Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China

Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost

On the geometry of wave solutions of a delayed reaction-diffusion equation

The aim of this paper is to study the existence and the geometry of positive bounded wave solutions to a non-local delayed reaction-diffusion equation of the monostable type.Comment: 25 pages, several important modifications are made. Some references added to the previous versio

Function value-based multi-objective optimisation of reheating furnace operations using Hooke-Jeeves algorithm

Improved thermal efficiency in energy-intensive metal-reheating furnaces has attracted much attention recently in efforts to reduce both fuel consumption, and CO2 emissions. Thermal efficiency of these furnaces has improved in recent years (through the installation of regenerative or recuperative burners), and improved refractory insulation. However, further improvements can still be achieved through setting up reference values for the optimal set-point temperatures of the furnaces. Having a reasonable expression of objective function is of particular importance in such optimisation. This paper presents a function value-based multi-objective optimisation where the objective functions, which address such concerns as discharge temperature, temperature uniformity, and specific fuel consumption, are dependent on each other. Hooke-Jeeves direct search algorithm (HJDSA) was used to minimise the objective functions under a series of production rates. The optimised set-point temperatures were further used to construct an artificial neural network (ANN) of set-point temperature in each control zone. The constructed artificial neural networks have the potential to be incorporated into a more advanced control solution to update the set-point temperatures when the reheating furnace encounters a production rate change. The results suggest that the optimised set-point temperatures can highly improve heating accuracy, which is less than 1 °C from the desired discharge temperature

Glycidyl-methacrylate-based electrospun mats and catalytic silver nanoparticles

P(AN-GMA) and PGMA fibers coated with monodisperse silver nanoparticles have been prepared by a combination of electrospinning and electroless plating. The morphology of the electrospun fibers remains unchanged after surface hydrazination. Oxidation of hydrazine in an ammoniacal solution of AgNO3 reduces and deposits silver atoms along the fiber surface, which then coalesce to Ag particles. The size of the silver nanoparticles is varied between 20-60 nm. Since the density of the active sites for silver reduction is lower in P(AN-GAAA), a smaller particle size could be obtained. The catalytic activity of the silver nanoparticles has been confirmed

Sensitive Detection of Silver Ions Based on Chiroplasmonic Assemblies of Nanoparticles

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100155/1/adom201300148.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/100155/2/adom201300148-sup-0001-S1.pd

Feasibility study of biomass gasification integrated with reheating furnaces in steelmaking process

This paper investigates the integration of biosyngas production, reheating furnace and heat recovery steam cycle, in order to use biosyngas directly as fuel in the furnace. A system model was developed to evaluate the feasibility of the proposed system from the perspective of heat and mass balance. To particularly study the impacts of fuel switching on the heating quality of the furnace, a three-dimensional furnace model considering detailed heat transfer processes was embedded into the system through an Aspen PlusTM user defined model. The simulation results show that biosyngas is suitable for direct use as fuel for reheating furnaces. Should CO capture be considered in the proposed system, it has a potential to achieve the capture without external energy input which results in so-called negative emissions of CO

Glyconanoparticles for colorimetric bioassays

Carbohydrate molecules are involved in many of the cellular processes that are important for life. By combining the specific analyte targeting of carbohydrates with the multivalent structure and change of solution colour as a consequence of plasmonic interactions with the aggregation of metal nanoparticles, glyconanoparticles have been used extensively for the development of bioanalytical assays. The noble metals used to create the nanocore, the methodologies used to assemble the carbohydrates on the nanoparticle surface, the carbohydrate chosen for each specific target, the length of the tether that separates the carbohydrate from the nanocore and the density of carbohydrates on the surface all impact on the structural formation of metal based glyconanoparticles. This tutorial review highlights these key components, which directly impact on the selectivity and sensitivity of the developed bioassay, for the colorimetric detection of lectins, toxins and viruses

Dark-Exciton-Mediated Fano Resonance from a Single Gold Nanostructure Deposited on Monolayer WS2 at Room Temperature

Strong spatial confinement and highly reduced dielectric screening provide monolayer transition metal dichalcogenides (TMDCs) with strong many-body effects, thereby possessing optically forbidden excitonic states (i.e., dark excitons) at room temperature. Herein, we explore the interaction of surface plasmons with dark excitons in hybrid systems consisting of stacked gold nanotriangles (AuNTs) and monolayer WS2. We observe a narrow Fano resonance when the hybrid system is surrounded by water, and we attribute the narrowing of the spectral Fano linewidth to the plasmon-enhanced decay of dark K-K excitons. Our results reveal that dark excitons in monolayer WS2 can strongly modify Fano resonances in hybrid plasmon-exciton systems and can be harnessed for novel optical sensors and active nanophotonic devices

Detection and monitoring of the multiple inflammatory responses by photoacoustic molecular imaging using selectively targeted gold nanorods

In vitro cell experiments have been performed to detect and monitor the upregulation of intercellular adhesion molecule-1 (ICAM-1) and E-selectin simultaneously by photoacoustic molecular imaging (PMI). Human umbilical vein endothelial cells (HUVECs) were grown on gelatin-coated glass slides and stimulated with inflammatory cytokines to induce the expression of the inflammatory biomarkers, ICAM-1 and E-selectin. Gold nanorods (GNRs) of aspect ratio (AR) 1:3 with absorption centered at 715 nm conjugated to anti-ICAM-1 antibody and GNRs of AR 1:3.5 with absorption centered at 800 nm conjugated to anti-E-selectin were exposed to HUVECs with different stimulation conditions. A focused high frequency ultrasonic transducer (60 MHz, f/1.5) was used to scan the photoacoustic (PA) signal over the top surface of the cell containing slides. Averaged PA signal intensity from the stimulated cells was about 3 folds higher (~10 dB) compared to the un-stimulated cells for both ICAM-1 and E-selectin. The strong binding of GNRs to the stimulated HUVEC cells was evidenced by fluorescence imaging. Exposure of HUVEC cells to GNRs conjugated to isotype control antibodies confirms a low level non-specific binding. Also, at 0, 2, 6, and 24 hours after inflammatory stimulation, the HUVECs were exposed to GNRs conjugated anti-ICAM-1 antibody and anti-E-selectin antibody. PA intensity at each stage of inflammation compares well with fluorescence imaging and rt-PCR quantification