Development of autonomous monitoring and performance evaluation system of grid-tied photovoltaic station

This work aims to improve the existing monitoring systems MS for two grid-connected PV stations GCPVS of URERMS ADRAR, to eliminate its limitations. This improvement consists of developing an MS which is used for two PV stations with different configurations. This MS contains new LabVIEW-based monitoring software for visualizing real-time measured data and evaluating GCPVS performance. In addition, it illustrates the 2D and 3D real-time relationships of PV system parameters, which allow us to understand the dynamic behavior of PV system components. This developed monitoring software synchronizes also the various data acquisition units DAU of GCPVS, allowing simultaneous data access.To perform a reliable performance analysis and a comparative study of different GCPVS based on accurate measurements, the sensor's calibration is performed with its DAU. The MS autonomy is ensured by integrating developed PV-UPS. A graphical user interface is provided for the evaluation of PV-UPS performance.     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。     

Potential of renewable energy system utilisation at decentralised level in the state of Uttarakhand in India

ABSTRACT

Design and implementation of an effective dissemination programme for decentralised renewable energy system necessitate an accurate estimate of its utilisation potential. Hence, in this study, an attempt has been made to develop frameworks to estimate the utilisation potential of decentralised renewable energy systems in the state of Uttarakhand in India. Estimations imply large resource, technical and economic potentials of the domestic solar water heater, solar home system, solar lantern, family size biogas plant and improved biomass cookstove in Uttarakhand. With higher impact on the purchasing power of households, prevailing soft loan scheme has been found to be more appropriate than a capital subsidy for promoting the usage of decentralised renewable energy systems.     

Rogowski coil current transducer compensation method for harmonic active power error

In the harmonic active power measurement, the highest uncertainties are generally introduced by the current and voltage transducers. In a previous paper, the authors showed that the current transformer (CT) can introduce significant errors in such measurement, especially if the phase shift between voltage and current is close to ±90°. In such condition the errors on harmonic power measurement are mainly due to the CT phase displacement. This paper shows that better results can be achieved with more linear transducers, such as the Rogowski coil current transducers (RCCTs), whose metrological performance in distorted condition can be improved, by means of a proper compensation method. The proposed method for RCCTs compensation is based on the frequency response and it allows to reduce the errors on harmonic power measurement, also for phase shift close to ±90°. The study is supported by several experimental tests.     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

A web-based software tool for participatory optimization of conservation practices in watersheds

WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) is a web-based, participatory planning tool that can be used to engage with watershed stakeholder communities, and involve them in using science-based, human-guided, interactive simulation–optimization methods for designing potential conservation practices on their landscape. The underlying optimization algorithms, process simulation models, and interfaces allow users to not only spatially optimize the locations and types of new conservation practices based on quantifiable goals estimated by the dynamic simulation models, but also to include their personal subjective and/or unquantifiable criteria in the location and design of these practices. In this paper, we describe the software, interfaces, and architecture of WRESTORE, provide scenarios for implementing the WRESTORE tool in a watershed community's planning process, and discuss considerations for future developments.     

Managing readiness-relevant activities for the organizational dimension of ERP implementation

An organization requires performing readiness-relevant activities to ensure successful implementation of an enterprise resource planning (ERP) system. This paper develops a novel approach to managing these interrelated activities to get ready for implementing an ERP system. The approach enables an organization to evaluate its ERP implementation readiness by assessing the degree to which it can achieve the interrelated readiness relevant activities using fuzzy cognitive maps. Based on the interrelationship degrees among the activities, the approach clusters the activities into manageable groups and prioritizes them. To help work out a readiness improvement plan, scenario analysis is conducted.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

基于“天空地”一体化技术的安全监测系统建设与应用

西藏江达县白格村金沙江右岸于2018年10月11日和2018年11月3日先后发生2次大规模滑坡—堰塞湖堵江事件,溃堰洪水对下游拉哇库区不良地质体的稳定性造成不同程度的影响。为保障下游水电站建设安全,对拉哇库区主要不良地质体建立了基于星载InSAR技术、无人机技术和地面传感器实时监测的“天空地”一体化监测预警体系,以多维空间采集技术获取变形信息,通过智能监控平台对信息及时进行处理、分析和可视化呈现,利用平台、短信等方式向相关人员进行分级告警,取得了较好的应用效果。