US Power System Research Articles

Data Center Problems

“Hyperscale” data centers accompanying the rapid growth of artificial intelligence (AI) is one of the fastest growing uses of electricity in the United States and the rest of the world. Indeed, such growth, with the retirement of dispatchable fossil fuel electricity plants, drives persistent warnings about potential reliability problems for the US power system. As Federal Energy Regulatory Commission's (FERC's) Commissioner Mark Christie warned in late July, to the House Subcommittee on Energy, Climate, and Grid Security.

Accelerating transmission capacity expansion by using advanced conductors in existing right-of-way

As countries pursue decarbonization goals, the rapid expansion of transmission capacity for renewable energy (RE) integration poses a significant challenge due to hurdles such as permitting and cost allocation. However, we find that large-scale reconductoring with advanced composite-core conductors can cost-effectively double transmission capacity within existing right-of-way, with limited additional permitting. This strategy unlocks a high availability of increasingly economically viable RE resources in close proximity to the existing network. We implement reconductoring in a model of the US power system, showing that reconductoring can help meet over 80% of the new interzonal transmission needed to reach over 90% clean electricity by 2035 given restrictions on greenfield transmission build-out. With $180 billion in system cost savings by 2050, reconductoring presents a cost-effective and time-efficient, yet underutilized, opportunity to accelerate global transmission expansion.

Distributional labour challenges and opportunities for decarbonizing the US power system

The transition towards a low-carbon power system presents challenges and opportunities for the workforce with important implications for just transitions. Studies of these distributional labour impacts could benefit from tighter linkages between energy and employment modelling. Here, we couple a power-sector optimization model, an employment impact model and demographic databases to understand state-level job characteristics and the societal implications of low-carbon transitions in the US. Although decarbonization brings consistent job growth, it heightens the need for investment in human capital and supply chain restructuring. Major fossil fuel-producing states need to prepare for fewer mining jobs under the US Long-Term Strategy, so other opportunities should be created or seized. The lowest-skilled workers will experience more uncertain employment outcomes. Expanding renewable energy could improve opportunities for women in fossil fuel-dependent states, but not enough to disrupt the national gender status quo. This work provides a new quantitative perspective to inform proactive just transition policies.

Dispatch of highly renewable energy power system considering its utilization via a data-driven Bayesian assisted optimization algorithm

In recent years, renewable energy (RE) has been widely deployed, and the power system with high penetration RE is gradually formed. However, the high proportion of RE may threaten transmission security of power systems, which in turn limits its utilization. What is more, the interaction between RE penetration and power system transmission security has not been comprehensively investigated so far. To this end, we develop a bi-objective stochastic dispatch model to investigate the relationship between RE utilization and transmission security. It aims to solve the optimal power system dispatch (OPSD) problem with high penetration RE, in which the RE curtailment and the capacity margin of transmission lines are considered as two objectives of the dispatch problem and formulated in the probabilistic forms. With this, the proposed model is a complicated bi-objective stochastic optimization problem, which is difficult to be solved for traditional optimization algorithms. Therefore, we propose a data-driven Bayesian assisted optimization (DBAO) algorithm, based on Bayesian evolutionary optimization and estimation of distribution algorithm to improve the searching efficiency for the proposed model. Case studies on a modified Midwestern US power system verify the effectiveness of our proposed dispatch model and the optimization algorithm of DBAO.

Application of Big Data Analytics and Machine Learning to Large-Scale Synchrophasor Datasets: Evaluation of Dataset ‘Machine Learning-Readiness’

This manuscript presents a data quality analysis and holistic ’machine learning-readiness’ evaluation of a representative set of large-scale, real-world phasor measurement unit (PMU) datasets provided under the United States Department of Energy-funded FOA 1861 research program [1]. A major focus of this study is to understand the present-day suitability of large-scale, real-world synchrophasor datasets for application of commercially-available, off-the-shelf big data and supervised or semi-supervised machine learning (ML) tools and catalogue any major obstacles to their application. To this end, dataset quality is methodically examined through an interconnect-wide quantifications of basic bad data occurrences, a summary of several harder-to-detect data quality issues that can jeopardize successful application of machine learning, and an evaluation of the adequacy of event log labeling for supervised training of models used for online event classification. A global ’six-point’ statistical analyses of several key dataset variables is demonstrated as a means by which to identify additional hard-to-detect data quality issues, also providing an example successful application of big data technology to extract insights regarding reasonable operational bounds of the US power system. Obstacles for application of commercial ML technologies are summarized, with a particular focus on supervised and semi-supervised ML. Lessons-learned are provided regarding challenges associated with present-day event labeling practices, large spatial scope of the dataset, and dataset anonymization. Finally, insight into efficacy of employed mitigation strategies are discussed, and recommendations for future work are made.

Economic Dispatch with High Penetration of Wind Power Using Extreme Learning Machine Assisted Group Search Optimizer with Multiple Producers Considering Upside Potential and Downside Risk

The power system with high penetration of wind power is gradually formed, and it would be difficult to determine the optimal economic dispatch (ED) solution in such an environment with significant uncertainties. This paper proposes a multi-objective ED (MuOED) model, in which the expected generation cost (EGC), upside potential (USP), and downside risk (DSR) are simultaneously considered. The heterogeneous indices of upside potential and downside risk mean the potential economic gains and losses brought by high penetration of wind power, respectively. Then, the MuOED model is formulated as a tri-objective optimization problem, which is related to uncertain multi-criteria decision-making against uncertainties. After-wards, the tri-objective optimization problem is solved by an extreme learning machine (ELM) assisted group search optimizer with multiple producers (GSOMP). Pareto solutions are obtained to reflect the trade-off among the expected generation cost, the upside potential, and the downside risk. And a fuzzy decision-making method is used to choose the final ED solution. Case studies based on the Midwestern US power system verify the effectiveness of the proposed MuOED model and the developed optimization algorithm.

A systematic evaluation of wind's capacity credit in the Western United States

AbstractThe degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.

Highlighting and overcoming data barriers: creating open data for retrospective analysis of US electric power systems by consolidating publicly available sources

Studies of power system operation commonly draw from two key databases produced by the US Environmental Protection Agency: the Acid Rain Program’s Continuous Emission Monitoring System (CEMS) data, and the Emissions and Generation Resource Integrated Database (eGRID). Separate reporting requirements and heterogeneity in data aggregation between these two databases creates a barrier to systematic spatial and temporal retrospective power system analysis. This work describes the inherent challenges to this undertaking and documents a method for reconciling the two seemingly disparate data sources. While fundamental differences in data reporting and aggregation prevent us from achieving full coverage, this work represents an important initial step to aligning these two repositories of US power system data. We demonstrate the value of this linkage by computing relative unit-level, hourly utilization metrics for most thermal power plants in the US. Analysis of these metrics across time illustrates thermal generator cycling trends in California between 2011 and 2017. These unit-level results indicate that combined cycle units within California increased their part-load generation by 15% and resultant CO2 emissions by 17% and decreased their start/stop frequency over time by 8.5% and resultant emissions by 47%. Open cycle gas turbines overall increased their generation- number of start/stop cycles by 97% and resultant emissions by 85%, part-load generation by 120% and resultant emissions by 100%, and full load generation by 40% and resultant emissions 18%. We also observe a temporal shift in thermal generation from morning hours to evening in California.

Protecting ‘Cybersecurity & Resiliency’ of Nation’s Critical Infrastructure – Energy, Oil & Gas

Cyber and sophistication of cyber adversaries grow, so too must the US power system’s defenses, situational awareness, and response and recovery strategies. Traditionally power dedicated communication channels to large generators and utility-owned assets but network connectivity in today’s industrial entities, including electrical utilities, has exposed many digital communication and control aspects to the threat of cyber-attacks.When forward-looking improvements including smart grid, smart meters and other advancements are considered, security is of foremost concern. In fact, governments around the world have recognized the existing vulnerability and need to protect the grid infrastructure. To solve the problem, regulations and standards are being developed to ensure that the proper security steps are taken. In addition, cyber attackers have targeted crude oil and natural gas (O&G) companies, with attacks growing in frequency, sophistication and impact as the industry employs ever more connected technology. But the industry’s cyber maturity is relatively low, and O&G boards show generally limited strategic appreciation of cyber issues. research paper documents the current spread throughout US, highlights required security enhancements and recommendations to foster Cyber-secure, resilient energy is paramount to the prosperity of the United States. As the experience additionally, power systems were operated with control aspects to the threat of cyber companies, with attacks growing in frequency, sophistication, and Cyber security gaps across Energy, Oil & Gas sector systems Security & Resiliency of our Critical Infrastructure.

Sunny with a Chance of Curtailment: Operating the US Grid with Very High Levels of Solar Photovoltaics.

SummaryWith rapid declines in solar photovoltaic (PV) and energy storage costs, futures with PV penetrations approaching or exceeding 50% of total annual US generation are becoming conceivable. The operational merits of such a national-scale system have not been evaluated sufficiently. Here, we analyze in detail the operational impacts of a future US power system with very high annual levels of PV (>50%) with storage. We show that load and operating reserve requirements can be met for all hours while considering key generator operational constraints. Storage plays an active role in maintaining the balance of supply and demand during sunset hours. Under the highest PV penetration scenario, hours with >90% PV penetration are relatively common, which require rapid transitions between predominately conventional synchronous generation and mostly inverter-based generation. We observe hours with almost 400 GW (over 40%) of economic curtailment and frequent (up to 36%) hours with very low energy prices.

A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges

Power systems are the most complex systems and have great importance in modern life. They have direct impacts on the modernization, economic, political and social aspects. To operate such systems in a stable mode, several control and protection techniques are required. However, modern systems are equipped with several protection schemes with the aim of avoiding the unpredicted events and power outages, power systems are still encountering emergency and mal-operation situations. The most severe emergencies put the whole or at least a part of the system in danger. If the emergency is not well managed, the power system is likely to have cascading failures that might lead to a blackout. Due to the consequences, many countries around the world have research and expert teams who work to avoid blackouts on their systems. In this paper, a comprehensive review on the major blackouts and cascading events that have occurred in the last decade are introduced. A particular focus is given on the US power system outages and their causes since it is one of the leading power producers in the world and it is also due to the ready availability of data for the past events. The paper also highlights the root causes of different blackouts around the globe. Furthermore, blackout and cascading analysis methods and the consequences of blackouts are surveyed. Moreover, the challenges in the existing protective schemes and research gaps in the topic of power system blackout and cascading events are marked out. Research directions and issues to be considered in future power system blackout studies are also proposed.

Power and energy [Technology 2000 analysis and forecast

Partly because it is the turn of the Century and the Millennium, and partly because the huge challenges facing the electric power industry cry out for bold new approaches, a number of influential organizations have formulated sweeping plans for the world's energy future. Ironically, at just the time these far-reaching roadmaps have been appearing, the US power system has been plagued by concrete, workaday problems that just as manifestly are not being adequately addressed. Over the last decade, the power system has been converted into a common carrier network; the vertically integrated utilities of tradition have been unbundled into generators, distributors, and transmitters of electricity and much of the time-honored regulatory apparatus has been dismantled or weakened. From one point of view, the system looks to be separating Lear-like into a set of feuding baronies. Even as each proffers its own view of the situation and vies with the others- to impose or sell a preferred approach, none has the legal, political, or moral authority to do so.

The new-but is it improved?-power system [deregulation issues

In this paper, the author examines the effect that deregulation will have on the US power system. The paper details how the electric power industry in the USA is undergoing major changes, both politically and technically, as a result of the Federal Energy Regulatory Commission's Orders 888 and 889 issued in 1996. These orders essentially deregulate the transmission network, allowing producers and customers access to the network for electricity transactions.

Becoming proactive about environmental risks: Regulatory reform and risk management in the US electricity sector

Future environmental requirements are an important component of investment risk for long-lived facilities such as electric power plants. Yet the industry's current regulatory compact discourages proactive environmental investments, and thus encourages suboptimal long-term compliance strategies. This paper develops an indicative estimate of the resulting inefficiency by analysing a typical US power system. It argues that market-oriented regulatory reform can encourage environmental risk management by utilities.

Damping enhancement in the Western US power system: a case study

This paper describes a case study using power system stabilizers to enhance the damping of the Western US power system. The study is based on a particular model of the system. Local and inter-area modes are first identified for two load flow cases and then stabilization and damping improvement of these modes are obtained. Approaches for further damping improvement of a 0.7 Hz inter-area mode are recommended. >

Application of Prony analysis to the determination of modal content and equivalent models for measured power system response

It has been shown by J.F. Hauer et al. (ibid., vol.5, p.80-90, Feb. 1990) that Prony analysis can be very effective in response-based modal analysis of noise-free linear time-invariant (LTI) systems. This methodology extends Fourier analysis by directly estimating the frequency, damping, strength, and relative phase of the modal components present in a recorded signal. This earlier work is extended, concentrating upon power system planning applications, for stability program outputs. Results are presented for modal analysis and detailed model construction based on response data obtained through large-scale tests of the western US power system. An optimal modeling program, SYSFIT, is used to supplement the measurements. >