The latest report from the Intergovernmental Panel on Climate Change (IPCC)  indicates that anthropogenic emissions, including CO2, methane, and others, have already caused approximately 1°C of global warming above pre industrial levels. Based on their estimates, if it is possible to achieve a net zero CO2 emissions by 2055, it is likely that global warming could be limited to 1.5°C and the worst aspects of climate change could be avoided.
The goal of this thesis is to investigate and document how the Colorado School of Mines in Golden, CO (Mines) can reduce its CO2 emissions in a cost effective way and contribute to solving this climate change problem. Specifically, we investigate the technical and economic feasibility of implementing rooftop photovoltaic (PV) and battery energy storage system (BESS) at Mines. The proposed analysis and design, also known as solar plus storage, enables Mines to reduce energy costs, reduce CO2 emissions, and create a living experiment to improve educational capabilities in this field.
The analysis is a combination engineering and economic model written in R, an open source programming language. The primary tasks are to study the Mines electrical system to develop a baseline energy model and forecast for the analysis period, and to use an optimization methodology to find the best design for a rooftop PV and BESS system under multiple scenarios. Optimization is carried out using a combination of convex optimization algorithms and parametric search. Forecasting is carried out using four test years of actual data that are scaled based on analysis of ten years of historic trends.
The results indicate a positive business case for a solar plus storage system, although the recommended designs fall short of a 100% renewable microgrid. Unless the federal investment tax credit (ITC) is included, the cost per kWh of the solar plus storage system exceeds the average electricity price Mines pays on their bills. However, a solar plus storage system still has a positive business case because it can reliably reduce the peak demand for the Mines campus, thereby reducing the demand charge paid to the utility. The proposed designs enable Mines to reduce electricity costs, reduce carbon dioxide emissions, and to create a living experiment to improve educational capabilities in this field.
The major contributions of this thesis include but not limited to the following:
(1) Application of a unique and practical method for long term electric load forecasting (2) Comparison and analysis of existing microgrid software tools for such applications (3) Design of an optimization framework that expands upon existing software tools for finding the optimal solar plus storage system (4) Multi dimensional mapping of the search space for finding the optimal solar plus storage system, thereby establishing the convex nature of the problem (5) Application of a technique for estimating the effect of ambient temperature on electric loads, using hourly data only (6) Development of a mountain shading adjustment methodology for hourly PV output simulations
|Advisor:||Sen, PK, Tabares-Velasco, Paulo|
|School:||Colorado School of Mines|
|Department:||Electrical Engineering and Computer Sciences|
|School Location:||United States -- Colorado|
|Source:||MAI 58/06M(E), Masters Abstracts International|
|Subjects:||Electrical engineering, Sustainability|
|Keywords:||Energy storage, Microgrid, Optimization, Renewable energy, Solar, Sustainability|
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