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1. Quantifying the electricity, CO ₂ emissions, and economic tradeoffs of precooling strategies for a single-family home in Southern California*

   https://doi.org/10.1088/2634-4505/ac5d60  

   Mayes, Stepp; Sanders, Kelly (May 2022, Environmental Research: Infrastructure and Sustainability)

   Abstract High fractions of variable renewable electricity generation have challenged grid management within the balancing authority overseen by the California’s Independent System Operator (CAISO). In the early evening, solar resources tend to diminish as the system approaches peak demand, putting pressure on fast-responding, emissions-intensive natural gas generators. While residential precooling, a strategy intended to shift the timing of air-conditioning usage from peak-demand periods to cheaper off-peak periods, has been touted in the literature as being effective for reducing peak electricity usage and costs, we explore its impact on CO₂emissions in regional grids like CAISO that have large disparities in their daytime versus nighttime emissions intensities. Here we use EnergyPlus to simulate precooling in a typical U.S. single-family home in California climate zone 9 to quantify the impact of precooling on peak electricity usage, CO₂emissions, and residential utility costs. We find that replacing a constant-setpoint cooling schedule with a precooling schedule can reduce peak period electricity consumption by 57% and residential electricity costs by nearly 13%, while also reducing CO₂emissions by 3.5%. These results suggest the traditional benefits of precooling can be achieved with an additional benefit of reducing CO₂emissions in grids with high daytime renewable energy penetrations. 

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2. Residential precooling on a high-solar grid: impacts on CO ₂ emissions, peak period demand, and electricity costs across California

   https://doi.org/10.1088/2753-3751/acfa91  

   Mayes, Stepp; Zhang, Tong; Sanders, Kelly T (October 2023, Environmental Research: Energy)

   Abstract As regional grids increase penetrations of variable renewable electricity (VRE) sources, demand-side management (DSM) presents an opportunity to reduce electricity-related emissions by shifting consumption patterns in a way that leverages the large diurnal fluctuations in the emissions intensity of the electricity fleet. Here we explore residential precooling, a type of DSM designed to shift the timing of air-conditioning (AC) loads from high-demand periods to periods earlier in the day, as a strategy to reduce peak period demand, CO₂emissions, and residential electricity costs in the grid operated by the California Independent System Operator (CAISO). CAISO provides an interesting case study because it generally has high solar generation during the day that is replaced by fast-ramping natural gas generators when it drops off suddenly in the early evening. Hence, CAISO moves from a fleet of generators that are primarily clean and cheap to a generation fleet that is disproportionately emissions-intensive and expensive over a short period of time, creating an attractive opportunity for precooling. We use EnergyPlus to simulate 480 distinct precooling schedules for four single-family homes across California’s 16 building climate zones. We find that precooling a house during summer months in the climate zone characterizing Downtown Los Angeles can reduce peak period electricity consumption by 1–4 kWh d⁻¹and cooling-related CO₂emissions by as much as 0.3 kg CO₂ d⁻¹depending on single-family home design. We report results across climate zone and single-family home design and show that precooling can be used to achieve simultaneous reductions in emissions, residential electricity costs, and peak period electricity consumption for a variety of single-family homes and locations across California. 

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3. Discriminant effects of consumer electronics use-phase attributes on household energy prediction

   https://doi.org/j.enpol.2018.03.059  

   Raihanian Mashhadi, Ardeshir; Behdad, Sara (July 2018, Energy policy)

   The aim of this study is to provide a better understanding of the heterogeneities in user-product relationships and their consequences regarding the household energy predictions. Several supervised and unsupervised machine learning algorithms have been applied to a comprehensive data set of residential energy consumptions collected by the US Energy Information Association. The results of the analyses reveal that, while the heterogeneities in the use-phase of consumer electronics could skew their environmental assessment results, they do not possess the same discriminant influences on the household electricity consumption compared to certain socio-demographics or usage of home appliances. Various cross-comparisons among product features and use-phase behaviors have been made and the most important predictors of the residential electricity consumption based on the data have been introduced. Product-level and user-level discussions on the findings have also been provided. 

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4. The Impact of Urban Heat Island on Calibrated Building Energy Model Predictions

   Jahani, Elham; Vanage, Soham; Cetin, Kristen (January 2020, ASCE Construction Research Congress)

   Among various elements of urban infrastructure, there is significant opportunity to improve existing buildings’ sustainability, considering that approximately 40% of the total primary energy consumption and 72% of electricity consumption in United States is consumed by the building sector. Many different efforts focus on reducing the energy consumption of residential buildings. Data-validated building energy modeling methods serve the role of supporting this effort, by enabling the identification of the potential savings associated with different potential retrofit strategies. However there are many uncertainties that can impact the accuracy of energy model results, one of which is the weather input data. Measured weather data inputs located at each building can help address this concern, however, weather station data collection for each building is also costly and typically not feasible. Some weather station data is already collected, however, these are generally located at airports rather than near buildings, and thus do not capture local, spatially-varying weather conditions which are documented to occur, particularly in urban areas. In this study we address the impact of spatial temperature differences on residential building energy use. An energy model was developed in EnergyPlus for a residential building located in Mueller neighborhood of Austin, TX, and was validated using actual hourly measured electricity consumption. Using the validated model, the impact of measured spatial temperature differences on building energy consumption were investigated using multiple weather stations located throughout the urban area with different urban fractions. The results indicate that energy consumption of a residential building in a city with a 10% higher urban fraction would increase by approximately 10%. This variation in energy consumption is likely due to the impact of UHI effects occurring in urban areas with high densities. 

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5. Powering racial capitalism: Electricity, rate-making, and the uneven energy geographies of Atlanta

   https://doi.org/10.1177/25148486211016736  

   Luke, Nikki (January 2021, Environment and Planning E: Nature and Space)

   In this paper, I bring together scholarship on racial capitalism and critical energy studies to investigate how electrification contributes to racialized uneven development. I work toward a theory of racialized electricity capital as a state-supported circuit of accumulation through corporate provision of electricity, which is basic need essential to everyday life. I develop a case study of the electrification of Atlanta, Georgia to examine the historical–geographical formation of the relationship between the city’s electric utility, Georgia Power, and the state agency that regulates the Company, the Georgia Public Service Commission. I ask how regulation functioned simultaneously to expand and differentiate electricity consumption across Atlanta and in so doing reinforce a racialized labor hierarchy and unequal access to affordable electricity. This case study emphasizes the importance of analyzing the central role of the state in allowing and perpetrating systems of energy provision that create racialized and gendered poverty. Drawing from the most recent hearings regulating electricity rates before the Commission in 2019, I bring to the fore the work of energy equity activists leading a campaign to Fight the Hike who enact demands for racial justice and a democratic energy system. 

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