State monitoring of future power distribution grid using micro-PMU and state estimation

• Main Author: Chen, Xuebing
• Other Authors: Rusli
• Format: Theses and Dissertations
• Language: English
• Published: 2019
• Subjects: Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution; Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries
• Online Access: https://hdl.handle.net/10356/85366; http://hdl.handle.net/10220/49230
• Institution: Nanyang Technological University

In recent years, distributed energy resources (DER) systems have increasingly played an important role in the electric power distribution system. Nevertheless, they also concurrently introduce new characteristics to the distribution system, such as bi-directional power flows, unstable power supply, unintentional islanding, and voltage profile issues. The evolvement of distribution networks necessitates rapid and accurate distribution network monitoring. Thanks to the high accuracy and synchronization of Phasor Measurement Unit (PMU) measurements, a more reliable and accurate state estimation (SE) is expected if the system is monitored using only PMU. However, so far PMUs have been used almost exclusively in transmission systems monitoring. This thesis discusses the application of µPMUs in distribution networks, with a focus on their optimal placement (OPP). Many OPP algorithms have been well documented. However, most of them are designed and tested on transmission networks, and very few studies have been conducted on distribution networks. Distribution networks have very different topology from transmission networks, and hence there is a need to study how the µPMUs can be optimally placed in radial topology networks. This thesis fully considers the characteristics of the distribution system and proposes two customization steps to improve the efficiency of OPP for the distribution system. Customization steps are applied to exhaustive search and simulated annealing, and the proposed customized OPP methods have been tested on several networks. Besides the above mentioned exhaustive method, application of integer linear programming (ILP) on OPP has been investigated in this thesis. Compared to exhaustive algorithm, integer linear programming is much faster in solving the OPP problem. However, common solver can only give limited solutions, while in practice it is possible that there are multiple solutions that can satisfy the given constraints. Obtaining all the alternative solutions efficiently will allow the decision maker to examine and select the overall best solution, taking into consideration the factors that are mathematically difficult to express, without suffering any deterioration in the objective function. An ILP based OPP method is proposed in this thesis to identify all alternative optimal placements that satisfy certain constraints. This method is efficient in determining the solution when applied to large-scale power system. This thesis also discusses distribution system state estimation (DSSE). The methods and techniques used in transmission system state estimation may not be valid when applied directly to distribution system due to its distinct characteristics. Several state estimators including weighted least squares (WLS), multiple-segment (MS), quadratic-linear (QL) and square-root (SR) estimators are implemented and tested on IEEE 13 node test feeder. A full phase linear state estimator is developed for three phase unbalanced distribution system. Considering distribution systems usually have limited number of measurements, state estimation has been carried out with different level of measurement redundancy and the performance was evaluated in terms of mean square error (MSE). Simulation shows that the introduction of µPMUs makes those mentioned SE better suit DSSE. It is also indicated that the performance of all the estimators deteriorates with the decrease of measurement redundancy, which gives us the guidance to have more measurement redundancy when considering placement of µPMUs in order to improve DSSE accuracy.