Natural Resources

Low-cost Monitoring to Improve Grid Reliability

Veronica Jacome, Energy Resources Group

Spring 2018

Frequent electrical power failures drastically reduce the quality of life and weaken the economic opportunities enabled through access to the electric grid. High-resolution measurements of the frequency and duration of power outages are critical to understanding and improving grid reliability. These measurements are also necessary to study deeper economic and socio-economic questions about how unreliable electricity impacts economic development and growth. But, due to the lack of appropriate monitoring technologies, it is not economically feasible for many utility companies in the developing world to gather this data. This projects build on a long partnership with the Zanzibar Electricity Corporation (ZECO), the sole electricity distribution utility in Unguja, Tanzania, to deploy the second generation of our novel, low-cost power grid monitoring system. This system monitors the location, duration, and scope of problems at low-voltage, distribution level of the grid in near real-time. Over the course of our proposed pilot, we aim to both measure and improve the reliability and accuracy of our system. Additionally, we plan to leverage our connections with ZECO to co-develop an interface that allows data from our pilot to directly help inform utility grid maintenance.

Electric Systems Modeling in Multiple Scales for High-Performance Computing 

Jose Daniel Lara, Energy Resources Group

Spring 2018

The project is to develop modular multi-energy system simulation platform in collaboration The National Renewable Energy Laboratory (NREL) and Los Alamos National Laboratory (LANL). In this work, a new framework to model and study the effects of renewable energy at multiple time scales and in different sectors will be developed. The current practices in renewable energy integration studies don't allow analysists to perform integrated assessments and require ad-hoc mixtures of software packages developed by different vendors, making the evaluation costly and in many cases incomplete. Moreover, current tools do not reliably integrate electric power systems modeling with other sectors that in the recent years have acquired great relevance to advance the integration of renewable energy, such as natural gas and water networks.

The final objective is the development of a platform to model and analyzes the interaction of renewable energy sources other sectors considering multiple timescales. The platform will be developed as an OpenSource tool available to operators and analysts to reduce the costs and technical challenges of performing a thorough assessment of renewable energy integration. The project will be coded in the programming Language Julia with a focus in High-Performance Computing Applications. The job responsibilities include the development of code to build the models and the produce the accompanying documentation for future development.

Energy Systems Modeling of Mexico (SWITCH- Mexico)

Sergio Castellanos, Energy Resources Group

Fall 2016

The objective of SWITCH-Mexico will be to test your research skills by expanding on (1) literature on decarbonization pathways, and their methodologies, and (2) wrangling data (python, SQL, GIS). For this, your work will consist first in summarizing some literature and then proposing some exciting scenarios (ex.: energy efficiency, EVs, etc.) that you will help build in our still-developing model. The results will contribute and potentially inform policy makers in Mexico, so you will experience first-hand the impact of your work. We are also looking to implement a solid visualization who has been already established (first steps) in Javascript, and which we’d expect you to continue taking it to the next level. 

Evaluating Air Quality from Big Data - This is a big data problem around the evaluation of air quality data from transportation and one that will require a strong time commitment. Your tasks will involve: (a) literature review, (b) database scripting, (c) statistical analysis, (d) visualization and (e) proposed future work.  Qualifications: We are looking for highly motivated and passionate students proficient in Python, SQL, GIS, and/or postGIS who have the time availability to immerse in this project.