Michael E. Webber

ReCreateIt, led by re:3D, Inc. and partnering with Austin Habitat for Humanity (AHFH) ReStore, Georgia Tech, University of Texas at Austin, Western Sydney University (Australia) and the University of Wollongong (Australia), is developing a local circular economy by deploying a Gigalab, a sustainable manufacturing lab capable of repurposing plastic waste through fused granular fabrication 3D printing. ReCreateIt has set a goal to divert at least 10,000 lbs of plastic waste from entering landfills, train at least 20 workers in advanced manufacturing and engage and educate more than 500 community members. To create high value items from recycled plastic, re:3D built a Gigalab from a modified shipping container, which houses a GigabotX 3D printer, a granulator, and a material dryer. Georgia Tech is leading the implementation of an interactive design tool customers can use to select and customize home goods. UT Austin and the University of Wollongong are developing a sustainability dashboard which collects and communicates the environmental impacts of the project. Western Sydney University and the previously mentioned collaborators are conducting polymer research to characterize bulk recycled materials, enhance the printability of recycled materials, and ensure the structural integrity of printed parts. All research, metrics and data will be made accessible via a project-built public-facing website. The ReCreateIt Gigalab installed at a ReStore site in Austin, TX enables customers to design sustainable home goods 3D printed directly from recycled plastic waste collected on-site during normal ReStore operations. The project is increasing access to plastic recycling solutions while stimulating new job creation and education for historically underserved communities. The team is also researching solutions for 3D printing with hard-to-reuse commodity plastics. To date, over 4000 lbs of plastics has been collected, and over 650 lbs has been processed and granulated for 3D printing. Ten employees have been trained or are being trained on the collection, processing and manufacturing processes, and the resulting products created in the Gigalab are creating revenue that supports the AHFH mission. A part of the National Science Foundation’s Convergence Accelerator in Track I: Sustainable Materials for Global Challenges, this project is also funded by CSIRO, Australia’s national science agency. The international collaboration is providing the research and development foundations for community-led sustainable manufacturing and a template for transferring the approach to broader community stakeholders.

This analysis integrates the ResStock and ComStock physics-based aggregate building models with GenX power grid dispatch models to characterize natural gas demand in the Electric Reliability Council of Texas (ERCOT) during Winter Storm Uri in February 2021. To investigate how building retrofits might have impacted natural gas demand and electricity supply during the storm, the framework was applied to simulate energy demand for the baseline building stock and for three building stock cases with efficiency and heat pump retrofits. Hourly total ERCOT natural gas demand for the Baseline Case indicates that ERCOT annual coincident peak natural gas demand (for buildings, power generation and industrial uses) occurred during Winter Storm Uri at ∼ 1,200,000 MMBtu/hr, 67 % of which was attributable to building space heating. For an Efficiency Case where buildings were retrofitted with envelope improvements, total natural gas demand would have been lower during every hour of the storm. For an Electrification Case where buildings were retrofitted with heat pumps, ERCOT would have needed an additional 28.1 GW of generation capacity to serve peak electric load. For an Efficiency + Electrification Case, total natural gas demand would have been lower during every hour of the storm. This analysis finds that natural gas savings for each retrofit package could have fully served fuel demand for natural gas power generators that were derated due to fuel limitations. Furthermore, our analysis indicates that the upfront costs for the residential retrofit packages could be essentially recouped within 15 years via tax credits and energy cost savings.

Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and CO 2 emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options. • Computational grid modeling to optimize future power sector development. • Novel modeling techniques to construct a unique zonal model of 29 consolidated regions. • Simulated grid development with and without interregional transmission construction. • Simulated grid operation during extreme winter weather with and without interregional connections. • Cumulative costs and emissions are reduced in scenarios with interregional transmission. • Lost load and unserved energy during extreme winter weather are not always reduced in connected scenarios.

as sustainable carbon sources and explore the enabling potential of electrification, low-carbon hydrogen, and direct air capture. Novel process pathways and infrastructure scenarios are analyzed to highlight strategic opportunities for cross-sectoral collaboration. Our findings underscore the need for coordinated investment, policy support, and alignment with renewable energy geography to achieve a resilient, fossil-free future.

Abstract Hydrogen is not a greenhouse gas, but its interactions with other species in the atmosphere indirectly induce radiative forcing. This study evaluates the relative impacts of hydrogen emissions across 23 different net-zero scenarios from five prominent US economy-wide analyses. Hydrogen emissions associated with venting and leakages across energy supply chains are considered. The magnitude of these energy-related hydrogen emissions is estimated and compared to the remaining positive energy-related carbon dioxide and methane emissions in the 23 US net-zero scenarios. This methodology facilitates consideration of the potential magnitude of hydrogen emissions relative to the other emissions reductions and/or carbon dioxide removal strategies that would be required to balance those hydrogen emissions across a wide range of possible net-zero scenarios. Magnitudes of energy-related hydrogen and methane emissions are estimated for each scenario across a range of possible emissions rates (Low, Central, and High) and global warming potentials based on literature. The results indicate that when evaluated over a 100 year horizon, hydrogen emissions span a range of 0.02–0.15 Gt CO2e yr −1 and are lower than remaining positive carbon dioxide emissions in the Central emissions case of all 23 scenarios. In the 19 scenarios that do not constrain fossil fuels, hydrogen emissions (0.02–0.11 Gt CO2e yr −1 ) account for less than 14% of combined hydrogen, methane, and carbon dioxide emissions. The four scenarios that constrain fossil fuels have higher levels of hydrogen consumption and correspondingly higher levels of hydrogen emissions (0.10–0.15 Gt CO2e yr −1 ). These results suggest that hydrogen emissions are non-negligible in net-zero energy systems; however, the potential climate impacts associated with hydrogen emissions can be balanced through relatively small reductions in remaining positive emissions and/or increases in carbon dioxide removal. Further effort is needed to advance hydrogen emissions measurement, quantification, and mitigation strategies to maximize the potential climate benefits of hydrogen for decarbonization.

In this analysis we examine the economic costs and benefits of installing dozens of small modular reactors at recently retired coal power plants in Texas to determine the viability of a grid or “program-level” approach to nuclear power plant planning in the United States. Previous studies have indicated that utilizing stranded infrastructure assets at retired coal power plants, known as the “coal-to-nuclear” transition, could greatly reduce the amount of time and capital required to build just a single commercial nuclear plant. A discounted cash flow analysis was created using data from regional electricity markets, coal-to-nuclear studies, and other industry sources to estimate the potential value of SMR projects. The analysis includes multiple scenarios to account for varying project sizes, changes in technology learning rates, and recently implemented energy tax credits. Results indicate that increasing the rate of learning has only a minimal lowering effect on the Levelized Cost of Electricity (LCOE), as both the learning rate and LCOE quickly plateau. The most significant cost reductions were enabled by tax credits and coal-to-nuclear cost enhancements that decreased the LCOE to a competitive range of $43–52/MWh. However, our work finds that program-level benefits will likely be the result of cost sharing and risk modularization rather than direct improvement in metrics like LCOE and net present value as those are still smaller in comparison. • Economic analysis to determine viability of program-level nuclear plant planning. • SMRs can be financially attractive replacements for recently retired coal power plants. • Cost savings from reusing coal power plant assets are especially significant. • Detailed cash flow analysis includes federal energy tax credits and learning rates. • Resulting LCOE and NPV indicate competitiveness with renewable energy generation sources.

Hydrogen has emerged as a key contender for decarbonizing hard-to-abate sectors, as it has the advantage of emitting no direct carbon dioxide emissions during combustion. However, modeled indirect climate warming impacts from additional hydrogen in the atmosphere have raised questions about its role in achieving net-zero energy transitions. Here we will present findings from two complementary modeling efforts that evaluated the climate implications of hydrogen emissions, and the life cycle impacts across various applications.The first model effort evaluated emissions in 23 net-zero scenarios from prominent U.S. economy-wide studies, estimating the magnitude of hydrogen emissions relative to residual energy-related carbon dioxide and methane emissions. The model was used to evaluate the potential impact of hydrogen emissions relative to emissions reductions and carbon dioxide removal strategies needed for net-zero scenarios. Then the model was used to estimate energy-related hydrogen and methane emissions rates and global warming potentials with the best available data in literature. Modeling results indicated that hydrogen emissions ranged from 0.02–0.15 GtCO2e/year (using GWP100), with higher emissions in scenarios featuring increased hydrogen production. Despite these emissions, the calculated climate impacts represent less than 15% of combined hydrogen, methane, and carbon dioxide emissions in most scenarios. These impacts can be largely abated through reductions in residual CO2 emissions or enhanced carbon dioxide removal. More specifically, residual CO2 emissions would need to be reduced by 1-25% in scenarios allowing fossil fuels and 32-98% in scenarios restricting fossil fuels to abate the warming effect of H2 emissions.The second modeling effort involved a life cycle assessment (LCA) of electrolysis and steam methane reforming, highlighting that production methods and feedstock emissions are the dominant factors influencing life cycle emissions, rather than hydrogen leakage. Comparisons of hydrogen-based and fossil fuel-based systems revealed greenhouse gas emission reductions in steel production (800–1400 kgCO2e per tonne of steel) when hydrogen is used in direct reduction steel manufacturing (producing iron from iron ore without melting) rather than fossil fuels in blast furnaces, as well as in heavy-duty transportation (0.1–0.17 kgCO2e per tonne-km of cargo). Importantly, decarbonization potential of hydrogen varies by application, with steel production consistently showing emissions reductions, while benefits in heavy-duty transportation depend on the hydrogen production pathway.These findings underscore the importance of advancing hydrogen emissions measurement, mitigation strategies, and tailored application areas to maximize its potential climate benefits while addressing indirect warming impacts.

Hydrogen is of interest for decarbonizing hard-to-abate sectors because it does not produce carbon dioxide when combusted. However, hydrogen has indirect warming effects. Here we conducted a life cycle assessment of electrolysis and steam methane reforming to assess their emissions while considering hydrogen’s indirect warming effects. We find that the primary factors influencing life cycle climate impacts are the production method and related feedstock emissions rather than the hydrogen leakage and indirect warming potential. A comparison between fossil fuel-based and hydrogen-based steel production and heavy-duty transportation showed a reduction in emissions of 800 to more than 1400 kg carbon dioxide equivalent per tonne of steel and 0.1 to 0.17 kg carbon dioxide equivalent per tonne-km of cargo. While any hydrogen production pathway reduces greenhouse gas emissions for steel, this is not the case for heavy-duty transportation. Therefore, we recommend a sector-specific approach in prioritizing application areas for hydrogen. Production method (such as electrolysis and steam methane reforming) and related feedstock emissions are the key factors which influence hydrogen emissions from supply chains, according to life cycle assessment of hydrogen production pathways.

emissions by over 90%, with any remaining emissions to be addressed through carbon dioxide removal (CDR) solutions. Sixteen CDR strategies are evaluated by integrating technical potential, environmental, social, and governance (ESG) criteria, along with sequestration permanence. This evaluation, conducted by ENGIE's scientific council using an interdisciplinary Delphi panel methodology, proposes a "quality" measure for each technology. This measure combines ESG scores and sequestration timescales to rank and select the most promising solutions. The findings highlight the necessity for further research to understand and mitigate ESG impacts, aiming to inform both future research and current decision-making to support the effective and legitimate use of CDR strategies.

Grid reliability in Texas is an increasingly highlighted concern due to recent winter storms and heat waves threatening the reliability of the power sector. In this analysis, we compare two improvements on power grid reliability: building more firm generation capacity and connecting the Texas electricity grid to other regions, like WECC. To do so, we created a novel analytical framework that is comprised of the following four elements: (1) integration of open-source modeling tools, such as PowerGenome, pyGRETA, and GenX; (2) synthesis of multiple datasets containing information on historic weather, existing power fleet, energy technology performance factors, future projections of economics, etc.; (3) development of unique zonal profiles for load projections and weather dependent renewable resource performance; and (4) a newly consolidated network of 20 model regions representing the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, and the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous US. Our flexible modeling approach can be applied globally to other grid modeling regions, though the method is demonstrated in this work with unique zonal profiles and a 20-region network, specific to our use case of connecting ERCOT to WECC. These 20 regions were used to simulate different developmental pathways of capacity expansion and operational dispatch across the combined regions while simultaneously optimizing cost and avoiding outage events by planning for winter storm. The primary focus of our work is to analyze the trade-offs of connecting two independently functioning grids and how their future development might be impacted. This analysis considered eight primary forward-looking grid modeling scenarios in ERCOT and WECC. We also completed two sensitivity analyses on some of the critical parameters needed to define the eight primary scenarios. All analyses found that building power plants and transmission connecting ERCOT and WECC lowers total system cost and avoids future CO 2 emissions across both regions when compared to solely expanding ERCOT’s power plant capacity. Further, the analyses found that plant hardening and weatherization is important, and can be done in parallel with transmission development for maximum benefit. • Computational grid modeling to optimize future power sector development. • Novel modeling techniques to construct a zonal model of 20 consolidated regions. • Simulated development with and without interregional transmission construction. • Pathways analyzed with normal and winter storm weather conditions. • Cumulative costs and emissions reduced in scenarios with interregional transmission.

Due to its ability to reduce emissions in the hard-to-abate sectors, hydrogen is expected to play a significant role in future energy systems . This study modifies a sector-coupled dynamic modeling framework for electricity and hydrogen by including policy constraints, carbon prices, and possible hydrogen pathways and applies it to Texas in 2050. The impact of financial policies, including the US clean hydrogen production tax credit, on required infrastructure and costs are explored. Due to low natural gas prices, financial levers are necessary to promote low-carbon hydrogen production as the optimized solution. The Levelized Costs of Hydrogen are found to be $1.50/kg in the base case (primarily via steam methane reformation production) and lie between $2.10 - 3.10/kg when production is via renewable electrolysis. The supporting infrastructure required to supply those volumes of renewable hydrogen is immense. The hydrogen tax credit was found to be enough to drive production via electrolysis.

This paper examines the emissions tradeoffs of additive manufacturing (i.e., 3D printing) using plastic waste in fused granular fabrication (FGF) versus traditional fused filament fabrication (FFF) and injection molding (IM). A ‘cradle-to-gate’ life cycle assessment (LCA) was utilized to compare these methods, built in OpenLCA v1.11.0 with the Ecoinvent v3.9.1 database. Different scenarios were used to evaluate the impacts of varying transportation and material inputs, highlighting critical emission contributors in manufacturing plastic goods. FGF with waste plastic can significantly reduce climate impact by 82.1% relative to FFF and 70.6% relative to IM for a specified unit product. Even with varied transportation and materials, FGF is a lower CO2-equivalent emitting method. Utilizing FGF with waste plastic as a manufacturing method could reduce emissions and divert plastic from landfills and the environment, thereby contributing to a circular plastic economy.

There is recognition among power and water utilities that the frequency and magnitude of high consequence and low probability events could increase as a result of climate change. The interconnected nature of energy-water systems raises the possibility of cascading failures, increasing complexity and risks. Resilience and long-term planning are important ways of weathering the effects of climate change. First, to understand more about resilience, we reviewed existing literature on resilience definitions, metrics, and modeling, focusing on integrated water-power systems. Second, to understand how resilience and planning are being applied in practice, we interviewed utilities and organized, curated, and synthesized the interview data to arrive at several key findings, which are presented here. We found that there is not a consistent definition for resilience, yet it is something that utilities regularly plan for, often with different names and varying methods/measures. However, there is a tangible shift in the industry towards defining and determining measurable resilience metrics. While the exact metrics are a work in progress, utilities are taking steps forward by (1) putting people and culture at the center of resilience, (2) recognizing their own interdependencies, and (3) pursuing better cross-sector collaboration.

Distributed energy resources (DER) as non-wires alternatives, regardless of owner, have the potential to reduce system operating costs and delay system upgrades. However, it is difficult to determine the appropriate economic signal to incentivize DER investors to install capacity that will benefit both the DER investors and the system operator. To determine this co-optimal price signal, we present a bilevel optimization framework that determines the least cost solution to distribution system over-loads. A key output of the framework is a spatiotemporal price signal to DER owners that simultaneously guarantees the DER owners’ required rate of return and minimizes the system operation costs. The framework is demonstrated with a case by which the system operator considers utility owned battery energy storage systems, traditional system upgrades, and energy purchased from DER owners. The results show that utility owned storage combined with DER for non-wires alternatives can result in lower operating costs with similar upfront costs to traditional system upgrades by avoiding or delaying upgrades. In a use-case example we show that when valuing DER the operating costs over 20 years can be reduced by over 40% resulting in a $3M net present value. • Valuing DER for NWA in grid planning can result in reduced distribution grid operating costs. • Novel framework is proposed to account for both DER owner and grid operator requirements. • A co-optimal price signal is determined that maximizes the social welfare of DER. • Bilevel optimization framework leverages recent advancement in linearization of bilinear terms with shadow prices.

This analysis investigates energy performance of the residential and commercial building sectors in the Electric Reliability Council of Texas (ERCOT) during Winter Storm Uri. ERCOT electricity demand was modeled for the ERCOT baseline building stock as well as for the baseline building stock retrofitted with an efficiency upgrade package, an electrification upgrade package, and an efficiency + electrification upgrade package. The electrification scenario that retrofitted buildings with air-source heat pumps (ASHPs) would have lowered ERCOT daily peak electricity demand relative to the baseline scenario for every day of the year, except during the week of Winter Storm Uri. As the mean outdoor temperature dropped below -5°C (23°F), diminishing ASHP efficiency would have resulted in electrification scenario demand exceeding the two distinct baseline scenario daily demand peaks on February 15th and 16th (87.3 GW and 88.7 GW) to hit 111.8 GW and 117.5 GW. The efficiency package would have lowered daily peak demand on these days to 67.0 GW and 68.0 GW. The efficiency + electrification package would have lowered peak demand on these days to 81.5 GW and 85.6 GW. When electricity shortfall profiles were produced by comparing modeled electricity demand to actual ERCOT electricity generation during the storm, the results indicate that the electrification scenario electricity shortfall (1741 GWh) would have been larger than for the baseline scenario (1225 GWh) and the electricity shortfalls for the efficiency scenario (347 GWh) and efficiency + electrification scenario (704 GWh) would have been lower than the baseline. The efficiency, electrification, and efficiency + electrification scenarios would all have lowered summer daily peak demand due to improvements in building cooling efficiency and would have lowered annual electricity consumption by 5.9%, 6.8%, and 11.9%, respectively.

Abstract The massive deployment of clean energy technologies plays a vital role in the strategy to attain carbon neutrality by 2050 and allow subsequent negative CO 2 emissions in order to achieve our climate goals. An emerging challenge, known as ‘From Emissions to Resources,’ highlights the significant increase in demand for critical raw materials (CRMs) in clean energy technologies. Despite the presence of ample geological reserves, ensuring sustainable access to these materials is crucial for the successful transition to clean energy, taking into account the environmental and social impacts. The commentary centers on four renewable energy technologies namely solar photovoltaics, wind turbines, Li-ion batteries, and water electrolysers. Four pathways for mitigation are quantitatively examined to assess their potential in reducing the vulnerability of the CRM supply chain for these four clean energy technologies: (i) Enhancing material efficiency, (ii) employing substitutivity strategies, (iii) exploring recycling prospects, and (iv) promoting relocalisation initiatives. It is important to note that no single mitigation lever can completely eliminate the risk of CRM supply, rather the accelerated adoption of all four levers is necessary to minimize the CRM supply risk to its absolute minimum. Hence, the study underscores the significance of increased research, innovation, and regulatory initiatives, along with raising social awareness, in effectively addressing the challenges faced by the CRM supply chain and contributing to a sustainable energy transition.

This project presented many

We analyzed data for the Electric Reliability Council of Texas (ERCOT) to assess shoulder seasons -- that is, the 45 days of lowest total energy use and peak demand in the spring and fall typically used for power plant maintenance -- and whether their occurrence has changed over time. Over the period 1996--2022, the shoulder seasons never started earlier than late March nor later than mid-October, corresponding well with the minimum of total degree days. In the temperature record 1959--2022, the minimum in degree days in the spring moved earlier, from early March to early February, and in the fall moved later, from early to mid-November. Warming temperatures might cause these minima in degree days to merge into a single annual minimum in December or January by the mid-2040s, a time when there is a non-trivial risk of 1-day record energy use and peak demand from winter storms.

Abstract While Texas political leaders openly dismiss and mock the risks of climate change and suspiciously eye policymakers in other states or countries who seek to reduce emissions, Texas industry, consumers, and cities are decarbonizing and doing so faster than those same countries. A recent study exploted multiple pathways for getting emissions down even farther.

Reducing methane emissions from solid waste is already technically possible.

A growing hydrogen economy requires new hydrogen distribution infrastructure to link geographically distributed hubs of supply and demand. The Hydrogen Optimization with Deployment of Infrastructure (HOwDI) Model helps meet this requirement. The model is a spatially resolved optimization framework that determines location-specific hydrogen production and distribution infrastructure to cost-optimally meet a specified location-based demand. While these results are useful in understanding hydrogen infrastructure development, there is uncertainty in some costs that the model uses for inputs. Thus, the project team took the modeling effort a step further and developed a Monte Carlo methodology to help manage uncertainties. Seven scenarios were run using existing infrastructure and new demand in Texas exploring different policy and tax approaches. The inclusion of tax credits increased the percentage of runs that could deliver hydrogen at <$4/kg from 31% to 77% and decreased the average dispensed cost from $4.35/kg to $3.55/kg. However, even with tax credits there are still some runs where unabated SMR is deployed to meet new demand as the low-carbon production options are not competitive. Every scenario, except for the zero-carbon scenario (without tax credits), resulted in at least 20% of the runs meeting the $4/kg dispensed fuel cost target. This indicates that multiple pathways exist to deliver $4/kg hydrogen.

This analysis quantitatively compares the evolution in summer and winter peak demands in the Electric Reliability Council of Texas (ERCOT) service area from 1997 through 2021. Weather data for the days in which peak demand occurred were also compiled to investigate the relationship between peak heating and cooling loads and ambient temperature. This relationship was then applied along with population projections and a climate scenario with medium to high radiative forcing to create winter and summer peak demand growth scenarios for 2025 through 2050. This analysis informs resource planners about how ERCOT peak demand might change in the future and provides new insight into how electric load growth and non-flexible electrified heating demand could have contributed to the February 2021 ERCOT blackouts. We found that historically, summer peak demand growth has been generally stable and approximately linear with time. The stable summer peak load is likely a consequence of fairly constant temperatures observed on summer peak demand days. Conversely, the winter peak demand growth has been less consistent, varying much more around the broader trend. This phenomenon is likely a consequence of high residential electrical heating load on winter peak demand days, which saw temperatures that varied widely from the mean value. Future peak winter and summer electricity demand scenarios indicated that while average temperatures on winter peak demand days will remain fairly constant, they will be more erratic than temperatures on summer peak demand days. As a result, winter peak demand will remain more erratic and will sporadically surpass summer peak demand between 2025 and 2050. Thus, resource planners in ERCOT should place less certainty on winter peak demand projections and an increased level of winter preparedness on both the supply and demand sectors appears warranted.

We analyzed data for the Electric Reliability Council of Texas (ERCOT) to assess shoulder seasons -- that is, the 45 days of lowest total energy use and peak demand in the spring and fall typically used for power plant maintenance -- and whether their occurrence has changed over time. Over the period 1996--2022, the shoulder seasons never started earlier than late March nor later than mid-October, corresponding well with the minimum of total degree days. In the temperature record 1959--2022, the minimum in degree days in the spring moved earlier, from early March to early February, and in the fall moved later, from early to mid-November. Warming temperatures might cause these minima in degree days to merge into a single annual minimum in December or January by the mid-2040s, a time when there is a non-trivial risk of 1-day record energy use and peak demand from winter storms.

A method, system and computer program product for optimally placing photovoltaic arrays to maximize a value of energy production. Incident solar radiation for various placements of the photovoltaic arrays accommodating different azimuths and tilts is calculated. Alternating current solar photovoltaic electricity energy and power production is then estimated from the calculated solar radiation on a plane and weather data. Furthermore, a value of solar photovoltaic electricity energy and power produced by the photovoltaic arrays for the various placements is calculating using the estimated alternating current solar photovoltaic electricity production. A placement out of the various placements for the photovoltaic arrays is then selected corresponding to a highest value of the solar photovoltaic electricity produced by the photovoltaic arrays. In this manner, the appropriate placement for the photovoltaic arrays is determined that maximizes the value of energy production (where “value” may correspond to an economic value or a non-economic value).