Thermoplastic materials aging under various stresses

The most popular cable insulation material used is XLPE due to its excellent electrical and thermal properties. However, it does not lend itself to ease of recycling. As a result of an increase in concern worldwide regarding environmental protection, it is the objective of this work to investigate whether a thermoplastic material could be used to replace XLPE for cable insulation. Among thermoplastic materials, HDPE is regarded as one with the most similar properties as XLPE. Although it is clear that the performance of polymeric material changes with different stresses, especially polymer nanocomposites aging process under AC electric field stresses, there are also not many publications on how a superimposed AC voltage would affect the insulation’s performance in HVDC power systems. This paper reports the dielectric properties of HDPE under thermo-electrical stresses. DC stress with and without a superimposed AC stress were applied in the experiments undertaken. The degradation of materials with change in frequencies are summarized and discussed

Enhancement of performance and response time of cascaded vsc statcom in the presence of voltage variation and low power factor

The power system is an extremely non-linear system with several interconnected loads. When several loads are suddenly connected at distribution ends or when the power system is subjected to the fault, the stability of the system will be disturbed. The major problems here are the voltage sag, voltage swell and low power factor (PF). A static synchronous compensator (STATCOM) is one of the most effective flexible alternating current transmission systems (FACTS) device that can inject or absorb proper reactive power to retrieve the reliability of the grid-connected systems in presence of mentioned disturbances. STATCOM circuit comprises a control circuit, voltage source converter (VSC), and PWM technique. The STATCOM performance is mainly relying on how accurately and quickly the error signal (input of control unit) is compensated. Various controllers for STATCOM control circuit have been proposed to regulate its performance, artificial neural network (ANN)- based STATCOM control circuit is the dominant and liberal solution for enhancing STATCOM performance during the period of different disturbances. The recent researches are training ANN-based STATCOM upon tackling one or two case of disturbances, which leads to creating a weak and unreliable STATCOM during the period of other disturbances that could happen through normal daily operations, whereby the STATCOM will work in reliability if ANN trains on a different range of operating states. Also, although space vector PWM (SVPWM) that uses with STATCOM is an advanced PWM method and possibly the best among all the PWM techniques, the currently used SVPWM circuit is considered complexity since it requires the calculation of switching time and sector identification. Moreover, even-though the PWM technique and VSC are parts of the STATCOM circuit, there is a lack of investigation on the effect of VSC level and switching frequency on enhancement of performance and response time while tackling disturbances. In this thesis, a developed approach for the STATCOM circuit has been introduced. The proposed STATCOM circuit includes a modified circuit of SVPWM to reduce the implementation complexity in conventional technique, hence minimizing volumetric size, and a reliable ANN control unit able to enhance performance and response time in terms of improving voltage magnitude, power factor (PF) amplitude, and STATCOM current's total harmonic distortion (THD) in the presence of five various types of disturbances, which are voltage sag ( SLG and LL fault case), voltage swell, lagging PF load, and leading PF load. Also, this thesis presented the characteristic responses of affecting factors (VSC level and switching frequency) that enhances STATCOM performance and its response time while tackling aforementioned disturbances. The simulation outcomes showed that the developed STATCOM circuit was able to enhance voltage and PF rapidly in 0.02 sec with THD less than 5% during all disturbances. Moreover, the results of changing the factors from the point of VSC level and switching frequency have proven the possibility of enhancing response time and performance of STATCOM, whereby the response time and improvement in bus voltage increase when the STATCOM based on 5-level VSC rather than 3-level VSC. In contrast, response time decreases without enhancement in voltage when the switching frequency is raising, whereas the PF amplitude and THD value are enhanced once the VSC level and switching frequency increases

System identification and adaptive current balancing ON/OFF control of DC-DC switch mode power converter

PhD ThesisReliability becomes more and more important in industrial application of Switch Mode Power Converters (SMPCs). A poorly performing power supply in a power system can influence its operation and potentially compromise the entire system performance in terms of efficiency. To maintain a high reliability, high performance SMPC effective control is necessary for regulating the output of the SMPC system. However, an uncertainty is a key factor in SMPC operation. For example, parameter variations can be caused by environmental effects such as temperature, pressure and humidity. Usually, fixed controllers cannot respond optimally and generate an effective signal to compensate the output error caused by time varying parameter changes. Therefore, the stability is potentially compromised in this case. To resolve this problem, increasing interest has been shown in employing online system identification techniques to estimate the parameter values in real time. Moreover, the control scheme applied after system identification is often called “adaptive control” due to the control signal selfadapting to the parameter variation by receiving the information from the system identification process. In system identification, the Recursive Least Square (RLS) algorithm has been widely used because it is well understood and easy to implement. However, despite the popularity of RLS, the high computational cost and slow convergence speed are the main restrictions for use in SMPC applications. For this reason, this research presents an alternative algorithm to RLS; Fast Affline Projection (FAP). Detailed mathematical analysis proves the superior computational efficiency of this algorithm. Moreover, simulation and experiment result verify this unique adaptive algorithm has improved performance in terms of computational cost and convergence speed compared with the conventional RLS methods. Finally, a novel adaptive control scheme is designed for optimal control of a DC-DC buck converter during transient periods. By applying the proposed adaptive algorithm, the control signal can be successfully employed to change the ON/OFF state of the power transistor in the DC-DC buck converter to improve the dynamic behaviour. Simulation and experiment result show the proposed adaptive control scheme significantly improves the transient response of the buck converter, particularly during an abrupt load change conditio

New Control Algorithms for the Robust Operation and Stabilization of Active Distribution Networks

The integration of renewable distributed generation units (DGs) alters distribution systems so that rather than having passive structures, with unidirectional power flow, they become active distribution networks (ADNs), with multi-directional power flow. While numerous technical, economic, and environmental benefits are associated with the shift toward ADNs, this transition also represents important control challenges from the perspective of both the supervisory and primary control of DGs. Voltage regulation is considered one of the main operational control challenges that accompany a high penetration of renewable DGs. The intermittent nature of renewable energy sources, such as wind and solar energy, can significantly change the voltage profile of the system and can interact negatively with conventional schemes for controlling on-load tap changers (OLTCs). Another factor is the growing penetration of plug-in electric vehicles (PEVs), which creates additional stress on voltage control devices due to their stochastic and concentrated power profiles. These combined generation and load power profiles can lead to overvoltages, undervoltages, increases in system losses, excessive tap operation, infeasible solutions (hunting) with respect to OLTCs, and/or limits on the penetration of either PEVs or DGs. With regard to the dynamic control level, DG interfaces are typically applied using power electronic converters, which lack physical inertia and are thus sensitive to variations and uncertainties in the system parameters. Grid impedance (or admittance), which has a substantial effect on the performance and stability of primary DG controllers, is nonlinear, time-varying, and not passive in nature. In addition, constant-power loads (CPLs), such as those interfaced through power electronic converters, are also characterized by inherited negative impedance that results in destabilizing effects, creating instability and damping issues. Motivated by these challenges, the research presented in this thesis was conducted with the primary goal of proposing new control algorithms for both the supervisory and primary control of DGs, and ultimately of developing robust and stable ADNs. Achieve this objective entailed the completion of four studies: Study#1: Development of a coordinated fuzzy-based voltage regulation scheme with reduced communication requirements Study#2: Integration of PEVs into the voltage regulation scheme through the implementation of a vehicle-to-grid reactive power (V2GQ) support strategy Study#3: Creation of an estimation tool for multivariable grid admittance that can be used to develop adaptive controllers for DGs Study#4: Development of self-tuning primary DG controllers based on the estimated grid admittance so that stable performance is guaranteed under time-varying DG operating points (dispatched by the schemes developed in Study#1 and Study#2) and under changing grid impedance (created by network reconfiguration and load variations). As the first research component, a coordinated fuzzy-based voltage regulation scheme for OLTCs and DGs has been proposed. The primary reason for applying fuzzy logic is that it provides the ability to address the challenges associated with imperfect information environments, and can thus reduce communication requirements. The proposed regulation scheme consists of three fuzzy-based control algorithms. The first control algorithm was designed to enable the OLTC to mitigate the effects of DGs on the voltage profile. The second algorithm was created to provide reactive power sharing among DGs, which will relax OLTC tap operation. The third algorithm is aimed at partially curtailing active power levels in DGs so as to restore a feasible solution that will satisfy OLTC requirements. The proposed fuzzy algorithms offer the advantage of effective voltage regulation with relaxed tap operation and with utilization of only the estimated minimum and maximum system voltages. Because no optimization algorithm is required, it also avoids the numerical instability and convergence problems associated with centralized approaches. OPAL real-time simulators (RTS) were employed to run test simulations in order to demonstrate the success of the proposed fuzzy algorithms in a typical distribution network. The second element, a V2GQ strategy, has been developed as a means of offering optimal coordinated voltage regulation in distribution networks with high DG and PEV penetration. The proposed algorithm employs PEVs, DGs, and OLTCs in order to satisfy the PEV charging demand and grid voltage requirements while maintaining relaxed tap operation and minimum curtailment of DG active power. The voltage regulation problem is formulated as nonlinear programming and consists of three consecutive stages, with each successive stage applying the output from the preceding stage as constraints. The task of the first stage is to maximize the energy delivered to PEVs in order to ensure PEV owner satisfaction. The second stage maximizes the active power extracted from the DGs, and the third stage minimizes any deviation of the voltage from its nominal value through the use of available PEV and DG reactive power. The primary implicit objective of the third stage problem is the relaxation of OLTC tap operation. This objective is addressed by replacing conventional OLTC control with a proposed centralized controller that utilizes the output of the third stage to set its tap position. The effectiveness of the proposed algorithm in a typical distribution network has been validated in real time using an OPAL RTS in a hardware-in-the loop (HiL) application. The third part of the research has resulted in the proposal of a new multivariable grid admittance identification algorithm with adaptive model order selection as an ancillary function to be applied in inverter-based DG controllers. Cross-coupling between the and grid admittance necessitates multivariable estimation. To ensure persistence of excitation (PE) for the grid admittance, sensitivity analysis is first employed as a means of determining the injection of controlled voltage pulses by the DG. Grid admittance is then estimated based on the processing of the extracted grid dynamics by the refined instrumental variable for continuous-time identification (RIVC) algorithm. Unlike nonparametric identification algorithms, the proposed RIVC algorithm provides a parametric multivariable model of grid admittance, which is essential for designing adaptive controllers for DGs. HiL applications using OPAL RTS have been utilized for validating the proposed algorithm for both grid-connected and isolated ADNs. The final section of the research is a proposed adaptive control algorithm for optimally reshaping DG output impedance so that system damping and bandwidth are maximized. Such adaptation is essential for managing variations in grid impedance and changes in DG operating conditions. The proposed algorithm is generic so that it can be applied for both grid-connected and islanded DGs. It involves three design stages. First, the multivariable DG output impedance is derived mathematically and verified using a frequency sweep identification method. The grid impedance is also estimated so that the impedance stability criteria can be formulated. In the second stage, multi-objective programming is formulated using the -constraint method in order to maximize system damping and bandwidth. As a final stage, the solutions provided by the optimization stage are employed for training an adaptation scheme based on a neural network (NN) that tunes the DG control parameters online. The proposed algorithm has been validated in both grid-connected and isolated distribution networks, with the use of OPAL RTS and HiL applications.1 yea