A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance grows.Traditional approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering concepts.The approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

对萼猕猴桃CDPK基因家族鉴定及非生物胁迫应答分析

【目的】鉴定对萼猕猴桃(Actinidia valvata)CDPK家族基因,并分析其在不同组织的表达模式以及对盐胁迫和淹水胁迫的响应。【方法】基于3代全长转录组测序数据,通过多种生物信息学手段,分析和鉴定对萼猕猴桃CDPK家族基因,利用实时荧光定量PCR(quantitative real-time PCR,qRT-PCR)技术分析这些基因在不同组织中的表达,及在不同非生物胁迫条件下的表达情况。【结果】在对萼猕猴桃基因型KR5的全长转录组测序数据中共鉴定出63个CDPK基因,命名为AvCDPK1~AvCDPK63。系统发育分析将AvCDPK基因蛋白分为4个亚家族,同一亚家族具有相似的结构和基序(motif)。AvCDPK基因存在明显的组织表达特异性。AvCDPK49在盐胁迫和淹水胁迫条件下,均显著诱导表达,Av CDPK30和31在2种胁迫下均显著抑制表达。【结论】在对萼猕猴桃中共鉴定出63个CDPK基因,系统发育树显示Av CDPK基因家族与拟南芥CDPK基因家族在进化上高度保守。不同组织中AvCDPK的表达量存在明显差异,其中Av CDPK49受盐害、淹水诱导显著高表达,表明其可能在猕猴桃的耐盐和耐涝响应过程中发挥着重要作用。

太阳能集热器强化传热技术的局限性与挑战

目前,太阳能集热器在可再生能源领域发挥着至关重要的作用,这在核心能源专家和研究界得到了广泛的认可。由于这种太阳能收集技术的高能量转换率,迫切需要评价方法,以期改善传热过程。前期研究人员主要致力于工作流体的增强上,而忽略了其他同样有助于增强太阳能集热器传热过程的技术,这使得其他方向的研究逐渐过时了。本研究的主要目的是提供最新的进展和方法,以加强太阳能集热器的传热过程的最新概述。研究了传统技术和创新技术,探讨了它们在提高热性能和整体系统效率方面的有效性。对太阳能集热器强化传热技术的最新研究进行了全面的文献综述。确定了主要挑战、知识差距和局限性,并推荐了潜在的未来研究方案。这篇全面的综述将作为研究人员和主要能源参与者的指南,为太阳能集热器领域提供参考的研究方向。

Multiphase Flow Simulations through Tarbela Dam Spillways and Tunnels

Tarbela dam is one of the largest earth filled dam in the world used for power generation and irrigation purposes. Like all reservoirs the sediments inflow in the Tarbela reservoir has resulted in reduction in water storage capacity and is also causing damage to the tunnels, power generating units and ultimately to the plant equipment. This numerical study was performed to predict the flow patterns and characteristics in Tarbela dam. Tunnel 3 and 4 inlets;originally on the bed level were raised in the 3-D model and meshed. Analysis was performed using multiphase flow (water and air) for maximum inflow in the reservoir, i.e., considering summer season and discharging water through different locations, i.e., tunnels and spillways. Pressure, velocities, flow rate and free surface height results obtained were found in good agreement with the analytical and existing results where available. Results show uneven discharge through each gate due to maximum velocity near exits and overall stagnant phenomena of water within the reservoir. Maximum velocity was observed along the spillways outlet. Strong vortex motion was observed near the spillways outlet and tunnel inlets. New design of Tunnel 3 and 4 were suggested to WAPDA in order to decrease the sediment inflow and improvements in design of the spillways were suggested.

Turbulent Flow Simulations through Tarbela Dam

Tarbela dam is one of the largest earth filled dam in the world. The sediments inflow in the Tarbela reservoir has resulted in reduction in water storage capacity. In addition damage to the tunnels, power generating units and ultimately to the plant equipment by the sediments particles carried by water is observed. To the authors knowledge, to-date no comprehensive simulation studies are performed for this dam reservoir and tunnels, especially at present when sediment delta and presence of sediment particles in the tunnels is observed to a reasonable extent. The aim of this study is to investigate the damage to the Tunnel 2 of the Tarbela Dam with and without considering the affect of sediment particles for one way and two way/full coupling during summer, winter and average seasons, using turbulent flows of water. Numerically calculated erosion results are compared with the experimental erosion results. Pressure, velocity and erosion rate density results are discussed in detail.

Conceptual design,modeling and compliance characterization of a novel 2-DOF rotational pointing mechanism for fast steering mirror

In this paper,a novel 2-DOF rotational pointing mechanism(RPM)is designed inspired by the guidelines of the graphical approach.The mechanism integrates with a fast steering mirror(FSM)for compensating pointing errors of a laser beam.The design intends to achieve an angular travel of±10 mrad and steers a 25 mm mirror aperture.A planar flexure with beam flexures accompanied in parallel with an axial flexure build-up mechanism configuration.Compliant mechanismbased RPM ensures high precision and compactness.Compliance characteristics are established based on the stiffness matrix method for four different planar flexure layouts.One layout with best in-plane rotational compliance is then assessed for performance sensitivity to mechanism dimension parameters and parasitic error,thus informing the design space.Rotational stiffness in both the inplane rotational axes and stress is determined based on finite element analysis(FEA).The wire electrical discharge machining(EDM)is employed for developing the proof of concept for the RPM and is then assembled in FSM.Experiments are conducted to determine the rotational stiffness and angular travel about both in-plane rotational axes.Comparison among theoretical,numerical and experiments reveal excellent linearity of rotational stiffness along the rotational travel range.The maximum theoretical error is less than 5.5%compared with FEA while,the experimental error has a mean of 5%and 3%for both rotational axes thus satisfying the intended design requirement.

Macroscopic assembled graphene nanofilms based room temperature ultrafast mid-infrared photodetectors

Graphene with linear energy dispersion and weak electron-phonon interaction is highly anticipated to harvest hot electrons in a broad wavelength range.However,the limited absorption and serious backscattering of hot-electrons result in inadequate quantum yields,especially in the mid-infrared range.Here,we report a macroscopic assembled graphene(nMAG)nanofilm/silicon heterojunction for ultrafast mid-infrared photodetection.The assembled Schottky diode works in 1.5-4.0μm at room temperature with fast response(20-30 ns,rising time,4 mm2 window)and high detectivity(1.61011 to 1.9109 Jones from 1.5 to 4.0μm)under the pulsed laser,outperforming single-layer-graphene/silicon photodetectors by 2-8 orders.These performances are attributed to the greatly enhanced photo-thermionic effect of electrons in nMAG due to its high light absorption(~40%),long carrier relaxation time(~20 ps),low work function(4.52 eV),and suppressed carrier number fluctuation.The nMAG provides a long-range platform to understand the hot-carrier dynamics in bulk 2D materials,leading to broadband and ultrafast MIR active imaging devices at room temperature.