Browsing by Author "Patiño-Echeverri, Dalia"

There are currently 22 states with full or partial disclosure requirements for their electricity suppliers. These requirements differ significantly across states, in terms of the specific information content, structure, and presentation, but all have the potential of increasing customers' awareness about the links between their electricity consumption and air emissions, and perhaps create incentives for utilities to reduce those emissions or for customers to reduce their consumption or to switch to a different electricity supplier.

How effective this policy has been is still unclear. The main criterion for effective communication strategies is that they include relevant information for the readers in a usable form. Information needs as well as the ability to process and apply it vary significantly across individuals. However, people are limited in their information-processing capabilities. Policy makers therefore face the trade-off between a large amount of potentially relevant information that ideally needs to be included on the label on the one hand, and decrease in usability as more information is included on the label, on the other.

This paper examines the design, readability and usability of sample labels from 18 different states with information disclosure requirements. The labels are compared and rated according to how they balance the two main dimensions of label design, information content and usability, demonstrating the difficult trade-off between the two. In addition to this, the labels are analyzed along several key aspects: information load, focus on environmental impact, comparability, understandability, and materiality of information. As part of the analysis, measures for these different aspects of label effectiveness are created. The main finding of the analysis is that there are difficult trade-offs between information content and label usability. However, this trade-off can partially be avoided by carefully designing the labels, easing the cognitive burden of users while still conveying relevant information to the decision maker.

The results of the analysis can help evaluate the various existing disclosure policies, and offer approaches to improve upon them. It will also be shown that while preferred levels of information content are incommensurate with maximum usability, certain structures and form elements succeed at making more complex information content easier to use, improving the overall performance of the labels.

A cost-effective pathway towards net-zero electric power systems requires an extraordinary deployment of new solar and wind generation assets. This aggressive expansion driving unprecedented investment entails a fundamental understanding of the challenge ahead of us. This dissertation seeks to provide a multidisciplinary perspective of research questions that shine the light on rapid and cost-efficient strategies for the energy transition. Integrating operations research and geospatial analysis methods, the dissertation utilizes a multidisciplinary approach when addressing three questions.

First, the dissertation examines the role of battery energy storage technologies (i.e., utility-scale lithium-ion batteries) on reducing the greenhouse gas emissions of an electric power system while simultaneously achieving a reduction in carbon abatement costs. The study uses a cost-based production model (day-ahead unit commitment and a real-time economic dispatch) to simulate the optimal operation of all the generation resources in the largest vertically-integrated electric service region in the U.S. The study explores a multitude of configurations to identify optimal sizing of battery energy storage systems when paired with utility-scale photovoltaics.

Next, the dissertation studies the effect of incorporating high-resolution data when identifying suitable land for renewable energy projects over a geographically defined region. Using a python-based user-friendly siting tool implemented in ArcGIS Pro to perform suitability and cost analysis of utility-scale photovoltaic projects in North Carolina under three scenarios (representing conditions ranging from favorable to restrictive). The study finds that the land suitable for utility-scale photovoltaics reduces substantially when parcel-level data reflecting local land-use restrictions are incorporated. The study's findings highlight the necessity of integrating detailed land-use data that reflects local regulation (zoning ordinances) into siting models while simultaneously increasing their spatial granularity.

Lastly, the dissertation analyzes the benefits of weatherizing wind power farms enabling their operation under extreme climates (winter storms). The study uses global reanalysis data with operational information from the Electric Reliability Council of Texas (ERCOT) during the 2021 winter storm Uri to simulate a continued operation of wind power farms under low-temperature environments. The study finds that the financial benefits that winterized wind turbines would have received during winter storm Uri would have outweighed the capital costs required to implement ice-accretion mitigation actions (before winter storm URI).

Carbon Capture and Storage (CCS) technologies provide a means to significantly reduce carbon emissions from the existing fleet of fossil-fired plants, and hence can facilitate a gradual transition from conventional to more sustainable sources of electric power. This is especially relevant for coal plants that have a CO2 emission rate that is roughly two times higher than that of natural gas plants. Of the different kinds of CCS technology available, post-combustion amine based CCS is the best developed and hence more suitable for retrofitting an existing coal plant. The high costs from operating CCS could be reduced by enabling flexible operation through amine storage or allowing partial capture of CO2 during high electricity prices. This flexibility is also found to improve the power plant’s ramp capability, enabling it to offset the intermittency of renewable power sources. This thesis proposes a solution to problems associated with two promising technologies for decarbonizing the electric power system: the high costs of the energy penalty of CCS, and the intermittency and non-dispatchability of wind power. It explores the economic and technical feasibility of a hybrid system consisting of a coal plant retrofitted with a post-combustion-amine based CCS system equipped with the option to perform partial capture or amine storage, and a co-located wind farm. A techno-economic assessment of the performance of the hybrid system is carried out both from the perspective of the stakeholders (utility owners, investors, etc.) as well as that of the power system operator.

In order to perform the assessment from the perspective of the facility owners (e.g., electric power utilities, independent power producers), an optimal design and operating strategy of the hybrid system is determined for both the amine storage and partial capture configurations. A linear optimization model is developed to determine the optimal component sizes for the hybrid system and capture rates while meeting constraints on annual average emission targets of CO2, and variability of the combined power output. Results indicate that there are economic benefits of flexible operation relative to conventional CCS, and demonstrate that the hybrid system could operate as an energy storage system: providing an effective pathway for wind power integration as well as a mechanism to mute the variability of intermittent wind power.

In order to assess the performance of the hybrid system from the perspective of the system operator, a modified Unit Commitment/ Economic Dispatch model is built to consider and represent the techno-economic aspects of operation of the hybrid system within a power grid. The hybrid system is found to be effective in helping the power system meet an average CO2 emissions limit equivalent to the CO2 emission rate of a state-of-the-art natural gas plant, and to reduce power system operation costs and number of instances and magnitude of energy and reserve scarcity.