12/04/2024
By Danielle Fretwell

The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Victor Eniola on: "Optimization of Hydrogen Energy Storage Systems for Microgrids Considering Geospatial and Temporal Variations"

Candidate Name: Victor Eniola
Degree: Doctoral
Defense Date: Friday, December 20, 2024
Time: 11 a.m.-1 p.m.
Location: Southwick Hall, Room 240

Committee:
Advisor: Christopher Niezrecki, Ph.D., Professor, Mechanical & Industrial Engineering, UMass Lowell
Co-Advisor: Xinfang Jin, Ph.D., Associate Professor, Department of Mechanical Engineering, UT Dallas

Committee Members*
1. David Willis, Ph.D., Associate Professor, Department of Mechanical & Industrial Engineering, UMass Lowell
2. Juan Pablo Trelles, Ph.D., Professor, Department of Mechanical & Industrial Engineering, UMass Lowell
3. Hanping Ding, Ph.D., Assistant Professor, School of Aerospace & Mechanical Engineering, The University of Oklahoma

Brief Abstract:
In response to the net-zero climate goal, there has been a significant shift from fossil fuel reliance to renewable energy sources over the past several decades. Addressing the intermittency of renewable resources is critical for the effective design of renewable power generation systems. Hydrogen, as a long-term energy storage medium, shows promise for enhancing renewable integration into the grid. Hybrid hydrogen energy systems can substantially impact the future landscape of energy storage and utilization.

This research aims to investigate cost-effective hybrid wind-hydrogen microgrids (HWHM) through a system-level approach to component sizing, design, and optimization. The local availability of renewable resources and load demand will dictate the system type and optimal design, balancing capacity and cost. Utilizing low-order physics-based models, this study investigates the performance of a HWHM comprising various components, including wind turbine generators (WTGs), step-down transformers, AC/DC rectifiers, proton exchange membrane electrolyzers and fuel cells, gas dryers, compressors, high-pressure tanks, and DC/AC inverters, represented in Simscape-MATLAB. The preliminary study focuses on analyzing the effects of wind speed fluctuations and frequency on the optimal sizing of the HWHM using a rule-based optimization algorithm, running simulations that model seven days of operation with several different wind speed profiles and actual load demand data for the U.S. Navy base located at San Nicolas Island, which currently relies on diesel generators. The transition to renewables is motivated by the high costs and environmental impacts associated with transporting and burning diesel fuel.

The main motivation for this research stems from the lack of understanding on how the intermittent nature of renewable energy sources can be characterized by various statistical parameters, each of which impacts the optimal design differently. Among the existing studies, the optimal design of a HWHM remains a unique solution for the specific geographic location (RE resources and power demand). This research addresses gaps in existing literature concerning the statistical characterization of wind speed and its influence on HWHM design. The preliminary findings from this study are as follows: When the WTG power supply and load demand profiles are shifted synchronously in time without any changes in their statistical measures, the design results remain largely unchanged even though the tank’s initial state-of-charge varies. An increase in the standard deviation of the hypothetical WSPs results in a decrease in the number of WTGs and a corresponding increase in the number of tanks required for any given case number. For relatively high case numbers, even with an increased wind speed standard deviation, the power contribution from WTGs remains largely unchanged. Wind speed frequency has a negligible impact on the optimal sizing and overall performance of the HWHM. Notably, in the case where the wind turbine's average power is designed to be 90% of the peak load, the WTG capacity of 3.44 MW is nearly six times greater than the average demand of 555 kW to maintain a balance between power supply and demand. The study provides general guidance for designing HWHMs with quantifiable statistical measures of wind speed profiles, aiming to offer the U.S. Navy optimal system configurations tailored to various geographical contexts.
The research plan encompasses gaining multi-objective insights into optimal hydrogen system integration, considering the effects of geospatial and temporal variations. This multifactorial approach is vital for identifying effective energy solutions across diverse Naval facilities worldwide.