Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Natural Resources

First Advisor

Jon Erickson

Abstract

Innovation in the electric sector has the potential to drive job growth, decrease environmental impacts, reduce rate payer costs, and increase reliability and resiliency. However, the traditional electric system was built to deliver a controlled flow of energy from a centralized location with maximum reliability and minimum cost. As both customer expectations and generation technologies change, new avenues for grid innovation are being explored. Residential customers, commercial and industrial clients, and electric utilities must all find a way to balance goals for decarbonization and social justice with maintaining a least cost, reliable power grid. Grounded in Geel’s energy system transition framework, this dissertation explores how each of these three stakeholder groups is navigating the transition to renewables.

The first study tests the idea that residential customers will be more inclined to change their behavior when altruistically contributing to a greater goal. Renewed Darwinian theory was explored to question the exclusive use of financial incentives in demand response programs, with evidence that enabling altruism may influence electricity demand even more effectively than traditional financial incentives. A difference in differences approach was designed to test the impact of the Burlington Electric Department’s Defeat the Peak program on residential energy use where the incentive was a group donation to a local charity. Results suggest utility savings of over $12 in energy supply costs for every $1 they invested in the program.

Financial levers, however, can be quite effective in influencing electricity demand, and may result in cost-shifting from high to low demand consumers. The second study focused on rate design for commercial and industrial customers through an analysis of the utility demand charge. For over a century the demand charge has been a primary means to recover total cost-of-service including fixed, embedded, and overhead costs. Under the current system, most small commercial and residential customers do not receive a strong direct price signal to invest in storage, load shifting, or renewables. Larger commercial and industrial customers exercise some measure of control over their loads to reduce demand charges, but with only modest benefit or value to the system as a whole. The system costs are then redistributed to all customer classes, potentially falling disproportionately on low demand customers. To investigate, a regression analysis was conducted with cost and market characteristics from 447 US electric utilities. Results suggest that demand charges predict a significant degree of variability in residential pricing, confirming suspected cost shifting. Redesigning the demand charge could open up new markets for renewable energy entrepreneurs and lower grid costs and customer rates, supporting goals of decarbonization while also achieving reliable least-cost power.

In the third study, an iterative approach was employed to understand why some utilities lean into the energy system transition while others take a more conservative stance. A database of 170 US electric utilities was constructed including a qualitative assessment of Integrated Resource Plans for renewability orientation. Institutional resource-based theory was utilized to take a striated approach to understanding firm heterogeneity, identifying factors at the individual manager level, firm level, and external environment that can influence a utility’s energy supply characteristics. Independent variables in a simultaneous regression analysis included CEO gender and tenure at the individual level, ownership structure and firm age at the firm level, and the impact of policies and state rurality at the inter-firm level. Results indicate that a significant amount of a utility’s commitment to the renewable energy transition can be predicted based on these firm characteristics.

Language

en

Number of Pages

185 p.

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