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DOE OSTI2020

A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems

Use of renewable energy resources can play a significant role in mitigation of climate change since they reduce the dependency on fossil fuels. However, high penetration of renewable energy resources into the power grid may cause some reliability problems. Ancillary services are key to realize the potential of renewable resources without disturbing the grid reliability. In recent years, many control approaches focused on exploiting the aggregate flexible heating, ventilation, and air-conditioning (HVAC) loads of buildings. However, there are still research gaps in assessing in advance the resulting indoor temperature responses for given total power and weather profiles before implementing the controls in the buildings. Such an assessment is critical to guarantee satisfying both the grid related objective (reliability) and the building related objective (occupants' comfort). Towards addressing this research gap, this paper presents a machine-learning approach for predicting the ratings of indoor temperature responses. In this approach, a prediction model was developed using a dataset generated by a set of model-free control simulations. The developed model achieved high prediction accuracy and showed the potential of the proposed approach.

Amasyali, Kadir↗

DOE OSTI2020

Scalable Transmission Expansion Under Uncertainty Using Three-Stage Stochastic Optimization

The intermittent nature of renewable energy poses new challenges for power grids due to its variable and uncertain power output. These features of renewable generation are becoming more relevant to transmission planning as grids reach higher penetration levels of renewable energy. In this paper we present an approach for transmission planning based on scalable computational approaches which enable the explicit consideration of operational uncertainties in the planning process. Using three-stage stochastic programming and the progressive hedging algorithm, we compute transmission expansion decisions on a modified RTS-GMLC test system. We augment the grid with large amounts of wind generation and consider many operational scenarios subject to wind uncertainty.

multi-stage stochastic optimization↗

DOE OSTI2021

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗

DOE OSTI2021

Island Power Systems With High Levels of Inverter-Based Resources: Stability and Reliability Challenges

As many island power systems seek to integrate high levels of renewable energy, they face new challenges on top of the existing difficulties of operating an isolated grid. With their drastically declining cost, variable renewables, such as wind and photovoltaics (PVs), are increasingly being integrated into island grids to reduce the use of imported fuels. These deployments of renewable energy are dominated by PV and wind generators, which bring unique challenges of their own. While the integration issues span numerous timescales (from microseconds to many months), this article focuses on reliability and stability challenges on short timescales (microseconds to seconds). In other words, we seek to answer (to the extent that it is currently known) how to ensure the frequency and voltage stability in an island power system with very high instantaneous levels of wind and PVs. And because island power systems are often among the first to reach these very high instantaneous levels of wind and PV generation, we note that they are forging a path for larger interconnected power systems to follow.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Building Energy Systems as Behind-the-Meter Resources for Grid Services: Intelligent load control and transactive control and coordination

To mitigate the impacts of climate change, significant reductions in emissions from all sectors of the economy are needed. The electricity generation sector has embarked on an ambitious plan to include renewable generation as part of its decarbonization efforts, and many cities and states are mandating all-electric buildings. While renewable resources will reduce emissions, they are not dispatchable, they vary temporally, and their generation is uncertain. Under these conditions, traditional approaches to managing grid reliability, where supply follows demand, will not be efficient and may not be cost-effective. Further, there is a more efficient alternative for balancing the supply–demand imbalance and for absorbing variability and uncertainty of renewable energy using distributed energy resources (DERs) as opposed to reserve generation. Because buildings consume more than 75% of total U.S. annual electricity consumption, behind-the-meter (BTM) DERs have a load flexibility of 77 GW of power and 90 GWh of virtual energy storage capacity nationwide (Kalsi, 2017). Therefore, some portion of the supply–demand imbalance can be met by these DERs at a lower cost compared to business-as-usual solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Optimal Complementarity Analysis of Potential Floating Solar Co-Located With Existing Hydropower Assets Across the Contiguous United States

The U.S. is expected to double its rate of renewable capacity from 2024 to 2030. However, the stochastic nature of renewable energy poses challenges to the operation and reliability of our power grid. The combined generation from renewable energy sources, with dispatchable sources (such as hydropower) operating as a hybrid energy plant, could mitigate this variability. In this paper, the complementarity analysis of selected U.S. reservoirs with existing hydropower assets (EHAs) and potential floating photovoltaics (FPVs) is conducted for the continuous U.S. (CONUS). The optimal FPV capacity for each site is determined by minimizing the variability of the combined output, while adhering to the FPV potential. Our results indicate that over 50% of the analyzed reservoirs achieve a stability coefficient exceeding 0.5, leading to a less-variable output after optimization. Finally, we analyze the complementary hydro-FPV hybrid reservoirs by considering both the Pearson correlation coefficient and the stability coefficient on daily, monthly, and yearly scales. Summaries are included of locations of theoretical FPVs co-located with hydropower plants that exhibit high complementarity based on the selected metrics.

13 - HYDRO ENERGY↗

DOE OSTI2022

Incentivizing Distributed Energy Resource Participation in Grid Services

The bulk power system is experiencing a dramatic shift as renewable generation growth continues to accelerate. Large-scale renewables adoption will help societies transition to a low-carbon, low-cost, and environmentally friendly electrical power system. However, the transition from a paradigm of generation following load to one where load follows generation will require large-scale interconnection and coordinated operation of Distributed Energy Resources (DERs), supported by open communication protocols. In this future grid scenario, DER aggregations will provide critical grid services that enable high penetration levels of renewable generation. This position paper presents an Energy Service Interface (ESI) that defines scope for ensuring secure, trustworthy information exchange between grid service providers and DERs. The goal of the ESI is to encourage large-scale participation of DERs in order to provide grid services through dispatch of DER aggregations. This position paper also presents an open smart energy communications protocol that allows DERs to advertise their characteristics and participate in grid services, within constraints established by the ESI. The paper presents several monetization incentives that grid service providers could use to encourage large-scale DER participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗

DOE OSTI2022

Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration

This paper focuses on the critical load restoration problem in distribution systems following major outages. To provide fast online response and optimal sequential decision-making support, a reinforcement learning (RL) based approach is proposed to optimize the restoration. Due to the complexities stemming from the large policy search space, renewable uncertainty, and nonlinearity in a complex grid control problem, directly applying RL algorithms to train a satisfactory policy requires extensive tuning to be successful. To address this challenge, this paper leverages the curriculum learning (CL) technique to design a training curriculum involving a simpler steppingstone problem that guides the RL agent to learn to solve the original hard problem in a progressive and more effective manner. We demonstrate that compared with direct learning, CL facilitates controller training to achieve better performance. To study realistic scenarios where renewable forecasts used for decision-making are in general imperfect, the experiments compare the trained RL controllers against two model predictive controllers (MPCs) using renewable forecasts with different error levels and observe how these controllers can hedge against the uncertainty. Results show that RL controllers are less susceptible to forecast errors than the baseline MPCs and can provide a more reliable restoration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Developing of Quaternary Pumped Storage Hydropower for Dynamic Studies

Quaternary pumped storage hydropower (Q-PSH) technology, as one of the new advanced-PSH technology, has been developed by taking advantage of Conventional-PSH (C-PSH) and Adjustable Speed-PSH (AS-PSH). By combining adjustable-speed pump unit and conventional hydropower turbine unit in the quaternary configuration, Q-PSH has the more competitive capability of providing fast power support in the future high renewable penetrated power system. Acting as energy storage (ES), Q-PSH provides promising power supply to deal with the uncertainty and variability from renewable energy generation. This paper focuses on the dynamic modeling of Q-PSH technology employing full-converter machine and the impact of Q-PSH on the frequency response in a system. The detailed model of Q-PSH is developed and implemented in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform, which captures the dynamic of multiple operation modes, especially hydraulic short-circuit (HSC) operation mode. Several cases are set up to reveal the advantages of Q-PSH technology when power electronic based renewable energy generation is deployed in the system. Sensitivity studies of the controller in pump governor show the impact of parameters in pump response performance. The comparison case illustrates the impact of frequency response provided by the Q-PSH in the system.

dynamic modeling↗

DOE OSTI2020

Material efficiency and climate change mitigation of passenger vehicles

A transition to electric vehicles and renewable energy is currently underway but may not be rapid enough in order to reach ambitious climate change mitigation targets. Therefore, additional, preferably instantaneous, measures are needed for quick emissions reductions, which is where material efficiency (ME) could constitute a promising solution. ME strategies include but are not limited to vehicle lightweighting through material substitution, increased recycling of materials, reuse and remanufacturing of vehicle components, vehicle downsizing (switching to a smaller vehicle) and more intensive use by means of increased vehicle occupancy through sharing practices. While recent analyses have focused on a narrow subset of these, we find striking differences in the overall potential of different strategies to decrease vehicular carbon footprints. Downsizing and more intensive use offer the largest mitigation potential but strongly depend on consumer behavior and are highly sensitive to modeling assumptions. Combined, the analyzed strategies can achieve emission reductions of up to 57% over the life cycle of a single vehicle, which is comparable to up to 83% achieved through a shift to low-carbon energy supply. ME can cut carbon footprints of already efficient vehicles charging renewable electricity by half again. This makes ME both an excellent short-term solution for climate change mitigation targeting the light vehicle sector but also an important complementary strategy to the long-term transition towards electric vehicles and renewable energy supply.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Circular economy framework for automobiles: Closing energy and material loops

Abstract Corporations, including automotive manufacturers, are increasingly exploring extended circular economy strategies as a means to enhance the sustainability of their products. The circular economy paradigm focuses on reducing nonrenewable materials and energy, promoting renewable feedstocks and energy, and keeping products/materials in use across the life cycle of a system. As such, life cycle environmental burdens associated with vehicle manufacturing, use, and disposal could potentially be reduced through circular economy strategies; however, no such comprehensive circular economy framework currently exists for the automotive industry. We develop the first circular economy schematic of automobiles, derived from the Ellen MacArthur Foundation's framework. Further, we characterize the current automotive circular economy using metrics of renewable energy and recycled materials. Specifically, for current U.S. average sedans, we find that internal combustion engine vehicles (ICEVs) use ∼6% renewable life cycle primary energy and 27% recycled materials; for battery electric vehicles (BEVs), these measures are ∼8% and 21%, respectively. On a vehicle‐miles‐traveled basis, BEVs use ∼47% less nonrenewable life cycle primary energy than ICEVs, highlighting the importance of electrification as a strategy for automotive manufacturers to reduce environmental burdens. Our proposed circular economy framework is then applied to Ford Motor Company's sustainability programs and initiatives as an example. This schematic aims to provide a starting point for the automotive industry to operationalize circular economy strategies, the application of which could advance its overall sustainability performance.

Aguilar Esteva, Laura C.↗

DOE OSTI2025

Engineering the hyperthermophilic archaeon Pyrococcus furiosus for 1-propanol production

ABSTRACT Society relies heavily on chemicals traditionally produced through the refinement of fossil fuels. The conversion of renewable biomass to value-added chemicals by microbes, particularly hyperthermophiles (T opt ≥80°C), offers a renewable alternative to this traditional approach. Herein, we describe the engineering of the hyperthermophilic archaeon Pyrococcus furiosus , which grows optimally (T opt ) at 100°C, for the conversion of sugar to 1-propanol. This was accomplished by constructing a hybrid metabolic pathway consisting of two native and seven heterologously produced enzymes to convert acetyl-CoA from carbohydrate metabolism to 1-propanol. A total of eleven foreign genes from two other organisms were utilized, one from the thermophilic bacterium Thermoanaerobacter sp. strain X514 and 10 from the thermoacidophilic archaeon Metallosphaera sedula, both of which grow optimally near 70°C. The recombinant P. furiosus strain produced 1-propanol at similar concentrations (up to ~1 mM) when incubated at 75°C to activate the gene products of Thermoanaerobacter sp. strain X514 and M. sedula and by initially incubating at 95°C for P. furiosus growth and then subsequently returning to 75°C to promote 1-propanol formation. Note that 1-propanol was not produced if the culture was grown only at 95°C. This work has the potential for future optimization through harnessing the genome-scale metabolic model of P. furiosus that was used herein to identify engineering targets to increase 1-propanol titer. IMPORTANCE As petroleum reserves become increasingly strained, the development of renewable alternatives to traditional chemical synthesis becomes more important. In this work, a high-temperature biological system for sugar to 1-propanol conversion was demonstrated by metabolic engineering of the hyperthermophilic archaeon Pyrococcus furiosus (T opt 100°C). The engineered strain produced 1-propanol by temperature shifting from 75°C to 95°C and then back to 75°C to accommodate the temperature ranges for native and foreign proteins associated with 1-propanol biosynthesis. Genome-scale metabolic modeling informed the carbon and reductant flux in the system, identified potential factors limiting 1-propanol production, and revealed potential optimization targets.

O'Quinn, Hailey C. (ORCID:0009000274865755)↗

DOE OSTI2023

(Invited) Utilization of Bio-CO 2 and Bio-Methane for Fuel Production: Integration Solid Oxide Electrolyzer, Low Energy Plasma Reformer with Fischer-Tropsch Synthesis

Transition to renewable energy is essential to achieve climate protection objectives. Besides storing electricity for later use, fuel production using renewable energy is an essential part of reducing fossil dependance. The highest value application in current markets is the production of liquid transportation fuels such as sustainable aviation fuels (SAF) from sustainable, ideally biogenic carbon resources. A system is presented for processing anaerobic digester gas for liquid hydrocarbon production. Bio-CO 2 is processed through a solid oxide electrolysis cell and bio-CH 4 through a low energy plasma reformer. The combined synthesis gas is supplied to a Fischer-Tropsch reactor for the production of liquid hydrocarbons. The combination of technologies nearly doubles the yield of biofuel by utilizing the bio-CO 2 in addition to the bio-CH 4 . Here, the product fuel is all bio-carbon but it also embodies renewable electric energy in a high-value, storable and transportable liquid hydrocarbon.

09 BIOMASS FUELS↗

DOE OSTI2022

Hydrogen and Battery Storage Technologies for Low-Cost Energy Decarbonization in Distribution Networks

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.

25 ENERGY STORAGE↗

DOE OSTI2020

SAM™ (System Advisor Model™) [SWR-16-02, SWR-10-13]

See the SAM™ website to build a desktop version of the National Laboratory of the Rockies' (NLR's) System Advisor Model™ (SAM). https://sam.nlr.gov/ The System Advisor Model™ (SAM™) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry: -Project managers and engineers -Policy analysts -Technology developers -Researchers SAM can model many types of renewable energy systems: -Photovoltaic systems, from small residential rooftop to large utility-scale systems -Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications -Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel -Industrial process heat from parabolic trough and linear Fresnel systems -Wind power, from individual turbines to large wind farms -Marine energy wave and tidal systems -Solar water heating -Fuel cells -Geothermal power generation -Biomass combustion for power generation -High concentration photovoltaic systems SAM's financial models are for the following types of projects: -Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill. -Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement. -Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement. For a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. https://www.nrel.gov/docs/fy18osti/70414.pdf

Ryberg, David↗

DOE OSTI2024

test-grid-buildouts [SWR-23-112]

Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.

Satkauskas, Ignas↗

DOE OSTI2020

Conversion of poplar biomass into high-energy density tricyclic sesquiterpene jet fuel blendstocks

In an effort to ensure future energy security, reduce greenhouse gas emissions and create domestic jobs, the US has invested in technologies to develop sustainable biofuels and bioproducts from renewable carbon sources such as lignocellulosic biomass. Bio-derived jet fuel is of particular interest as aviation is less amenable to electrification compared to other modes of transportation and synthetic biology provides the ability to tailor fuel properties to enhance performance. Specific energy and energy density are important properties in determining the attractiveness of potential bio-derived jet fuels. For example, increased energy content can give the industry options such as longer range, higher load or reduced takeoff weight. Energy-dense sesquiterpenes have been identified as potential next-generation jet fuels that can be renewably produced from lignocellulosic biomass. We developed a biomass deconstruction and conversion process that enabled the production of two tricyclic sesquiterpenes, epi-isozizaene and prespatane, from the woody biomass poplar using the versatile basidiomycete Rhodosporidium toruloides. We demonstrated terpene production at both bench and bioreactor scales, with prespatane titers reaching 1173.6 mg/L when grown in poplar hydrolysate in a 2 L bioreactor. Additionally, we examined the theoretical fuel properties of prespatane and epi-isozizaene in their hydrogenated states as blending options for jet fuel, and compared them to aviation fuel, Jet A. Our findings indicate that prespatane and epi-isozizaene in their hydrogenated states would be attractive blending options in Jet A or other lower density renewable jet fuels as they would improve viscosity and increase their energy density. Saturated epi-isozizaene and saturated prespatane have energy densities that are 16.6 and 18.8% higher than Jet A, respectively. These results highlight the potential of R. toruloides as a production host for the sustainable and scalable production of bio-derived jet fuel blends, and this is the first report of prespatane as an alternative jet fuel.

09 BIOMASS FUELS↗