We use a large California database of over 32,000 hourly observations in the 45-month period of April 2010 through December 2013 to document the ex post variable profit effects of multiple fundamental drivers on natural-gas-fired electricity generation. These drivers are the natural-gas price, system loads, nuclear capacities available, hydro conditions, and renewable generation. We find that profits are reduced by increases in generation from nuclear plants and wind farms, and are increased by increases in the natural-gas price and loads. Solar generation has a statistically insignificant effect, although this will likely change as solar energy increases its generation share in California's electricity market. Our findings support California's adopted resource adequacy program under which the state's load-serving entities may sign long-term bilateral contracts with generation developers to provide sufficient revenues to enable construction of new natural-gas-fired generation plants.

Jurisdictions throughout the world are contemplating greenhouse gas (GHG) mitigation strategies that will enable meeting long-term GHG targets. Many jurisdictions are now focusing on the 2020–2050 timeframe. We conduct an inter-model comparison of nine California statewide energy models with GHG mitigation scenarios to 2050 to better understand common insights across models, ranges of intermediate GHG targets (i.e., for 2030), necessary technology deployment rates, and future modeling needs for the state. The models are diverse in their representation of the California economy: across scenarios with deep reductions in GHGs, annual statewide GHG emissions are 8–46 % lower than 1990 levels by 2030 and 59–84 % lower by 2050 (not including the Wind-Water-Solar model); the largest cumulative reductions occur in scenarios that favor early mitigation; non-hydroelectric renewables account for 30–58 % of electricity generated for the state in 2030 and 30–89 % by 2050 (not including the Wind-Water-Solar model) ; the transportation sector is decarbonized using a mix of energy efficiency gains and alternative-fueled vehicles; and bioenergy is directed almost exclusively towards the transportation sector, accounting for a maximum of 40 % of transportation energy by 2050. Models suggest that without new policies, emissions from non-energy sectors and from high-global-warming-potential gases may alone exceed California's 2050 GHG goal. Finally, future modeling efforts should focus on the: economic impacts and logistical feasibility of given scenarios, interactive effects between two or more climate policies, role of uncertainty in the state's long-term energy planning, and identification of pathways that achieve the dual goals of criteria pollutant and GHG emission reduction.

An assessment of the performance of the day-ahead wind generation forecast published by Bonneville Power Administration in the hydro-rich Pacific Northwest region finds BPA's daytime forecast unbiased, but not the nighttime forecast. Using market-price regressions to estimate the day-ahead merit-order effects of BPA's forecast finds that the merit-order effect estimates do not materially depend on whether the forecast or actual MW are used, as the forecast and actual wind MW data are highly correlated. Finally, the merit-order effect estimates are small, implying small short-term price-related benefits to end users from wind generation development.

Jurisdictions throughout the world are contemplating greenhouse gas (GHG) emission mitigation strategies that will enable meeting long-term GHG targets; many jurisdictions are now focusing on the 2020-2050 timeframe. The authors conduct an inter-model comparison of nine California statewide energy models with GHG mitigation scenarios to 2050 to better understand common insights across models, ranges of intermediate GHG targets (i.e. for 2030), necessary technology deployment rates, and future modeling needs for the state. The models are diverse in their representation of the California economy: across scenarios with deep reductions in GHGs by 2050, annual statewide GHG emissions are 8-46% lower than 1990 levels by 2030 and 59-84% by 2050; the largest cumulative reductions occur in scenarios that favor earlier reductions; non-hydroelectric renewables account for 30%-54% of all electricity generated for the state in 2030 and 59-89% by 2050; the transportation sector is decarbonized using a mix of energy efficiency gains and alternative-fueled vehicles; and bioenergy is directed towards the transportation sector, accounting for a maximum of 40% of transportation energy by 2050. Models suggest that without new policy, emissions from other non-energy sectors and from high-global-warming-potential gases may exceed California’s 2050 GHG goal. Finally, high priority areas of future model development include: implementation of uncertainty analysis, improved representation of economic impacts and logistical feasibility of given scenarios, simultaneous modeling of criteria and GHG emissions, and greater modeling of interactions between two or more specific policies.

An energy imbalance market between PacifiCorp and the California Independent System Operator (CAISO) would bring benefits of $21 million to $129 million for the year 2017, an analysis suggests. Preliminary cost estimates of setting up the EIM range from $3 million to $6 million, with an estimated annual cost of $2 million to $5 million. This suggests that a two-party EIM provides a low-cost, low-risk means of achieving operational savings and enabling greater penetration of variable energy resources.

Robust transmission planning is critical for ensuring well-functioning electricity markets. This is particularly true in Alberta, which has a single market clearing price system and significant uncertainty in future load and generation growth. The authors find that a proposed north-south transmission expansion project in Alberta has the potential to reduce customer costs and mitigate the asymmetric risk of transmission shortages.

Several states and countries have adopted targets for deep reductions in greenhouse gas emissions by 2050, but there has been little physically realistic modeling of the energy and economic transformations required. We analyzed the infrastructure and technology path required to meet California’s goal of an 80% reduction below 1990 levels, using detailed modeling of infrastructure stocks, resource constraints, and electricity system operability. We found that technically feasible levels of energy efficiency and decarbonized energy supply alone are not sufficient; widespread electrification of transportation and other sectors is required. Decarbonized electricity would become the dominant form of energy supply, posing challenges and opportunities for economic growth and climate policy. This transformation demands technologies that are not yet commercialized, as well as coordination of investment, technology development, and infrastructure deployment.

The numerous benefits of electricity forward trading come at a cost to consumers when a forward price contains a risk premium. An analysis based on the theory of cross hedging suggests that there is a risk premium of about 5 percent in the forward price for delivery at the Mid-Columbia hub of the Pacific Northwest. The existence of a relatively large risk premium suggests that forward contract buyers are more risk-averse than sellers.

The extant literature on wind generation and wholesale electricity spot prices says little about how wind generation may affect any price differences between two inter-connected sub-markets. Using extensive data from the four ERCOT zones of Texas, this paper develops a two-stage model to attack the issue. The first stage is an ordered-logit regression to identify and quantify, for example, the impact of wind generation in the West zone on the estimated probability of a positive or negative price difference between the North and West zones. The second stage is a log-linear regression model that identifies and quantifies the estimated impact of wind generation on the sizes of those positive and negative price differences. It is shown that high wind generation and low load in the wind-rich ERCOT West zone tend to lead to congestion and zonal price differences, that those differences are time-dependent, and that other factors such as movements in nuclear generation and natural-gas prices, as well as fluctuating non-West zone loads, also play a role. The results have broad implications for energy policy makers that extend well beyond the borders of Texas and, indeed, those of the United States.

This paper develops a linear regression model for using actively traded NYMEX natural gas futures as a cross-hedge against electricity spot-price risk in the Pacific Northwest and for pricing the forward contracts in the presence of temperature and hydro risks. Our approach comports with reality and provides power purchasers with an effective instrument through which they can hedge their electricity bets through natural gas futures. It also demonstrates the sharp month-to-month variations in the natural gas futures' optimal hedge ratios and hedge effectiveness. Finally, it finds significant risk premiums in the Pacific Northwest forward prices, supporting the hypothesis that forward-contract buyers are relatively more risk-averse than sellers. Copyright © 2011 John Wiley & Sons, Ltd.

New, long-distance transmission lines to remote areas with concentrations of high-quality renewable resources can help western states meet the challenges of increasing renewable energy procurement and reducing greenhouse gas emissions more cost-effectively than reliance on local resources alone. The approach applied here to the Western Electricity Coordinating Council is useful for an initial determination of the net benefits of long-line transmission between regions with heterogeneous resource quality.

California is entering uncharted territory in terms of scaling-up energy efficiency (EE) savings goals. In 2006, California’s Assembly Bill 2021 tasked the California Energy Commission (CEC) with setting statewide savings targets, aiming to reduce total forecasted electrical consumption by 10% over the ten-year period of 2007 – 2016, or approximately 1% per year. The state is also speeding up the development of renewable energy via legislated renewable portfolio standards (RPS). Specifically, California’s Senate Bill 107 mandates that the investor-owned utilities obtain generation equivalent to 20% of their retail sales from renewable energy by 2010, while municipally-owned utilities must set their own corresponding RPS targets. The Governor has set an even more aggressive, non-binding goal for renewable energy to total 33% of retail sales by 2020. This paper quantifies the effect of EE savings on the state’s RPS compliance cost. The effect arises because reduced retail sales result in less renewable energy being required to meet the RPS. If California reduces electricity demand by an additional 1% per year between 2007 and 2010, the state will reduce its cumulative RPS compliance costs by approximately $98 million. If this 1% per year rate of energy efficiency savings is extended through 2020, and the state achieves the 33% RPS goal by 2020, the cumulative RPS compliance cost reduction due to energy efficiency will be as much as $770 million. This analysis is based on renewable energy cost and potential data derived from a publicly available ‘Greenhouse Gas Calculator,’ developed for the California Public Utilities Commission (CPUC) to model the state’s electricity sector greenhouse gas emissions reduction potential by 2020.