Stabilised Control of Converter Interfaced DERs for Reliable Operation of Microgrid and Microgrid Clusters

This thesis aims to achieve a stabilised control of converter interfaced DER for the reliable and resilient operation of microgrid and microgrid clusters. The suitability of voltage and current control for VSCs is evaluated and corrective measures are proposed to stabilise converter operation. Furthermore, the accurate power demand distribution in islanded MGs and interconnected MGs are ensured by advanced control strategies. The proposal presented in the thesis is verified both through simulation and experimental work

Voltage Rise Problem in Distribution Networks with Distributed Generation: A Review of Technologies, Impact and Mitigation Approaches

Energy demand has constantly been on the rise due to aggressive industrialization and civilization. This rise in energy demand results in the massive penetration of distributed generation (DG) in the distribution network (DN) which has been a holistic approach to enhance the capacity of distribution networks. However, this has led to a number of issues in the low voltage network, one of which is the voltage rise problem. This happens when generation exceeds demand thereby causing reverse power flow and consequently leading to overvoltage. A number of methods have been discussed in the literature to overcome this challenge ranging from network augmentation to active management of the distribution networks. This paper discusses the issue of voltage rise problem and its impact on distribution networks with high amounts of distributed energy resources (DERs). It presents different DG technologies such as those based on conventional and unconventional resources and other DERs such as battery storage systems and fuel cells. The study provides a comprehensive overview of approaches employed to curtail the issue of voltage increase at the point of common coupling (PCC), which includes strategies based on the network reinforcement methodology and the active distribution network management. A techno-economic comparison is then introduced in the paper to ascertain the similarities and dissimilarities of different mitigation approaches based on the technology involved, ease of deployment, cost implication, and their pros and cons. The paper provides insights into directions for future research in mitigating the impact of voltage rise presented by grid-connected DGs without limiting their increased penetration in the existing power grid

Investigation of FACTS devices to improve power quality in distribution networks

Flexible AC transmission system (FACTS) technologies are power electronic solutions that improve power transmission through enhanced power transfer volume and stability, and resolve quality and reliability issues in distribution networks carrying sensitive equipment and non-linear loads. The use of FACTS in distribution systems is still in its infancy. Voltages and power ratings in distribution networks are at a level where realistic FACTS devices can be deployed. Efficient power converters and therefore loss minimisation are crucial prerequisites for deployment of FACTS devices. This thesis investigates high power semiconductor device losses in detail. Analytical closed form equations are developed for conduction loss in power devices as a function of device ratings and operating conditions. These formulae have been shown to predict losses very accurately, in line with manufacturer data. The developed formulae enable circuit designers to quickly estimate circuit losses and determine the sensitivity of those losses to device voltage and current ratings, and thus select the optimal semiconductor device for a specific application. It is shown that in the case of majority carrier devices (such as power MOSFETs), the conduction power loss (at rated current) increases linearly in relation to the varying rated current (at constant blocking voltage), but is a square root of the variable blocking voltage when rated current is fixed. For minority carrier devices (such as a pin diode or IGBT), a similar relationship is observed for varying current, however where the blocking voltage is altered, power losses are derived as a square root with an offset (from the origin). Finally, this thesis conducts a power loss-oriented evaluation of cascade type multilevel converters suited to reactive power compensation in 11kV and 33kV systems. The cascade cell converter is constructed from a series arrangement of cell modules. Two prospective structures of cascade type converters were compared as a case study: the traditional type which uses equal-sized cells in its chain, and a second with a ternary relationship between its dc-link voltages. Modelling (at 81 and 27 levels) was carried out under steady state conditions, with simplified models based on the switching function and using standard circuit simulators. A detailed survey of non punch through (NPT) and punch through (PT) IGBTs was completed for the purpose of designing the two cascaded converters. Results show that conduction losses are dominant in both types of converters in NPT and PT IGBTs for 11kV and 33kV systems. The equal-sized converter is only likely to be useful in one case (27-levels in the 33kV system). The ternary-sequence converter produces lower losses in all other cases, and this is especially noticeable for the 81-level converter operating in an 11kV network

Protection of Active Distribution Networks and Their Cyber Physical Infrastructure

Today’s Smart Grid constitutes several smaller interconnected microgrids. However, the integration of converter-interfaced distributed generation (DG) in microgrids has raised several issues such as the fact that fault currents in these systems in islanded mode are way less than those in grid connected microgrids. Therefore, microgrid protection schemes require a fast, reliable and robust communication system, with backup, to automatically adjust relay settings for the appropriate current levels according to the microgrid’s operation mode. However, risks of communication link failures, cyber security threats and the high cost involved to avoid them are major challenges for the implementation of an economic adaptive protection scheme. This dissertation proposes an adaptive protection scheme for AC microgrids which is capable of surviving communication failures. The contribution is the use of an energy storage system as the main contributor to fault currents in the microgrid’s islanded mode when the communication link fails to detect the shift to the islanded mode. The design of an autonomous control algorithm for the energy storage’s AC/DC converter capable of operating when the microgrid is in both grid-connected and islanded mode. Utilizing a single mode of operation for the converter will eliminate the reliance on communicated control command signals to shift the controller between different modes. Also, the ability of the overall system to keep stable voltage and frequency levels during extreme cases such as the occurrence of a fault during a peak pulse load period. The results of the proposed protection scheme showed that the energy storage -inverter system is able to contribute enough fault current for a sufficient duration to cause the system protection devices to clear the fault in the event of communication loss. The proposed method was investigated under different fault types and showed excellent results of the proposed protection scheme. In addition, it was demonstrated in a case study that, whenever possible, the temporary disconnection of the pulse load during the fault period will allow the utilization of smaller energy storage device capacity to feed fault currents and thus reduce the overall expenditures. Also, in this dissertation we proposed a hybrid hardware-software co-simulation platform capable of modeling the relation between the cyber and physical parts to provide a protection scheme for the microgrid. The microgrid was simulated on MATLAB/Simulink SimPowerSystems to model the physical system dynamics, whereas all control logic was implemented on embedded microcontrollers communicating over a real network. This work suggested a protection methodology utilizing contemporary communication technologies between multi-agents to protect the microgrid

Framework for assessment of economic feasibility of voltage sag mitigation solutions

Current practices of power quality mitigation in the industry are characterized by sub-optimal investment decisions where over compensation is often the norm such causing huge wastage in financial resources. Providing power quality management services to industrial customers in the form of power quality contracts could yield substantial return for the network operator. With better understanding of network parameters, and the option of installing network level mitigation devices, network operators could employ wider range of cost effective mitigation solutions. Tapping into the market however, entails bearing the risks for the customers which network operators are not always willing or encouraged to do. With potentially millions at stake, extensive risk assessments are crucial for any proposed power quality management scheme. This thesis investigates the voltage sag aspect of the problem as part of a larger power quality management scheme. The aim is to develop general framework for technical and financial assessments of voltage sags prior to the introduction of power quality management service. The thesis focuses on five major aspects of voltage sag assessment: identification of customer requirement, financial loss assessment, network sag performance estimation, sag mitigation, and financial appraisal of mitigating solutions. The first part of the thesis gives a comprehensive overview of current power quality problems faced by industrial customers and provides ranges of typical financial losses incurred by different types of industries around the world. It then proposes robust methodology for assessment of typical financial loss, i.e., customized customer damage function (CCDF), for a given industry based on available survey data and taking into account characteristics of the assessed customer plant. For failure and financial risk assessments, the thesis introduces new customer models employing probabilistic methods to quantify risks induced by voltage sags and proposes generic models that incorporate full flexibility in failure risk assessment, taking into account the effect of unbalanced sags on equipment behavior. It further quantifies the error introduced by sag performance estimation using limited monitoring data with a case study on actual sag profile. It demonstrates how different estimation methods and different durations of monitoring period affect accuracy of estimation of voltage sag profile and associated risk of industrial process failure. Following this, the thesis presents new models for plant and network level sag mitigation devices. They include power injecting mitigation devices, devices that reduce number of faults in the network and devices that reduce the severity of faults. Developed models are then used to investigate the cost-effectiveness of sag mitigation at different levels. Finally, the thesis presents Genetic Algorithm based methodology for deciding on optimal investment scheme in voltage sag mitigation in the network. The sensitivity of the solution to various influential parameters, including plant type and size, sensitive equipment type, process characteristics, financial loss resulting from process interruption, cost and effectiveness of mitigating solution and network fault rates is also established.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods