Integrated North American energy markets under different futures of cross-border energy infrastructure
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Siddiqui, Sauleh↗
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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.
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Sensitivity of future regional and global energy markets and macroeconomic activity to a hypothetical global energy market disruption
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29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Ocean Energy: Markets - Currency - Impact. Dimension of & Choices in the Technology Development Space: Preprint
This paper presents considerations of the employment of ocean wave energy to support different energy demand side applications. The key aspect in these considerations is the wave energy supported achievable positive impact and associated tangible contribution in service of common societal good and of the natural commons. The level of impact that can be delivered is dependent on both, the level of contribution of the supported energy use application, and the compatibility and unique suitability of the wave energy resource and its characteristics with the needs of the application. Thus, a variety of ocean wave energy markets, the key value indicators or "currency' in which these markets trade the value delivered and the achievable positive impact, are reflected upon. Ocean wave energy supported acquisition of high quality ocean system data across a wide spectrum of system properties is identified as a highly impactful application enabling and/or improving a comprehensive range of impactful ocean system activities. The technology development process towards these markets and desired impacts requires relevant technology development progress guidance and metrics. Going beyond technology readiness levels and technology performance levels, the notion of further technology development progress scales towards high impact and high contribution are proposed. These scales and the associated technology properties can be regarded as additional technology development dimensions to span-up the technology development space in which desired system capability and functional requirement choices and subsequent ideation, innovation, research and technology development decisions can and are to be made.
data market↗
Blockchain smart contracts for energy markets
A successful architecture that depicts the relationship between the energy market engineering requirements and blockchain requirements (shown as enablers). Software includes sequential and relational architectures supported by the UML flow diagrams. For a successful blockchain agnostic implementation of energy markets, the proposed architecture/blueprint supported by prototype implementation is very efficient. The proposed invention also depicts various means of the use of blockchain technology for energy market systems.
Gourisetti, Sri Nikhil Gupta↗
Voluntary Renewable Energy Markets 101 Workshop
These slides are for the Voluntary Renewable Energy Markets 101 Workshop at the annual Renewable Energy Markets Conference.
101↗
Hierarchical Flexibility Offering Strategy for Integrated Hybrid Resources in Real-time Energy Markets
This paper proposes a hierarchical model for determining the energy flexibility offering strategy of integrated hybrid resources (IHRs) in power distribution systems to participate in real-time energy markets. The proposed model utilizes the scalability, fast response time, and uncertainty observation of deep reinforcement learning (DRL) to overcome the scalability issue of operating numerous flexible resources and deliverability of energy flexibility to the real-time markets in the presence of the network constraints. To that end, the power distribution system is divided into multiple IHRs, where different types of flexible loads, energy storage systems, and solar plants with controllable inverters are operated through local IHR controllers, trained by deep deterministic policy gradient (DDPG) algorithm. Active power request and reactive power capacity of IHRs are then transmitted to a central flexibility controller, where a quadratic optimization model ensures the deliverability of the energy flexibility to the real-time energy market by satisfying the distribution network constraints. The proposed model is implemented on the 123-bus test power distribution system, demonstrating the capability of DRL-based hierarchical model for scalable operation of IHRs in order to offer deliverable energy flexibility to the real-time energy market.
Majidi, Majid↗
Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets
Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a “fossil-fueled development” scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8–2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Solar energy market penetration models - Science or number mysticism
The forecast market potential of a solar technology is an important factor determining its R&D funding. Since solar energy market penetration models are the method used to forecast market potential, they have a pivotal role in a solar technology's development. This paper critiques the applicability of the most common solar energy market penetration models. It is argued that the assumptions underlying the foundations of rigorously developed models, or the absence of a reasonable foundation for the remaining models, restrict their applicability.
Warren, E. H., Jr.↗
Emerging Energy Market Analysis Initiative, Methodological Framework
Planning and operations of the electric power sector are undergoing radical changes. Climate change mitigation efforts have forced rapid changes to the technology mix. Technologies like wind and solar have experienced rapid growth, while investment in fossil sources has peaked or is declining. These foundational changes are forcing changes to energy systems. Demand-side adoption of electrified technologies, including electric vehicles, is changing load profiles and opening up new avenues for consumer participation in the power systems. The implications of an evolving power system pertain to more than environmental and technical dimensions. Changes to the generation mix and its consequent upstream and downstream impacts such as fuel production have significant and highly concentrated consequences on economies and employment. Shifts towards distributed (or decentralized) generating assets offer the potential to reshape economic and employment opportunities associated with the energy sector across space and socioeconomic groups. The Emerging Energy Market Analysis (EMA) initiative aims to identify sustainable, regionally acceptable, and high-value energy solutions that are secure and equitable. Unlike short-term, least-cost choices that can narrowly account for traditional options, EMA’s focus on emerging energy markets recognizes that new or adapted practices and technologies can alter the frontier of solutions and advance a community’s social, economic, and natural pathways. Such change requires a more comprehensive analysis of societal input, resources, capabilities, and infrastructure. These considerations lay the foundation for community decision-making models that are responsive to community values as well as the history and drivers. The result is a community-based decision and engagement model that will be valuable to decisionmakers and developers of advanced and emerging energy solutions, seeking a social license to operate prior to project development.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
An Analysis of the Operating Characteristics of Natural Gas-Fired Turbines in the U.S. and Implications for Energy Market Models
The objective of this project is to investigate the operating characteristics of the existing NGCC fleet in more detail to better inform energy markets modeling assumptions.
Nichols, Chris↗
Estimating Energy Market Schedules using Historical Price Data
The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets creates uncertainty as well as new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. The proposed algorithm is approximately 100 times faster and uses orders of magnitude less data than a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.
electricity generation↗
Estimating Energy Market Schedules Using Historical Price Data: Preprint
The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets increases uncertainty and creates new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. This is orders of magnitude less data than required for a market clearing calculation with a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.
electricity generation↗
Reduced Order Costs for CO 2 Saline Storage for Use in Energy Market Models
This report provides the results of a collaboration between NETL, Los Alamos National Laboratory (LANL) and FECM headquarters personnel. NETL's FECM/NETL CO 2 Saline Storage Cost Model (CO2_S_COM) and LANL's Sequestration of CO 2 Tool (SCO 2 T) model were run with the same assumptions to generate costs for 314 potential storage formations in the U.S. The two models gave similar results. The results from CO2S_COM were then aggregated into a smaller number of costs that can be utilized in energy market models. The report has a companion spreadsheet called red_ord_costs_CO2_S_COM with the reduced order costs. The spreadsheet can be viewed online here: https://www.netl.doe.gov/energy-analysis/details?id=fb6d93df-0702-47aa-8147-59a5ae0c7cfd
54 ENVIRONMENTAL SCIENCES↗
Co-simulation of transactive energy markets: A framework for market testing and evaluation
The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Taming the wild edge of smart grid – Lessons from transactive energy market deployments
For two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Smart Contract Architectures and Templates for Blockchain-based Energy Markets (V.1.0)
Within the field of Transactive Energy Systems (TES), there is an active need for tools that can support and accelerate the development of these new grid solutions. Among the many tools available, blockchain stands out as a viable instrument that can help researchers develop decentralized, autonomous, and tamper-resistant grid applications. In this work, we explore the use of smart contracts (SCs), a subset of blockchain technology, and analyze their applicability to facilitating the implementation of TES solutions. In particular, we focus on presenting areas of opportunity and potential drawbacks, along with use cases that can benefit from this technology building upon previous research developed by Pacific Northwest National Laboratory and other research organizations. This work builds upon the fundamentals of TES and smart contract technology to develop a series of software templates that can be used by industry to build TES-oriented grid solutions. These templates are intended to be platform agnostic and take into consideration the unique properties of SCs and distributed ledger storage mechanisms to ensure actual code implementations remain aware of the limitations of the technology. The proposed templates have the potential to enable software architects to mix and match components to satisfy their application requirements, thereby reducing the number of resources required to implement blockchain-based solutions. These templates are divided into two main components—data and behavioral models. The data models are intended to help software engineers represent the underlying grid objects along with their properties in a ledger-based storage system. The behavioral models are used to describe the processes and actions that actors within a system must perform to achieve a given outcome such as registering an asset, placing a bid, and performing bid clearances. These two components are documented in a Unified Modeling Language (UML) format and are intended for use in SC-based implementations, with special behavioral considerations to account for the asynchronous properties of the underlying ledger and the typical execution model of smart contracts. Finally, future research ideas and potential extensions to this work are discussed. In particular, known limitations and potential improvements of the developed product are identified and expected to be addressed in future revisions of the template model.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Factors Impacting Nuclear Energy Share in U.S. Energy Markets
The purpose of this report is to collate information and findings from recent studies conducted by national and international bodies/institutes to identify approaches for maintaining/enhancing the role of nuclear energy in the current and future energy mix of the United States. This report shows how nuclear generation grew quickly to provide 20% of U.S. electricity, sustaining that level for three decades without the benefit of new construction, but is now projected to decline going forward. Nuclear construction costs in the U.S. spiraled out of control, ending construction for two decades and the recent resumption of construction has continued the pattern of schedule delays and cost overruns. However, nuclear operations exhibited strong learning, achieving and sustaining the highest capacity factor of any electricity generation technology and license extensions and uprates have sustained nuclear market share. The share of nuclear energy in the U.S. electricity market is projected to decline by ~1/3rd over the next 30 years The report provides an overview of how the markets work in theory and in practice. It indicates how market deregulation and clean energy policies have created conditions where nuclear plants are being retired for economic rather than technical reasons. The report also shows how many of the markets do not in practice have free competition but instead have outcomes that are being determined more and more by policy instead of market forces. While electricity costs from existing nuclear plants are low, electricity from new builds is projected to be too expensive to be competitive head-to-head with natural gas, even for nth-of-a-kind costs. Wind and solar energy have enjoyed an extended period of sustained subsidy. This protected environment has resulted in a sustained reduction in plant level costs to the point that some of these Variable Renewable Energy (VRE) technologies are becoming competitive even if their direct subsidies are removed. But plant level costs underestimate total VRE costs which include a number of system-level externalities. The incremental system value of additional VRE capacity was shown to decline as market share increases, with solar value declining more quickly than wind. The report closes with examination of a possible future for nuclear generation as part of deep decarbonization of the electricity sector. This approach avoids direct competition with natural gas. The two options for achieving 100% decarbonization are to use only renewables or to use all zero emissions technologies, and the report shows the second approach is much less expensive than the first.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Modeling hydrogen markets: Energy system model development status and decarbonization scenario results
Hydrogen can be used as an energy carrier and chemical feedstock to reduce greenhouse gas emissions, especially in difficult-to-decarbonize markets such as medium- and heavy-duty vehicles, aviation and maritime, iron and steel, and the production of fuels and chemicals. Significant literature has been accumulated on engineering-based assessments of various hydrogen technologies, and real-world projects are validating technology performance at larger scales and for low-carbon supply chains. While energy system models continue to be updated to track this progress, many are currently limited in their representation of hydrogen, and as a group they tend to generate highly variable results under decarbonization constraints. Here, the present work provides insights into the development status and decarbonization scenario results of 15 energy system models participating in study 37 of the Stanford Energy Modeling Forum (EMF37), focusing on the U.S. energy system. The models and scenario results vary widely in multiple respects: hydrogen technology representation, scope and type of hydrogen end-use markets, relative optimism of hydrogen technology input assumptions, and market uptake results reported for 2050 under various decarbonization assumptions. Most models report hydrogen market uptake increasing with decarbonization constraints, though some models report high carbon prices being required to achieve these increases and some find hydrogen does not compete well when assuming optimistic assumptions for all advanced decarbonization technologies. Across various scenarios, hydrogen market success tends to have an inverse relationship to success with direct air capture (DAC) and carbon capture and storage (CCS) technologies. While most model-scenario combinations predict modest hydrogen uptake by 2050 – <10 million metric tons (MMT) – aggregating the top 10 % of market uptake results across sectors suggests an upper range demand potential of 42–223 MMT. The high degree of variability across both modeling methods and market uptake results suggests that increased harmonization of both input assumptions and subsector competition scope would lead to more consistent results across energy system models. The wide variability in results indicates strongly divergent conclusions on the role of hydrogen in a decarbonized energy future.
08 HYDROGEN↗