MULTI-AREA CONTINUOUS-TIME OPTIMAL POWER FLOW AND GENERATION SCHEDULING USING DISTRIBUTED ALGORITHM

Author

Bishal Lamichhane, Southern Illinois University CarbondaleFollow

Date of Award

12-1-2024

Degree Name

Master of Science

Department

Electrical and Computer Engineering

First Advisor

Tragoudas, Spyros

Abstract

Electric power grids are undergoing major changes mainly driven by integrating high levels of renewable energy, advancing energy storage technologies, and deploying electric vehicles at scale. Along with numerous benefits offered by this grid modernization, technical challenges also arise largely due to variability and uncertainty of renewable energy resourcesas well as the stochastic nature of electric transportation charging demand. This thesis intends to cater the need of such modern power systems by developing a new computationally efficient function space-based distributed solution methodology for continuous-time optimal power flow (OPF) and unit commitment (UC) problems in multiarea power system. This solution methodology serves as the enhanced operation tool to enable continuous-time power exchange between interconnected systems, leveraging the operational flexibility unlocked through higher-fidelity modeling, while preserving data privacy among the participating areas. The core formulation of the proposed methodology is divided into two chapters, addressing the solutions for OPF and UC problems, respectively. Both solution methodology for OPF and UC problems amalgamate the unique properties of variational optimization, function space representation, and appropriate distributed algorithms, alternating direction method of multipliers (ADMM) and analytical target cascading (ATC), respectively to enable continuous-time power exchange between adjacent areas. At first, the centralized multi-area OPF and UC problems are formulated as variational optimization problems with continuous-time load and decision variables (power generation, voltage phase angles, line/ tieline power flows), which is then converted to a conventional optimization problem by projecting the load and decision trajectories into the Bernstein function space. While the OPF is formulated as a Quadratic Programming (QP) with linear and quadratic constraints to represent the transmission network, UC problem includes more involved formulation with consideration for additional energy storage and is modeled as a Multi-Integer Linear Programming (MILP) to incorporate binary commitment variables of the generating units. The next step involves decomposing the centralized formulation to individual sub-problems of individual areas using distributed algorithm- ADMM and ATC, which are selected based on careful analysis of references from related works.The developed solution methodology for OPF and UC problems are then implemented on a synthesized three-area network and the three-area IEEE Reliability Test System (IEEE-RTS) respectively. The numerical results are presented as different cases to highlight the performance of the proposed methods in terms of solution accuracy and achieving optimal decisions on interconnection power exchange such that the energy and ramping needs of areas are met in both OPF and UC problems.