Renewable Energy in the Electricity Sector
Paper Session
Friday, Jan. 5, 2024 12:30 PM - 2:15 PM (CST)
- Chair: Akshaya Jha, Carnegie Mellon University
Component Manufacturing, Disadvantaged Communities, and the Energy Transition
Abstract
Understanding the labor market impacts of a transition to renewable energy sources, including how these impacts are distributed among historically disadvantaged communities, is crucial for stakeholders who may be guiding the location and type of renewable energy investments. In particular, the Biden administration has focused significant resources on expanding both renewable energy generation and domestic renewable energy component manufacturing. Recent studies have found local employment and earnings impacts from U.S. renewable energy generation that are too large to be explained by direct employment at solar or wind generation facilities (Gilbert et al, 2023; Chan and Zhou 2023). Some authors point to rent and royalty payments to landowners and tax payments to local jurisdictions as possible mechanisms for an indirect economic multiplier effect (Brunner et al, 2022; Castleberry and Greene, 2017; Shoeib et al 2021). In this paper, we explore an additional mechanism: domestic manufacturing of renewable energy components. Previous research has suggested that wind component manufacturing facilities are more likely to be located in counties with greater wind resources, i.e., closer to the location of development of generation facilities (Kim, 2019). We estimate the causal effect of wind component manufacturing activity on local household income. We further evaluate whether this component manufacturing effect differs in counties that contain historically disadvantaged communities.We combine panel data from several sources in order to quantify these effects in a difference-in-differences framework. We collect data on the presence/absence and number of wind component manufacturing facilities per county from American Clean Power (ACP), an industry association. We combine this with a state-level panel of aggregate annual revenues at wind component manufacturing facilities gathered by IBISWorld, a private industry data aggregator. We combine this data with county-level data on household earnings from the American Community Survey.
Pricing Synthetic Inertia: Strategies for Grid Stability in a Renewable Energy Future
Abstract
Inertia, essential for power system stability, is traditionally supplied by rotational power generators. Synthetic inertia becomes increasingly crucial as the energy sector shifts towards renewables, which inherently lack this attribute. Using 4-second data from Australian Electricity Market, our study first identifies events that require inertia and their impact on system frequency. We then explore synthetic inertia, particularly sourced from batteries, addressing its integration and procurement. This process involves optimizing battery operations, considering both the provision of synthetic inertia and the potential revenue generation in our renewable-dominated energy future.Do Red States have a Comparative Advantage in Generating Green Power?
Abstract
The passage of the 2022 Inflation Reduction Act will lead to a significant increase in US wind and solar power investment. Renewable power generation requires more land than fossil fuel fired power generation. The land that will be allocated to renewables depends on several demand side and supply side factors that include the land’s renewable power potential, cost of acquisition, proximity to final power consumers, and local land use regulations. We find that Republican areas issue generation permits faster than progressive areas. We present evidence that rural Republican areas have a cost advantage for generating wind power; however, Democratic areas have sited more solar capacity. We use our statistical model to identify Republican Congressional districts that have the potential to scale up green power production.Discussant(s)
Robert Harris
,
Georgia Institute of Technology
Mark Curtis
,
Wake Forest University
Timothy Fitzgerald
,
Texas Tech University
Akshaya Jha
,
Carnegie Mellon University
JEL Classifications
- L9 - Industry Studies: Transportation and Utilities
- Q5 - Environmental Economics