| PhD Viva

Name of the Speaker: Mr. Alamanda Sudheer Kumar (EE15D049)
Guide: Dr. Kalyan Kumar B
Online meeting link: https://meet.google.com/qsg-jpgc-kfr
Date/Time: 18th June 2025 (Wednesday), 3:00 PM
Title: RELATIVE DISTANCE MEASURE ARITHMETIC BASED POWER FLOW ANALYSIS AND AVAILABLE TRANSFER CAPABILITY CALCULATION UNDER UNCERTAINTY

Abstract :

Contemporary power systems are subjected to uncertainties due to the rapidly increasing integration of renewable energy resources into the power system. Variations in wind and solar power generation, changes in network topology, and forecasting errors in power demand all contribute to the uncertainty in the system. To deal with this uncertainty, Monte Carlo (MC) simulations are commonly used. In MC simulations, a large number of samples are drawn from the PDF, and then various analyses, like distribution power flow analysis, are performed for each sample to obtain a set of solutions. However, obtaining the PDF of a power generation and/or power demand is practically very difficult. MC simulations can be computationally expensive due to the need for repeated analyses and handling a large number of samples. Affine Arithmetic (AA), a range arithmetic-based tool, has been used as an alternative method to model uncertain parameters. Unlike MC simulations, AA does not require sampling of uncertain parameters and repeated analyses. This results in a significantly reduced computation time. However, AA-based methods can introduce additional noise terms in the resulting affine form, leading to wider solution intervals compared to MC simulations.

In the present work, a new method, called relative distance measure arithmetic based power flow analysis (RDMA-PFA), has been developed to handle uncertainty in power flow analysis. This method has been implemented and tested on the IEEE 30-Bus and IEEE 118-Bus systems. Both the proposed RDMA-PFA and affine arithmetic power flow analysis (AA-PFA) methods have been compared with Monte Carlo simulation. . The results show that the RDMA-PFA method provides tighter bounds for voltage magnitudes, bus angles, and active and reactive power flows compared to the AA-PFA. A new method has been proposed for calculating ATC (Available Transfer Capability). This method considers the uncertainty in wind power generation and uses a relative distance measure arithmetic approach. By using this approach, the optimization process for determining the ATC range with uncertainty has been transformed into a continuous, deterministic linear optimization problem. This new method has been tested on the IEEE 30-Bus and IEEE 118-Bus systems and compared with the Monte Carlo Simulation and Interval arithmetic optimization based ATC (IAO-ATC) methods. The simulation results show the effectiveness of RDMA-ATC with uncertainty in wind power generation. A new method called relative distance measure arithmetic-based unbalanced power flow analysis (RDMA-UPFA) has been developed to analyze power flow in a three phase unbalanced radial distribution system. This method considers uncertainties in power injections, load imbalances, and mutual coupling among the phases. It has been tested on 19-Bus and 25-Bus systems and compared with two other methods: affine-arithmetic power flow analysis (AA-PFA) and Monte Carlo simulation-based power flow analysis (MCS-PFA), with MCS-PFA used as the benchmark for evaluation.