Measurements, Models, Systems and Design

531 s.

Nonlinear Systems

Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in physics and mathematics, as well as in many other fields, as highly correlated nonlinear phenomena, evolving over a large range of time scales and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods. The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects. Potential topics include, but are not limited to: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems

Medium voltage DC power systems on ships: An offline parameter estimation for tuning the controllers' linearizing function

Future shipboard power systems using Medium Voltage Direct (MVDC) technology will be based on a widespread use of power converters for interfacing generating systems and loads with the main DC bus. Such a heavy exploitation makes the voltage control challenging in the presence of tightly controlled converters. By modeling the latter as constant power loads (CPLs), one possibility to ensure the bus voltage stability is offered by the linearizing via state feedback technique, whose aim is to regulate the generating DC-DC power converters to compensate for the destabilizing effect of the CPLs. Although this method has been shown to be effective when system parameters are perfectly known, only a partial linearization can be ensured in case of parameter mismatch, thus, jeopardizing the system stability. In order to improve the linearization, therefore, guaranteeing the voltage stability, an estimation method is proposed in this paper. To this aim, offline tests are performed to provide the input data for the estimation of model parameters. Such estimated values are subsequently used for correctly tuning the linearizing function of the DC-DC converters. Simulation results for bus voltage transients show that in this way converters become sources of stabilizing power

SciTech News Volume 70, No. 2 (2016)

Table of Contents: Columns and Reports From the Editor 3 Division News Science-Technology Division 4 New Members 6 Chemistry Division 7 New Members11 Engineering Division 12 Aerospace Section of the Engineering Division 17 Reviews Sci-Tech Book News Reviews 1

New Analysis Framework for Transient Stability Evaluation of DC Microgrids

Because of the low inertia of dc microgrids, system state variables are easily changed acutely after being disturbed. Hence, dc microgrids meet the serious transient stability issues especially for some stressed states. But the transient stability analysis is a very challenging problem since the dc microgrid system is high-order and nonlinear. To offer a new and more effective analysis framework, this paper proposes a nonlinear decoupling method to evaluate the transient stability of dc microgrids. The proposed nonlinear decoupling method takes full consideration of the nonlinearity of the dc microgrid system and approximately transforms the original nonlinear system into a series of decoupled first-order quadratic or second-order quadratic systems. For these decoupled low-order quadratic systems, their dynamics and stability can be analyzed easily, then the transient stability of the original system can be reflected indirectly. Also, the nonlinear decoupling based analysis framework can be extended to other power electronics dominated power systems to evaluate their transient stability. The accuracy of the proposed analysis method has been validated through related case studies

Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems

Fault detection, control, and forecasting have a vital role in renewable energy systems (Photovoltaics (PV) and wind turbines (WTs)) to improve their productivity, ef?ciency, and safety, and to avoid expensive maintenance. For instance, the main crucial and challenging issue in solar and wind energy production is the volatility of intermittent power generation due mainly to weather conditions. This fact usually limits the integration of PV systems and WTs into the power grid. Hence, accurately forecasting power generation in PV and WTs is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. Also, accurate and prompt fault detection and diagnosis strategies are required to improve efficiencies of renewable energy systems, avoid the high cost of maintenance, and reduce risks of fire hazards, which could affect both personnel and installed equipment. This book intends to provide the reader with advanced statistical modeling, forecasting, and fault detection techniques in renewable energy systems