SEARCH · Engineering Papers

Results for “renewable variable generation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Systematic Approach to Better Understanding Integration Costs: Preprint

When someone mentions integration costs, thoughts of the costs of integrating renewable generation into an existing system come to mind. We think about how variability and uncertainty can increase power system cycling costs as increasing amounts of wind or solar generation are incorporated into the generation mix. However, seldom do we think about what happens to system costs when new baseload generation is added to an existing system or when generation self-schedules. What happens when a highly flexible combined-cycle plant is added? Do system costs go up, or do they go down? Are other, non-cycling, maintenance costs impacted? In this paper we investigate six technologies and operating practices--including VG, baseload generation, generation mix, gas prices, self-scheduling, and fast-start generation--and how changes in these areas can impact a system's operating costs. This paper provides a working definition of integration costs and four components of variable costs. It describes the study approach and how a production cost modeling-based method was used to determine the cost effects, and, as a part of the study approach section, it describes the test system and data used for the comparisons. Finally, it presents the research findings, and, in closing, suggests three areas for future work.

17 WIND ENERGY↗

DOE OSTI2019

Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence

Here, we synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted or might in the future impact bulk power system assets, pricing, and costs in the United States. Most studies of future scenarios indicate that VRE reduces wholesale energy prices and capacity factors of thermal generators. Traditional baseload generators are more exposed to these changing market conditions than low-capital cost and more flexible intermediate and peak-load generators. From analysis of historical data we find that VRE is already influencing the bulk power market through changes in temporal and geographic patterns areas with higher levels of VRE. The most significant observed impacts have concentrated in areas with significant VRE and/or nuclear generation along with limited transmission, with negative pricing also often occurring during periods with lower system-wide load. So far, however, VRE, has had a relatively modest impact on historical average annual wholesale prices across entire market regions, at least in comparison to other drivers. The reduction of natural gas prices is the primary contributor to the decline in wholesale prices since 2008. Similarly, VRE impacts on thermal plant retirements have been limited and there is little relationship between the location of recent retirements and VRE penetration levels. Finally, although impacts on wholesale prices have been modest so far, impacts of VRE on the electricity market will be more significant under higher VRE penetrations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

The Use of Statistically Based Rolling Supply Curves for Electricity Market Analysis: A Preliminary Look

In light of the changing electricity resource mixes across the United States, an important question in electricity modeling is how additions and retirements of generation, including additions in variable renewable energy (VRE) generation could impact markets by changing hourly wholesale energy prices. Instead of using resource-intensive production cost models (PCMs) or building and using simple generator supply curves, this analysis uses a 'top-down' approach based on regression analysis of hourly historical energy and load data to estimate the impact of supply changes on wholesale electricity prices, provided the changes are not so substantial that they fundamentally alter the market and dispatch-order driven behavior of non-retiring units. The rolling supply curve (RSC) method used in this report estimates the shape of the supply curve that fits historical hourly price and load data for given time intervals, such as two-weeks, and then repeats this on a rolling basis through the year. These supply curves can then be modified on an hourly basis to reflect the impact of generation retirements or additions, including VRE and then reapplied to the same load data to estimate the change in hourly electricity price. The choice of duration over which these RSCs are estimated has a significant impact on goodness of fit. For example, in PJM in 2015, moving from fitting one curve per year to 26 rolling two-week supply curves improves the standard error of the regression from 16 dollars/MWh to 6 dollars/MWh and the R-squared of the estimate from 0.48 to 0.76. We illustrate the potential use and value of the RSC method by estimating wholesale price effects under various generator retirement and addition scenarios, and we discuss potential limits of the technique, some of which are inherent. The ability to do this type of analysis is important to a wide range of market participants and other stakeholders, and it may have a role in complementing use of or providing calibrating insights to PCMs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Forecasting Commercial Building Electricity Consumption, Zone Airflow and Zone Temperature: Update - Development of a Generalized Machine Learning Approach

The U.S. power grid is being transformed to make it smarter, more efficient, and cleaner. This transformation is leading to the addition of a significant of energy generated by distributed, variable, and renewable resources. Because of the variable nature of renewable generation, the short- and long-term supply and demand imbalances are less predictable, and conventional approaches to mitigating the imbalances will be less efficient or cost effective. To address this challenge and to support the mission and the vision of the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) Building Technologies Office has developed a Grid-Interactive Efficient Building Strategy. The strategy focuses on simultaneously improving building energy efficiency and supporting reliability and resilience of the electric grid more efficiently and at a lower cost. In addition, EERE and DOE’s Office of Electricity created an initiative led by DOE and supported by the national laboratories under the Grid Modernization Lab Consortium structure to enhance grid modernization. The work reported in this document is part of the first set of projects funded under the initiative to design, develop, and validate scalable transactive control technologies for the commercial buildings sector. Transactive controls requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical grey- and black-box models have been widely used to express flexibility. Although this approach is generally easy to construct and simple to use, it does not capture non-linear behavior that some end-use loads represent. Therefore, Pacific Northwest National Laboratory (PNNL) with support from Western Washington University conducted this research to explore the use of deep machine learning (ML) techniques. The work reported in this document is limited to forecasting whole building electricity consumption, the zone airflow and the zone temperature predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

A robust approach to chance constrained optimal power flow with renewable generation

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved using a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Pilot Development Progress to Demonstrate Electric Thermal Energy Storage (ETES) Using Low-Cost Particles

The rapid growth of variable renewable power generation increases the need to economically store electrical energy over durations up to several days in long-duration energy storage (LDES) applications. LDES can bridge the intermittency of increasing variable renewable energy (VRE) and facilitate emission-free dispatchable electricity to improve the resilience of the grid and provide reliable and potentially cost-effective energy. Several energy storage approaches including mechanical, chemical and electrochemical methods are currently deployed or under development. However, LDES requirements pose unique challenges for scalability, energy capacity, and cost. Electro-thermal energy storage (ETES) can store a large capacity of energy with site flexibility and has attracted significant interest for LDES purposes. This paper shows the progress of developing a demonstration test facility for particle ETES technology including pilot-scale component design and fabrication.

25 ENERGY STORAGE↗

DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗

DOE OSTI2017

An Evaluation of Energy Storage Options for Nuclear Power

The dynamics of energy generation, delivery, and consumption in the United States continue to change as new energy sources come online and consumers purchase more energy-intensive devices. The percentage of electricity generation from variable renewable energy sources like wind and solar power has grown year after year. Meanwhile, the evolution of electric vehicles, smart devices, and consumer appliances is changing the way that electricity is used. As a result of these trends, nuclear power plants (NPPs) are being asked to operate more flexibly. Newly constructed, advanced nuclear power plants (A-NPPs) will likely need to adapt their business models with these market shifts in mind. In the future, A-NPPs might operate in an electricity system that values flexibility (e.g. fast ramping) more than stability (e.g. baseload supply). The current fleet of NPPs is struggling to remain economically viable in competitive markets that favor low natural gas prices and renewable energy sources with low marginal costs. Rising construction costs and ambiguous national policies have only added to the challenges facing plant operators. The industry as a whole is in decline, with 19 reactors in the process of being decommissioned and 5 of these plants retiring in the past decade. However, NPPs also provide several performance and environmental benefits by maintaining a high capacity factor and generating almost zero greenhouse gas (GHG) emissions over the life cycle of the plant. As more areas of energy consumption in the United States are electrified, NPPs could potentially replace coal and natural gas as a source of heat and power to help decarbonize the U.S. energy mix. Improving the flexibility of newly constructed A-NPPs to increase revenue through market hedging and reduce costs via stable operation was explored in this analysis. The increasing penetration of variable energy resources could contribute to the uncertainty of electricity demand, which could in turn increase the need for dispatchable electricity generating units. This role is currently filled by inexpensive natural gas combined cycle (NGCC) plants, whereas coal and NPPs have traditionally been called upon to provide baseload power by maintaining a constant power output. As wholesale electricity prices continue to fall due to low natural gas prices and federally subsidized renewable energy, this business model has begun to fail, resulting in incidences of NPPs selling electricity at a loss. Since it has not been economically favorable for NPPs to operate flexibly in this situation in the past, due to their low variable costs compared to fossil fuel power plants, NPPs in the United States were not built with this purpose in mind. Therefore, legacy NPPs have had difficulty adapting to these shifting dynamics due to regulatory and technical constraints, coupled with a lack of meaningful experience. NPPs in France have operated in this manner for years, due to a much higher percentage of baseload generators and a lower percentage of fast-ramping NGCC plants. The integration of energy storage technologies (ESTs) alongside newly constructed A-NPPs will be investigated in this analysis as an alternative method for helping NPPs resolve the economic challenges they currently face. Although the deregulation of energy markets in the United States is responsible for much of the increased competition from natural gas and renewable energy that has negatively impacted NPPs, this process has also led to the creation of ancillary service markets. ESTs can provide many of these services, so an integrated energy storage system could supplement both the reliability of the electricity grid and the economic performance of a NPP by bidding into these markets. However, many technical, financial, and regulatory barriers still prevent ESTs from operating profitably in this space. The purpose of this body of work is to compile a transparent database of metrics for available ESTs and identify barriers to widespread deployment. An analytical selection methodology was also developed to identify favorable technologies for integration with specific NPPs based on information supplied by an interested developer. These tools could help reduce the perceived risk surrounding investment in energy storage systems, which could help both NPPs in need of economic assistance and ESTs in need of further research and development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Modeling and Analysis of Wholesale Electricity Market Design. Understanding the Missing Money Problem. December 2013 - January 2015

This project examined the impact of renewable energy sources, which have zero incremental energy costs, on the sustainability of conventional generation. This “missing money” problem refers to market outcomes in which infra-marginal energy revenues in excess of operations and maintenance (O&M) costs are systematically lower than the amortized costs of new entry for a marginal generator. The problem is caused by two related factors: (1) conventional generation is dispatched less, and (2) the price that conventional generation receives for its energy is lower. This lower revenue stream may not be sufficient to cover both the variable and fixed costs of conventional generation. In fact, this study showed that higher wind penetrations in the Electric Reliability Council of Texas (ERCOT) system could cause many conventional generators to become uneconomic.

16 TIDAL AND WAVE POWER↗

DOE OSTI2016

Dynamic performance analysis of two regional Nuclear Hybrid Energy Systems

In support of more efficient utilization of clean energy generation sources, including renewable and nuclear options, hybrid energy systems (HES) can be designed and operated as flexible energy resources (FER) to meet both electrical and thermal energy needs in the electric grid and industrial sectors. These conceptual systems could effectively and economically be utilized, for example, to manage the increasing levels of dynamic variability and uncertainty introduced by variable energy resources (VER) such as renewable sources (e.g., wind, solar), distributed energy resources, demand response schemes, and modern energy demands (e.g., electric vehicles) with their ever changing usage patterns. HES typically integrate multiple energy inputs (e.g., nuclear and renewable generation) and multiple energy outputs (e.g., electricity, gasoline, fresh water) using complementary energy conversion processes. This work reports a preliminary dynamic analysis of two realistic HES including a nuclear reactor as the main baseload heat generator and to assess the local (e.g., HES owners) and system (e.g., the electric grid) benefits attainable by their application in scenarios with multiple commodity production and high renewable penetration. It is performed for regional cases - not generic examples - based on available resources, existing infrastructure, and markets within the selected regions. This study also briefly addresses the computational capabilities developed to conduct such analyses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Repurposing Fossil-Fueled Assets For Energy Storage

The annual retirement of U.S. coal-fired electricity generation units (CF-EGU) is at an all-time high and is expected to continue. This loss of reliable baseload generation, combined with predicted growth of variable renewable energy (VRE) generation, is expected to stress grid reliability as the number of load-following resources drops below the experienced load variability. Many regions are already experiencing challenges, and fossil retirement-related warnings by the North American Electric Reliability Corp. are becoming more dire. All CF-EGU retirements pose significant challenges to asset owners, local workforces, and their communities. Repurposing a retiring CF-EGU as a long-duration energy storage plant can address these challenges and offer a suite of additional benefits to asset owners, the grid, and society. This project performed a techno-economic evaluation and assessment of repurposing a Duke Energy fossil-fueled asset (in particular, a coal plant) into an energy storage system by integrating the retiring asset with a Malta long duration Pumped Heat Energy Storage (PHES) system. The project validated the technoeconomic benefits of repurposing retiring coal plants into long-duration energy storage using Malta’s PHES. Key findings for this project are summarized below: (1) Technical: (a) Retiring coal plants (and other steam turbine fossil generation) can be repurposed to enable the clean energy transition using Malta’s technology. (b) For older retiring coal plants, repurposing the site and electrical interconnection for a standalone PHES plant is the most economically favorable option. (c) For newer coal plants where there is also a local peaking capacity need, repowering the steam cycle into a hybrid integration with PHES is attractive. (d) A process was developed to assist fossil generation owners in choosing the best path for each plant’s circumstances. (2) Economic (a) Communities facing economic challenges caused by the retirement of fossil generation would benefit from repurposing the plant as long-duration energy storage using Malta’s PHES. (b) On a $/MW basis, repowering retiring coal units into Malta PHES plants can maintain the same number and types of jobs and economic activity. (c) For a 70% carbon reduction scenario, a 10-hour Malta PHES plant is more economic for the asset owner than similar-power 4-hour batteries. This project showed that repurposing a retiring coal unit into thermal energy storage, by integrating it with a Malta PHES system, makes techno-economic sense. At least two integration options are available, with the optimal solution depending on the coal plant and its location. Repurposing retiring coal plant into energy storage results in economic benefits for the plant owner and local communities.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Operational Analysis of the Eastern Interconnection at Very High Renewable Penetrations

The primary objective of the study reported here is to build on work by Mai et al. (2012) and Brinkman (2015) by performing detailed modeling of the U.S. Eastern Interconnection operations with approximately 70% of all energy coming from wind and solar generation. The study assesses the ability to balance supply and demand for electricity using a unit commitment and economic dispatch model with a five-minute time resolution. In addition, the study explores the implications of different amounts of physical and institutional flexibility for balancing. We also present an analysis of system “stress” by quantifying various metrics, such as the amount of spare online capacity, penetration levels of non-synchronous generators, day-ahead compared to real-time curtailment, and start-ups of peaking generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2012

Impacts of Solar Power on Operating Reserve Requirements (Fact Sheet)

A one-page, two-side fact sheet on the impacts of solar power on operating reserve requirements.

14 SOLAR ENERGY↗

DOE OSTI2022

Enhanced Long-Duration Energy Storage Modeling [Slides]

As our power grid evolves toward a more renewable future, energy storage is poised to take a larger role in meeting growing energy needs. Energy storage could help keep the power system reliable even through potential outages, periods of extreme weather, and when generation from variable renewable technologies like wind and solar is low. Given the different durations of these stressors, grid analysts at the National Renewable Energy Laboratory (NREL) are working to better understand the role and benefits of long-duration energy storage - or storage technologies with 8-24 hours of storage capacity - in high variable renewable energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

DOE OSTI2023

Beyond Expected Values Evolving Metrics for Resource Adequacy Assessment

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2013

Impact of Wind and Solar on the Value of Energy Storage

This analysis evaluates how the value of energy storage changes when adding variable generation (VG) renewable energy resources to the grid. A series of VG energy penetration scenarios from 16% to 55% were generated for a utility system in the western United States. This operational value of storage (measured by its ability to reduce system production costs) was estimated in each VG scenario, considering provision of different services and with several sensitivities to fuel price and generation mix. Overall, the results found that the presence of VG increases the value of energy storage by lowering off-peak energy prices more than on-peak prices, leading to a greater opportunity to arbitrage this price difference. However, significant charging from renewables, and consequently a net reduction in carbon emissions, did not occur until VG penetration was in the range of 40%-50%. Increased penetration of VG also increases the potential value of storage when providing reserves, mainly by increasing the amount of reserves required by the system. Despite this increase in value, storage may face challenges in capturing the full benefits it provides. Due to suppression of on-/off-peak price differentials, reserve prices, and incomplete capture of certain system benefits (such as the cost of power plant starts), the revenue obtained by storage in a market setting appears to be substantially less than the net benefit (reduction in production costs) provided to the system. Furthermore, it is unclear how storage will actually incentivize large-scale deployment of renewables needed to substantially increase VG penetration. This demonstrates some of the additional challenges for storage deployed in restructured energy markets.

14 SOLAR ENERGY↗