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Some of the deadliest wildfires in the U.S., such as California’s 2018 wildfires, have been ignited by power systems. In an effort to prevent and minimize the ignition of wildfires, or control them if ignited, energy companies have developed wildfire mitigation plans. This paper provides energy companies and power system operators, engineers, researchers, and suppliers an overview of the state-of-the-art studies that address key topics in these wildfire mitigation plans and compares the wildfire mitigation plans of several energy companies. The key topics include grid design and system hardening, asset management and inspection, situational awareness and forecasting, operational response, vegetation management, public safety power shutoff, and risk-spend efficiency. This paper also presents a comparison of several energy companies’ decision-making criteria for initiating a public safety power shutoff. Finally, we discuss opportunities for future research studies that could help energy companies prevent wildfire ignitions. [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]

Convergence bidding, a.k.a., virtual bidding, has been widely adopted in wholesale electricity markets in recent years. It provides opportunities for market participants to arbitrage on the difference between the day-ahead market locational marginal prices and the real-time market locational marginal prices. Given the fact that convergence bids (CBs) have a significant impact on the operation of electricity markets, it is important to understand how market participants strategically select their CBs in real-world electricity markets. We address this open problem with focus on the electricity market that is operated by the California Independent System Operator (ISO). In this regard, we use the publicly available electricity market data to learn, characterize, and evaluate different types of convergence bidding strategies that are currently used by market participants. Our analysis includes developing a data-driven reverse engineering method that we apply to three years of real-world California ISO market data. Our analysis involves feature selection and density-based data clustering. It results in identifying three main clusters of CB strategies in the California ISO market. Different characteristics and the performance of each cluster of strategies are analyzed. Interestingly, we unmask a common real-world strategy that does not match any of the existing strategic convergence bidding methods in the literature. Next, we build upon the lessons learned from the advantages and disadvantages of the existing real-world strategies in order to propose a new CB strategy that can significantly outperform them. Our analysis includes developing a new strategy for convergence bidding. The new strategy has three steps: net profit maximization by capturing price spikes, dynamic node labeling, and strategy selection algorithm. We show through case studies that the annual net profit for the most lucrative market participants can increase by over 40% if the proposed convergence bidding strategy is used. [ABSTRACT FROM AUTHOR]

A pseudo-tie resource model is a means by which a resource (i.e., generation unit or load) is operationally transferred from one balancing authority (BA) area in which the resource is physically located (i.e., native BA) to another (i.e., attaining BA area). The attaining BA has responsibility for operational control of the pseudo-tie resource for both system reliability and electricity market purposes. By implementing a pseudo-tie, the California Independent System Operator Corporation (ISO) BA is able to attain control of resources physically located external to its jurisdiction for its BA area services. [ABSTRACT FROM PUBLISHER]

The California energy crisis in 2000-2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This paper presents a flexible and integrative method to assess market designs through agent-based modeling. Realistic simulation scenarios are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GENCO) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. [ABSTRACT FROM AUTHOR]

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]

Wind power production is variable, but also has diurnal and seasonal patterns. These patterns differ between sites, potentially making electric power from some wind sites more valuable for meeting customer loads or selling in wholesale power markets. This paper investigates whether the timing of wind significantly affects the value of electricity from sites in California and the Northwestern United States. We use both measured and modeled wind data and estimate the time-varying value of wind power with both financial and load-based metrics. We find that the potential difference in wholesale market value between better-correlated and poorly correlated wind sites is modest, on the order of 5%-10%. A load-based metric, power production during the top 10% of peak load hours, varies more strongly between sites, suggesting that the capacity value of different wind projects could vary by as much as 50% based on the timing of wind alone. [ABSTRACT FROM AUTHOR]

Transmission faults caused by recent wildfires in California have induced the disconnection of utility-scale converters in photovoltaic (PV) power plants. Postmortem investigations reported that tripping commands were caused by phase-locked loops (PLLs) and dc-side dynamics, which are typically unmodeled in classical transient stability studies. Since existing simulation packages rely on simplified models that neglect these dynamics, they have a limited capability to predict converter behavior during faults. To address this shortcoming, we set forth a positive-sequence model for PV power plants that is derived from physics and controls first principles. As seen on utility-scale three-phase converters, the model includes PLLs, dc-side dynamics, and closed-loop controllers. Instances of the developed model are integrated into illustrative power systems containing conventional generators. Numerical simulations of the obtained multi-machine multi-converter power systems are assessed via a suitable set of stability and performance metrics. [ABSTRACT FROM AUTHOR]

Recent work suggests that further integration of wind and solar resources into the power grid will increase the demand for regulation and load following. The purpose of this letter is to investigate an important aspect of using energy storages for providing regulation: The short-term energy restoration of such limited energy resources (LERs) coincides with load following operations and could therefore lead to higher load following requirements. We therefore analyze the impact of corresponding scheduling approaches on load following energy and capacity using stochastic simulations. In particular, we compare the load following impact of a basic control strategy proposed by the stakeholders of the Independent System Operator in California (CAISO) to a strategy that attempts to manage the energy level of LERs such that their impact on load following requirements is optimal. Our results show that such smart state of charge management could even reduce the demand for load following while satisfying the full regulation demand in the CAISO control region. [ABSTRACT FROM PUBLISHER]

As compared to load demand, frequent wind energy intermittencies produce large short-term (sub 1-h to 3-h) deficits (and surpluses) in the energy supply. These intermittent deficits pose systemic and structural risks that will likely lead to energy deficits that have significant reliability implications for energy system operators and consumers. This work provides a toolset to help policy makers quantify these first-order risks. The thinking methodology/framework shows that increasing wind energy penetration significantly increases the risk of loss in California. In addition, the work presents holistic risk tables as a general innovation to help decision makers quickly grasp the full impact of risk. [ABSTRACT FROM PUBLISHER]

We examine price by season and by year in 14 deregulated markets, by looking at diurnal price patterns and price volatility. Power price volatility is measured by price velocity, the daily average of the absolute value of price change per hour, which is broken into a component expected from the average diurnal pattern, and an unexpected component. Deregulated markets can be categorized into three groups: stable markets, markets that experienced one bad period or season of high price excursion, and chaotic markets. Britain, Spain and Scandinavia show consistent price patterns and low unexpected price velocity; a thoughtful consumer could reasonably implement demand side management (DSM) by shaping consumption patterns to reflect price. California, New Zealand and Alberta are examples of markets that had a period of very high price excursion; we discuss factors affecting public reaction to this. Australian power markets have inconsistent price patterns from season to season and year to year, and very high unexpected price velocity. Planned DSM in these markets would be very difficult. We offer four policy considerations for markets considering deregulation in the future. [ABSTRACT FROM AUTHOR]

Provides an overview of elements necessary for effective design and implementation of electricity market monitoring systems. Definition of the concept of market power, market inefficiency and gaming; Summary of the main market monitoring activities of independent system operators in California; Recommendations for developing effective market monitoring systems.

Presents a study that determined the potential impacts of distributed energy resource (DER) on future transmission grid stability in California. Approaches in determining the effect of DER on the Western Systems Coordinating Council dynamic stability; Influences of DER on the transmission grid; Application of the prony method on the problem.

Presents information on a study which characterized the price behavior in the electricity industry in California. Background on the hourly-unconstrained market clearing prices; Methodology of the study; Results and discussion.

Presents the Power System program at the Naval Postgraduate School (NPS). Offers of the Power System program at NPS; Program structure; Program research; Future initiatives of the program at NPS; Conclusions.

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.