Christopher T M Clack

Aditya Choukulkar

Brianna Cote

Sarah A McKee

Vibrant Clean Energy (VCE®) partnered with Energy Innovations to study the potential impact of a regional transmission organization (RTO) for the Southeastern United States (SE-RTO). The modeling (using WIS:dom®-P) found that with an RTO the region could save $384 billion by 2040, create 285,000 full time jobs, reduce emissions by 37% and provide transparency in the region. The team modeled four scenarios. Importantly, the first scenario mimicked the utilities’ integrated resource plans (IRPs) and found that an increase in thermal generation exceeded requirements and inflated costs. Conversely, the SE-RTO scenario reduced the dependency on thermal generation and shifted to low-cost variable generation. One of the sensitivity scenarios studied an alternative IRP, which allowed for competitive build out and economic dispatch. This scenario produced approximately 60% of the savings of the SE-RTO. Finally, a fourth scenario determined the benefit of an SE-RTO when nuclear power plants remained online through 2040. This scenario was very slightly more expensive than the SE-RTO scenario, but had far fewer emissions. Interestingly wind power, in the modeling, became an important contribution to the electricity mix. With it increasingly providing capacity requirements for winter demand profiles. Further, the modeling found that distributed energy resources (DERs) and their co-optimization provided 10% of the system savings.

Technical Report

Economic & Clean Energy Benefits of Establishing a Competitive Wholesale Electricity Market in the Southeast United States

Michael O'Boyle

Eric Gimon

America has officially entered the “coal cost crossover” – where existing coal is increasingly more expensive than cleaner alternatives. Today, local wind and solar could replace approximately 74 percent of the U.S. coal fleet at an immediate savings to customers. By 2025, this number grows to 86 percent of the coal fleet. This analysis complements existing research into the costs of clean energy undercutting coal costs, by focusing on which coal plants could be replaced locally (within 35 miles of the existing coal plant) at a saving. It suggests local decision-makers should consider plans for a smooth shut-down of these old plants—assessing their options for reliable replacement of that electricity, as well as financial options for communities dependent on those plants. This report should begin a longer conversation about the most cost-effective replacement for coal, which may include combinations of local or remote wind, solar, transmission, storage, and demand response.

THE COAL COST CROSSOVER: ECONOMIC VIABILITY OF EXISTING COAL COMPARED TO NEW LOCAL WIND AND SOLAR RESOURCES

The WIS:dom® (Weather-Informed energy Systems: for design, operations and markets) optimization planning model is the state-of-the-art energy model developed by Vibrant Clean Energy, LLC (VCE®). It is the first commercial co-optimization model of energy grids that was built from the ground up to incorporate vast volumes of data; starting with high-resolution weather and demand data. WIS:dom®-P simultaneously co-optimizes the capacity expansion requirements (generation, transmission, and storage) and the dispatch requirements (production cost, power flow, reserves, ramping, and reliability) for the entire electric (energy) grid of interest. Not only does WIS:dom® co-optimize these critically linked properties, it was developed from the ground up to work with “big data”. The model can determine the cost/benefit ratios for new HVDC transmission lines, compared with other technologies. It can also determine the risk and rewards from retiring existing generators for the topology of the transmission infrastructure; simultaneously to determining how more variable generation is deployed to replace them. WIS:dom® utilizes high-resolution (spatially and temporally) weather data to determine resource properties over vast spatial-temporal horizons. Thus, WIS:dom® can be used on scales as small as campuses, cities, counties or states/provinces; but uniquely can also be used for sovereign entities and continents. Moreover, these scales can be nested, allowing high-fidelity local modeling accompanied with lower-fidelity larger areas to create feedbacks within the model that simulate outside influences on local markets. The model relies on publically available data where possible, and contains default values for generators, transmission, storage, production cost and resource siting. However, WIS:dom® was designed from the beginning to allow “plug-and-play” capability, whereby it can take advantage of customized datasets required for detailed modeling of specific questions, markets or balancing areas. For example, higher-resolution weather data over a utility or ISO; or proprietary heat rates for generators within a utility. The modeling framework is unique and consistent across various scales facilitating more transparent analysis between results derived. With WIS:dom® new opportunities are identified due to the co-optimization detecting patterns ignored by other modeling endeavors. The WIS:dom® optimization model allows datasets to be added for specific local interests. For example, WIS:dom® can be deployed for any country or continent around the globe. The model requires the local datasets (or uses the default global one) and then can study various questions of interest – such as greenhouse gas emission, HVDC transmission links, variable generation and reliability, water consumption, air pollution, electric vehicle penetrations, electric heating, jobs and tax revenues, and more.

Technical Documentation

WIS:dom®-P v9.0 Weather-Informed energy Systems: for design, operations and markets (Planning Version)

Dataset Overview

Renewable Generation, Electric Demand, Transmission Line Ratings & Losses, and Climate Change

Christopher T M Clack

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