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At least 199 records · Page 11

Energy, economic, and environmental tradeoffs at run-of-river hydropower facilities

Hydropower’s ability to quickly adapt to variability from wind and solar generation by fluctuation flow rates can allow the electricity grid to integrate more renewable capacity. However, these rapid flow fluctuations, required to meet variability needs, can negatively impact aquatic ecosystems. In this study, we quantified energy-economic-environment tradeoffs at five conventional hydropower facilities (i.e. hydropower produced ad a dam on a river channel) across the United States to identify a mix of operational regimes that can provide flexibility to support variable renewable energy integration and environmental protections. Model results show a range of ability to meet demand from 4.7% to 97.8% depending on which case study is considered. Additionally, when modeling the case study facilities on a range of RoR conditions, allowing a % of inflow as discharge, we found the range of 140–200% of inflow allowed as discharge lead to lowest environmental impact while meeting the highest amount of demand. Our sensitivity analysis results demonstrated the Richard-Baker Flashiness Index, used to measure flowrate changes, and Revenue, were negatively correlated with the percent of hydropower generation within the defined Regional Energy Deployment System balancing area (i.e. region in which energy demand and energy supply is balanced based on the Regional Energy Deployment System model) yet positively correlated to the variable renewable energy generation percentage in the defined balancing area. In conclusion, our results suggest hydropower operations can aid in increasing renewable energy generation while limiting environmental impacts when considering a holistic analysis of energy-economic-environment tradeoffs.

Economic impact↗

Review of Variable Generation Integration Charges

The growth of wind and solar generation in the United States, and the expectation of continued growth of these technologies, dictates that the future power system will be operated in a somewhat different manner because of increased variability and uncertainty. A small number of balancing authorities have attempted to determine an 'integration cost' to account for these changes to their current operating practices. Some balancing authorities directly charge wind and solar generators for integration charges, whereas others add integration charges to projected costs of wind and solar in integrated resource plans or in competitive solicitations for generation. This report reviews the balancing authorities that have calculated variable generation integration charges and broadly compares and contrasts the methodologies they used to determine their specific integration charges. The report also profiles each balancing authority and how they derived wind and solar integration charges.

14 SOLAR ENERGY↗

Electric Vehicle Managed Charging: Forward-Looking Estimates of Bulk Power System Value

When and where electric vehicle charging occurs has significant implications for power systems supporting widespread electric vehicle deployment with high shares of wind and solar generation. Numerous studies have estimated the value of scheduling or otherwise managing electric vehicle charging in such power systems. This study improves on those earlier works by leveraging detailed simulation models for electric vehicle adoption, electric vehicle use, electric vehicle charging, and bulk power system operations; and linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This study closely analyzes electric vehicle managed charging (EVMC) performance along the dimensions of flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and participation rate, under the assumptions of ubiquitous chargers and all trips completed on time. The study is located in a passenger light-duty vehicle adoption scenario with 100% electric vehicle sales by 2035, and in an envisioned 2038 New England power system for which within-region generation is 84% clean.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Siting Analysis of a Solar-Nuclear-Desalination Integrated Energy System

Nuclear power is typically deployed as a baseload generator. Increased penetration of variable renewables motivates combining nuclear and renewable technologies into Integrated Energy Systems (IES) to improve dispatchability, component synergies and, through cogeneration, address multiple markets. However, combining multiple energy resources heavily depends on the proper selection of each system’s location and design limitations. In this paper, co-siting options for IES that couple nuclear and concentrating solar power (CSP) with thermal desalination are investigated. A comprehensive siting analysis is performed that utilizes global information survey data to determine possible co-siting options for nuclear and solar thermal generation in the United States. Viable co-siting options are distributed across the Southwestern U.S., with the greatest concentration of siting options in the southern Great Plains, although siting with higher solar direct normal irradiance is possible in other states such as Arizona and New Mexico. Brackish water desalination is also attractive across the southwest U.S. due to high water stress, but for brackish water desalination reverse osmosis (an electricity driven process) is most cost- and energy-efficient, which does not require co-siting with the thermal generator. The most attractive state for nuclear and thermal desalination (which is more attractive when using seawater) is Texas, although other areas may become attractive as water stress increases over the coming decades. Co-siting of all CSP and thermal desalination is challenging as attractive CSP sites are not coastal.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Balancing Authority Cooperation Concepts to Reduce Variable Generation Integration Costs in the Western Interconnection: Consolidating Balancing Authorities and Sharing Balancing Reserves

The study described in this chapter demonstrates the benefits of BA consolidation with the help of a detailed WECC system model and advanced methodology, which is also described in this chapter. The study aims to determine the potential savings in production cost and reduction in balancing reserve requirements in the WECC system. The study has found that effective use of the diversity in load and variable generation over a wide area can indeed help to achieve significant savings. The implementation cost for the consolidation was beyond the scope of this study. The analysis was performed for two different scenarios of VG penetration: 11% (8% wind and 3% solar) and 33% (24% wind and 9% solar) of WECC projected energy demand in 2020. In analysis of balancing reserves, the objective was to determine the reduction in balancing reserve requirements due to BA consolidation, in terms of required capacity and ramp-rates. Hour-ahead and 10-minute ahead forecast errors for load, wind, and solar were simulated. In addition, 1-minute resolution load, wind and solar data were used to derive balancing reserve requirements i.e. load-following and regulation requirements for each individual BA and for the consolidated BA (CBA). The reduction in balancing reserves was determined by calculating the difference between total reserve requirements that need to be carried by different BAs if they operate individually, and reserve requirements that need to be carried by the CBA. The study results show that the consolidated WECC system would have about a 50% overall reduction in balancing reserves for the 11% penetration scenario and a 65% reduction for the 33% penetration scenario in comparison with total reserve requirements that need to be carried by different BAs if they operate individually.

balancing authorities consolidation↗

Computational Needs for the Next Generation Electric Grid Proceedings

The April 2011 DOE workshop, 'Computational Needs for the Next Generation Electric Grid', was the culmination of a year-long process to bring together some of the Nation's leading researchers and experts to identify computational challenges associated with the operation and planning of the electric power system. The attached papers provide a journey into these experts' insights, highlighting a class of mathematical and computational problems relevant for potential power systems research. While each paper defines a specific problem area, there were several recurrent themes. First, the breadth and depth of power system data has expanded tremendously over the past decade. This provides the potential for new control approaches and operator tools that can enhance system efficiencies and improve reliability. However, the large volume of data poses its own challenges, and could benefit from application of advances in computer networking and architecture, as well as data base structures. Second, the computational complexity of the underlying system problems is growing. Transmitting electricity from clean, domestic energy resources in remote regions to urban consumers, for example, requires broader, regional planning over multi-decade time horizons. Yet, it may also mean operational focus on local solutions and shorter timescales, as reactive power and system dynamics (including fast switching and controls) play an increasingly critical role in achieving stability and ultimately reliability. The expected growth in reliance on variable renewable sources of electricity generation places an exclamation point on both of these observations, and highlights the need for new focus in areas such as stochastic optimization to accommodate the increased uncertainty that is occurring in both planning and operations. Application of research advances in algorithms (especially related to optimization techniques and uncertainty quantification) could accelerate power system software tool performance, i.e. speed to solution, and enhance applicability for new and existing real-time operation and control approaches, as well as large-scale planning analysis. Finally, models are becoming increasingly essential for improved decision-making across the electric system, from resource forecasting to adaptive real-time controls to online dynamics analysis. The importance of data is thus reinforced by their inescapable role in validating, high-fidelity models that lead to deeper system understanding. Traditional boundaries (reflecting geographic, institutional, and market differences) are becoming blurred, and thus, it is increasingly important to address these seams in model formulation and utilization to ensure accuracy in the results and achieve predictability necessary for reliable operations. Each paper also embodies the philosophy that our energy challenges require interdisciplinary solutions - drawing on the latest developments in fields such as mathematics, computation, economics, as well as power systems. In this vein, the workshop should be viewed not as the end product, but the beginning of what DOE seeks to establish as a vibrant, on-going dialogue among these various communities. Bridging communication gaps among these communities will yield opportunities for innovation and advancement. The papers and workshop discussion provide the opportunity to learn from experts on the current state-of-the-art on computational approaches for electric power systems, and where one may focus to accelerate progress. It has been extremely valuable to me as I better understand this space, and consider future programmatic activities. I am confident that you too will enjoy the discussion, and certainly learn from the many experts. I would like to thank the authors of the papers for sharing their perspectives, as well as the paper discussants, session recorders, and participants. The meeting would not have been as successful without your commitment and engagement. I also would like to thank Joe Eto and Bob Thomas for their vision and leadership in bringing together such a well-structured and productive forum.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Big Data Analytic for Cascading Failure Analysis

With the challenges of increased grid dynamics and more variability of power generation from renewable energy sources, rapidly increasing complexity in the grid model, and abundant data from measurements and simulations, the requirements for computational analysis have also increased dramatically. Power system operators and engineers need to analyze more scenarios, extract meaningful information from a larger set of data, and respond more quickly when faced with these new challenges for large-scale applications, such as contingency analysis. This paper proposes a novel big data analysis approach for power system cascading analysis, prevention, and remediation. The developed techniques will be capable of cascading analysis, better assessment of the system’s vulnerability level, as well as proposing potential remediation. Case studies using IEEE 118-bus system and a 500-bus system, with a comparison against a commercial tool, validate the advantages of the developed big data approach: accurate prediction, and more importantly, faster and effective correction actions.The developed techniques could be further used for other power system applications.

big data, cascading analysis, corrective action, m↗

Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning

One major difficulty in transmission expansion planning is selecting the representative scenarios to use to evaluate candidate transmission networks. The variability in demand and renewable generation makes the inclusion of several scenarios critical when calculating reliability and cost, but including too many scenarios in an optimization is computationally intractable. To reduce the number of representative operating conditions needed to obtain an accurate approximation of the system, we propose a method rooted in multivariate statistics that exploits the latent correlative structure between different scenarios and network configurations. The proposed algorithm includes an objective and rigorous way to select a subset of scenarios that provide as much information about the system as possible, and a method to accurately approximate the system cost from that scenario subset. The result is a set of scenarios and weights that are easily incorporated into traditional transmission expansion planning formulations. We apply this to a 312-bus WECC model with 8,736 distinct operating conditions. The transmission plans found with the proposed method are more reliable and have a lower total cost than those from other scenario reduction techniques, as well as a smaller error between the expected system performance from the optimization objective and the actual system performance.

42 ENGINEERING↗

Future Roles of Milli-, Micro-, and Nano- Grids

Although it has slowed considerably, consumption of electricity continues to grow in developed economies. Further, there are some unknowns which might accelerate this growth, such as electrification of vehicle fleets and geothermal heat pump space and water heating. Most analysts anticipate that distributed energy resources (DER) will provide a large share of the expanded generation capacity required to meet this seemingly inexorably increasing electricity demand. Further, given the urgency of tackling the climate change problem, most of the added assets must be carbonfree renewables or nuclear, end-use efficiency improvements, or highly efficient fossil-fired technologies. In developed economies worldwide, the current power delivery paradigm has been in place for more than a century, i.e. since the emergence of polyphase AC systems around the turn of the last century. A key feature of this structure is that, in principle, universal service is delivered at a consistent level of power quality and reliability (PQR) throughout large regions. This paper describes a future possible structure for the electricity generation and delivery system that leaves the existing high voltage meshed grid paradigm in place, but involves radical reorganization of parts of the distribution network and customer sites. Managing a much more diverse dispersed system poses major challenges to the current centralized grid paradigm, particularly since many of these assets are small to tiny by macrogrid standards and they may ultimately number in the millions. They are also not ones that centralized control can rely upon to function in traditionally dependable ways, e.g. renewable generation can be highly variable and changes in output of generators are not independent. Although most involved in the industry agree that a paradigm shift is both necessary and desirable to manage the new system, the nature of the future system remains quite unclear. In the possible structure described here, the traditional grid, or macrogrid, remains similar at the high voltage meshed level. Three new entities are added more locally: community grids or milligrids that operate a segment of the existing distribution system, microgrids which are akin to current customer sites but which have automonous control, and nanogrids, such as telecom or Ethernet networks that currently distribute power to many low-power devices. The latter exist currently in the local electrical systems but are not typically considered a part of the traditional electricity supply system. Because all these new entities exhibit some localized control, providing appropriate local heterogeneous PQR becomes a possibility. These new grid concepts enable a more"bottom-up" approach to electricity distribution, in contrast to the historic 'top-down' model. The future will almost certainly include a mix of the two, but the balance among them and the interface (if any) between them is unclear.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Potential of Wind Power to Provide Flexible Ramping Products and Operating Reserve: Preprint

With increasing penetration levels of variable renewable energy sources, such as wind and solar, electric power systems need flexible resources that can provide fast-response ramping capabilities to counter the variability and uncertainty of renewable generation. Although the California Independent System Operator and Midcontinent System Operator have lauched ramp products, determining how wind power can participate using their flexible ramping models is still largely unclear. This paper proposes a security-constrained unit commitment (SCUC) model considering a flexible ramping constraint representing the system's flexible ramping requirements that account for the net load probabilistic forecast uncertainty. Through this explicit modeling of the uncertainty, the true cost of the flexible ramp service can be determined after solving the SCUC problem. In addition, the potential of wind power to provide operating reserves is analyzed. Numerical case studies demonstrate that with wind power providing both flexible ramping products and operating reserve, the system operating costs and ramp shortages will be reduced significantly.

17 WIND ENERGY↗

H2@Scale: Economic Potential of Hydrogen as an Energy Intermediate

The H2@Scale concept envisions hydrogen as an energy intermediate across multiple energy sectors. The concept is motivated both by the opportunity to produce hydrogen from low-cost energy resources, and by the many potential applications of hydrogen, including as energy for transportation - used directly in fuel cell electric vehicles (FCEVs), as a feedstock for synthetic fuels, and to upgrade oil and biomass - feedstock for industry (e.g., for ammonia production, metals refining, and other end uses), heat for industry and buildings, and electricity storage. A key hydrogen production opportunity is using variable renewable electricity (i.e., electricity generated by wind turbines or solar photovoltaic panels) during hours when generation exceeds the load on the grid as a source of low-cost, dispatch constrained electricity (LDE). In addition to producing low-cost hydrogen, electrolysis can also serve as a form of responsive load on the electric grid, which can enhance grid stability, reduce curtailment, and create a supplementary revenue stream for generators. The future use and adoption of hydrogen across end-use applications depends both the cost of hydrogen production and on each application's threshold price (i.e., the maximum price each application will pay for hydrogen - above that price, the application has an alternative that is more economic). We estimate economic potential of the hydrogen market - the quantity of hydrogen at an equilibrium price at which suppliers are willing to produce and consumers are willing to buy the same quantity of hydrogen - by developing supply and demand curves for hydrogen production and use. The demand curves are based on the threshold price for various quantities of hydrogen in each market, which is affected by projected prices for alternatives that could provide the same service (e.g., fuel for vehicles, feedstock for metals refining). The supply curves include hydrogen produced via natural gas steam methane reforming, high-temperature electrolysis coupled with nuclear power plants, biomass gasification, and low-temperature electrolysis using LDE. We use a range of market and technology-advancement assumptions to estimate the economic potential for five scenarios in the mid 21st century timeframe, and the corresponding impacts on energy use and emissions. We estimate hydrogen's economic potential to be 14-48 MMT/yr in the contiguous United States - corresponding to 1.5-5 times current annual consumption - depending on key assumptions about the future market conditions and the success of hydrogen production research and development (R&D) in our five scenarios. As a result of the estimated economic potential markets, we also approximate that grid-integrated electrolysis can increase the penetration of wind generation in the electricity market by providing a value stream for LDE, and that total U.S. fossil fuel use could decline below a scenario with high renewable penetration on the grid. We find that hydrogen has potential to provide technical and economic synergies when integrated across multiple sectors of the U.S. energy system, but continued R&D, infrastructure, and market development for LDE are required.

08 HYDROGEN↗

Role of Electric Vehicles in the U.S. Power Sector Transition: A System-Level Perspective

After over a century of petroleum dominance many anticipate that electrification could disrupt the transportation energy landscape. At the same time, the electric power systems are undergoing profound changes: variable renewables are displacing conventional generation sources; distributed generation is disrupting utility business models; energy storage and other new technologies are emerging; and the traditional system based on the premise that generation is dispatched to match an inelastic demand is evolving to create a system with greater participation in power system planning and operations from traditionally passive consumers. In this context, it is important to understand how transportation electrification will impact electricity demand and in turn electricity supply, including changes in the load shapes that characterize the system and the opportunity to leverage flexible electric vehicle (EV) charging to better integrate demand and supply. Assessing the impacts of electrification on the energy system requires an understanding of how it might impact the amount and shape of electricity consumption, and how this electricity can be supplied. In particular, increased adoption of electric vehicles introduces a new source of demand altogether, potentially very flexible. Moreover, electrification could shift the consumption of natural gas between sectors, thereby affecting the economics for natural gas-fired generation relative to other electricity generation options. Several factors will impact the evolution of the power system under a widespread electrified future, which, in turn, could have far-reaching effects on future energy costs and emissions.

47 OTHER INSTRUMENTATION↗

Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions

There are fewer conventional, dispatchable generation resources and more variable renewable energy (VRE) and distributed energy resources (DERs). There is more uncertainty from bulk-level VRE and net demand from distribution systems with high DER levels. FAST-DERMS aims to develop and demonstrate a scalable solution for managing uncertainties in supply and demand at the grid edge. We propose that distribution system operators (DSOs) provide firm net load forecasts to the bulk system operator's energy management system (EMS).

distributed energy resources↗

Projecting Electric Vehicle Electricity Demands and Charging Loads

After over a century of petroleum dominance, electric vehicles are rapidly disrupting the transportation energy landscape. At the same time, the electric power systems are undergoing profound changes as variable renewables replace dispatchable fossil generators. It is critically important to understand how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system, and the value of flexible electric vehicle charging to better balance electricity demand and supply. This talk focuses on methods to project electricity demand for EV charging with high spatiotemporal fidelity to enable electricity system modeling and analysis and summarizes results from recent NREL studies in this area.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗

The RenewElec Project: Variable Renewable Energy and the Power System (Final Report)

Variable energy resources, such as wind power, now produce about 4% of U.S. electricity. They can play a significantly expanded role if the U.S. adopts a systems approach that considers affordability, security and reliability. Reaching a 20-30% renewable portfolio standard goal is possible, but not without changes in the management and regulation of the power system, including accurately assessing and preparing for the operational effects of renewable generation. The RenewElec project will help the nation make the transition to the use of significant amounts of electric generation from variable and intermittent sources of renewable power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗