No abstract

No abstract

It has been suggested that the Dupal isotopic anomaly in the mantle can be traced in the Paleozoic ophiolites from the . The Karamaili ophiolite (KO) and Dalabute ophiolite (DO) in the eastern and western corners, respectively, of the Junggar basin in NW China represent remnants of the relatively older (N 350 Ma) Paleo-Asian Ocean (PAO) crust. Thus, these ophiolites can provide additional constraints on the long-term composition and evolution of the Paleozoic suboceanic mantle. We present new major-trace element and Sr, Nd and high-precision Pb isotope data for the basalts, gabbros and a plagioclase separate from the KO and DO. Our results indicate that the PAO crust indeed has a Dupal-like isotopic signature. In detail, all samples have relatively low ε Nd(t) and high 208 Pb/ 204 Pb (t) for given 206 Pb/ 204 Pb (t) ratios (i.e., positive Δ8/4 values), similar to the Dupal isotopic characteristics of Indian Ocean mid-ocean ridge basalts (MORB). The trace element signature of DO mafic rocks is similar to that of normal-and enriched-MORB whereas that of the KO is transitional between MORB and arc basalt. Therefore, the DO mantle domain reflects the PAO asthenosphere and the KO domain additionally shows the influence of the subduction process. Geochemical modeling using Th/Nd as well as Nd and Pb isotopic ratios indicates that up to 2% subduction component had been added to a depleted Indian MORB-type mantle to produce the bulk of KO rocks. The subduction component in the KO rocks consisted of variable proportions of ≤1% partial melt of unradiogenic sediment similar to modern Izu-Bonin trench sediment and hydrous fluid dehydrated from the subducted altered oceanic crust. The Devonian asthenospheric mantle beneath the southern PAO is isotopically heterogeneous, but lends support to the idea that the Dupal isotopic anomaly existed prior to the opening of the Indian Ocean. Finally, plate tectonic reconstruction indicates that the anomaly was present in the Neo-and Paleo-Tethyan oceans in the southern hemisphere and in the southern part of PAO in the northern hemisphere during the late Paleozoic.

With the increasing penetration of renewable energy generators in power grid, traditional vector control (VC) strategy for double fed induction generator (DFIG) is unable to provide extra active power support to grid because DIFG inertia is made decoupled from grid frequency fluctuations. To solve this problem, Virtual Synchronous Generator (VSG) control strategy as well as Inertial Synchronization Control (ISynC) strategy are proposed for DFIG rotor side converter (RSC) and grid side converter (GSC) respectively, so that DFIG rotor speed will experience an acceleration or a deceleration process to release or absorb the kinetic energy stored in DFIG wind turbines, which can prevent grid frequency from deep drop or increase. However, VSG-ISynC control strategy has its limitations in that rotor speed may lose its stability when large load is added into power system, at the same time, the secondary frequency drop is serious if rotor speed has decreased lower than the admissible minimum value. To address this issue, a modified VSG (M-VSG) control strategy is proposed by dynamically changing the P-f droop coefficient of conventional VSG control strategy, aiming to expand the stability boundary of DFIG operation. Additionally, an extra rotor speed closed loop is added into VSG control strategy, which can significantly reduce serious frequency secondary drop by controlling rotor speed directly. Simulation and hardware-in-loop (HIL) verification are both carried out in RTDS & GH Bladed co-simulation research platform to verify the effectiveness of proposed M-VSG control strategy.

In this paper, a fault detection (FD) problem is studied for non-linear dynamic stochastic systems with non-Gaussian disturbances and faults (or abrupt changes of system parameters). After a filter is constructed to generate the detected error, the FD problem is reduced to an optimization problem for the error system, which is represented by a non-linear non-Gaussian stochastic system. Since generally (extended) Kalmen filtering approaches are insufficient to characterize the non-Gaussian variables, we propose the entropy optimization principle for the stochastic error system. The design objective is to maximize the entropies of the stochastic detection errors when the faults occur, and to minimize the entropies of the stochastic estimator errors resulting from the other stochastic noises. Following the formulation of the probability density functions of the stochastic error in terms of those of both the disturbances and the faults, new recursive approaches are established to calculate the entropies of the detection errors. By using the novel performance index and the formulations for the entropies, the real-time optimal FD filter design method is provided. Finally, simulations are given to demonstrate the effectiveness of the proposed FD filtering algorithms.