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Like everything for the past 2 centuries, agriculture has depended increasingly on fossil fuel energy. Pressures to shift to renewable energy and changes in the fossil fuel industry are set to massively alter the energy landscape over the next 30 years. Two near-certainties are increased overall prices and/or decreased stability of energy supplies. The impacts of these upheavals on specialty crop production and consumption are unknowable in detail but the grand lines of what will likely change can be foreseen. This foresight can guide the research, extension, and teaching needed to successfully navigate a future very unlike the recent past. Major variables that will influence outcomes include energy use in fertilizer manufacture, in farm operations, and in haulage to centers of consumption. Taking six increasingly popular fruit and vegetable crops and the top two horticultural production states as examples, here we use simple proxies for the energy requirements (in gigajoules per ton of produce) of fertilizer, farm operations, and truck transport from Florida or California to New York to compare the relative sizes of these requirements. Trucking from California is the largest energy requirement in all cases, and three times larger than from Florida. As these energy requirements themselves are all fairly fixed, but in future will likely rise in price and/or be subject to interruptions and shortages, this pilot study points to two commonsense inferences: First, that fruit and vegetable production and consumption are set to reposition to more local/regional and seasonal patterns due to increasing expenses associated with fuel, and second, that coastto-coast produce shipment by truck will become increasingly expensive and difficult. [ABSTRACT FROM AUTHOR]

When critical infrastructure system services are disrupted, households typically respond by reducing, delaying, or relocating their demand (e.g., delaying laundry), or augmenting supply (e.g., using a generator). While this phenomenon is well known, there has been little systematic empirical investigation of it. Focusing on electric power and water service interruptions and using revealed and stated preference survey data from Los Angeles County, California, we develop 24 mixed logit models, one each to predict the probability an individual undertakes a specified adaptation as a function of outage duration and characteristics of the individual. The analysis aims to determine: (1) how common different household adaptations are; (2) how adaptation implementation varies with infrastructure type, outage duration, and uses of the service; (3) what household characteristics are associated with implementation of different adaptations; and (4) how adaptations tend to occur together. The percentage of individuals who report doing an adaptation varies greatly across adaptations and outage durations, from 2% to 88%. In general, adaptations that require moving out of the home are the least common of those investigated. For electric power outages, adaptations that could be done at home are less likely as the outage duration increases, while those that require going somewhere are more likely as the duration increases. For water outages, all adaptations (except delaying consumption) are more likely as an outage lasts longer. Using electric power or water for medical devices and/or work and business has a large effect on the likelihood of implementing many adaptations. Preevent conservation habits are also associated with an increased likelihood of implementing adaptations. The influence of household characteristics varies greatly across adaptations. There is evidence that some adaptations tend to occur together (e.g., using water from lakes and the government) and others tend not to (e.g., delaying electricity use and going to a hotel). Knowing what kinds of adaptations are found among different segments of the population, how common they are, and when they are likely to be implemented can help policymakers know what sorts of crisis-coping behaviors to expect in their locality, and can help them to know the timeframe in which those adaptations would be implemented. This in turn can provide needed knowledge for how to support those adaptations. Such support could take the form of enhanced contacts and outreach in specific populations (e.g., medically fragile), advance planning (having materials on hand, or including adaptations in drills or exercises), or timely improvising as an event unfolds. [ABSTRACT FROM AUTHOR]

This paper presents a methodological framework to evaluate the resilience, with the primary focus on performance degradation, of levee-protected electric power networks to flooding in a changing climate. To this end, a multi-disciplinary framework is established by integrating climate science, hydrology, and electric power network analysis. The framework quantifies the effect of climate change on flood hazard levels in a levee-protected area and the subsequent changes in the resilience of the electric power network. In the first step, the changes in the exposure of levee-protected regions to flooding hazard in a warming climate are calculated. Then, the probabilities of failure of power network components due to flooding under current and projected future climate are determined. Finally, the power system resilience index is used to assess the system resiliency for pre-flooding (baseline), historic flooding, and two projected future flooding scenarios. For demonstration, the proposed framework is applied to a levee-protected area in Northern California. The IEEE 118-bus standard test system is employed to represent the power network in the study area. Results reveal that climate change can considerably decrease the system resilience of the levee-protected electric power network. The findings of this study can contribute towards more resilient power network systems under a changing climate. [ABSTRACT FROM AUTHOR]

Electric power utilities face a wide range of risks that cause financial uncertainty, with potential impacts on prices for customers. Among these, weather variability and retail load defection are perhaps two of the most studied. Whereas weather extremes expose utilities to unpredictable swings in electricity supply and demand, retail load defection, in which customers adopt distributed energy resources or switch to alternative providers, can alter utility business models fundamentally. We showed for the first time that these two phenomena can interact dynamically, with potential negative consequences for electricity ratepayers. We found that retail load defection could alter utilities' financial exposure to weather risk in a matter of years. Using open-source power system simulation software coupled with a utility financial model, we simulated outcomes for a major hydropower-producing California electric utility under stationary hydrometeorological uncertainty, and under three different load defection scenarios ranging from 0% to 90%. We found that as load defection increases, the utility's three main businesses (wholesale generation, transmission, and retail distribution) shift in relative importance. As a consequence, the impacts of interannual variability in hydropower production and demand in the utility's system (a function of streamflow and air temperatures, respectively) become significantly altered. Air temperatures (a proxy for demand) become more predictive of utility financial performance, whereas the utility's exposure to hydrology is poised to shift in complex ways. Drought will remain a major risk, but extremely wet years (which historically are beneficial to the utility's significant hydropower holdings) may become damaging due to their association with low market prices. Our results also suggest that load defection could put much more pressure on utilities to make major annual rate adjustments or quickly adapt current strategies for managing weather risk. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic model is proposed for a joint statistical description of solar photovoltaic (PV) power and outdoor temperature. The underlying correlation emerges from solar irradiance that is responsible in part for both the variability in solar PV power and temperature. The proposed model can be used to capture the uncertainty in solar PV power and its correlation with the electric power consumption of thermostatically controlled loads. First, a model for solar PV power that explicitly incorporates the stochasticity due to clouds via a regime-switching process between the three classes of sunny, overcast and partly cloudy is proposed. Then, the relationship between temperature and solar power is postulated using a second-order Volterra model. This joint modeling is leveraged to develop a joint probabilistic forecasting method for solar PV power and temperature. Real-world datasets that include solar PV power and temperature measurements in California are analyzed and the effectiveness of the joint model in providing probabilistic forecasts is verified. The proposed forecasting methodology outperforms several reference methods thus portraying that the underlying correlation between temperature and solar PV power is well defined and only requires a simple lower-complexity sampling space. [ABSTRACT FROM AUTHOR]

Battery vehicles and fuel cell vehicles can facilitate the use of low-carbon energy sources in stationary applications, as well as for transportation. For instance, battery vehicles might enable peak load shifting and short-term electricity storage when connected to the electric grid. Hydrogen infrastructure that provides refueling of fuel cell vehicles might also absorb peak solar generation, and provide hydrogen to the natural gas network. Here, the cost and emissions impacts of these system-level effects are integrated into an overall cost-benefit analysis of battery vehicles and fuel cell vehicles. An integrated analysis of a community energy system under various electric vehicle penetration scenarios is conducted, using a linear cost optimization model. The model determines the cost-optimal energy infrastructure mix in different penetration rate scenarios, using hourly time series data for the community's power generation and energy demand. The optimization considers a wide variety of technical and economic parameters, and determines results for 2025 and 2035. The findings show, that while both battery vehicles and fuel cell vehicles can modestly reduce the community's overall carbon dioxide emissions, the latter carry higher overall costs, primarily due to the hydrogen generation infrastructure. Battery vehicles are therefore a more cost-efficient choice for reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Deployment of high-penetration photovoltaic (PV) power is expected to have a range of effects – both positive and negative – on the distribution grid. The magnitude of these effects may vary greatly depending upon feeder topology, climate, PV penetration level, and other factors. In this paper we present a simulation study of eight representative distribution feeders in three California climates at PV penetration levels up to 100%, supported by a unique database of distributed PV generation data that enables us to capture the impact of PV variability on feeder voltage and voltage regulating equipment. We find that feeder location (i.e. climate) has a stronger impact than feeder type on the incidence of reverse power flow, reductions in peak loading and the presence of voltage excursions. On the other hand, we find that feeder characteristics have a stronger impact than location on the magnitude of loss reduction and changes in voltage regulator operations. We find that secondary distribution transformer aging is negligibly affected in almost all scenarios. [ABSTRACT FROM AUTHOR]

The California Independent System Operator (CAISO) has implemented Convergence Bidding (CB) on February 1, 2011 under Federal Energy Regulatory Commission's September 21, 2006 Market Redesign and Technology Upgrade Order. CB is a financial mechanism that allows market participants, including electricity suppliers, consumers and virtual traders, to arbitrage price differences between the day-ahead (DA) market and the real-time (RT) market without physically consuming or producing energy. In this paper, market efficiency is defined in terms of trading profitability, where a zero-profit competitive equilibrium implies market efficiency (Jensen in, J Financial Econ 6(2):95-101, ). We analyze market data in the CAISO electric power markets, and empirically test for market efficiency by assessing the performance of trading strategies from the perspective of virtual traders. By viewing DA-RT spreads as payoffs from a basket of correlated assets, we can formulate a chance constrained portfolio selection problem, where the chance constraint takes two different forms as a value-at-risk constraint and a conditional value-at-risk constraint, to find the optimal trading strategy. A hidden Markov model (HMM) is further proposed to capture the presence of the time-varying forward premium. This is meant to be a contribution to the modeling of regime shifts in the electricity forward premium with unobservable states. Our backtesting results cast doubt on the efficiency of the CAISO electric power markets, as the trading strategy generates consistent profits after the introduction of CB, even in the presence of transaction costs. Nevertheless, by comparing with the performance before the introduction of CB, we find that the profitability decreases significantly, which enables us to identify the efficiency gain brought about by CB. Convincing evidence for the improvement of market efficiency in the presence of CB is further provided by the test for the Bessembinder and Lemmon (J Finance 57(3):1347-1382, ) model. [ABSTRACT FROM AUTHOR]

ABSTRACT The California generation fleet manages the existing variability and uncertainty in the demand for electric power (load). When wind power is added, the dispatchable generators manage the variability and uncertainty of the net load (load minus wind power). The variability and uncertainty of the load and the net load are compared when 8790 MW of wind power are added to the California power system, a level expected when California achieves its 33% renewable portfolio standard, using a data set of 26,296 h of synchronous historic load and modeled historic wind power output. Variability was calculated as the rate of change in power generated by wind farms or consumed by the load from 1 h to the next (MW/h). Uncertainty was calculated as the 1 h ahead forecast error [MW] of the wind power or of the load. The data show that wind power adds no additional variability than is already present in the load variability. However, wind power adds additional uncertainty through increased forecast errors in the net load compared with the load. Forecast errors in the net load increase 18.7% for negative forecast errors (actual less than forecast) and 5.4% for positive forecast errors (actual greater than forecast). The increase in negative forecast errors occurs only during the afternoon hours when negative load forecasts and positive wind forecasts are strongly correlated. Managing the integration of wind power in the California power system should focus on reducing wind power forecast uncertainty for wind ramp ups during the afternoon hours. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Regulators have proposed various institutional alternatives to secure network resource adequacy and reasonably priced electric power for consumers. These alternatives prompt many difficult questions: Does the development of Demand Response reduce the need for new capacity? How effectively can a government-mandated Capacity Market foster efficient investment? How does centralized generator commitment (with revenue guarantees) compare to a system in which Generators voluntarily commit themselves with no revenue guarantees? If exclusive distribution contracts were replaced by unregulated retail competition, what would be the effects on investment and market prices? We use laboratory experiments to address these questions. [ABSTRACT FROM AUTHOR]

Abstract: Tradable emission permits have received considerable attention recently. One emerging issue is its interaction with electricity markets, specifically, market power in the permit markets. One challenge in studying market power in the permit markets is that the demand for permits is implicitly determined by the system conditions. Traditional ways of modeling market power (e.g., standard Cournot model) cannot directly apply. This paper develops a model in which Cournot firms in the market can manipulate the permit price through fringe firms. We have two central findings in this paper. First, diverting emission permits from Cournot to fringe producers always reduce the power and the permit prices, which could improve social surplus. Second, when the fringe producer’s emission rate is low, diverting permits from the “dirty” (i.e., more-polluting) Cournot producer to the “clean” (i.e., less-polluting) Cournot producer leads to a decline of both power and permit prices. Therefore, the initial allocation of the emission permits could be a useful regulatory tool to mitigate the abuse of market power. We also illustrate these results through a numerical simulation of the California electricity market. [Copyright &y& Elsevier]

Abstract: This paper assesses the potential energy profile impacts of plug-in hybrid electric vehicles and estimates gasoline and electricity demand impacts for California of their adoption. The results are based on simulations replicating vehicle usage patterns reported in 1-day activity and travel diaries based on the 2000–2001 California Statewide Household Travel Survey. Four charging scenarios are examined. We find that circuit upgrades to 240V not only bring faster charging times but also reduce charging time differences between PHEV20 and PHEV60; home charging can potentially service 40–50% of travel distances with electric power for PHEV20 and 70–80% for PHEV60; equipping public parking spaces with charging facilities, can potentially convert 60–70% of mileage from fuel to electricity for PHEV20, and 80–90% for PHEV60; and afternoons are found to be exposed to a higher level of emissions. [Copyright &y& Elsevier]

The paper analyzes the impact of integrating wind generation on the regulation and load following requirements of the California Independent System Operator (CAISO). These requirements are simulated and compared for the study cases with and without wind generation impacts included into the study for the years 2006 and 2010. Regulation and load following models were built based on hour-ahead and five-minute ahead load and wind generation forecasts. In 2006, the CAISO system peaked at 50270 MW. Wind generation (at the installed capacity of 2600 MW) had limited impact on the requirement of load following and regulation in the CAISO Balancing Authority. However, in 2010 (with an expected installed capacity of approximately 6700 MW), this impact will significantly increase. The results provide very useful information for the CAISO to adjust its scheduling and real-time dispatch systems to reliably accommodate future wind generation additions within the CAISO Balancing Authority. [ABSTRACT FROM AUTHOR]

The article presents a study on an intelligent simulator to examine why a price hike occurred in the California electricity crisis. A multiagent intelligent simulator (MAIS) is compared with other methods, such as neural network (NN) and genetic algorithm (GA), using a real data set on power trading related to the crisis. The comparison showed that MAIS and the other methods performed in predicting the price fluctuation of wholesale electricity. Findings indicate that the price hike was due to an increase in fuel prices and real demand.

• Renewable hydrogen can compete with lithium-ion batteries for seasonal storage. • Hydrogen's competitiveness depends on heat rate of plant it is replacing. • Net present value of hydrogen-fired gas turbine varies based on operation of plant. • Lack of infrastructure will impede demand growth for hydrogen in the United States. Non-emitting variable renewable energy (VRE) resources are needed on the power grid if the United States is to "deeply decarbonize" the power sector. The intermittent nature of these resources makes them difficult to integrate into the power system. Existing energy storage technologies, such as lithium-ion (LI) batteries, could be used to aid the integration of these resources, but these technologies are sized to produce power for hours at a time before needing to be charged again. While these energy storage technologies could address daily imbalances between supply and demand for electric power, they cannot address the seasonal nature of power production of VREs. This paper details a methodology to estimate the levelized cost of energy (LCOE) of meeting this seasonal imbalance with either a hydrogen-fired gas turbine (HFGT) or lithium-ion battery system (LI) as a measure of economic efficiency of the technologies. Applying our model, we find the average LCOE associated with meeting this seasonal imbalance is $2400/MWh using a HFGT fueled with green hydrogen and $3000/MWh using a LI. If we allow the model to operate the HFGT with blue hydrogen the average LCOE decreases to $1560/MWh. However, we find the power prices required to justify investment in an HFGT to replace a natural gas-fired gas turbine are considerably higher than those seen in the market today. [ABSTRACT FROM AUTHOR]

Toyota Motor North America unveiled its first hydrogen fuel cell powered electric utility tractor rig (UTR), developed in collaboration with Fenix Marine Services, at the recent 2019 Fuel Cell Seminar & Energy Exposition in Long Beach, California. [ABSTRACT FROM AUTHOR]

Theory provides limited understanding of auctions in complex, multi-unit settings. This absence became apparent when performance concerns were raised over wholesale electric power auctions in England and California. This research used experiments involving 234 subjects to partially bridge the gap in knowledge with regard to bidding behaviour. Using a complex procurement setting motivated by power markets, bidding in the last accepted and first rejected uniform price auctions and the multi-unit Vickrey were examined across group sizes of 2, 4, and 6. To allow opportunity for tacit collusion, constant cost and demand conditions were maintained for 75 periods. Group size and experience were found to be most significant in explaining the differences between bids and costs. For groups of 2, this difference was significantly higher than with the other sizes, suggesting market power. Across sizes, after experience there was no significant difference in bidding behaviour between the uniform price auctions, with subjects in both bidding well above costs. Differences in the multi-unit Vickrey decreased after experience but, unexpectedly, bids were often below costs. Under no combinations did bids equal costs as would be desired by market designers. Results should give concern to policy analysts, and research suggestions to theorists. [ABSTRACT FROM AUTHOR]

Discusses several litigation and administrative proceedings involving companies in the electric market brought about by the electric power restructuring in California. Impact of the differences in the decision rules imposed through jurisprudence on electricity transactions; Evaluation of legal bases and policy rationales in characterizing electricity as either a good or a service; Details of the decisions of the Federal Energy Regulatory Commission that applied the Uniform Commercial Code to electricity disputes.

The article comments on papers by Oren, Smith, and Wilson (1985) and Wilson (1989) which consider means of mitigating the social consequences of rationing by matching the high value users to the power provision. The papers are analyzed in light of the rolling blackout used by California as a means of rationing electricity. The goal is to use ex ante pricing, or priority pricing, to insure that high value users have a higher probability of receiving the good. The mathematical fact proved in the article is that if the distributions satisfy standard hazard rate hypotheses, the social value of using two priorities is at least half of the gains of using infinitely many priority classes.

The article focuses on the impact of electric supply to the natural gas market in California. In the first half of 2001, proposals for power plants surged, supported by favorable perceptions of supply and demand fundamentals. Natural gas pipelines into California experienced very high load factors relative to the receipt capacity of California's utilities, prompting proposals for expansion of storage facilities and interstate pipelines. In addition, the number of active U.S. drilling rigs increased.

Provides information on the energy industry in California. Details of the energy crisis in the state; Summary of how the power markets work; Indications of increasing market efficiency; Information provided by the spot markets.

Examines the impact of electricity deregulation to electric utility industry and the quality of people's lives. Benefits of the deregulation to the industry; Role of the federal government in encouraging deregulation; Legislation on electricity deregulation in California; Reasons for the failure of deregulation; Criticism against measures to remove retail price controls in electricity.

Examines the relationship between the deregulation of the California electricity market and agricultural shortages in the Pacific Northwest. Natural and man-made factors that caused an increase in electricity prices in the Pacific Northwest; Information on the irrigation electricity buyout program proposed by the Idaho Power Co.; Impact of the power shortage and drought on agriculture in the Pacific Northwest.

In the mid-1990s, California was the first U.S. state to fundamentally change the way in which its electricity supply was regulated. In order to achieve competition on the electricity market, production and transportation were separated and electricity exchanges were set up. Following the introduction of the reforms, electricity prices initially fell somewhat for most consumers. This was considered a success of deregulation. In the summer of 2000 and again in the following winter, however, wholesale prices on the electricity exchange rose drastically. In mid-January 2001, electricity demand out-stripped available capacities, so that the power supply of many consumers had to be cut. In addition to the conceptional problems of deregulaion, a series of other factors also contributed to this development, such as under-estimating economic growth, the increase in electricity consumption in the second half of the 1990s, the elaborate and time-consuming approval procedures for power stations and insufficient incentives to save electricity. In Europe, the starting position is more advantageous than it was in California, but here, too, deregulation of the electricity supply could contribute to reducing capacity reserves and thereby to endangering the security of the power supply.

Focuses on the importance of vesting contracts in managing electricity market transition in California. Requirements for the success of electricity deregulation; Usability of hedging contracts in achieving deregulation objectives; Significance of vesting contracts in the management of financial risk of market participants.

Focuses on the performance of the electric power market in California. Influence of politics on the reduction of electric rates; Deregulation of the electricity market; Economic impact of electricity deregulation.

Focuses on the application of a geometric hedging model in the deregulated electricity market in California. Reduction of the rising electricity prices; Minimization of purchase cost; Stabilization of profit margins.

Focuses on the portfolio management of electricity supply in California. Impact of neglected portfolio management on electricity supply; Effects of environmental constraints on rising energy costs; Impact of wholesale electric market deregulation on electricity crisis.

Focuses on the electricity crisis threatening California. Association of carbon dioxide emissions with global climate change; Use of aging natural gas plants to meet peak demands; Need of the state for wind power.

Outlines a framework for adding an electricity capacity market in California. Types of sellers; Principles that must be considered; Illustrative assumptions.

Presents information on the restructuring efforts of the California electric market caused by changes in electric wholesale and retail market in the area. Independent system operator (ISO); Power exchange; Impact on system reliability; Challenges in the implementation of ISO.

Refutes Steven Stoft's claim that power marketers have crippled the California power exchange. Reasons for the encouragement of competition between the power exchange and the power marketers; Answers to allegations about the exchange's effectiveness; Benefits of the power exchange during the transition to competition.