Mechanical Engineering ETDs

Publication Date

Summer 7-30-2024

Abstract

This paper investigates a real-time optimization algorithm for autonomously calibrating the heliostats in a concentrated solar power plant with the goal of maximizing power generation. The current state-of-the-art uses human operators to provide feedback for the heliostats. We use real-time/online measurements to produce an autonomous closed-loop system that does not require human intervention. The paper investigates tuning the gain of the real-time optimization algorithm to quickly and robustly converge to the optimal alignment and stabilize the system. The exponential stability of the system is certified using a quadratic Lyapunov function and static output feedback methods to couple the Lyapunov functions of the plant and the controller. To validate stability, performance, and robustness, the algorithm is simulated using different power distributions and gains, as well as tested using an actual heliostat, that show the need for the real-time optimization algorithm.

Keywords

Real-time Optimization, heliostat, Concentrated Solar Power, optimal pointing alignment

Degree Name

Mechanical Engineering

Level of Degree

Masters

Department Name

Mechanical Engineering

First Committee Member (Chair)

Dr. Claus Danielson

Second Committee Member

Dr. Meeko Oishi

Third Committee Member

Dr. Kenneth Armijo

Document Type

Thesis

Language

English

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