HydroWIRES Lab Call Projects

The U.S. power system has undergone a number of changes over the past decade driven in part by increasing penetrations of variable renewable energy, distributed energy resources and grid-scale battery storage, as well as increasing consumer participation and shifting load profiles to name a few. These changes are anticipated to continue in the coming decade and beyond, likely accompanied by others - technological, socio-political, and market-oriented - that may substantially change the operational requirements of the power grid. The varying degrees to which these changes manifest will drive changes in the value that hydropower resources can provide to power systems. Many hydropower resources have technical capabilities to provide a range of grid services that have traditionally been largely untapped due to either low system requirements for these services, or a lack of clear price signals for the value that they provide to the grid. This project will establish a framework for quantifying the system value generated by conventional hydropower and PSH through the provision of grid services, as well the system factors that may augment these value streams in the future as power systems continue to evolve. The outcomes of this work will help stakeholders make prudent decisions regarding changes in operating practices and directing capital investments to improve resources' abilities to provide various grid services.

Laboratory(s): ANL, PNNL, NREL

The benefits of utilizing and integrating large-scale hydropower into grid operation are multi-faceted. Run-of-river (RoR) hydropower by itself has limited dispatchability, but RoR and energy storage hybrid resources have much more flexibility and controllability in their operations. At the system level, these hybrid resources will impact electricity market operations, and the full benefit will depend on how these resources are configured, controlled and represented in market models. The project team will develop a RoR and energy storage hybrid resource representation model to represent the new combination of resources in the day-ahead market.  This model will be used for security constrained unit commitment and for siting and sizing of energy storage paired with RoR in an independent system operator size system. The objective of this project is to assess the benefits of co-located and/or co-optimized hybrid RoR hydroelectric generators and energy storage resources from a system operator perspective.

Laboratory(s): PNNL

Increased deployment of variable renewable generation (VRG) assets and lower costs of grid-scale battery energy storage have led to increased deployment of hybrid generation and storage systems. The objective of this work is to compare the technical and financial value of integrating battery energy storage with ROR hydropower, wind, solar, and tidal generation resources. The Revenue, Operation, and Device Optimization (RODeO) model will be used to account for the financial value of capacity, energy sales (including arbitrage), and ancillary services from a VRG-battery hybrid system. Addressing this is important to understand the value of hybridizing resources and which types of resources to prioritize. In this work, at least two resource profiles will be selected for each generation type, and corresponding forecast uncertainties will be analyzed. These resource profiles will be normalized based on total energy produced per year and used as input to RODeO for market conditions corresponding to two different U.S. Independent System Operators. Two of the key considerations that this work will address are: (1) How will forecast uncertainty affect the financial performance of a VRG-battery hybrid system? and (2) Is hybridization financially advantageous compared to operating the VRG and battery storage independently? This work will provide a quantitative comparison to help motivate enhancement of the industry’s perspectives on “hydro-hybrids” (i.e. ROR hydropower + batteries and tidal + batteries).

Laboratory(s): INL, NREL

The Hydropower Signal Processor project will develop a data-driven methodology for classifying and comparing the water-to-energy and energy-to-water “transfer functions” that characterize the essential regulating and converting behavior of hydropower facilities. If one considers the time series of flow (and the specific energy conveyed by that flow) in a river as the signal, insight may be gained by examining how this “inflow” signal, with its periodic fluctuations, is lagged, filtered, and otherwise converted into an outflow signal by a hydropower facility, with a corresponding electric power output signal. By taking advantage of analytics from the signal processing and information flow domains, this effort will develop an efficient method for encapsulating the complex and facility-specific behavior of many hydropower facilities. The hypothesis of the project is that the transfer functions of facilities, derived from time series data, in the same archetype (“run-of-river”, “ponding storage”, and “long-term storage” for example) will exhibit similarities and features that can be used to classify facilities and model facilities more coherently and consistently in river and power system models—these transfer functions can also be used to understand which hydropower project archetypes warrant more detailed study to improve their representation in models. Hydropower facility-specific parameters derived from historical time series data will ultimately be intuitively and quantitatively linkable to hydropower production cost modeling (e.g. modes of operation for hydropower facilities) and water balance modeling, routing, and scheduling. This research and proposed methodology will provide an analysis tool, lexicon, and set of concepts that enable river system and power system decision-makers and modelers to mutually convey the functionality and value of hydropower to electric power systems.

Laboratory(s): ORNL

Real-time prototyping of hydropower plant controls is important for reducing the cost and the risk of field deployment. This project will 1) collect design and operational data from actual hydro plants and 2) use a physics-informed machine learning approach for real-time emulation of hydropower plants, including hydro turbine and hydrodynamics. The data-driven models will be interfaced with digital real-time simulation at NREL’s Flatirons campus for hardware-in-the-loop (HIL) testing of the governor hardware device or controller-HIL (CHIL). The proposed approach will also establish the connectivity based remote CHIL testing capability using real-time data streams from an actual hydro plant. This integrated hydro-plant emulation with CHIL will be used to prototype hydro-governor controls and eventually provide an opportunity to test hydropower integrated with various technologies (e.g. conventional and renewable generation, energy conversion, etc.) as HIL.

Laboratory(s): NREL

The main objective for this project is to develop a series of forward-looking and technically rigorous white papers intended to motivate discussion of hydropower capabilities across the broader power system community. The project team will develop three white papers, focusing on topics such as evolving trends within electricity markets, contractual arrangements for hydropower, future grid requirements for a changing resource mix, and how hydropower can contribute to meet these needs. Each white paper will contribute to the HydroWIRES goal of increased awareness and buy-in from the energy community for hydropower and pumped storage to be part of the conversation about flexible, renewable electricity resources and a cleaner power grid. Overall, the project will lead to an increased understanding of hydropower’s role in evolving power systems and electricity markets.

Laboratory(s): ANL, PNNL, NREL

Hydropower operations are closely linked to requirements and capacity of reservoir storage. In hydropower and multipurpose reservoirs, managing storage is critical to controlling floods, providing water supplies throughout the year, and to produce suitable hydraulic head for power generation. Recognition of the potential for existing hydropower reservoir storage to improve grid resilience and reliability has led to a growing interest in understanding existing storage capacity for conventional hydropower facilities. An understanding of the storage capacity (volume, timing, and variability of storage), and how it translates to benefits to the grid (potential generation), is essential for more strategic and effective application of existing hydropower infrastructure. The creation of a national dataset of attributes related to storage capacity will ultimately help inform flexible plant operation and management strategies and will enable more effective support of the grid as it continues to evolve.

Laboratory(s): ORNL

Operational needs of US power systems are changing due to increasing penetration of variable renewable energy (VER) resources and retirement of conventional fossil fuel-based generation. The nature of grid services, such as inertia and primary frequency response, may change too as more of these services are likely to be provided by inverter-based VERs and batteries. Consequently, the role of hydropower is also expected to change, as it relates to provision of these grid services. Modeling of hydropower plants in power systems analysis has been studied for decades but there are still modeling gaps that are being acutely realized due to the changing nature of power system operations; for instance, the modeling of hydropower resource capabilities in short-term power flow and dynamic stability models, which are used for analysis of system (and resource) response to contingency events, such as loss of a large generator. These modeling gaps need to be addressed to better understand the opportunities and challenges for hydropower resources in a changing power grid landscape. This project will produce a report on a list of hydro unit modeling gaps in steady-state power flow and dynamic stability models, developed through an extensive stakeholder engagement process.

Laboratory(s): PNNL, NREL, INL

Life cycle assessment (LCA) is an internationally accepted method for making consistent comparisons among technologies providing the same service based on environmental metrics. LCAs utilize similar inputs as techno-economic analysis (TEA). Traditionally, energy generation technologies have been evaluated through LCA, and in recent years, some energy storage technologies have likewise been evaluated, like pumped storage hydropower. However, with newer forms of energy storage being proposed (e.g. closed loop pumped storage configurations), there is a need for detailed assessment of life cycle environmental impacts to provide a consistent comparison with other storage technologies and to TEAs. With advice from an expert review panel, NREL will develop an LCA of closed loop pumped storage hydropower, while leveraging TEAs to inform decision makers such as DOE, ISOs, NGOs and other researchers on credible, objective environmental indicators that can be fairly and commensurately compared to other storage technologies.

Laboratory(s): NREL

A review of hydropower operations across market regions has revealed that hydropower operations are changing in many parts of the country due to evolving grid conditions. In particular, system operators are increasingly relying on hydropower’s capabilities—such as inertia, primary frequency response, spinning reserves, and regulation reserves—to support grid reliability. Provision of these services depends on the plant’s technical capabilities, but there are often other constraints that limit full utilization of those capabilities, which could be of electro-mechanical, environmental, and regulatory nature. Research has also shown that operating regimes associated with flexible operations can also have a detrimental effect on equipment condition that translates into higher operations and maintenance costs. Technology innovation is needed to address these challenges and improve hydropower’s capability as a fast-acting and flexible resource. ORNL, in partnership with INL and PNNL, are performing a comprehensive assessment to describe the current flexibility capabilities of hydropower components, establish existing constraints to fully utilize them, and identify novel opportunities for improvement.

Laboratory(s): ORNL, PNNL, INL

Pumped storage hydropower, with a total of 22 GW of installed capacity in the United States, represent over 95% of the domestic electric energy storage available today. However, no large PSH projects have been commissioned in the last 20 years due to challenges associated with the magnitude of project costs and financing interest during development and construction; the length of time from project investment until project revenue; permitting challenges and construction risks; competition from other storage technologies; and unrecognized energy storage valuation. To address these challenges, research and development efforts have focused on radically new designs and technologies that can dramatically reduce costs and commissioning timelines. In this study, Argonne National Laboratory will perform a landscape analysis to establish the current state of the art of PSH technology, identify promising new concepts and innovations, and highlight technology gaps that have yet to be addressed.

Laboratory(s): ANL

(A) Improving Hydropower Benefits by Linking Environmental Decisions and Power System Trade-offs Through Flow Release Decisions: Hydropower has a new and potentially important role in enhancing resilience of the electric system due to its ability to generate power without inputs from the grid. It is imminently important to understand if hydropower can have the necessary operational flexibility to provide these services given environmental flow requirements placed on the fleet. Environmental flow requirements included in Federal Energy Regulatory Commission (FERC) hydropower licenses are an important component to preserving, and in some cases, restoring, ecological function and services provided by riverine ecosystems. While environmental flow requirements in a FERC license may improve outcomes such as water quality, fish habitat, or recreation, they may limit the operational flexibility of hydropower plants, narrowing their ability to respond to the grid. Defining linkages between flow requirements and specific environmental outcomes is essential to not only producing favorable environmental outcomes but also to enabling greater operational flexibility within a given hydropower facility. This project will provide pathways for this co-optimization in hydropower systems by quantitatively linking power system and environmental outcomes through the common hub of flow decisions. It is anticipated that the co-optimization framework created in this project will provide a guide for designing environmental flow requirements that create value propositions for a diversity of stakeholders in FERC licensing proceedings. 

Laboratory(s): ORNL, PNNL, ANL, INL, NREL

(B1) Enhancing the representation of conventional hydropower flexibility in production cost models: Hydropower is in high demand from a power grid coordination perspective because of its operational and economic characteristics. But production cost models (PCMs)—a tool traditionally used to plan and optimize power generation sources to meet demand within security constraints at the lowest cost—currently oversimplify hydropower operations. As part of the HydroWIRES initiative, researchers from PNNL, ANL, and ORNL are teaming with the Center for Advanced Decision Support for Water and Environmental Systems to improve the representation of hydropower operations in PCMs across regional power grids. The PNNL-led team is leveraging large scale integrated water modeling tools and unit commitment models to build a module that characterizes potential hydropower operations based on daily hydrologic conditions, regulatory water management compliance rules, and economic signals. This module, referred to as dynamic classification by PCM modelers, will support more robust PCM-based studies. The dynamic classification will be developed over the western United States as proof of concept. Results from this effort will guide future model development and research to improve generator fleet dispatch, scheduling, and planning, toward the goal of better co-optimizing water and energy systems.

Laboratory(s): PNNL, ANL, INL, ORNL

(B2) Improving the Representation of Hydrologic Processes and Reservoir Operations in Production Cost Models: Although there have been many advances in PCM techniques over the past decade, the representation of hydropower operations has remained relatively rudimentary.  Hydropower operational constraints (e.g. equipment, water use priorities and rules, environmental constraints) are not easily characterized in unit commitment and economic dispatch models. Uncertainties involved with hydropower planning also do not align well with grid operation methodologies. These misalignments make it difficult for grid operations models to comprehensively value and make best use of the flexibility available with hydropower generation. To address these challenges, NREL will lead integration of intraday and day ahead grid operations models with a river basin model, enabling a global optimization across both grid and reservoir operations. The lab will also use stochastic hydropower forecasts combined with progressive hedging to perform multi-stage, multi-time period optimization. This allows the combined grid and water model to value multiple timescales and uncertainties in a single optimization, enabling more accurate value of real-time flexibility to help balance supply and demand under different scenarios while enforcing precise, long-term water level constraints. In essence, the project will help to improve both grid and water system resilience while making better use of the water throughout the season.

Laboratory(s): NREL

(C) Characterization of Hydropower Generation Attributes Relevant to Grid Reliability and Resilience: The US power system is continuing to evolve both in terms of system composition, as well as the definition of and requirements for attributes related to reliability and resilience of operations. While conventional contributors to system reliability are being replaced by as-available and variable renewable energy resources, extreme events (e.g. man-made (cyber) and natural) continue to afflict the power system on a more routine basis, causing damage and potential disruptions to the grid. Hence, the role of hydropower in meeting reliability and resilience needs will become even more important. This project will develop frameworks, evaluation methodologies, and tools to identify hydropower’s contribution to grid reliability and resilience. These methods will be demonstrated through various use cases representing a variety of future grid conditions and extreme event scenarios. The project will also provide insights into the specific operational and design attributes of hydropower resources that may need to be adapted to ensure that resources are best equipped to meet the power system’s reliability and resilience needs.

Laboratory(s): PNNL, INL, NREL, ORNL, ANL

(D1) Improving Hydropower and PSH Representations in Capacity Expansion Models: Long-term planning tools have difficulty representing detailed hydropower operating characteristics, which depend not only on technological specifications but also on water management practices and regulations. As a result, the value of hydropower is incompletely characterized, and the potential role of hydropower in the performance and resiliency of the future electric grid is not fully understood. This work will fill that gap by developing new ways to represent hydropower resource, technology, and operational characteristics in electric sector capacity expansion models and implementing them in the open-source version of the National Renewable Energy Laboratory’s Regional Energy Deployment System (ReEDS) model. ReEDS is a well-established national scale planning tool used since 2003 by the U.S. Department of Energy and others to explore the evolution of the U.S. electric sector. Improvements will include a comprehensive national resource assessment for pumped storage hydropower and methods for modeling multiple hydropower technology categories characterized by technical, regulatory, and economic characteristics. The project will provide guiding principles and strategies for improving hydropower modeling in capacity expansion models and deliver a first-of-its kind versatile PSH dataset. All data, code, and methods will be publicly available, allowing the industry to better identify the value of hydropower in the future electricity system and make more informed planning decisions.

Laboratory(s): NREL

(D2) Addressing Barriers to Energy Storage in Transmission Planning and Operations: A complex set of technical and regulatory issues creates significant barriers that prevent pumped storage hydropower (PSH) and other forms of energy storage from accurate representation in transmission planning and operational processes. These barriers are numerous and complex, and a full evaluation of them has not yet been done. As a result, current transmission planning, deployments and operations may be inefficient and, ultimately, may result in higher costs for customers. This project will identify those barriers, create a proposed participation model for PSH to provide transmission and market functions, and conduct a techno-economic analysis of PSH that fully quantifies its technical capability and economic value as a transmission asset.

Laboratory(s): PNNL, ANL

(D3) Value of flow forecasts to power system analytics: Hydropower operators use weekly water inflow forecasts to optimize reservoir releases and unit commitment and to meet power grid needs. The accuracy of inflow forecasts, combined with related scheduling adjustments, contracts, and market opportunities, are reflected in a utilities’ revenue. One of the goals of the HydroWIRES initiative is to quantify the flexibility of hydropower operations and understand its adaptability to changes in water supply, regulation, markets, and power grid needs. In partnership with North Carolina State University and the National Corporation of Atmospheric Research, researchers from PNNL and INL will use inflow forecasts, reservoir and power system models, and case studies to demonstrate the contribution of flow forecast to provide hydropower services to the grid. Flow forecast accuracy metrics, combined with regional power system analytics (including regional economics and generation portfolios) will help detangle the value of incremental improvement in flow forecasts. This research supports DOE in developing strategic partnerships with other institutions to invest in information products and decision-support practices for meeting power grid needs.

Laboratory(s): PNNL, INL