Date of Award

January 2025

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Energy Engineering

First Advisor

Olusegun S. Tomomewo

Abstract

Renewable energy integration into existing power grids is crucial for a sustainable future, but its intermittency poses technical challenges to grid stability and reliability. Hybrid Energy Storage Systems (HESS), combining lithium-ion batteries, supercapacitors, and flywheels, offer a promising solution by leveraging the complementary strengths of these technologies. This study explores optimal configurations of HESS using HOMER Pro software and a theoretical analysis approach to establish unified mathematical models for the three storages with constraints to address various operational scenarios, including normal operation, absence of renewable sources, and component failures. The proposed system integrates an Energy Management System (EMS) using a network switch and Automatic Transfer Switch (ATS) with a supervisory control algorithm that combines Moving Average Window Width filtering with threshold-based cutoff logic to ensure stable power distribution. Lithium-ion batteries provide long-term energy storage, supercapacitors handle short-term fluctuations, and flywheels offer intermediate-term storage and frequency regulation. Key parameters monitored include battery voltage (650V–800V, capacity: 270 kWh), supercapacitor voltage (2.5V–3.0V, capacity: 265 kWh), flywheel voltage (400V–600V, capacity: 265 kWh), temperature ranges (-40°C to 65°C), and SOC limits for each storage device (battery: 0.1–0.8, supercapacitor: 0.2–0.95, flywheel: 0.15–0.9). The proposed algorithm successfully reduces false cutoff triggers, ensuring cutoffs occur only when parameters exceed thresholds. To further validate the Unified Mathematical Method, Homer Pro software is utilized for HESS system optimization, focusing on power flow simulation and grid interaction analysis. Grand Forks Area location (47.925259, -97.087752) in North Dakota, U.S.A was used in the Homer Pro Simulation. Results indicate that HOMER Pro’s optimization model aligns with the proposed Unified Mathematical Method (UMM), confirming the algorithm’s effectiveness in maintaining system stability and reliability while maximizing energy efficiency.

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