Patrick Murphy defended his doctoral dissertation proposal on the topic of “A Method for Determining the Cost of Reliable Electricity, Considering Grid Unreliability: A Case Study and Applied Analysis in Uganda” in November 2014. In his research, Patrick plans to address a shortfall in past efforts to address a lack of electricity access to grid-connected, distributed generation and stand-alone, distributed energy resources.
This shortfall is a consideration when, even though grid electricity reaches people, it is not always reliable. Customers often experience hundreds of outage hours per month. His research will address this analytical shortfall to provide new methods to:
- analyze reliable electricity and identify optimal systems to improve its reliability;
- apply these methods for an analyzing Economic Distance Limits (EDL), which refers to the distance at which grid extension and self-generation have the same economic cost.
To perform this analysis, Patrick intends to adapt the Hybrid Optimization Model for Electric Renewables. This will be used to address unreliable electricity from the grid, to develop a method for determining optimal system configurations and to predict electricity costs for reliable power generation in regions with unreliable grid electricity. The process involves simulating an unreliable grid and using it to perform a detailed analysis of stand-alone generation versus grid extension and hybrid grid-tied systems. He intends to undertake this using data from Uganda to demonstrate the validity of the approach.
Patrick expects that his results will indicate that improved reliability does increase cost, but the cost increase can be justified for users needing greater reliability. Options to improve energy access and reliability may include: grid extension, decentralized microgrids using diesel, and renewable-based, distributed energy resources.
A recent paper by Patrick on his research topic can be seen by clicking on this link: Energy Policy paper by Murphy, et al.
Patrick’s Research Committee consists of Professors Rene van Dorp (advisor), Thomas Mazzuchi and Jonathan Deason.