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Purpose The purpose of this paper is to describe a novel universal error estimator and the adaptive time-stepping process in the generalized single-step single-solve (GS4-1) computational framework, applied for the fluid dynamics with illustrations to incompressible Navier–Stokes equations. Design/methodology/approach The proposed error estimator is universal and versatile that it works for the entire subsets of the GS4-1 framework, encompassing the nondissipative Crank–Nicolson method, the most dissipative backward differential formula and anything in between. It is new and novel that the cumbersome design work of error estimation for specific time integration algorithms can be avoided. Regarding the numerical implementation, the local error estimation has a compact representation that it is determined by the time derivative variables at four successive time levels and only involves vector operations, which is simple for numerical implementation. Additionally, the adaptive time-stepping is further illustrated by the proposed error estimator and is used to solve the benchmark problems of lid-driven cavity and flow past a cylinder. Findings The proposed computational procedure is capable of eliminating the nonphysical oscillations in GS4-1(1,1)/Crank–Nicolson method; being CPU-efficient in both dissipative and nondissipative schemes with better solution accuracy; and detecting the complex physics and hence selecting a suitable time step according to the user-defined error threshold. Originality/value To the best of the authors’ knowledge, for the first time, this study applies the general purpose GS4-1 family of time integration algorithms for transient simulations of incompressible Navier–Stokes equations in fluid dynamics with constant and adaptive time steps via a novel and universal error estimator. The proposed computational framework is simple for numerical implementation and the time step selection based on the proposed error estimation is efficient, benefiting to the computational expense for transient simulations.

Liquid air energy storage (LAES) is a promising solution for electricity energy storage and grid load shifting. The storage and application of cold energy can significantly affect the performance of LAES systems. A stable and sufficient source of cold energy in the liquefaction process is the key factor for the stable and efficient operation of an LAES system. Hence, a novel hybrid LAES system combined with organic Rankine cycle (ORC) systems based on the utilization of liquefied natural gas (LNG) cold energy is proposed in this paper. In the charging process, the LNG helps cool the compressed air, and the cold energy of the liquid air and excess compression heat are utilized in a two-stage ORC system to generate additional electricity during the discharging process. A mathematical model comprising energy and exergy analyses was developed to analyze the performance of the proposed system and the influence of key parameters. Compared to standalone LAES systems, the cold energy storage system is extremely simplified in the proposed system, and higher electricity storage efficiency and density are obtained. Therefore, the proposed system has a promising prospect in LNG terminals owing to its stability and ease of implementation.

In the paper, melting performance of a latent heat thermal energy storage (LHTES) unit with phase change materials (PCMs) locally enhanced by porous media was numerically investigated. The filling ratio of the porous inserts was fixed to a low degree to reduce the material cost. The optimal configuration of the porous inserts was obtained after the discussion about the effects of porous geometry and porosity on the velocity and temperature distribution of melting process. To reveal the superiority of the optimized result, different cases were compared with the help of a new comprehensive criterion about the input-output performance. Then a generalization expression was fitted out with some dimensionless parameters for the rapid calculation of melting fraction of the optimized result in practical application. The results indicated that in the horizontal LHTES unit, the limited porous inserts should be concentrated in the bottom part without interval between the neighboring porous inserts, providing an effective enhancement in the lower part and a low degree of thermal stratification. If the mass of porous inserts is fixed, high porosity is preferred to make the thermal-conduction-dominated area sufficiently covered by the porous inserts. Compared with the non-enhancement case, the selected result in this study can remarkably save more than 80% of the melting time and enhance the melting rate by 5.1 times. More significantly, the selected result has the highest melting rate per cost of the material when the price ratio of the addition to the PCM is larger than 5 based on the results of economic assessment. Therefore, it offers an economical solution to the thermal enhancement problem of the LHTES unit in the practical application. The normalized equation of melting fraction is obtained for the parameter range of 0.187 f = 0.596 X + 0.0438 X 2 - 0.0825 X 3 + 0.0130 X 4 , where X = SteFoRa1/8

The extremely non-uniform solar flux distribution in the solar power tower plant can badly cause some crucial problems for the solar receiver such as the local hot spot, the thermal stress, and the thermal deformation. Homogenization of the solar flux distribution is an effective method to avoid these problems, and has become an important research topic. The objective of the present study is to homogenize the solar flux distribution on the inner surfaces within the cavity receiver while keeping the optics loss as low as possible by replacing the conventional single-point aiming strategy with optimal multi-point aiming strategies. Multi-objective optimizations of the aiming strategy for the solar power tower with cavity receivers are performed by using the non-dominated sorting genetic algorithm. The distribution of the aiming points on the cavity aperture and the allocation of the aiming points for each heliostat are optimized simultaneously. The following conclusions can be made: (1) The uniformity of the solar flux distribution on the aperture does not always signify the uniformity of the solar flux distribution on the inner surfaces, where the later one is what we are truly concerned about. Therefore, the optimization of the aiming strategy should take charge of the solar flux distribution on the inner surfaces rather than on the aperture. (2) The multi-objective optimization can provide the trade-off between the non-uniformity of the solar flux distribution and the optics loss in the form of Pareto optimal fronts. (3) The optimal aiming strategies provided by the multi-objective optimization can significantly homogenize the solar flux distribution on the inner surfaces within the cavity at a minimum cost of optics loss. (4) For the optimal aiming strategies at all time except the noon, there exists a west-east asymmetry of the aiming point distribution on the aperture. Moreover, the asymmetry gets less obvious as the time gets closer to the noon.

Liquid air energy storage (LAES) is a promising large-scale energy storage technology in improving renewable energy systems and grid load shifting. In baseline LAES (B-LAES), the compression heat harvested in the charging process is stored and utilized in the discharging process to enhance the power generation. Due to the low liquid air yield, a large amount of compression heat is wasted. In order to improve the round-trip efficiency (RTE) and extend the application field, a novel combined cooling, heating and power system based on the LAES (LAES-CCHP) is proposed and investigated. In the proposed system, an organic Rankine cycle (ORC) is employed to recover the high-temperature surplus compression heat to generate electricity and an absorption refrigeration system (ARS) is introduced to utilize the low-temperature compression heat to realize district cooling and heating. Based on a mathematical model, performance evaluation and exergy analysis of the system is performed. It is found that the effective and cascaded utilization of the compression heat could significantly improve the efficiency and performance of the system. With optimal operational parameters, the RTE and exergy efficiency of the LAES-CCHP could reach 69.64% and 57.02%, respectively, which are 37.66% and 12.71% higher than those of the B-LAES.

Advanced adiabatic compressed air energy storage (AA-CAES) is a scalable storage technology with a long lifespan, fast response and low environmental impact, and is suitable for grid-level applications. In power systems with high-penetration renewable generation, AA-CAES is expected to play an active role in flexible regulation. This paper proposes a state-space set-point control model of AA-CAES for the application in the power tracking mode considering off-design characteristics. The part-load features of the multi-stage turbine and heat exchanger are captured by simplified models, and then tailored for improving computational efficiency in the applications with a timescale of 1 min. The set-point control (power tracking) of AA-CAES entails the coordination of turbine inlet pressure, air mass flow rate and heat transfer fluid (HTF) mass flow rate, while ensuring the secure pressure at the throttle valve linking the air storage tank and the expansion train. The set-point control problem is cast to a differential-algebraic equation (DAE) constrained optimization problem, and is reformulated as a nonlinear program via the simultaneous collocation method. Case studies validate the accuracy and applicability of the proposed AA-CAES model for power tracking under off-design generating conditions.

International audience; Non-uniform solar flux may lead to negative effects in the receiver of the linear Fresnel reflector (LFR), including the failure of the receiver and the fluctuating operation. For reducing these effects, an aiming strategy optimization approach is presented by combining a multi-objective Genetic Algorithm (GA) and Monte Carlo ray tracing to homogenize the flux distribution in current work. Both the flux non-uniformity index and the optical loss (ηloss) are used as the objective functions. Based on the approach, first, the flux distributions in the Multi-Tube Cavity Receiver (MTCR) and the Single-Tube Receiver with a Secondary Collector (STRSC) are optimized at a typical condition. Optimal results indicate that the GA optimization strategy (S2) can reach a compromise between the flux non-uniformity and the optical loss in both MTCR and STRSC systems. Furthermore, the optimal strategy obtained at a specific transversal incidence angle can be applied in a relatively large range around it. Moreover, parameter study indicates that the aiming line number (naim) has little impact on the efficiencies of the two systems. naim has almost no effect on the flux non-uniformity in the MTCR, but the effect is visible in the STRSC. Finally, the application of S2 under a real-time condition indicates that fluxes in the two receivers can be homogenized efficaciously in the whole time range with a small drop of 0.2–3.8 percentage points in efficiency compared with those of traditional one-line aiming strategy (S1). It is also found that the flux non-uniformity indexes of the MTCR are greatly reduced from 0.77–1.09 to 0.02–0.06 when S1 is replaced by S2, and those of the STRSC are steeply reduced from 0.59–0.70 to 0.29–0.37. It is concluded that the present approach is effective and suitable for homogenizing the fluxes in the receivers of LFRs.