This report summarizes Fiscal Year 2023 accomplishments from Sandia National Laboratories Wind Energy Program. The portfolio consists of funding provided by the DOE EERE Wind Energy Technologies Office (WETO), Advanced Research Projects Agency-Energy (ARPA-E), Advanced Manufacturing Office (AMO), the Sandia Laboratory Directed Research and Development (LDRD) program, and private industry. These accomplishments were made possible through capabilities investments by WETO, internal Sandia investment, and partnerships between Sandia and other national laboratories, universities, and research institutions around the world. Sandia’s Wind Energy Program is primarily built around core capabilities as expressed in the strategic plan thrust areas, with 29 staff members in the Wind Energy Design and Experimentation department and the Wind Energy Computational Sciences department leading and supporting R&D at the time of this report. Staff from other departments at Sandia support the program by leveraging Sandia’s unique capabilities in other disciplines.
This report summarizes Fiscal Year 2022 accomplishments from Sandia National Laboratories Wind Energy Program. The portfolio consists of funding provided by the DOE EERE Wind Energy Technologies Office (WETO), Advanced Research Projects Agency-Energy (ARPA-E), Advanced Manufacturing Office (AMO), and the Sandia Laboratory Directed Research and Development (LDRD) program. These accomplishments were made possible through capabilities investments by WETO, internal Sandia investment, and partnerships between Sandia and other national laboratories, universities, and research institutions around the world. Sandia’s Wind Energy Program is primarily built around core capabilities as expressed in the strategic plan thrust areas, with 29 staff members in the Wind Energy Design and Experimentation department and the Wind Energy Computational Sciences department leading and supporting R&D at the time of this report. Staff from other departments at Sandia support the program by leveraging Sandia’s unique capabilities in other disciplines.
This report summarizes Fiscal Year 2021 accomplishments from Sandia National Laboratories Wind Energy Program. The portfolio consists of funding provided by the DOE EERE Wind Energy Technologies Office (WETO), Advanced Research Projects Agency-Energy (ARPA-E), DOE Small Business Innovation Research (SBIR), and the Sandia Laboratory Directed Research and Development (LDRD) program. These accomplishments were made possible through capabilities investments by WETO, internal Sandia investment, and partnerships between Sandia and other national laboratories, universities, and research institutions around the world.
Costs to permit Marine Energy projects are poorly understood. In this paper we examine environmental compliance and permitting costs for 19 projects in the U.S., covering the last 2 decades. Guided discussions were conducted with developers over a 3-year period to obtain historical and ongoing project cost data relative to environmental studies (e.g., baseline or pre-project site characterization as well as post-installation effects monitoring), stakeholder outreach, and mitigation, as well as qualitative experience of the permitting process. Data are organized in categories of technology type, permitted capacity, pre-and post-installation, geographic location, and funding types. We also compare our findings with earlier logic models created for the Department of Energy (i.e., Reference Models). Environmental studies most commonly performed were for Fish and Fisheries, Noise, Marine Habitat/Benthic Studies and Marine Mammals. Studies for tidal projects were more expensive than those performed for wave projects and the range of reported project costs tended to be wider than ranges predicted by logic models. For eight projects reporting full project costs, from project start to FERC or USACE permit, the average amount for environmental permitting compliance was 14.6%.
The marine and hydrokinetic (MHK) industry plays a vital role in the U.S. clean energy strategy by providing a renewable, domestic energy source that may offset the need for traditional energy sources. The first MHK deployments in the U.S. have incurred very high permitting costs and long timelines for deploying projects, which increases project risk and discourages investment. A key challenge to advancing an economically competitive U.S. MHK industry is reducing the time and cost required for environmental permitting and compliance with government regulations. Other industries such as offshore oil and gas, offshore wind energy, subsea power and data cables, onshore wind energy, and solar energy facilities have all developed more robust permitting and compliance pathways that provide lessons for the MHK industry in the U.S. and may help inform the global consenting process. Based on in-depth review and research into each of the other industries, we describe the environmental permitting pathways, the main environmental concerns and types of monitoring typically associated with them, and factors that appear to have eased environmental permitting and compliance issues.
Survey data from the Energy Information Administration (EIA) was combined with data from the Environmental Protection Agency (EPA) to explore ways in which operations might impact water use intensity (both withdrawals and consumption) at thermoelectric power plants. Two disparities in cooling and power systems operations were identified that could impact water use intensity: (1) Idling Gap - where cooling systems continue to operate when their boilers and generators are completely idled; and (2) Cycling Gap - where cooling systems operate at full capacity, while their associated boiler and generator systems cycle over a range of loads. Analysis of the EIA and EPA data indicated that cooling systems operated on average 13% more than their corresponding power system (Idling Gap), while power systems operated on average 30% below full load when the boiler was reported as operating (Cycling Gap). Regression analysis was then performed to explore whether the degree of power plant idling/cycling could be related to the physical characteristics of the plant, its environment or time of year. While results suggested that individual power plants' operations were unique, weak trends consistently pointed to a plant's place on the dispatch curve as influencing patterns of cooling system, boiler, and generator operation. This insight better positions us to interpret reported power plant water use data as well as improve future water use projections.
Meeting technology-based policy goals without sufficient lead time may present several technology, regulatory and market-based challenges due to the speed of technological adoption in existing and emerging markets. Installing incremental amounts of technologies, e.g., cleaner fossil, renewable or transformative energy technologies throughout the coming decades, may prove to be a more attainable goal than a radical and immediate change 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 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). A system dynamics model was developed to illustrate the TRM framework. The framework helps identify the factors, and specifically the rate at which we must support technology development, necessary to meet our desired technical and policy goals in the coming decades.
This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.
Solar photovoltaic systems provide cost savings to the property owner in terms of avoided electricity costs that accrue over the system lifetime. From an investment standpoint, the equipment and the value of the energy generated can potentially increase the underlying property value. This first-of-a-kind study presents real market data collected from real estate appraisers using the PV Value® tool to develop a market value for solar as part of a property sale or refinance. Aggregated results at the state level are discussed for California, Arizona and Massachusetts, using 2015 and 2016 data where appraisers used the income capitalization approach to develop a market value for solar. Additional data collection using future transaction data could reveal market-specific trends and insights at the zip code, city and metropolitan statistical area (MSA) levels.
This user manual is intended to provide instructions to volunteer beta testers on how to use Sandia National Laboratories (SNL) PV Reliability Performance Model (PV-RPM) features in the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) version 2017.1.17 r4 (NREL, 2017). This new feature is provided in SAM to allow users with reliability data the ability to develop and run scenarios where PV performance and costs are impacted from components that can fail stochastically. This is intended to be an advanced user feature as it requires knowledge and data regarding different PV component failure modes. It also relies heavily on the SAM LK scripting language, which is not utilized by a majority of SAM users. NREL has published a SAM LK users guide (Dobos, 2017) and has multiple online help topics and videos to get users familiar with the scripting language and what it can do. This user instruction manual will provide some background on how data collected from a PV system can be used as inputs in the PV-RPM model, which will give data owners the ability to develop their own reliability and repair distributions outside of the example provided here.
This paper describes efforts made by Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) to validate the SNL developed PV Reliability Performance Model (PV - RPM) algorithm as implemented in the NREL System Advisor Model (SAM). The PV - RPM model is a library of functions that estimates component failure and repair in a photovoltaic system over a desired simulation period. The failure and repair distributions in this paper are probabilistic representations of component failure and repair based on data collected by SNL for a PV power plant operating in Arizona. The validation effort focuses on whether the failure and repair dist ributions used in the SAM implementation result in estimated failures that match the expected failures developed in the proof - of - concept implementation. Results indicate that the SAM implementation of PV - RPM provides the same results as the proof - of - concep t implementation, indicating the algorithms were reproduced successfully.
The use of the term 'availability' to describe a photovoltaic (PV) system and power plant has been fraught with confusion for many years. A term that is meant to describe equipment operational status is often omitted, misapplied or inaccurately combined with PV performance metrics due to attempts to measure performance and reliability through the lens of traditional power plant language. This paper discusses three areas where current research in standards, contract language and performance modeling is improving the way availability is used with regards to photovoltaic systems and power plants.
With rising grid interconnections of solar photovoltaic (PV) systems, greater attention is being trained on lifecycle performance, reliability, and project economics. Expected to meet production thresholds over a 20-30 year timeframe, PV plants require a steady diet of operations and maintenance (O&M) oversight to meet contractual terms. However, industry best practices are only just beginning to emerge, and O&M budgets—given the arrangement of the solar project value chain—appear to vary widely. Based on insights from in-depth interviews and survey research, this paper presents an overview of the utility-scale PV O&M budgeting process along with guiding rationales, before detailing perspectives on current plant upkeep activities and price points largely in the U.S. It concludes by pondering potential opportunities for improving upon existing O&M budgeting approaches in ways that can benefit the industry at-large.
With rising grid interconnections of solar photovoltaic (PV) systems, greater attention is being trained on lifecycle performance, reliability, and project economics. Expected to meet production thresholds over a 20-30 year timeframe, PV plants require a steady diet of operations and maintenance (O&M) oversight to meet contractual terms. However, industry best practices are only just beginning to emerge, and O&M budgets—given the arrangement of the solar project value chain—appear to vary widely. Based on insights from in-depth interviews and survey research, this paper presents an overview of the utility-scale PV O&M budgeting process along with guiding rationales, before detailing perspectives on current plant upkeep activities and price points largely in the U.S. It concludes by pondering potential opportunities for improving upon existing O&M budgeting approaches in ways that can benefi t the industry at-large.
This document outlines the foundation for developing language that can be utilized in an Equipment Availability Guarantee, typically included in an O&M services agreement between a PV system or plant owner and an O&M services provider, or operator. Many of the current PV O&M service agreement Availability Guarantees are based on contracts used for traditional power generation, which create challenges for owners and operators due to the variable nature of grid-tied photovoltaic generating technologies. This report documents language used in early PV availability guarantees and presents best practices and equations that can be used to more openly communicate how the reliability of the PV system and plant equipment can be expressed in an availability guarantee. This work will improve the bankability of PV systems by providing greater transparency into the equipment reliability state to all parties involved in an O&M services contract.
Characterizing the factors that affect reliability of a photovoltaic (PV) power plant is an important aspect of optimal asset management. This document describes the many factors that affect operation and maintenance (O&M) of a PV plant, identifies the data necessary to quantify those factors, and describes how data might be used by O&M service providers and others in the PV industry. This document lays out data needs from perspectives of reliability, availability, and key performance indicators and is intended to be a precursor for standardizing terminology and data reporting, which will improve data sharing, analysis, and ultimately PV plant performance.
To fill a major knowledge gap, Sandia National Laboratories (SNL) and the Electric Power Research Institute (EPRI) are jointly engaged in a multi-year research effort, supported by the Department of Energy’s SunShot Program, to examine real-world photovoltaic (PV) plant reliability and performance. Findings and analyses, derived from field data documented in the PV Reliability Operations Maintenance (PVROM) database tool as well as from convened workshops and working group discussions, are intended to inform industry best practices around the optimal operations and maintenance (O&M) of solar PV assets. To improve upon and evolve existing solar PV O&M approaches, this report: 1. Provides perspective on the concept of PV “system” reliability and how it can inform plant design, operations, and maintenance decisions that produce better long-term outcomes; 2. Describes the PVROM data collection tool, its technical capabilities, and results generated from database content in 2014; 3. Presents ongoing research efforts that are meant to drive the solar industry toward PV O&M best practice protocols and standards; and 4. Reflects on future areas of inquiry that can help better forecast plant health (e.g., system component availability, component wear out, etc.) and associated lifecycle costs. Ultimately, this report adds to the knowledge base of improving PV system O&M activities by discussing data collection and analysis techniques that can be used to better understand and enhance the reliability, availability, and performance of a photovoltaic system.
As greater numbers of photovoltaic (PV) systems are being installed, operations & maintenance (O&M) activities will need to be performed to ensure the PV system is operating as designed over its useful lifetime. To mitigate risks to PV system availability and performance, standardized procedures for O&M activities are needed to ensure high reliability and long-term system bankability. Efforts are just getting underway to address the need for standard O&M procedures as PV gains a larger share of U.S. generation capacity. Due to the existing landscape of how and where PV is installed, including distributed generation from small and medium PV systems, as well as large, centralized utility-scale PV, O&M activities will require different levels of expertise and reporting, making standards even more important. This report summarizes recent efforts made by solar industry stakeholders to identify the existing standards and best practices applied to solar PV O&M activities, and determine the gaps that have yet to be, or are currently being addressed by industry.
Sandia National Laboratories, working with Energy Sense Finance developed the proof-ofconcept PV Valueª tool in 2011 to provide real estate appraisers a tool that can be used to develop the market value and fair market value of a solar photovoltaic system. PV Valueª moved from a proof-of-concept spreadsheet to a commercial web-based tool developed and operated exclusively by Energy Sense Finance in June 2014. This paper presents the results of a survey aimed at different user categories in order to measure how the tool is being used in the marketplace as well as elicit information that can be used to improve the tools effectiveness.