RESL is always on the lookout for top-quality post-doctoral fellows, graduate students, and undergraduate research assistants. Applicants should have some background in renewable energy, analytical and experimental skills, and the ability to write clearly and present their work. An undergraduate degree in engineering is necessary (typically mechanical, electrical, or chemical). Please inquire with the Principal Investigator of RESL, Dr. Lukas Swan.
These are FULLY FUNDED POSITIONS for MASc and PhD Degrees in Mechanical Engineering at Dalhousie University.
TOPIC 1: HYBRID SHORT-TERM ELECTRICAL (BATTERY) AND THERMAL ENERGY STORAGE FOR DWELLINGS
Present short-term energy storage systems for buildings are optimized for one end-use and/or one electricity service; they are rule-base-controlled and lack coordinated control to support multiple end-uses for resiliency in the building and for the local communities. This project will create new hybridized electrical (battery) and thermal energy system storage system designs and control strategies to meet short-term needs. It is unique in its treatment of, and balancing of, competing objectives of the building vs. community and the daily operations vs. unexpected resiliency events. For example, under normal operations it will mitigate electrical demands of backup resistance heaters of heat pumps while optimizing for time-of-use rates; in outage situations, it will direct electricity to key loads, including heating/cooling and critical appliances. This project will contribute new technology models and practical system sizing/operations recommendations for implementation by industry.
Short-term hybrid electric and thermal energy storage system design (MASc)
Model predictive control strategies for short-term hybrid energy storage (PhD)
Hybrid electric and thermal storage systems for the remote Northern climates (MASc)
TOPIC: CONTROL OF A MIXED BATTERY ARRAY FOR ELECTRICITY GRID STORAGE
This program develops new artificial intelligence and model-predictive-control strategies to optimize performance of large battery energy storage systems using repurposed electric vehicle batteries in a second-life application for electricity grid storage. These controls strategies are in their infancy for energy storage and has not yet been applied to second-life applications. Imagine a warehouse filled with used EV batteries. How do you allocate a service call for peak shaving during high electrical demand periods (cold winter day, hot summer air condition) or mitigate ramp rates of solar, wind, or tidal generators?
Battery testing to map performance trends and develop new system architectures of mixed battery arrays (MASc)
New model predictive control strategy development for mixed battery arrays (PhD)
Demonstration/validation on multiple batteries simultaneously using real-time electricity grid information (MASc)