Future energy scenarios with distributed technology options for residential city blocks in three climate regions of the United States

Yuan, Shengxi; Stainsby, Wendell; Li, Mo; Xu, Kewei; Waite, Michael; Zimmerle, Daniel; Feiock, Richard C.; Ramaswami, A.; Modi, Vijay

doi:10.1016/j.apenergy.2019.01.048

Cited by 11 publications

(3 citation statements)

References 21 publications

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“…To quantify EUI in a more granular way to address seasonality and account for thermal comfort, we separated EUI for heating/cooling homes (temperature sensitive) from the rest (non-temperature sensitive). We also evaluated the relationship of monthly EUI versus ambient temperature (40) to delineate the apparent "turning point temperature"-that is, the temperature below which homes turn on gas heat (SI Appendix, Fig. S4).…”

Section: Resultsmentioning

confidence: 99%

Measuring social equity in urban energy use and interventions using fine-scale data

Tong

Ramaswami

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating–cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non-White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities.

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Section: Resultsmentioning

confidence: 99%

Measuring social equity in urban energy use and interventions using fine-scale data

Tong

Ramaswami

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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“…Different climate variables, such as merely using the current climate's characteristics [30] or choosing a warm past year to represent climate warming [31], have been used to determine future electricity demand in the residential sector. However, parametric (based on the relationship between demand and temperature) [32], energy balance (based on heat gains and losses of buildings using building simulation tools) [33], and degree day (based on relating temperature with the heating/cooling requirements) [34] models are the most common methods used to determine the future residential energy demand.…”

Section: Introductionmentioning

confidence: 99%

Cooling Degree Models and Future Energy Demand in the Residential Sector. A Seven-Country Case Study

et al. 2021

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The intensity and duration of hot weather and the number of extreme weather events, such as heatwaves, are increasing, leading to a growing need for space cooling energy demand. Together with the building stock’s low energy performance, this phenomenon may also increase households’ energy consumption. On the other hand, the low level of ownership of cooling equipment can cause low energy consumption, leading to a lack of indoor thermal comfort and several health-related problems, yet increasing the risk of energy poverty in summer. Understanding future temperature variations and the associated impacts on building cooling demand will allow mitigating future issues related to a warmer climate. In this respect, this paper analyses the effects of change in temperatures in the residential sector cooling demand in 2050 for a case study of nineteen cities across seven countries: Cyprus, Finland, Greece, Israel, Portugal, Slovakia, and Spain, by estimating cooling degree days and hours (CDD and CDH). CDD and CDH are calculated using both fixed and adaptive thermal comfort temperature thresholds for 2020 and 2050, understanding their strengths and weaknesses to assess the effects of warmer temperatures. Results suggest a noticeable average increase in CDD and CDH values, up to double, by using both thresholds for 2050, with a particular interest in northern countries where structural modifications in the building stock and occupants’ behavior should be anticipated. Furthermore, the use of the adaptive thermal comfort threshold shows that the projected temperature increases for 2050 might affect people’s capability to adapt their comfort band (i.e., indoor habitability) as temperatures would be higher than the maximum admissible values for people’s comfort and health.

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“…Several studies used multiple methods to estimate future residential heating and cooling energy demand in buildings. While some authors choose simple approaches such as using current climate, discarding climate variability [12] or choosing a warm past year to represent a warming climate [13], others opt to use climate models using several datasets, namely global climate simulation models (GCMs) [11,[14][15][16][17][18][19]. The most common methods used to determine residential demand in the future use parametric energy balance and degree-day methods.…”

Section: Introductionmentioning

confidence: 99%

Heating and Cooling Degree-Days Climate Change Projections for Portugal

2021

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Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II

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Future energy scenarios with distributed technology options for residential city blocks in three climate regions of the United States

Cited by 11 publications

References 21 publications

Measuring social equity in urban energy use and interventions using fine-scale data

Measuring social equity in urban energy use and interventions using fine-scale data

Cooling Degree Models and Future Energy Demand in the Residential Sector. A Seven-Country Case Study

Heating and Cooling Degree-Days Climate Change Projections for Portugal

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