electricity generation decrease which will limit its contribution to the Nationally Determined Contribution target.

The secondary flow in the impeller of an axial flow pump is an important factor affecting the safe and stable operation of the unit. However, there is still a lack of systematic research on the generation mechanism of secondary flow and corresponding control strategies in axial flow pumps. To better understand the secondary flow characteristics in the axial flow pump, based on the momentum equation of relative motion, the basic distribution characteristics of the potential rothalpy gradient (PRG, or the reduced static pressure gradient) in the impeller of an axial flow pump were systematically analyzed. Two typical secondary flows were found, namely, trailing-edge hub-shroud type secondary flow at the blade outlet hub side and leading-edge hub-shroud type secondary flow at the blade inlet shroud side. The generation of these secondary flows is directly related to the effect of natural adverse PRG. A new blade design method is proposed. The essential idea of this method is to give the blade loading strategy based on grasping the macro-flow characteristics and control PRG characteristics by adjusting the real blade loading δp (i.e., the static pressure difference between the blade pressure and suction surfaces) and, thereby, control the above-mentioned secondary flows. The application of an axial flow pump showed that the blades designed based on this method can effectively control these secondary flows and reduce pressure fluctuations. The average decrease in pressure fluctuation on the blade inlet shroud side and the outlet hub side is 17.79% and 20.03%, respectively.