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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Case Study: Nuclear-Renewable-Water Integration in Arizona

This document reports the application of the N-R HES software framework to a case study for Arizona Public Service (APS); the manager and part owner of the Palo Verde (PV) nuclear power plant. The case study is a work in progress of which this report presents a detailed description of the current model input data, assumptions and the corresponding results produced by the developed software framework. The goal of the report is, that with this information APS (together with INL) should be able to identify where more detailed data and more accurate model assumptions are necessary to reproduce all driving physical and economic phenomena in order to capture enough complexity of the reality to allow APS to use the results for their strategic decisions. The N-R HES software framework started being developed at INL two years ago [ref]. The framework has reached some level of maturity so that it can be applied to more than simple demonstration cases, e.g. real industry problems. Nevertheless, more capabilities are constantly added to accommodate the special needs of these challenging real life problems. The N-R HES framework is built on top of the RAVEN code [ref] and uses it as driver and workflow manager for all calculations. The framework has specifically been developed for the economic assessment of N-R HES systems. There are four main cornerstones of the N-R HES simulation framework: 1) generation of stochastic time series, 2) a probabilistic analysis and optimization set of algorithms available in RAVEN, 3) a set of models for representation of the physical behavior of N-R HES, and 4) a RAVEN plug-in that maps physical performance into economic performance called CashFlow. Within this framework, a broad spectrum of questions related to N-R HES can be addressed. One of the challenges currently of high interest is that the increasing penetration of variable renewables is altering the profile of the net demand (demand after removing all non curtailable renewable energy sources), with which the other generators on the grid have to cope. The N-R HES software framework is capable to analyze the potential feasibility of mitigating the resultant volatility in the net electricity demand. One possible solution to that problem currently intensively studied by the energy industry is adding stabilizing loads to the grid. These loads can be external industrial processes that are able to ramp production up and down quickly or adding variable internal loads that will lift the base load of the power plant. The latter is a possible solution currently studied by APS. APS if currently anticipating several challenges that will likely arise in the near future. One of them is, as mentioned, coping with the rapid growth of variable renewable energy (VRE) sources put on the grid. Although APS can sell its electricity for a fixed retail price to cover the local demand first, it also sells electricity in excess of the local demand at the Palo Verde energy hub. Due to the growing VRE penetration, the Palo Verde hub electricity spot price is negative more and more frequently. To mitigate this price volatility, APS is seeking to add more base load, so that the quantity of excess energy to be sold for prices potentially less than the internal retail price or even negative prices at the hub is reduced. A second challenge APS is facing is that their cooling water acquisition contract with the Sub Regional Operating Group (SROG) will expire soon and a renewal can only be done for a significantly higher price of the water. Therefore, APS is also seeking for alternative sources for their cooling water. An opportunity currently under investigation is to pump a limited quantity of brackish water from the regional ground water. Although much cheaper than the water from the new SROG contract, the salinity of the brackish water is so high that a blend of brackish and SROG water would need additional treatment to improve its quality for use in the cooling towers. An on-site reverse osmosis (RO) desalination plant is envisaged to reduce the salinity to an acceptable level. This report investigates the economic impact of such an RO plant. As one can see, the RO plant would help with both problems APS is facing: First, it would rise the APS base load helping to mitigate VRE induced hub price volatility. From this perspective, the RO plant can be seen as a stabilizing load on the grid as would be any other industrial process. Second, the RO’s goods, e.g. the clean water produced can be used by APS itself for a (hopefully) lower cost than 100% SROG water would be. The report will first describe the APS water procurement strategy in detail and lay out the possible alternative scenarios studied in this document. This is covered in Chapter 2. Next, in Chapter 3, the APS case model developed within the N-R HES software framework is described. This chapter includes also a description of the needed framework developments to accommodate the APS study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Alternative Approaches to Calculate Benefits of an Energy Imbalance Market With Wind and Solar Energy: Preprint

The anticipated increase in variable generation in the Western Interconnection over the next several years has raised concerns about how to maintain system balance, especially in smaller Balancing Authority Areas (BAAs). Given renewable portfolio standards in the West, it is possible that more than 50 gigawatts of wind capacity will be installed by 2020. Significant quantities of solar generationare likely to be added as well. The consequent increase in variability and uncertainty that must be managed by the conventional generation fleet and responsive loads has resulted in a proposal for an Energy Imbalance Market (EIM). This paper extends prior work to estimate the reserve requirements for regulation, spinning, and non-spinning reserves with and without the EIM. We also discussalternative approaches to allocating reserve requirements and show that some apparently attractive allocation methods have undesired consequences.

17 WIND ENERGY↗
DOE OSTI2013

Ramping Performance Analysis of the Kahuku Wind-Energy Battery Storage System

High penetrations of wind power on the electrical grid can introduce technical challenges caused by resource variability. Such variability can have undesirable effects on the frequency, voltage, and transient stability of the grid. Energy storage devices can be an effective tool in reducing variability impacts on the power grid in the form of power smoothing and ramp control. Integrating anenergy storage system with a wind power plant can help smooth the variable power produced from wind. This paper explores the fast-response, megawatt-scale, wind-energy battery storage systems that were recently deployed throughout the Hawaiian islands to support wind and solar projects.

17 WIND ENERGY↗
DOE OSTI2021

IDAES Enterprise: Generation Expansion Planning with Enhanced Requirements for Capacity Adequacy Under Renewable Intermittency

Achieving net zero carbon emissions likely requires future power systems to integrate new, flexible energy technologies to accommodate higher levels of capacity from variable renewable energy sources. To determine the optimal deployment of new electricity capacity and to study the likelihood of deployments of new energy technologies, an expansion planning model has been developed as part of the IDAES-Enterprise suite of grid models. The Generation Expansion Planning (GEP) model is a multi-period model in which investment decisions occur yearly, and a Unit Commitment (UC) problem is examined on an hourly timescale. To reduce computational complexity of the GEP model, the UC problem is solved for average “representative days” which leaves out extreme, but relatively common, scenarios in which low renewable generation occurs, leaving the system with inadequacy in capacity. The IDAES-Enterprise GEP model has been modified to include these extreme scenarios while keeping the model reasonably tractable. Specifically, a lazy constraint technique was implemented to check for capacity adequacy on an hourly basis over a large data set of aligned load-wind-solar profiles. As a vast majority of the capacity constraints will not be violated, the technique lowers computational expense by searching for violated capacity constraints over an “iterative manner,” adding those infeasible constraints back into the model. Results on a test case of the Southwest Power Pool shows that the lazy constraint technique significantly reduces retirements and increases installments of natural gas combined cycles and flexible natural gas units. It also reduces some retirements of coal units. These modifications provide a more reasonable estimation of required dispatchable power generation capacity to ensure feasibility during peak net load.

Liu, Peng↗
DOE OSTI2023

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Decomposing sources of value for electricity and negative emissions technologies in net-zero power systems

Deep decarbonization of the US power system would require rapid deployment of variable renewable energy (VRE) resources, which are projected to provide a substantial share of electricity generation at the time of net-zero emissions. However, the exact share of generation met by VRE and the roles of other technologies in supplying key electricity services—energy and firm capacity—remain uncertain. This study employs a detailed model of the US power sector to decompose the provision and value of electricity services, including negative emissions, by technology across a range of deep decarbonization scenarios. Results indicate that while technology deployment and the share of services provided by each technology vary significantly depending on future technological and market conditions, the value composition and future roles of individual technologies remain consistent. These findings offer guidance for research and development priorities and provide insights to inform electricity policy and planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Operating Dynamic Reserve Dimensioning Using Probabilistic Forecasts

The rapid integration of variable energy sources (VRES) into power grids increases variability and uncertainty of the net demand, making the power system operation challenging. Operating reserve is used by system operators to manage and hedge against such variability and uncertainty. Traditionally, reserve requirements are determined by rules-of-thumb (static reserve requirements, e.g., NERC Reliability Standards), and more recently, dynamic reserve requirements from tools and methods which are in the adoption process (e.g., DynADOR, DRD, and RESERVE, among others). While these methods/tools significantly improve the static rule-of-thumb approaches, they rely exclusively on deterministic data (i.e., best guess only). Consequently, these methods disregard the probabilistic uncertainty thresholds associated with specific days and their weather conditions (i.e., best guess plus probabilistic uncertainty). This work presents practical approaches to determine the operating reserve requirements leveraging the wealth information from probabilistic forecasts. Proposed approaches are validated and tested using actual data from the CAISO system. Furthermore, results show the benefits in terms of risk reduction of considering the probabilistic forecast information into the dimensioning process of operating reserve requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

REPRA (Renewable Energy Probabilistic Resource Assessment) [SWR-14-18]

This package is the R implementation of the Renewable Energy Probabilistic Resource Assessment (REPRA) tool, developed at the National Renewable Energy Laboratory (NREL). REPRA is a statistical tool that models the effect of variable generation in the calculation of resource adequacy metrics. It is built as a research tool to explore different methodologies and technologies.

Ibanez, Eduardo↗
DOE OSTI2014

Flexible Geothermal Power: An Economic Assessment

State renewable portfolio standards requiring more intermittent wind and solar generation will substantially increase uncertainty and variability in grid operations. Geothermal power plant operators could help mitigate variability and uncertainty by operating plants in a more flexible mode. Plant operators would be compensated for flexibility through payments for ancillary services such as frequency regulation, load following, and spinning reserve.

14 SOLAR ENERGY↗
DOE OSTI2019

H2@Scale: Hydrogen Integrating Energy Systems

H2@Scale is a concept where hydrogen is an energy intermediate that complements the electricity grid and natural gas system. Hydrogen can be a valuable feedstock for oil and biofuel refining, ammonia production, steel production, and converting carbon dioxide to valuable products due to its chemical properties. It can also be a valuable energy carrier for transportation because it can be fast-filled, stored energy on fuel cell electric vehicles as well as providing storage for the grid. In addition, hydrogen is one of the few non-carbon emitting options to achieve high temperatures needed in industrial processes. If a hydrogen demand is available, hydrogen can be economically produced from variable renewable electricity (e.g., wind, photovoltaic solar) thus increasing the economically viable penetrations of those generation technologies. Likewise, hydrogen is an alternative product that can provide revenue to economically challenged nuclear power plants. This presentation summarizes the demand potential for hydrogen, the technical potential of resources that could be used to produce it, and a number of economic potential scenarios that identify key markets and technology development necessary to compete in them.

08 HYDROGEN↗
DOE OSTI2022

FORCE Development Status Update: Vertical Integration and Benchmarking of System Dynamics

Recent efforts to establish effective models for grid energy analysis, especially given the increase in variable renewable energy (VRE) sources and the economic challenges faced by traditional nuclear energy, have generated new technological considerations. One effort to improve the economic viability of nuclear power involves investigating integrated energy systems (IES) which include secondary energy systems that introduce flexibility and secondary market possibilities to existing and perceived future nuclear energy generation technologies. To analyze the technical and economic potential of IES, the Framework for Optimization of Resources and Economics (FORCE) tool suite was developed through a collaboration among national laboratories. Within the FORCE tool suite, the Holistic Energy Resource Optimization Network (HERON) provides algorithms for analyzing the long-term viability of potential IES technologies, while HYBRID provides algorithms and models to achieve high-resolution analysis of coupling physics over a short time period. Continued maturing of the FORCE tool suite requires further interconnections between the various tools in the suite in order to ensure consistent analysis. Analyses performed by applying HYBRID to transient process modeling should be easily harvestable as inputs to HERON analyses. The first item in this status update is a demonstration of an automated data pipeline for loading data from HYBRID into HERON analyses. Application of HYBRID results to HERON, as part of using the FORCE tool suite, relies on robust modeling assumptions for the various models included in HYBRID. The second result of this status update is the benchmarking and validation of cost and operational data, with a particular focus on natural gas energy generators. These generators are benchmarked with a focus on contrasting them with proposed thermal energy storage (TES) technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Scalable Energy System Expansion Under Uncertainty Using Multi-Stage Stochastic Optimization

The intermittent nature of renewable energy sources poses challenges for electrical grids. This is due to the variable and uncertain nature of the power output from these resources. These features of renewable generation are more relevant to energy system planning as grids reach higher penetration levels of renewable energy. We present approaches for energy system planning based on scalable computational approaches which enable explicit consideration of operational uncertainties in the planning process. Using multi-stage stochastic programming and the progressive hedging algorithm, we compute energy system expansion decisions on modified versions of the RTS-GMLC test system.

electrical↗
DOE OSTI2022

Scalable Energy System Expansion Under Uncertainty Using Multi-Stage Stochastic Optimization

The intermittent nature of power from renewable energy sources poses new challenges for electrical grids. This is due to the variable and uncertain nature of the power output from these resources. These features of renewable generation are becoming more relevant to energy system planning as grids reach higher penetration levels of renewable energy. In this presentation we present approaches for energy system planning based on scalable computational approaches which enable the explicit consideration of operational uncertainties in the planning process. Using multi-stage stochastic programming and the progressive hedging algorithm, we compute energy system expansion decisions on modified versions of the RTS-GMLC test system augmented with large amounts of renewable generation.

MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Capacity Payments in Restructured Markets under Low and High Penetration Levels of Renewable Energy

There is considerable debate about the degree to which restructured markets perform successfully in their use of capacity markets. In providing appropriate incentives for new and existing generation to meet reliability requirements, a variety of capacity market designs have developed across RTOs and ISOs in the United States and internationally. Growing levels of variable renewable energy (VRE) resources arguably create new challenges for capacity market designs, because VREs suppress energy prices while providing relatively little capacity, with these effects increase with VRE penetration. The purpose of this report is threefold. First, we provide a brief outline of the purpose and design of various capacity markets under consideration using variable resource requirement (VRR) demand curves. Second, we discuss some of the main challenges raised in existing literature and a set of interviews that we conducted with market participants, regulators, and observers, including where there substantive differences in opinion. Third, we consider some of the challenges that may be specific to higher penetration levels of VRE. While the well known 'merit order' effect from VRE can be expected to suppress wholesale energy prices and revenue, this may be partly mitigated by increased capacity payments and the greater importance of AS payments for flexible capacity. The potential for greater reliance on capacity markets for generator revenues may amplify any inefficiency and costs associated with capacity price volatility and other suboptimal market design choices. Regulatory intervention to ensure adequate capacity payments and ancillary service revenue may become more prevalent under current market designs as the timescale for market signals shifts increasingly from near term (e.g., day-ahead in wholesale electricity markets) to longer term (annual intervals in capacity markets). Our review and discussion with market participants suggest substantive challenges may remain in implementing capacity markets that provide both adequate operational and investment incentives, particularly under high-VRE scenarios with greater need for flexible capacity.

14 SOLAR ENERGY↗
DOE OSTI2025

Operating Wind Turbine as Synchronous Generator: Modeling and Power-Hardware-in-the-Loop Demonstration

Grid-forming (GFM) control of Type 3 and Type 4 wind turbine generators (WTGs) has attracted substantial attention in power systems research; however, the limited overcurrent capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. Synchronous wind, also referred to as a Type 5 WTG, offers a unique GFM solution to address grid integration and grid strength issues by keeping the grid largely synchronous at very high integration levels of renewable generation. A Type 5 WTG interfaces with the electric grid via a synchronous generator driven by a variable speed hydraulic torque converter; hence, the wind rotor operates in variable-speed mode for maximum power generation, and the generator shaft remains synchronous to the grid. This paper develops and tests a high-fidelity model of a Type 5 WTG in a power-hardware-in-the-loop testing environment, and it presents its operation characteristics under different grid contingencies. The power-hardware-in-the-loop demonstration shows that a Type 5 WTG inherently behaves as a GFM unit and can obtain similar performance in terms of power response, wind rotor dynamics, and stability enhancement compared to a Type 3 WTG in GFM control mode. Furthermore, the paper provides further insight into how Type 5 WTGs can support the smooth transition to power systems with high integration levels of inverter-based resources.

17 - WIND ENERGY↗
DOE OSTI2016

Hydro power flexibility for power systems with variable renewable energy sources: an IEA Task 25 collaboration: Hydro power flexibility for power systems

Hydro power is one of the most flexible sources of electricity production. Power systems with considerable amounts of flexible hydro power potentially offer easier integration of variable generation, e.g., wind and solar. However, there exist operational constraints to ensure mid-/long-term security of supply while keeping river flows and reservoirs levels within permitted limits. In order to properly assess the effective available hydro power flexibility and its value for storage, a detailed assessment of hydro power is essential. Due to the inherent uncertainty of the weather-dependent hydrological cycle, regulation constraints on the hydro system, and uncertainty of internal load as well as variable generation (wind and solar), this assessment is complex. Hence, it requires proper modeling of all the underlying interactions between hydro power and the power system, with a large share of other variable renewables. A summary of existing experience of wind integration in hydro-dominated power systems clearly points to strict simulation methodologies. Recommendations include requirements for techno-economic models to correctly assess strategies for hydro power and pumped storage dispatch. These models are based not only on seasonal water inflow variations but also on variable generation, and all these are in time horizons from very short term up to multiple years, depending on the studied system. Another important recommendation is to include a geographically detailed description of hydro power systems, rivers' flows, and reservoirs as well as grid topology and congestion.

13 HYDRO ENERGY↗