Coordinating Preventive Strategies and Restoration under Extreme Weather Conditions

It has been well identified that the extreme events significantly impact the system operation. In this work, a comprehensive operating strategy, which coordinates the preventive strategies and system restoration, was proposed. A re-dispatch model that limits the potential loss under extreme events, as well as provides adequate resources for system restoration after the extreme events, was proposed. An optimal power flow based method was established to solve the proposed model. The availabilities of components and the remaining system due to the extreme events were restored by extending the EPRI’s System Restoration Navigator (SRN) with a little modification. Case studies demonstrate the proposed model and methods.

Detection of Nonlinear Behavior Induced by Hard Limiting in Voltage Source Converters in Wind Farms Based on Higher-order Spectral Analysis

In recent years,sub-synchronous oscillation accidents caused by wind power integration have received extensive attention.The recorded constant-amplitude waveforms can be induced by either linear or nonlinear oscillation mechanisms.Hence,the nonlinear behavior needs to be distinguished prior to choosing the analysis method.Since the 1960s,the higher-order statistics(HOS)theory has become a powerful tool for the detection of nonlinear behavior(DNB)in production quality control wherein it has mainly been applied to mechanical condition monitoring and fault diagnosis.This study focuses on the hard limiters of the voltage source converter(VSC)control systems in the wind farms and attempts to detect the nonlinear behavior caused by bi-or uni-Iateral saturation hard limiting using the HOS analysis.First,the conventional describing function is extended to obtain the detailed frequency domain information on the bi-and uni-Iateral saturation hard limiting.Furthermore,the bi-and tri-spectra are introduced as the HOS,which are extended into bi-and tri-coherence spectra to eliminate the effects of the linear parts on the harmonic characteristics of hard limiting in the VSC control system,respectively.The effectiveness of the HOS in the DNB and the classification of the hard-limiting types is proven,and its detailed derivation and estimation procedure is presented.Finally,the quadratic and cubic phase coupling in the signals is illustrated,and the performance of the proposed method is evaluated and discussed.

Exploration of Artificial-intelligence Oriented Power System Dynamic Simulators

With the rapid development of artificial intelligence(AI),it is foreseeable that the accuracy and efficiency of dynamic analysis for future power system will be greatly improved by the integration of dynamic simulators and AI.To explore the interaction mechanism of power system dynamic simulations and AI,a general design for AI-oriented power system dynamic simulators is proposed,which consists of a high-performance simulator with neural network supportability and flexible external and internal application programming interfaces(APIs).With the support of APIs,simulation-assisted AI and AIassisted simulation form a comprehensive interaction mechanism between power system dynamic simulations and AI.A prototype of this design is implemented and made public based on a highly efficient electromechanical simulator.Tests of this prototype are carried out in four scenarios including sample generation,AI-based stability prediction,data-driven dynamic component modeling,and AI-aided stability control,which prove the validity,flexibility,and efficiency of the design and implementation for AI-oriented power system dynamic simulators.

前导肽介导的蛋白折叠机制及其对脂肪酶影响的研究进展

大多数蛋白质的形成过程主要由合成前体蛋白和合成功能蛋白两个步骤组成。在这个过程中,前导肽能够辅助蛋白质折叠或抑制它的活性。前导肽作为脂肪酶结构中重要的一段多肽链,通常作为分子内分子伴侣来辅助脂肪酶的折叠,同时该序列上包括糖基化位点在内的一些特殊位点,对酶的活性、极端环境稳定性、甲醇耐受性和底物特异性等性质具有重要影响。研究前导肽介导的蛋白折叠机制,以及前导肽对脂肪酶的作用和影响,可以实现通过改变前导肽来调控脂肪酶成熟肽性能的目的,进一步拓展蛋白质工程的研究。

Optimal power flow calculation in AC/DC hybrid power system based on adaptive simplified human learning optimization algorithm

This paper employs an efficacious analytical tool,adaptive simplified human learning optimization(ASHLO)algorithm,to solve optimal power flow(OPF)problem in AC/DC hybrid power system,considering valve-point loading effects of generators,carbon tax,and prohibited operating zones of generators,respectively.ASHLO algorithm,involves random learning operator,individual learning operator,social learning operator and adaptive strategies.To compare and analyze the computation performance of the ASHLO method,the proposed ASHLO method and other heuristic intelligent optimization methods are employed to solve OPF problem on the modified IEEE 30-bus and 118-bus AC/DC hybrid test system.Numerical results indicate that the ASHLO method has good convergent property and robustness.Meanwhile,the impacts of wind speeds and locations of HVDC transmission line integrated into the AC network on the OPF results are systematically analyzed.