Simulation and Management of Distributed Generating Units using Intelligent Techniques
Distributed generation is attracting more attention as a viable alternative to large centralized generation plants, driven by the rapidly evolving liberalization and deregulation environments. This interest is also motivated by the need for eliminating the unnecessary transmission and distribution costs, reducing the greenhouse gas emissions, deferring capital costs and improving the availability and reliability of electrical networks. Therefore, distributed generation is expected to play an increasingly important role in meeting future power generation requirements and to provide consumers with flexible and cost effective solutions for many of their energy needs. However, the integration of these sources into the electrical networks can cause some challenges regarding their expected impacts on the security and the dynamic behaviour of the entire network. It is essential to study these issues and to analyze the performance of the expected future systems to ensure satisfactory operation and to maximize the benefits of utilizing the distributed resources. The thesis focuses on some topics related to the dynamic simulation and operation of distributed generating units, specifically fuel cells and micro-turbines. The objective of this dissertation is to put emphasis on the following aspects: Dynamic modelling of fuel cells: Analyzing electrical power systems requires suitable dynamic models for all components forming the system. Since fuel cell units represent new promising sources, the research ascribes special consideration to developing models that describe their dynamic behaviour. It is envisaged to develop a simple and flexible model for stability studies and controller-design purposes in addition to an exhaustive nonparametric model for detailed analysis of the fuel cells. Simulation of a large number of DG units incorporated into a multi-machine network: With large numbers of distributed sources, it is expected that decentralized generation impacts the dynamic behaviour of the high voltage network. Therefore, it is intended to investigate the case, where several fuel cells and micro-turbines are integrated into the distribution system of a multi-machine network. This can help in studying the operation of the entire network and highlighting the mutual impact of the high-voltage and low-voltage networks on each other. Dynamic modelling and simulation of hybrid fuel cell/micro-turbine units: The hybrid configuration of fuel cells and micro-turbines exhibits many advantages enabling this technology to represent a considerable percentage of the next advanced power generation systems. The dynamic performance of such units, however, is still not fully understood. Hence, it is desirable for understanding their behaviour to highlight the dynamic interdependencies between the fuel cell and the micro-turbine, the overall system transient performance, and the dynamic control requirements. Dynamic equivalents of distribution power networks: The need for fast and simplified analysis of interconnected power networks obligates developing robust dynamic equivalents for certain electrical power subsystems. Nonparametric dynamic equivalents will avoid the identification of complicated mathematical models, which would adequately reflect the performance of the replaced network under various operating conditions. For distribution systems, the equivalent model has to take into consideration the characteristics of distributed generating units which are mostly connected to the network through inverters and in some cases their operating principles are not based on the electromechanical energy conversion mechanism. Impact of distributed generation on the stability of power systems: The existence of distributed sources with large numbers can impact the stability of the power system considerably. Angle-stability, frequency stability as well as voltage stability can be affected when the power from these units increases. It is essential to study this impact to ensure secure operation of the power system. Therefore, it is envisaged to study the performance of a hypothetical network and to demonstrate different stability classes at different penetration levels of the distributed generating units. Online management of fuel cells and micro-turbines for residential applications: The optimal management of the power in distributed generation for residential applications can significantly reduce the operating cost and contribute towards improving their economic feasibility. The management process, however, has to be accomplished in the online mode and to account for all decision variables that affect the setting values. Therefore, it is aimed to develop an online intelligent strategy to manage the power generated in fuel cells and micro-turbines when used to supply residential loads in order to minimize the daily operating cost and achieve an overall reduction in the electricity price.