Renewable Energy最新文献

Hybrid renewable energy systems, which utilize multiple renewable sources, are becoming increasingly popular due to the need for sustainable energy. In this study, a new hybrid power plant that combines a solar chimney power plant with geothermal energy is investigated. The new system that can be activated when solar radiation is inadequate is called “geothermal pipe” and can produce up to 71 kW of electricity using a 1000-m-deep well. A geothermal pipe power plant was designed to be integrated with a system similar to the Manzanares solar chimney with a well depth of 200 m, generating an average of 15 kW of power. By increasing the distance between wells to 1.5 km, the output power can reach 20 kW. The study analyzed the impact of different parameters, such as well array, size, and temperature, on the output power. The results indicate that a new type of geothermal pipe with six inlets has the potential to increase the performance of the conventional geothermal pipe (with one well) by 26 %. This hybrid renewable energy system benefits from the combination of more than one renewable source, allowing for year-round energy production despite weather conditions.

This research paper presents numerical and experimental investigations to examine the effectiveness of a honeycomb pattern as a form of the geometry of artificial roughness in solar air heaters. Utilizing Computational Fluid Dynamics (CFD) through three-dimensional simulations, the study explores how Thermo-Hydraulic Performance Parameter (THPP) is affected by variations in honeycomb geometry. The research examines various parameters, including the angle of attack (Ø), relative roughness pitch (P/e), and relative roughness height (e/D) within the respective ranges of (90°-120°), (8–12), and (0.03–0.05). The system's performance is evaluated across various flow scenarios, covering Reynolds numbers from (3000) to (21,000). Incorporating the honeycomb design into an absorber is observed to improve the heat transfer rates. The system achieves a maximum Nu of (140.65) at (e/D) of 0.04, (P/e) of 10, (Ø) of 120°, and Re of (21,000). The maximum FF of (0.039) was obtained at (e/D) of 0.05, (P/e) of 9, and (Ø) of 120° at a Reynolds number of (6000). The system exhibited a THPP of (1.7) at a Reynolds number of (6000). This Maximum THPP was associated with specific parameters, including (e/D) of 0.04, (P/e) of 10, and (Ø) of 120°.

As driven by thermodynamics and reaction kinetics considerations, conventional two-step solar thermochemical processes typically rely on non-isothermal cycling conditions to effectively couple the endothermic reduction and exothermic oxidation reactions. Nevertheless, recent discussions on isothermal cycles based on thermodynamics simulation and material characterization have sparked dissenting opinions, as certain reaction processes operating under isothermal cycling conditions have demonstrated the possibility of achieving higher energy conversion efficiency. To delve further into such phenomenon and potentially unveil the underlying scientific principles, this study conducts a reaction kinetic analysis and lab-scale systematic experiments on a novel methane-assisted two-step thermochemical process using iron-based oxygen carriers. Despite the fact that the reaction kinetics analysis of iron oxides indicates that isothermal cycles at reaction temperatures of 573–1173 K do not provide significant advantages in terms of energy conversion efficiency, surprisingly, the experiments conducted with the prepared cobalt–nickel ferrite materials conclude oppositely. More specifically, the observed increase in material reactivity with rising oxidation temperature contributes to an approximately two-fold enhancement in the CO yield under isothermal conditions, as well as a noteworthy improvement of about 15% in solar-to-fuel efficiency. This energy efficiency improvement could be attributed, at least in part, to the stable reaction temperature during isothermal cycling, which effectively mitigates the challenges associated with solid-phase sensible heat recovery caused by significant temperature fluctuations, particularly when operating at high feed flow rates. Accordingly, the applicability of isothermal cycles is linked to two crucial factors: the reactivity of the oxygen carrier and the specific operating conditions employed. The experiments herein conducted showed that the catalytic activity of the material reached a relatively stable state after 24 h of reaction, resulting in a peak CO yield of 20.5 mL min${}^{-1}$ g⁻¹ and a CO${}_2$ conversion exceeding 90%. Thorough analyses reveal several optimization measures for enhancing efficiency under the setting of the reaction system.

The horizontal ground heat exchanger (HGHE) possesses a complicated heat transfer mechanism as its extensive spatial scale, long operational duration, and vulnerability to meteorological conditions. Consequently, the long-period simulations of HGHE usually involve significant computational costs, posing challenges for its dynamic optimization implementation. Therefore, this study initially established and validated a conventional numerical (full-order) model for HGHE as the reference model. Subsequently, a hybrid model was developed using the proposed adaptive proper orthogonal decomposition (POD) method. By analyzing the influential characteristics, the study identified the solution strategy and the key parameter values for adaptive POD, followed by the generality tests. The hybrid model proved to successfully mitigate the issue of error accumulation commonly associated with native POD extrapolation. Finally, employing a long-running engineering case study, the accuracy and the solution efficiency of the hybrid model were compared against those of the conventional (full-order) model. The results demonstrated that the hybrid model maintained computational accuracy at a comparable level while exhibiting a computational efficiency 326 % higher than that of the conventional (full-order) model, without requiring additional computational resources. This study can provide efficient modeling support for the dynamic optimization design of HGHE.

Obtaining high-precision diffuse irradiance from global horizontal irradiance (GHI) can serve comprehensive and effective data for PV system design, operation and maintenance. This study has incorporated cloud features in an artificial neural network (ANN) model to improve the estimation accuracy of diffuse fraction on 1-min resolution dataset. The cloud features are extracted from ground-based cloud images, including spectrum features, texture features and cloud cover ratio, with image processing algorithms. After data validation, the ANN model which incorporated all the cloud features has achieved a normalized root mean square error (NRMSE) of 17.1 %, representing a 13 % reduction compared to the basic ANN model, we have investigated additional strategies that further optimize the model performance, including cloud classification, weather classification and data averaging, and quantified the effects of the proposed approaches based on actual station data. The data averaging based on proper time scale has brought about 2 % in accuracy improvement; the weather classification and cloud classification have both brought above 10 % of accuracy improvement in some cases but others may deteriorate for some reasons that need to be further investigated, based on this, we have analyzed and summarized the deficiencies in our research and proposed detailed research directions for future endeavors.

This paper introduces a novel hierarchical architecture aimed at enhancing coordination between distribution system operators and electric vehicle aggregators in order to minimize Electric Vehicle (EV) charging costs for users while optimizing EV hosting capacity to alleviate network congestion. Real-world distribution networks are employed to evaluate EV charging strategies and their impact on medium and low-voltage networks. Two distinct EV charging optimization strategies are proposed to ensure fair power allocation among EV Aggregators (EVAs), alleviating congestion while managing EV charging power efficiently. Results demonstrate that the proposed collaborative EV charging effectively flattens the load curve, reducing peak power and avoiding grid congestion. The main findings underscore the importance of incentivizing EV flexibility to support Distribution System Operator (DSO) objectives beyond static tariffs. Furthermore, a battery degradation model is introduced into the optimization problem, reducing high currents and capacity decay. Despite capturing a higher mean electricity price, the total cost of EV charging is reduced.

A reservoir model was coupled with a flash–binary cycle model to investigate the performance and economics of a geothermal system. The production temperature T_pro of the reservoir decreased with an increase in the operation time, which affected the net output power of the system; thus, a method for calculating the electricity production cost (EPC_M) and payback period (PBP_M) was developed. The net output power decreased with an increase in the operation time because of the effect of T_pro. This decrease resulted from the combined effect of a considerable decline and marginal increase in the net output power of a single-flash cycle (decline of 1278.86 kW) and an organic Rankine cycle (increase of 68.6 kW), respectively, with an increase in the operation time. For high flash pressure, the decreases in the output power, firs- and second-law efficiencies of the system ($W_{tot,net}$, ${\eta }_{tot,I}$, and ${\eta }_{tot,II}$, respectively) from the 1st to the 30th year of operation were 52.08 %, 34.53 %, and 24.53 %, respectively, with the percentage decrease in $W_{tot,net}$ being greater than those in ${\eta }_{tot,I}$ and ${\eta }_{tot,II}$. The system with a flash pressure of 800 kPa was discovered to achieve the best EPC_M and PBP_M values of 0.129 USD/kWh and 12.503 years, respectively.

As global efforts to decarbonise industries continue, there is increasing pressure to identify and proliferate sustainable methods of generating electricity, in-line with the United Nations’ Sustainable Development Goal 7. The in-stream water wheel is a pico-hydropower technology that generates electricity using only the kinetic energy in the fluid, rather than both potential and kinetic, like most forms of pico-hydropower. Current methods of estimating the power output of these turbines lack validation, robustness and proper justification for their assumptions. This study has developed a new method for predicting the power output of in-stream water wheels, based on fluid dynamics principles, and has been compared with a range of experimental results to confirm its robustness. The new model identifies novel characteristics of the power stroke of the turbine blade, including unsteady effects and negative torque production at certain blade angles. In addition, the model can be tuned to match experimental data, improving its accuracy in specific applications. The better prediction of power output aims to encourage the use of in-stream water wheels as part of the global decarbonisation strategy.

Increasing the proportion of renewable energy is of paramount importance for all countries in the world. In this work, a novel multi-generation system is designed to fully utilize solar energy, which includes a photovoltaic/thermal subsystem (PV/T), an absorption refrigeration cycle (ARC), a proton-exchange membrane (PEM) electrolysis, and a promising pumped thermal electricity storage (PTES) energy storage subsystem, which can simultaneously achieve the purposes of refrigeration, hydrogen production, heat production, and energy storage. Meanwhile, the solar radiation data of Wuwei City, Gansu Province, China for the year 2022 are selected for the study. According to different seasons, the thermodynamic and thermo-economic performances of the combined power, heat and hydrogen production (CPHH) mode operated in spring, autumn, winter, and the combined power, cooling and hydrogen production (CPCH) mode operated in summer are investigated, and multi-objective optimization is conducted. The results indicate that the direct normal irradiance (DNI) of solar, the area of PV/T, the thermal storage temperature of the PTES subsystem, and the pinch point temperature difference significantly affect the total energy efficiency, total exergy efficiency, and total product unit cost of the system. The multi-objective optimization results show that the optimal solutions of total energy efficiency and total product unit cost of the system are 85.90 %, 24.25 $·GJ⁻¹ and 86.97 %, 24.25 $·GJ⁻¹ for the CPHH mode in spring and winter, respectively, and 88.26 % and 22.21 $·GJ⁻¹ for the CPCH mode in summer. This work can provide a valuable reference for the research of multi-generation systems with integrated renewable energy sources.

Hydrogen generation via methanol steam reforming is a promising method for producing renewable energy. In this work, a series of Mn²⁺-substituted CuAl₂O₄ spinels were prepared by solution combustion method, and the crystal structure, micromorphology, chemical constitution, reduction behavior, acidity, specific surface area and surface chemical state of the spinels were comprehensively characterized by various equipments. The obtained spinels were washcoated on Cu foams to prepare monolithic catalysts, and the catalytic performance of the catalysts was evaluated in a methanol steam reforming microreactor. Compared with the binary Cu–Al spinel, the Mn²⁺ substitution led to a decrease in the particle size, a change in the chemical composition and reduction behavior, a decline in the acidity, an increase in the specific surface area, and an improvement in the surface chemical state. As a result, the release rate of active Cu from the Mn-containing CuAl₂O₄ spinel was significantly slowed down and the formed nanoparticles were fine, which was believed to be in favor of maintaining a stable catalytic performance longer. Among the prepared catalysts, the monolithic catalyst loaded with Cu_0.4Mn_0.6Al₂O₄ exhibited the highest activity and stability. The findings of this work suggested that introducing Mn²⁺ might be a promising way to regulate the Cu releasing property for obtaining a better sustained release catalyst system.