SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The Blackfeet Community College (BCC), under Topic Area 1.a. Energy Generating System(s), received funds to install solar photovoltaic (PV) systems to support four existing campus buildings. Blackfeet Community College seeks to bring renewable energy benefits to the Blackfeet Reservation Community.
Bangladesh faces several hurdles to achieving its renewable energy objectives, such as land availability and transmission congestion. Renewable Energy Zones (REZ), which are geographic areas with high-quality utility-scale renewable resources, suitable land topography, and commercial interest, can help address these challenges and support long-term generation and transmission planning. This study focuses on solar PV (fixed-tilt) and onshore wind, leveraging recently developed high temporal and spatial resolution resource data. In the moderate land exclusion scenario, large "study areas" are identified in Bangladesh with capacity factors in the top 25% for the entire country - 5 for wind and 8 for solar. Within these study areas, 19 candidates for REZ are identified based on the overlap between these study areas and upazilas (i.e., administrative subdivisions) containing economic development zones. Four of the identified candidate zones are opportunities for priority development, given the combination of strong wind and solar resources and the presence of economic zones. Furthermore, the geographic diversity of wind and solar resources in Bangladesh could help increase grid resilience by not concentrating all renewable energy development in the same region. Finally, pairing REZ with economic zones can bolster economic development, take advantage of large electricity demand, and leverage existing infrastructure investments.
The increasing penetration of renewable energy resources such as solar and wind via power electronic inverters is challenging grid dynamics, as well as grid planning, operation, and protection. Recently, the North American Electric Reliability Corporation (NERC) has reported a series of similar events of the unintended loss of solar generation in Southern California over a large geographic area following the transmission-level disturbances. These events highlight the importance of understanding the characteristics of the transmission-side disturbances propagating into the distribution systems and their impacts on the operation of inverter-based resources. In this paper, a real-time electromagnetic simulation testbed is constructed for real-time electromagnetic simulations to generate realistic transmission-level disturbances and investigate their impacts on the solar PV operation under different fault types and locations, solar penetration levels, and loading levels. Through the simulation analysis and grid strength assessment, it is found that the grid strength at points of integration (POIs) of solar PVs significantly affects the transient stability of solar generators. Particularly, undesirable transient stability events are more likely to occur at the weak POIs following the transmission-level disturbances. Moreover, undesirable transient stability events become severer when the transmission-level disturbance is closer to the weak POIs or the disturbances become more serious. Additionally, the impact of the transmission-level disturbances on the solar PVs at the weak POIs exacerbate with the increasing solar penetration levels and loading levels. Thus, it is important to study and develop new technologies for grid planning, operation, and protection in weak grid conditions to address the emerging issues of integrating the high penetration of solar PVs and other IBRs.
Utility-scale systems that combine solar photovoltaic and battery (PV+battery) technologies are growing in popularity on the U.S. bulk power system. The business case for PV+battery systems depends on both their ability to reduce costs and their ability to generate value synergies associated with the provision of energy, capacity, and ancillary services. Capacity value can constitute a significant portion of the value PV+battery hybrids provide to the grid (e.g., through avoided or deferred capacity) and receive through revenues. Throughout this report, we define capacity value as the monetary value of a plant's contribution towards the planning reserve margin, which ultimately depends on market rules and structures. PV+battery hybrids do not always fit into current market structures because of the interactions between the PV and battery components. Unique considerations for the capacity value of PV+battery hybrids include the disparate nature of participation models for PV and battery technologies in existing market rules and the potential influence of a shared interconnection capacity; limitations imposed by a shared inverter; limited ability to charge the battery in advance of capacity events if charging must be sourced from the coupled PV; and challenges or uncertainties associated with co-optimizing the operations of the PV and battery components. Grid operators are currently considering how market structures can be modified to optimally determine the capacity value provided by PV+battery systems, and the rules of how they are integrated into markets are still being written. As with any resource, poorly designed rules could increase the cost of energy and reduce system reliability, while well-designed rules could allow markets to receive the full benefits hybrid systems can offer without overcompensating them for the services they provide. Well-designed rules for PV+battery systems must consider the unique aspects listed above, while leveraging the commonalities with existing resource types. In this report, we summarize the technical capability and market rules that influence the capacity value of PV+battery systems. We further discuss the potential tradeoffs between computational complexity and accuracy for the various ways in which grid operators can credit PV+battery systems for capacity. Finally, we describe markets for capacity, survey current wholesale market rules applying to PV+battery systems, and provide a snapshot of the current regulatory landscape for PV+battery systems.
Deep energy decarbonization cannot be achieved without high penetration of renewables. At higher renewable energy penetrations, the variability and intermittent nature of solar photovoltaic (PV) electricity can cause ramping issues with existing fossil fuel generation, requiring longer term energy storage to increase the reliability of grid operation. Here, a proton exchange membrane electrolyzer can produce H 2 and serves as a utility controllable load. The produced H 2 can then be stored and converted back into electricity, or mixed with natural gas, or used as transportation fuel, or chemical feedstock. This paper considers the perspective of the distribution system operator that operates the distributed energy resources on a standard IEEE 33-node distribution network considering the technical and physical constraints with the goal of minimizing total investment and operation cost. Different case studies, at very high PV penetrations are considered to show the challenges and path to net-zero emission energy production using H 2 energy. Sensitivity of utility PV costs and electrolyzer capital costs on producing H 2 at $\$1$ /kg are presented showing that the distribution network could produce 100% renewable electricity and H 2 could be produced at a cost of $\$1$ /kg by 2050 with conservative cost estimates and by 2030 with accelerated cost declines.
Marine energy resources could promote clean energy and resilience of coastal and island microgrids, and thus, these applications are a key future market for marine energy development. To demonstrate these benefits, this paper illustrates how inclusion of wave resources into energy resilience solutions can improve overall grid efficiency and sustainability, as well as maintain electricity supply during grid outages. The paper describes a case study evaluation of the potential to add wave energy to the Moloka’i grid as Hawaii strives to meet a 100% clean energy target. The Microgrid Component Optimization for Resilience tool is used to simulate operation in off- grid conditions and size different combinations of wave, solar photovoltaic (PV), wind, storage, and fuel resources required to meet resilience objectives. This research in- vestigates how including wave resources in a microgrid contributes to reducing biofuel generation, producing a zero-greenhouse gas emission profile, and avoiding the over-sizing of PV and battery systems to accommodate periods of unavailability or high demand. Insight from this paper supports the value proposition of wave resources for future markets and informs the relationship between marine generators and microgrids or isolated grids.
As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.
Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.
The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.
Current commercial concentrating solar power (CSP) plants distinguish themselves from ordinary photovoltaic (PV) power plants by storing enough collected energy to enable generation for several hours after the sun goes down. CSP plants store this energy in the sensible heat of nitrate salts in large metallic storage tanks. Stainless-steel AISI 347H (SS347H) is needed for the hot tank operating at about 565 degrees C whereas carbon steel is sufficient for the cold-tank materials. Two-tank nitrate-salt thermal energy storage (TES) is presently in use in several trough-based CSP plants in Europe and in the U.S., operating up to about 390 degrees C. Three commercially operating tower-based CSP plants - Gemasolar in Spain, Crescent Dunes in Nevada, and Noor III in Morocco - use the same approach, storing nitrate salts at temperatures up to 580 degrees C. SS347H is many times more expensive than carbon steel and constitutes a significant cost element in today's CSP plants. Hence, CSP developers need to close the cost gap with PV-based solar plants by making cost reductions in every system of the plant. Redesigning the TES tanks is one opportunity for cost reduction.
PV (photovoltaic) systems, also known as solar panel systems, play an essential role in the mitigation of greenhouse gas emissions and the promotion of renewable energy. Through the conversion of sunlight into usable energy, electricity is generated without emitting greenhouse gases and producing pollutants. Notwithstanding the evolutionary significance of PV systems, the occurrence of defects and anomalies in PV systems may result in diminished power output, consequently impeding the efficiency of the systems and potentially resulting in hazards in certain circumstances. Therefore, early detection of faults and anomalies in PV systems is imperative to guarantee the reliability, efficiency, and safety of the systems. In this article, we develop a signal decomposition for the purpose of anomaly detection in PV systems. The proposed methodology is grounded on the concept of low-rank and sparse decomposition, with consideration given to the signs of the decomposed low-rank and sparse components, as well as the smooth variations within and between periods in the mean signals. Through the implementation of Monte Carlo simulations, we showcase the efficacy of our proposed methodology in identifying anomalies of varying durations and magnitudes in PV systems. A case study is employed to validate the proposed methodology in detecting anomalies in real PV systems.
The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.
The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.
The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.
Hospitals, emergency services, military bases, ports, airports, industries, commercial facilities, and others rely on backup power systems to provide electricity for their critical loads during grid outages. The purpose of this report it to provide accurate reliability information on commonly deployed distributed energy resources (DERs) to improve quantitative estimates for the reliability of these backup power systems during a grid outage. A backup power system consists of DERs, an electric distribution system with its associated switches and other devices, and mechanisms to control and manage the flow of electricity. Too often, facilities and campuses fail to properly quantify the reliability of their backup power systems. DERs are assumed to be 100% reliable, with the only concern being the availability of fuel. Such assumptions can lead to gross errors in the backup system's reliability estimates, particularly for long-duration outages. This report provides a set of estimates for reliability of emergency diesel generators (EDGs), natural gas prime generators and combined heat and power (CHP) prime movers, solar photovoltaics (PV), wind turbines, and Li-ion battery energy storage systems (BESS). The estimates are derived from empirical data when available and supplemented by modeling results when needed. These reliability estimates are for the DERs ability to provide power during a grid outage, ranging from an hour to 2 weeks.
The presentation, released quarterly, reviews major trends that occurred in the solar industry in 2019 and the first quarter of 2020. Major topics of focus will be global and U.S. supply & demand, module & system price, investment trends, and updates on U.S. government programs supporting the solar industry.
This work details a project to design reliable, resilient, and cost-effective networked microgrids considering grid constraints and resilience metrics focused on Puerto Rico distribution feeder locations with long outages after Hurricane Maria. The project consisted primarily of modeling and simulation tasks that accomplished the following objectives: 1. Selected 10 distribution feeder models in vulnerable areas. The sample feeders are geographically distributed across Puerto Rico and vary in length to capture the wide variety of feeders on the island. 2. Determined the optimal location and sizing of distributed energy resources (DERs) on the identified distribution feeders. The systems considered as part of the microgrid solutions were solar photovoltaic (PV), battery energy storage systems (BESS) and distributed fossil fuel generation (DFFG). 3. Estimated the cost-benefit of the proposed DER portfolios. 4. Provided a set of final recommendations that inform decision making on how to do targeted planning analysis for microgrids that can supply energy to critical infrastructures.
Grid-forming assets are required in microgrids to act as voltage-frequency masters. These grid-forming assets can operate in two modes of operation: grid-following mode and grid-forming mode. In grid-following mode of operation, these assets will follow real power and reactive power setpoints and in grid-forming mode of operation these assets will follow voltage and frequency setpoints. Traditionally, diesel generators or natural gas-based generators are widely used to act as a voltage-frequency master. However, many utilities are aiming to replace generators with grid forming-inverters supplied by solar photovoltaics (PV), batteries or fuel cells. Since grid-forming assets need a long-term reliable energy source, fuel cells are a reasonable and viable choice to supply the grid-forming inverters, but some of the challenges facing the wide deployment of grid-forming fuel cell inverters need to be addressed. Specifically, in our proposed work, we aim to focus on the interconnection and interoperability requirements of grid-forming fuel cell inverters. Currently, state-of-the-art fuel cell inverters follow the general interconnection requirements of distributed energy resources (DERs) and general interoperability requirements of DERs, but these requirements were built with PV and battery systems in mind. Fuel cells have different operational requirements, and therefore these requirements need to be appropriately modified for the grid operators to use. These additional steps add to the investment and operational cost to the grid operators. Through the ARIES platform, this proposed project aims to bridge this gap and use power hardware-in-the-loop (PHIL) and controller hardware-in-the-loop (CHIL) experiments to inform the creation of open-source interconnection and interoperability information that can aid in faster and cheaper installation and operation of grid-forming fuel cell inverters.