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In this paper, we utilize nodal price data at each thermal-generation facility within the ERCOT footprint between 2014 and 2016 to revisit an empirical question of great interest to various parties: how does wind integration affect the wholesale energy price? We find that for every additional 1000 MW of wind generation in a Real-Time 15-minute Settlement Interval, nodal prices at non-wind resources would be suppressed by $1.45/MWh to $4.45/MWh, with considerable heterogeneity across time and space.

This study examines the energy efficiency implications of a daily billed energy service, commonly known as ‘prepaid’ electricity, which is used by a growing percentage of residential customers in the competitive Texas electricity market. Our empirical analysis results suggest that this service could save 9.6% of average daily energy consumption, net of the effect of any disconnections. This quantitative study demonstrates that energy efficiency from prepaid energy products can extend to competitive marketplaces.

This paper examines the impacts of uncertainties in U.S. renewable energy policy on the investment decisions of renewable electricity producers. We develop and solve a dynamic optimization model to understand how investment in wind energy depends on market and policy uncertainties. These uncertainties include the federal government’s uncertain decision about the continuation of the Production Tax Credit (PTC) policy and the stochasticity of prices in the market for Renewable Electricity Credits (RECs). Our results show that investors require higher REC prices to invest without the PTC policy. Results contribute to our understanding of how policy uncertainty affects the profitability threshold required for investors to commit to renewable energy projects.

This paper explores the impacts of the stay-at-home advisory issued in response to the COVID-19 pandemic on regional electricity generation fuel mixes for the three major RTOs: NYISO, MISO, and PJM. We find that the COVID-19 pandemic affected these regional markets differently, although one common finding is that overall electricity generation declined after the stay-at-home advisories were issued. We also empirically tested the impact of the stay-at-home advisories on electricity generation for different fuel types.

The authors estimate price-responsiveness of the residential customers with increasing residential PV penetration and project future electricity sales to the residential sector considering various future PV penetration scenarios. This projection is potentially useful for utilities in their resource planning and ratemaking processes as they formally incorporate the expected reduction in residential electricity demand due to increased penetration of distributed generation.

In this study, we examine how family forest owners who receive various types of assistance differ from unassisted landowners with respect to their forestland management practices, attitudes and concerns, and future management, use, and ownership intentions. We do so by utilizing a national database containing information on private forest owners and the forestland they own. By defining an assisted landowner according to several attributes contained in this database (e.g., has a forest management plan, received cost-share assistance, or received advice), important similarities and differences between recipients and nonrecipients of various types of assistance are identified. The study shows that assisted and unassisted landowners are different with respect to several characteristics of the owners and the forestland they own, land management practices undertaken, and reasons for forest landownership. For example, assisted landowners are more likely to harvest timber and improve wildlife habitat than the unassisted owners. Yet no distinctions are found between assisted and unassisted landowners with respect to their plans to either subdivide or sell their land. In many cases, the differences between assisted and unassisted landowners are not related to the type of assistance the landowner received.

The USDA Forest Service’s Forest Stewardship Program (FSP) is the nation’s most prominent private forestry assistance program. We examined the FSP using a multiple analytic approach: analysis of annual FSP accomplishments, survey of state FSP coordinators, analytic comparison of family forest owners receiving and not receiving forestry practice assistance, and focus groups with family forest owners. We found the FSP reaches a small fraction of eligible landowners; states use FSP funds to address local private forestland issues; landowners obtaining assistance commonly associated with the FSP (e.g., management plans) differ from others in sociodemographics, ownership objectives, and land management actions but not in terms of intent to sell/subdivide forestland; and traditional FSP activities are not influencing inactive family forest owners to become active managers. We believe current practices (e.g., state-level flexibility) help the FSP reach its goals, alternative assistance-related efforts may increase the reach of the FSP and support strategic goals, and data collection improvements may enrich future FSP evaluations.

Dynamic pricing, also known as real-time pricing, provides electricity users with an economic incentive to adjust electricity use based on changing market conditions. This paper studies the economic implications of real-time pricing mechanisms in a cement manufacturing plant. Production for a representative cement manufacturing plant is modeled using stochastic mathematical programming. The results show that a cement plant can a) reduce electricity costs by shifting electricity load of certain processes to times when electricity prices are lower, and b) profitably reduce electricity use during peak prices through more efficient scheduling of production under real-time pricing compared to fixed pricing. The results suggest that building scheduling flexibility into certain industrial manufacturing processes to reschedule electricity consumption when the electricity prices at their peak may be economical. The results also suggest that shifts in the production schedule of a cement manufacturer that result from real-time pricing may also influence environmental impacts. The modelling framework modeled real-time pricing as a source of risk in this study, which is also applicable to other energy intensive industries. As such, dynamic pricing strategies that include the non-market impacts of electricity generation should be further explored.

An important and potentially underused source of biomass that could be utilized in energy production is from nonindustrial private woodlands. We employ the Theory of Planned Behavior to estimate the social availability of woody biomass as a function of landowner behavior intent, landowner characteristics, forest land characteristics, and biomass price on stated willingness to harvest biomass in conjunction with a commercial timber harvest. A mail survey was administered to 1109 nonindustrial private woodland owners in a 26county region in northeast Minnesota and northwest Wisconsin during the fall of 2009. Using binary logistic regression, we found payment level offered to harvest biomass plays a significant role in landowners’ decisions, but that non-monetary factors are also important. Landowner attitudes and opinions regarding soil impacts, aesthetics, and energy independence were important predictors of stated willingness to harvest. Social norms as manifested through the influence of neighbors were also significant. These findings expand existing research and are useful for profiling nonindustrial private woodland owners to identify sustainable sources of biomass to supply a burgeoning bioenergy sector in the Lake States.

This paper provides an empirical analysis of price responsiveness in retail and wholesale markets in the Midcontinent ISO electricity markets. In the retail market, consumers do not often observe real-time price changes and pay a pre-determined flat rate, but are able to respond to price over longer time periods. In the wholesale electricity market, buyers are able to adjust their electricity purchases based on real-time price changes. Our findings show that retail industrial customers respond differently in different across states in the Midwest. We also find differences in real-time wholesale price elasticities between sub-regional pricing hubs in the MISO footprint. Results suggest that the observed differences in price responsiveness of demand across market levels and sub-regions are associated with demand response program adoption.

This paper investigates demand response implementation in Midwest ISO from the perspective of large energy consumers. Acknowledging uncertain electricity prices, we develop a dynamic programming-based model using real-options theory to identify a profitability threshold for demand response (DR) schemes. Our model is tailored to energy-intensive industries, and the cement industry is used as illustrative example in the case study. Simulation results demonstrate season-dependent profitability threshold for a representative cement manufacturing plant.