Today’s power systems are based on a centralised system and distribution networks that are considered as passive terminations of transmission networks. The high penetration of Distributed Generation (DG) at the distribution network level has created many challenges for this structure. New tools and simulation approaches are required to address the subject and to quantify the dynamic characteristics of the system. A distribution network or part of it with DG, Active Distribution Network Cell (ADNC), can no longer be considered as passive. An equivalent dynamic model of ADNC is therefore extremely important, as it enables power system operators to quickly estimate the impact of disturbances on the power system’s dynamic behaviour. A dynamic equivalent model works by reducing both the complexity of the distribution network and the computation time required to run a full dynamic simulation. It offers a simple and low-order representation of the system without compromising distribution network dynamic characteristics and behaviour as seen by the external grid. This research aims to develop a dynamic equivalent model for ADNC. It focuses on the development of an equivalent model by exploiting system identification theory, i.e. the grey-box approach. The first part of the thesis gives a comprehensive overview and background of the dynamic equivalent techniques for power systems. The research was inspired by previous work on system identification theory. It further demonstrates the theoretical concept of system identification, system load modelling and the modelling of major types of DG. An equivalent model is developed, guided by the assumed structure of the system. The problem of equivalent model development is then formulated under a system identification framework, and the parameter estimation methodology is proposed. The validation results of the effectiveness and accuracy of the developed model are presented. This includes the estimation of the parameter model using a clustering algorithm to improve the computational performance and the analysis of transformer impedance effects on the ADNC responses. The evaluation of probability density function, eigenvalue analysis and parameter sensitivity analysis for the model parameters are also presented. Typical model parameters for different network topologies and configurations are identified. Finally, the developed equivalent model is used for a large power system application. The accuracy and robustness of the developed equivalent model are demonstrated under small and large disturbance studies for various types of fault and different fault locations.

yes / The current electricity grid suffers from numerous challenges due to the lack of an effective energy management strategy that is able to match the generated power to the load demand. This problem becomes more pronounced with microgrids, where the variability of the load is obvious and the generation is mostly coming from renewables, as it depends on the usage of distributed energy sources. Building a smart microgrid would be much more economically feasible than converting the large electricity grid into a smart grid, as it would require huge investments in replacing legacy equipment with smart equipment. In this paper, application of Internet of Things (IoT) technology in different parts of the microgrid is carried out to achieve an effective IoT architecture in addition to proposing the Internet-of-Asset (IoA) concept that will be able to convert any legacy asset into a smart IoT-ready one. This will allow the effective connection of all assets to a cloud-based IoT. The role of which is to perform computations and big data analysis on the collected data from across the smart microgrid to send effective energy management and control commands to different controllers. Then the IoT cloud will send control actions to solve microgrid's technical issues such as solving energy mismatch problem by setting prediction models, increasing power quality by the effective commitment of DERs and eliminating load shedding by turning off only unnecessary loads so consumers won't suffer from power outages. The benefits of using IoT on various parts within the microgrid are also addressed.

Liberalized electricity markets, increased awareness of clean energy resources and theirdecreasing costs have resulted in large numbers of distributed power generators beinginstalled on distribution network. Installation of distributed generation has altered thepassive nature of distribution grid. A concept of Active Distribution Network is proposedwhich will enable present day infrastructure to host renewable energy resources reliably.Fault management that includes fault localization, isolation and service restoration ispart of active management of distribution networks.This thesis aims to introduce a distributed protection methodology for fault localizationand isolation. The objective is to enhance reliability of the network. Faults are identifiedbased on root mean square values of current measurements and by comparing thesevalues with preset thresholds. The method based on multi-agent concept can be usedto locate the faulty section of a distribution network and for selection of faulty phases.The nodal Bus Agent controls breakers that are associated with it. Based on indicationof fault, adjacent bus Agents communicate with each other to identify location of fault.A trip signal is then issued to corresponding Breakers in adjacent Bus Agents, isolatingthe faulty section of line. A case study was carried out to verify suitability of the proposedmethod. A meshed network model and multi-agent based protection scheme wassimulated in Simulink SimPowerSystems. Considering nature of Distribution Network,separate breakers for each phase are considered. The distribution network protectionsystem identified fault introduced in the network correctly along with interrupting thefault current.Keywords