While a great deal of research has been performed to quantify and characterize the wave energy resource, there are still open questions about how a wave energy developer should use this wave resource information to design a wave energy converter device to suit a specific environment or, alternatively, to assess potential deployment locations. It is natural to focus first on the impressive magnitudes of power available from ocean waves, and to be drawn to locations where mean power levels are highest. However, a number of additional factors such as intermittency and capacity factor may be influential in determining economic viability of a wave energy converter, and should therefore be considered at the resource level, so that these factors can influence device design decisions. This study examines a set of wave resource metrics aimed towards this end of bettering accounting for variability in wave energy converter design. The results show distinct regional trends that may factor into project siting and wave energy converter design. Although a definitive solution for the optimal size of a wave energy converter is beyond the reaches of this study, the evidence presented does support the idea that smaller devices with lower power ratings may merit closer consideration.
A team at Sandia National Laboratories (SNL) recognized the growing need to maintain and organize the internal community of Techno - Economic Assessment analysts at the lab . To meet this need, an internal core team identified a working group of experienced, new, and future analysts to: 1) document TEA best practices; 2) identify existing resources at Sandia and elsewhere; and 3) identify gaps in our existing capabilities . Sandia has a long history of using techno - economic analyses to evaluate various technologies , including consideration of system resilience . Expanding our TEA capabilities will provide a rigorous basis for evaluating science, engineering and technology - oriented projects, allowing Sandia programs to quantify the impact of targeted research and development (R&D), and improving Sandia's competitiveness for external funding options . Developing this working group reaffirms the successful use of TEA and related techniques when evaluating the impact of R&D investments, proposed work, and internal approaches to leverage deep technical and robust, business - oriented insights . The main findings of this effort demonstrated the high - impact TEA has on future cost, adoption for applications and impact metric forecasting insights via key past exemplar applied techniques in a broad technology application space . Recommendations from this effort include maintaining and growing the best practices approaches when applying TEA, appreciating the tools (and their limits) from other national laboratories and the academic community, and finally a recognition that more proposals and R&D investment decision s locally at Sandia , and more broadly in the research community from funding agencies , require TEA approaches to justify and support well thought - out project planning.
Desirable outcomes for geologic carbon storage include maximizing storage efficiency, preserving injectivity, and avoiding unwanted consequences such as caprock or wellbore leakage or induced seismicity during and post injection. To achieve these outcomes, three control measures are evident including pore pressure, injectate chemistry, and knowledge and prudent use of geologic heterogeneity. Field, experimental, and modeling examples are presented that demonstrate controllable GCS via these three measures. Observed changes in reservoir response accompanying CO2 injection at the Cranfield (Mississippi, USA) site, along with lab testing, show potential for use of injectate chemistry as a means to alter fracture permeability (with concomitant improvements for sweep and storage efficiency). Further control of reservoir sweep attends brine extraction from reservoirs, with benefit for pressure control, mitigation of reservoir and wellbore damage, and water use. State-of-the-art validated models predict the extent of damage and deformation associated with pore pressure hazards in reservoirs, timing and location of networks of fractures, and development of localized leakage pathways. Experimentally validated geomechanics models show where wellbore failure is likely to occur during injection, and efficiency of repair methods. Use of heterogeneity as a control measure includes where best to inject, and where to avoid attempts at storage. An example is use of waste zones or leaky seals to both reduce pore pressure hazards and enhance residual CO2 trapping.
The availability of freshwater supplies to meet future demand is a growing concern. Water availability metrics are needed to inform future water development decisions. With the help of water managers, water availability was mapped for over 1300 watersheds throughout the 31 contiguous states in the eastern US complimenting a prior study of the west. The compiled set of water availability data is unique in that it considers multiple sources of water (fresh surface and groundwater, wastewater and brackish groundwater); accommodates institutional controls placed on water use; is accompanied by cost estimates to access, treat and convey each unique source of water; and is compared to projected future growth in consumptive water use to 2030. Although few administrative limits have been set on water availability in the east, water managers have identified 315 fresh surface water and 398 fresh groundwater basins (with 151 overlapping basins) as areas of concern (AOCs) where water supply challenges exist due to drought related concerns, environmental flows, groundwater overdraft, or salt water intrusion. This highlights a difference in management where AOCs are identified in the east which simply require additional permitting, while in the west strict administrative limits are established. Although the east is generally considered 'water rich' roughly a quarter of the basins were identified as AOCs; however, this is still in strong contrast to the west where 78% of the surface water basins are operating at or near their administrative limit. Little effort was noted on the part of eastern or western water managers to quantify non-fresh water resources.
This study presents a conceptual framework for capturing the spatial and temporal aspects of non-market dimensions of value (DOV) and how they vary as the result of policy changes for hydropower generation and developed water uses. The foundation of this project is a literature review that reveals that focused, sector specific valuations are no longer adequate if the goal is to provide decision makers with a complete understanding of their decisions. Rather, estimates of non-market values for informing decisions regarding dam operations and/or other water management alternatives must consider the entire spectrum of market and non-market values, and the tradeoffs (both positive and negative) between those values over time and space, while considering shifting preferences in an uncertain environment. This document describes the history and reasoning for these conclusions and presents a conceptual framework for understanding non-market values as a function of changes to hydropower operations and water resources management.
Developing nations incur a greater risk to climate change than the developed world due to poorly managed human/natural resources, unreliable infrastructure and brittle governing/economic institutions. These vulnerabilities often give rise to a climate induced “domino effect” of reduced natural resource production-leading to economic hardship, social unrest, and humanitarian crises. Integral to this cascading set of events is increased human migration, leading to the “spillover” of impacts to adjoining areas with even broader impact on global markets and security. Given the complexity of factors influencing human migration and the resultant spill-over effect, quantitative tools are needed to aid policy analysis. Toward this need, a series of migration models were developed along with a system dynamics model of the spillover effect. The migration decision models were structured according to two interacting paths, one that captured long-term “chronic” impacts related to protracted deteriorating quality of life and a second focused on short-term “acute” impacts of disaster and/or conflict. Chronic migration dynamics were modeled for two different cases; one that looked only at emigration but at a national level for the entire world; and a second that looked at both emigration and immigration but focused on a single nation. Model parameterization for each of the migration models was accomplished through regression analysis using decadal data spanning the period 1960-2010. A similar approach was taken with acute migration dynamics except regression analysis utilized annual data sets limited to a shorter time horizon (2001-2013). The system dynamics spillover model was organized around two broad modules, one simulating the decision dynamics of migration and a second module that treats the changing environmental conditions that influence the migration decision. The environmental module informs the migration decision, endogenously simulating interactions/changes in the economy, labor, population, conflict, water, and food. A regional model focused on Mali in western Africa was used as a test case to demonstrate the efficacy of the model.
The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.
This paper is the output from SNL's involvement in the Western Area Power Administration (WAPA), the Colorado River Energy Distributors Association (CREDA), and the Upper Colo rado River Commission's (UCRC) sponsored Phase II work to establish market and non - market valu es (NMV's) of water and hydropower asso ciated with Glen Canyon Dam (GCD) operations and the Colorado River ecosystem. It describes the purpose and need to develop a systems model for the Colorado River Basin that includes valuations in the economic, hydrologic, environmental, social, and cultural sectors . It outlines the benefits and unique features associated with such a model and provides a roadmap of how a syste ms model would be developed and implemented. While not meant to serve as a full development plan, the ideas and concepts herein represent what the Sandia National Laboratories (SNL) research team believes is the most impac tful and effective path forward to address an ever increasing complex set of problems that occur at the basin - scale and beyond .
People save for retirement throughout their career because it is virtually impossible to save all you’ll need in retirement the year before you retire. Similarly, without installing incremental amounts of clean fossil, renewable or transformative energy technologies throughout the coming decades, a radical and immediate change will be near impossible the year before a policy goal is set to be in place. This notion of steady installation growth over acute installations of technology to meet policy goals is the core topic of discussion for this research. This research operationalizes this notion by developing the theoretical underpinnings of regulatory and market acceptance delays by building upon the common Technology Readiness Level (TRL) framework and offers two new additions to the research community. The new and novel Regulatory Readiness Level (RRL) and Market Readiness Level (MRL) frameworks were developed. These components, collectively called the Technology, Regulatory and Market (TRM) readiness level framework allow one to build new constraints into existing Integrated Assessment Models (IAMs) to address research questions such as, ‘To meet our desired technical and policy goals, what are the factors that affect the rate we must install technology to achieve these goals in the coming decades?’
The Water, Energy, and Carbon Sequestration Simulation Model (WECSsim) is a national dynamic simulation model that calculates and assesses capturing, transporting, and storing CO2 in deep saline formations from all coal and natural gas-fired power plants in the U.S. An overarching capability of WECSsim is to also account for simultaneous CO2 injection and water extraction within the same geological saline formation. Extracting, treating, and using these saline waters to cool the power plant is one way to develop more value from using saline formations as CO2 storage locations. WECSsim allows for both one-to-one comparisons of a single power plant to a single saline formation along with the ability to develop a national CO2 storage supply curve and related national assessments for these formations. This report summarizes the scope, structure, and methodology of WECSsim along with a few key results. Developing WECSsim from a small scoping study to the full national-scale modeling effort took approximately 5 years. This report represents the culmination of that effort. The key findings from the WECSsim model indicate the U.S. has several decades' worth of storage for CO2 in saline formations when managed appropriately. Competition for subsurface storage capacity, intrastate flows of CO2 and water, and a supportive regulatory environment all play a key role as to the performance and cost profile across the range from a single power plant to all coal and natural gas-based plants' ability to store CO2. The overall system's cost to capture, transport, and store CO2 for the national assessment range from $74 to $208 / tonne stored ($96 to 272 / tonne avoided) for the first 25 to 50% of the 1126 power plants to between $1,585 to well beyond $2,000 / tonne stored ($2,040 to well beyond $2,000 / tonne avoided) for the remaining 75 to 100% of the plants. The latter range, while extremely large, includes all natural gas power plants in the U.S., many of which have an extremely low capacity factor and therefore relatively high system's cost to capture and store CO2.
People save for retirement throughout their career because it is virtually impossible to save all youll need in retirement the year before you retire. Similarly, without installing incremental amounts of clean fossil, renewable or transformative energy technologies throughout the coming decades, a radical and immediate change will be near impossible the year before a policy goal is set to be in place. Therefore, our research question is, To meet our desired technical and policy goals, what are the factors that affect the rate we must install technology to achieve these goals in the coming decades? Existing models do not include full regulatory constraints due to their often complex, and inflexible approaches to solve for optimal engineering instead of robust and multidisciplinary solutions. This project outlines the theory and then develops an applied software tool to model the laboratory-to-market transition using the traditional technology readiness level (TRL) framework, but develops subsequent and a novel regulatory readiness level (RRL) and market readiness level (MRL). This tool uses the ideally-suited system dynamics framework to incorporate feedbacks and time delays. Future energy-economic-environment models, regardless of their programming platform, may adapt this software model component framework or module to further vet the likelihood of new or innovative technology moving through the laboratory, regulatory and market space. The prototype analytical framework and tool, called the Technology, Regulatory and Market Readiness Level simulation model (TRMsim) illustrates the interaction between technology research, application, policy and market dynamics as they relate to a new or innovative technology moving from the theoretical stage to full market deployment. The initial results that illustrate the models capabilities indicate for a hypothetical technology, that increasing the key driver behind each of the TRL, RRL and MRL components individually decreases the time required for the technology to progress through each component by 63, 68 and 64%, respectively. Therefore, under the current working assumptions, to decrease the time it may take for a technology to move from the conceptual stage to full scale market adoption one might consider expending additional effort to secure regulatory approval and reducing the uncertainty of the technologys demand in the marketplace.