With the rapid evolution of technology, growing accessibility, and environmental appeal of wind and solar electric systems, distributed generation (DG) has been pushed from the fringe to a mainstream factor in the grid. However, due to the randomness and uncertainty of environmental and operational conditions, DG also brings many risks and may adversely affect the reliability and safety of the power grid when connected to the distribution network. Therefore, it is necessary to introduce the risk theory into the allocation and placement of DGs. This paper establishes a comprehensive set of risk and economic indexes by modeling the randomness and uncertainty of DG outputs. In addition, islanded operation, which is a promising development direction of microgrids, is explicitly studied and the related indexes are modeled. Putting them together, we propose a risk-based multi-objective optimal allocation model to optimize the placement and configuration of DGs and provide a reliable and cost-effective system. We solve the formulated multi-objective optimization problem by combining the gradient particle swarm optimization algorithm and the bacterial foraging algorithm. We demonstrate the validity and rationality of the proposed method through the analyses of the American PG&E 69-node system.
Base-isolated buildings subjected to extreme earthquakes or near-fault pulse-like earthquakes can exceed their design gap distance and impact against the surrounding moat wall. Based on equating energy dissipation and maximum collision compression deformation of isolated structure with the Hertz-damp model and Kevin-Voigt model in the process of collision, an equivalent linear impact model (ELIM) is proposed to better predict impact response of seismic isolated structure. The formula of the equivalent linear stiffness of ELIM is theoretically derived. The effectiveness of ELIM is verified by comparing the results of numerical analyses with the results of pounding experiments. Four near-fault earthquakes are selected to validate rationality and accuracy of the proposed model using numerical analysis. The results indicate that the proposed linear model can nearly capture impact behavior of isolated structure in simulating the pounding-involved structural response.
An experimental study was conducted to investigate the dynamic ice accretion process over the suction-side and pressure-side surfaces of a wind turbine blade with a DU91-W2-250 airfoil profile to elucidate the impact of angle of attack (AoA) on the underlying physics of the active pitch control (APC) technique for wind turbine icing mitigation. A glaze ice condition was simulated for this experiment in the Icing Research Tunnel of Iowa State University (ISU-IRT) with an ambient temperature T∞ =-5 °C, an oncoming flow velocity U ∞ = 40 m/s, and a liquid water content (LWC) level LWC = 3.0 g/m 3. Four typical AoAs (i.e. 0 °, 5 °, 10 °, and 15 °) were selected to represent the most commonly-used operation conditions of wind turbine blades. A high-speed imaging system was utilized to quantitatively measure the transient behaviors of water runback and the dynamic ice accretion process over the blade model surface. Simultaneously, an infrared (IR) thermal imaging system was also used to provide time evolutions of surface temperature distributions during the icing process. The experimental results show that AoA can affect the dynamic ice accretion process over the turbine blade model surface significantly. The ice impacted region over the suction-side surface and pressure-side surfaces decrease and increase, respectively, as AoA increases. The temperature distributions over both sides of the test model surface varies significantly with respect to AoA. Two 'peak' regions instead of the usual one have been observed in the measured surface temperature distributions due to the surface water runback over the ice accreting blade model surface. The upstream 'peak' region appears near the LE due to the locally larger liberation of latent heat with higher water collection. The location of downstream 'peak' region varies depending on AoA. As AoA increases, the downstream 'peak' moves upward over the suction-side surface and moves further downstream over the pressure-side surface. A water/ice film stretching from the TE towards the LE has been identified. The ice accretion near the LE leads to large-scale flow separations near the TE, which is responsible for this interesting phenomenon.
Developing high-efficiency lubricant additives and high-performance green cutting fluids has universal significance for maximizing processing efficiency, lowering manufacturing cost, and more importantly reducing environmental concerns caused by the use of conventional mineral oil-based cutting fluids. In this study, a nanocomposite is synthesized by filling sulfurized isobutylene (T321) into acid-treated carbon nanotubes (CNTs) with a liquid-phase wet chemical method. The milling performance of a nanocutting fluid containing CNTs@T321 composites is assessed using a micro-lubrication technology in terms of cutting temperature, cutting force, tool wear, and surface roughness. The composite nanofluid performs better than an individual CNT nanofluid regarding milling performance, with 12%, 20%, and 15% reductions in the cutting force, machining temperature, and surface roughness, respectively. The addition of CNTs@T321 nanocomposites improves the thermal conductivity and wetting performance of the nanofluid, as well as produces a complex lubricating film by releasing T321 during machining. The synergistic effect improves the cutting state at the tool–chip interface, thereby resulting in improved machining performance.
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