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DOE OSTI2023

Pinoresinol rescues developmental phenotypes of Arabidopsis phenylpropanoid mutants overexpressing FERULATE 5-HYDROXYLASE

Most phenylpropanoid pathway flux is directed toward the production of monolignols, but this pathway also generates multiple bioactive metabolites. The monolignols coniferyl and sinapyl alcohol polymerize to form guaiacyl (G) and syringyl (S) units in lignin, components that are characteristic of plant secondary cell walls. Lignin negatively impacts the saccharification potential of lignocellulosic biomass. Although manipulation of its content and composition through genetic engineering has reduced biomass recalcitrance, in some cases, these genetic manipulations lead to impaired growth. Here, the reduced-growth phenotype is often attributed to poor water transport due to xylem collapse in low-lignin mutants, but alternative models suggest that it could be caused by the hyper- or hypoaccumulation of phenylpropanoid intermediates. In Arabidopsis thaliana, overexpression of FERULATE 5-HYDROXYLASE (F5H) shifts the normal G/S lignin ratio to nearly pure S lignin and does not result in substantial changes to plant growth. In contrast, when we overexpressed F5H in the low-lignin mutants cinnamyl dehydrogenase c and d (cadc cadd), cinnamoyl-CoA reductase 1, and reduced epidermal fluorescence 3, plant growth was severely compromised. In addition, cadc cadd plants overexpressing F5H exhibited defects in lateral root development. Exogenous coniferyl alcohol (CA) and its dimeric coupling product, pinoresinol, rescue these phenotypes. These data suggest that mutations in the phenylpropanoid pathway limit the biosynthesis of pinoresinol, and this effect is exacerbated by overexpression of F5H, which further draws down cellular pools of its precursor, CA. Overall, these genetic manipulations appear to restrict the synthesis of pinoresinol or a downstream metabolite that is necessary for plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Hybrid Power Plants: Status of Operating and Proposed Plants, 2023 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2022, there were 374 hybrid plants (>1 MW) operating across the United States (+25% compared to the end of 2021), totaling nearly 41 GW of generating capacity (+15%) and 5.4 GW/15.2 GWh of energy storage (+69%/+88%). PV+storage plants are by far the most common, dominating in terms of plant number (213), storage capacity (4.0 GW/12.5 GWh), storage:generator capacity ratio (49%), and storage duration (3.1 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was another strong year for PV+storage hybrids in particular: 59 of the 62 hybrids added in 2022 were PV+storage. As of the end of 2022, there was roughly as much storage capacity operating within PV+storage hybrid plants as in standalone storage plants (~4 GW each). In storage energy terms, however, PV+storage edged out standalone storage by ~2 GWh (12.5 GWh vs. 10.4 GWh, respectively). -Interconnection queue data show continued strong developer interest in hybridization. At the close of 2022, there were 51% more hybrid plants—representing 59% more generating capacity—in interconnection queues across the United States than there were at the end of 2021. Solar dominates these proposed plants as well: at the close of 2022, there were 457 GW of solar capacity proposed as a hybrid (representing ~48% of all solar capacity in the queues), most typically pairing PV with battery storage. At the same time, there were 24 GW of wind capacity proposed as a hybrid (representing ~8% of all wind capacity in the queues), again most-often pairing wind with storage. Meanwhile, more than half of all storage in the queues is estimated to be part of a hybrid plant. While many of the plants proposed in the queues will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable, particularly in certain regions. For example, in CAISO, 97% of all solar capacity and 45% of all wind capacity in the queues is proposed as a hybrid. -The report also surveys power purchase agreement (PPA) price data from a sample of operating and proposed PV+storage plants. Though PV+storage PPA prices have fallen over time, “levelized storage adders” have recently increased somewhat to ~$\$ $7000/MW-month, ~$\$ $60/MWh-stored (assuming one full cycle per day), or ~$\$ $15/MWh-PV. Some of the recent price increase could simply reflect a trend towards higher battery:PV capacity ratios over time, which increases costs, all else being equal. The well-publicized impact of inflationary and supply chain pressures on battery prices is no doubt a contributor as well.

25 ENERGY STORAGE↗

DOE OSTI2024

Hybrid Power Plants: Status of Operating and Proposed Plants, 2024 Edition [Slides]

14 SOLAR ENERGY↗

DOE OSTI2024

Soil Sensors in Agriculture: From Unsustainable to Biodegradable

Soil sensors have been used in agriculture for over a century to detect environmental conditions relevant to plant growth and field heterogeneity. Although technological progression has improved these sensors' range and precision, the impact of introducint harmful electronic components necessary for detection and long-range transmission into agricultural soil has not been addressed by scientific community until the last two decades. This paper proposed a new mechanism for temperatur sensing based on differential thermal expansivity of plastics and metals, and explores a potential electronics-free transmission mechnanism that has been previously utilized in adjacent literature.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Mass spectrometry-based technologies for probing the 3D world of plant proteins

Abstract Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions—which are more difficult to study—dynamically regulate the proteome’s 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based “structural” proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.

Plant Sciences↗

DOE OSTI2024

Biomolecular and Characterization Imaging Science Program: 2023 Principal Investigator Meeting Proceedings

The 2023 U.S. Department of Energy (DOE) Biological and Environmental Research (BER) program’s Biomolecular Characterization and Imaging Science (BCIS) Principal Investigator Meeting expanded in scope from previous Bioimaging Science Program (BSP) meetings to include BER Structural Biology and Imaging Resources, which are located largely at DOE Office of Science national laboratories. The BCIS meeting was part of BER’s Biological Systems Science Division (BSSD) annual PI meeting, which was held April 17–19, 2023, and featured parallel meetings of the BCIS and Genomic Science programs (GSP). The meetings were held together to encourage networking and idea exchange across technologies and biological application areas, forging new multidisciplinary collaborations among researchers from adjacent BSSD programmatic areas. Two joint BCIS-GSP sessions were held: “BCIS Technologies for Investigating the Rhizosphere” and “Joint Emerging Topics and Technologies.” The rhizosphere session focused on scientific findings from BCIS and GSP PIs, including national laboratory collaborations. The intent was to identify new opportunities to measure and understand the complex community of microbes, roots, and soils that support plant growth under challenging environmental conditions. The emerging technologies session highlighted forward-looking approaches and tools to tackle challenges within the scope of BSSD research on investigating and modifying genomic and molecular function. A final interactive discussion of the BCIS program was led by plenary session chairs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Dynamics of ER stress-induced gene regulation in plants

Endoplasmic reticulum (ER) stress is a potentially lethal condition that is induced by the abnormal accumulation of unfolded or misfolded secretory proteins in the ER. In eukaryotes, ER stress is managed by the unfolded protein response (UPR) through a tightly regulated, yet highly dynamic, reprogramming of gene transcription. Although the core principles of the UPR are similar across eukaryotes, unique features of the plant UPR reflect the adaptability of plants to their ever-changing environments and the need to balance the demands of growth and development with the response to environmental stressors. Here, the past decades have seen notable progress in understanding the mechanisms underlying ER stress sensing and signaling transduction pathways, implicating the UPR in the effects of physiological and induced ER stress on plant growth and crop yield. Facilitated by sequencing technologies and advances in genetic and genomic resources, recent efforts have driven the discovery of transcriptional regulators and elucidated the mechanisms that mediate the dynamic and precise gene regulation in response to ER stress at the systems level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops

Abiotic stresses such as drought, heat, cold, salinity and flooding significantly impact plant growth, development and productivity. As the planet has warmed, these abiotic stresses have increased in frequency and intensity, affecting the global food supply and making it imperative to develop stress-resilient crops. In the past 20 years, the development of omics technologies has contributed to the growth of datasets for plants grown under a wide range of abiotic environments. Integration of these rapidly growing data using machine-learning (ML) approaches can complement existing breeding efforts by providing insights into the mechanisms underlying plant responses to stressful conditions, which can be used to guide the design of resilient crops. In this review, we introduce ML approaches and provide examples of how researchers use these approaches to predict molecular activities, gene functions and genotype responses under stressful conditions. Finally, we consider the potential and challenges of using such approaches to enable the design of crops that are better suited to a changing environment. This article is part of the theme issue ‘Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the ‘Resilience Revolution’?’.

abiotic stress↗

DOE OSTI2020

Development of Prognostic Models Using Plant Asset Data

The recent growth of machine learning and artificial intelligence technologies provides opportunities for leveraging data-driven algorithms to address the problems of diagnostics and prognostics in the nuclear power industry. The use of machine learning and other statistical methods as prognostic models is of particular interest in the nuclear industry to accurately predict future equipment or plant state given a set of measurements. Such predictive capability will enable predictive assessment of component condition and remaining life and allow for condition-based predictive maintenance. The resulting optimization of maintenance scheduling and reduction in unnecessary maintenance activities will lower overall maintenance costs and improve the economics of nuclear power. This report discusses the various aspects of data processing and model development that are likely to influence the performance of prognostic models. Data from a boiling-water reactor was used to evaluate several prognostic models to identify key considerations for developing such models to predict data-driven plant state and equipment degradation condition. Preliminary results indicate the need for data sets that are relevant to the problem at hand and contain signatures that may be correlated to the prediction problem. Assuming such data exist, development of prognostic models using data-driven methods requires an understanding of the various sources of influence on the prediction accuracy (such as the model architecture, data preprocessing approaches, and potentially external factors influencing the equipment or plant system under assessment). Ongoing research is evaluating these factors in greater detail and examining techniques for calculating prediction uncertainty bounds.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Evolution of Electric Sector Water Use Under Alternative Electricity Futures

Increasing competition for water resources in the United States could create future challenges for allocating and using thermal cooling water in the U.S. electric power sector. While thermal power plant retirements and the growth of wind and solar technologies can reduce national aggregate power sector cooling water use, local water constraints and growing demand for agricultural or municipal supply could create greater needs for higher-cost alternative water supplies such as groundwater or recycled wastewater. For some regions, these incentives could change future electricity planning and operational decisions. These relationships and impacts are studied here using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS), a national electric sector planning model that has recently been upgraded to include a highly detailed representation of thermal cooling water demand and supply. Thermal power technologies are differentiated by both cooling technology and water source type to track and constrain thermal cooling water use in a way that incorporates both physical and legal water considerations in the United States. This capability is exercised under a range of electricity sector futures with alternative technology costs, fuel prices, and water constraints to illustrate ways that U.S. electric sector water use could evolve under uncertain future electric sector drivers. In exploring changes to regional generation and transmission planning and operation, water requirements, and cost, we highlight the environmental and economic impacts of future power sector water decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Decarbonization and technology cost drivers: considerations for potential future thermoelectric water use in the power sector

The power sector is currently undergoing significant changes, driven by a combination of factors, including decarbonization and technology innovation. This study aims to assess implications of these drivers on U.S. power sector technology futures and the associated water and environmental implications for cooling thermoelectric power plants. Specifically, we evaluate four decarbonization scenarios for the contiguous United States that vary in assumptions concerning demand growth and technology costs, with technology costs driving alternative outcomes that prioritize either technologies that require low amounts of water (such as wind, solar, and battery) or high amounts of water (such as nuclear and carbon capture and storage). These scenarios are executed in a power sector capacity expansion model and compared to two reference scenarios that assume status quo with policy and cost drivers. Our analysis indicates that future U.S. thermoelectric water withdrawals could decrease by 25%–60%, but water consumption could more than triple in some scenarios. These changes are driven by a combination of retirement of some power facilities, shifts in cooling technologies, and new technology deployment. The water use patterns vary across the United States, with the eastern regions demonstrating a lot more variability in water consumption across scenarios than western regions. However, local concerns can influence these possible investments, since increased water consumption can exacerbate water scarcity, leading to conflicts among competing users and affecting regional social, environmental, and economic dynamics. Future work should consider possible costs associated with alternate water sources, as well as improve the representation of water constraints within simulations. Inclusion of extreme events and alternate modeling platforms (e.g. production cost modeling and resource adequacy) may also be warranted to further stress test the robustness of these possible technology futures. Such assessments will be critical for ensuring decarbonization and other infrastructure-oriented investments lead to a reliable and resilient power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Highly Efficient Magnetocaloric Natural Gas Liquefaction (Final Report)

Over the twelve-month project the following achievements were accomplished: • Liquefication of methane as primary component of natural gas was accomplished with a magnetocaloric liquefier (MCL) prototype. This was the first time an MCL was used to liquefy methane. • Improved MCL designs were completed. • Cooling to 135 K from room temperature was achieved for the first time in a single MCL stage with dual, reciprocating four-layer regenerators. • Techno-economic analysis for a multi-stage 5 tonne/day magnetocaloric liquefier was completed. The detailed thermodynamic analysis of this MCL design showed a figure of merit (FOM) of 0.6 was achievable. This is a ~2x improvement over current state of the art. • Cost of an efficient 5 tonne/day LNG multi-stage liquefier was projected to be ~$\$$3.1 MM for the 5 tonne/day MCL with achievable design assumptions. • Market study of U.S. merchant LNG demand by energy sector was completed showing that at beginning of 2019, total use was ~2.5 million gallons/day primarily in three sectors that was filled by ~20 small companies in the merchant LNG supply business producing ~2.3 million gpd. These data exclude LNG produced at dedicated peak shaving and large export plants. • Business case for MCL technology based on LNG market study was completed showing the high FOM feature of MCL reduces cost of plant power, and lower capital cost reduces debt repayment and plant depreciation operating expenses. However, today’s demand for U.S. merchant LNG in most sectors is satisfied with conventional technology. Further, with today’s extremely low natural gas (NG) feedstock costs (e.g., ~$\$$1.8/MMBtu), the cost of fuel for NG gensets and for LNG feedstock is already very low. Therefore, possible new merchant LNG liquefier plant developers anticipating demand growth in the transportation, industrial, and electricity generation sectors do not obtain sufficient cost benefits to adopt new, commercially unproven MCL technology. • Other market factors such as remoteness from existing NG pipelines, or unfilled or unsatisfied applications such as boil-off gas re-liquefaction in LNG vessels, or policy factors such as some form of emissions-related fees may make lower capital costs and higher FOM of MCL technology attractive for new small-scale (~50 tonne/day) LNG plants. Two potentially attractive niche markets for MCL technology were identified: i) re-liquefaction of boil-off gas from large LNG transport vessels where severe transport conditions are problematic for conventional technology; and ii) providing LNG in distributed-scale plants that eliminate road transport costs to meet diverse, smaller-scale, distributed LNG bunkering fuel demands. By eliminating significant cryogenic tanker delivery costs and create an attractive cost-savings benefit with small-scale MCL plants.

03 NATURAL GAS↗

DOE OSTI2022

Using CRISPR-Cas9 Technology to Eliminate Xyloglucan in Tobacco Cell Walls and Change the Uptake and Translocation of Inorganic Arsenic

Xyloglucan is a quantitatively major polysaccharide in the primary cell walls of flowering plants and has been reported to affect plants’ ability to tolerate toxic elements. However, it is not known if altering the amounts of xyloglucan in the wall influences the uptake and translocation of inorganic arsenic (As). Here, we identified two Nicotiana tabacum genes that encode xyloglucan-specific xylosyltransferases (XXT), which we named NtXXT1 and NtXXT2. We used CRISPR-Cas9 technology to generate ntxxt1 , ntxxt2 , and ntxxt1/2 mutant tobacco plants to determine if preventing xyloglucan synthesis affects plant growth and their ability to accumulate As. We show that NtXXT1 and NtXXT2 are required for xyloglucan biosynthesis because no discernible amounts of xyloglucan were present in the cell walls of the ntxxt1/2 double mutant. The tobacco double mutant ( ntxxt1/2 ) and the corresponding Arabidopsis mutant ( atxxt1/2 ) do not have severe growth defects but do have a short root hair phenotype and a slow growth rate. This phenotype is rescued by overexpressing NtXXT1 or NtXXT2 in atxxt1/2 . Growing ntxxt mutants in the presence of AsIII or AsV showed that the absence of cell wall xyloglucan affects the accumulation and translocation of As. Most notably, root retention of As increased substantially and the amounts of As translocated to the shoots decreased in ntxxt1/2 . Our results suggest that xyloglucan-deficient plants provide a strategy for the phytoremediation of As contaminated soils.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.

Mongird, Kendall↗

DOE OSTI2021

Impacts of turbine and plant upsizing on the levelized cost of energy for offshore wind

Turbine and plant upsizing are major trends in offshore wind deployment, although the quantitative impact on project costs has not been well-characterized. The uncertain value of continued wind turbine and project growth limits the ability of the supply chain to prepare for future technology trends, leading to challenges in the realization of larger projects. This analysis explores the levelized cost of energy impacts of turbine ratings between 6 and 20 MW and plant capacities between 250 and 2,500 MW for fixed-bottom offshore wind using techno-economic cost models for foundation, electrical, installation, and operation and maintenance costs, along with annual energy production. We consider a nominal set of technology assumptions for all scenarios to isolate economies of size and scale without additional benefits from decreasing turbine capital costs, quantity discounts for larger projects, or optimized technology solutions. These results indicate that using a 20-MW wind turbine in a 2,500-MW power plant array can reduce the levelized cost of energy by over 23% relative to the global average turbine and plant size installed in 2019; primarily because of reductions in the balance-of-system and operation and maintenance costs. We also identify improved installation vessels, optimized export systems, and novel operation and maintenance strategies as additional cost reduction opportunities. These results suggest that upsizing represents a significant cost reduction opportunity for offshore wind energy and will continue to be a main factor in shaping the future of the sector.

17 WIND ENERGY↗

DOE OSTI2024

Field Validation of Electrochemical Water Filtration System on an Open Loop Cooling Tower at Nissan Manufacturing Plant in Canton, Mississippi

The U.S. Department of Energy Industrial Efficiency and Decarbonization Office’s Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. This ITV demonstration investigated the performance of an early-commercial electrochemical water treatment technology on a cooling tower at an automotive plant. Cooling towers are vital equipment for dissipating heat from industrial processes, but they face challenges related to scaling, corrosion, and the growth of biological contaminants. Effective cooling tower water treatment is therefore essential in reducing these contaminants and other total suspended solids (TSS) and total dissolved solids (TDS). Various treatment systems, such as sand-based filters, centrifugal separators, and disc filters are available, each having its advantages and drawbacks. ElectroCell Systems, a filtration technology provider, offers an electrochemistry-based water treatment system that is skid-mounted and can be configured as a side-stream filtration system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report

In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗