Overcoming barriers and uncertainties in the adoption of residential solar PV
Not Available
Rai, Varun (ORCID:0000000240809299)↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Peak Reduction Using Mode Adjustment of Heat Pump Water Heaters in a Residential Neighborhood
Building electrification is putting pressure on distribution grid worldwide. Peak reduction is an important concern that can help reduce the growing stress and allow to defer investments in new capacity. Water heaters represent a convenient way of reducing peak because they are less dependent on weather, and their storage volume allows for asynchronous water heating and hot water use. Previous empirical studies investigated the ability of water heaters to reduce peak through the adjustment of the temperature setpoint. However, not all equipment vendors offer this option. This study aims at understanding the feasibility of peak reduction with an alternative configuration available in the market - by adjusting the device mode rather than temperature setpoint. The peak reduction methodology is tested in an occupied 46-townhome neighborhood located in Atlanta, GA. We find that peak shifting is possible with the adjustable mode approach, with the change in the peak load by 30-60%.
demand response↗
High-Resolution Residential Feeder Load Characterization and Variability Modelling.
Abstract not provided.
Pohl, Andrew Phillip↗
Electrical Power System Support-Function Capabilities of Residential and Small Commercial Inverters.
Abstract not provided.
Gonzalez, Sigifredo↗
Suitable low Global Warming Potential (GWP) refrigerants for two-speed Heat Pumps for residential applications based on speed Heat Pumps for residential applications based on simulated performance simulated performance
Cold climate Heat Pumps (CCHPs) using single-speed compressors in tandem have been successfully built and tested to reach its performance metrics with outdoor temperatures as low as -25°C. CCHPs must be designed to alleviate the problems of too high discharge temperatures, low suction pressure and high-pressure ratio at low ambient conditions and insufficient heating capacity relative to the heating capacity at 8.3°C. In this paper we recognize those concerns. Low-GWP refrigerants are screened based on the shape of their T-S saturation boundary. Simulations of the performance of low-GWP refrigerants (R32, R454B, R466A, and R452B) relative to R410A is done using the DOE/ORNL Heat Pump Design Model at the component level. Systemic inefficiency, the root cause of lost work, is addressed by component-level exergy analysis to refine design options. CCHPs using low-GWP refrigerants addresses issues of reducing energy consumption, lowering carbon footprint, and enabling environmentally sustainability. The CCHP was designed to meet a HSPF > 11.0 and SEER > 15.0 having adequate heat pump heating capacity down to -25°C. It is estimated that at least 2.6 million U.S homes using electric furnaces and heat pumps in cold or very old climates with an annual energy consumption of 0.17EJ would benefit by CCHPs.
Ally, Moonis↗
Development of Residential Prototype Building Models and Analysis System for Large-Scale Energy Efficiency Studies Using EnergyPlus
ABSTRACT: Recent advances in residential building energy efficiency and codes have resulted in increased interest in detailed residential building energy models using the latest energy simulation software. One of the challenges of developing residential building models to characterize new residential building stock is to allow for flexibility to address variability in house features like geometry, configuration, HVAC systems etc. Researchers solved this problem in a novel way by creating a simulation structure capable of creating fully-functional EnergyPlus batch runs using a completely scalable residential EnergyPlus template system. This system was used to create a set of thirty-two residential prototype building models covering single- and multifamily buildings, four common foundation types and four common heating system types found in the United States (US). A weighting scheme with detailed state-wise and national weighting factors was designed to supplement the residential prototype models. The complete set is designed to represent a majority of new residential construction stock. The entire structure consists of a system of utility programs developed around the core EnergyPlus simulation engine to automate the creation and management of large-scale simulation studies with minimal human effort. The simulation structure and the residential prototype building models have been used for numerous large-scale studies, one of which is briefly discussed in this paper.
Mendon, Vrushali V.↗
Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements
Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Cost-Reduction Roadmap for Residential Solar Photovoltaics (PV), 2017-2030
The installed cost of solar photovoltaics (PV) has fallen rapidly in recent years and is expected to continue declining in the future. In this report, we focus on the potential for continued PV cost reductions in the residential market. From 2010 to 2017, the levelized cost of energy (LCOE) for residential PV declined from 52 cents per kilowatt-hour (cents/kWh) to 16 cents/kWh (Fu et al. 2017). The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) recently set new LCOE targets for 2030, including a target of 5 cents/kWh for residential PV. We present a roadmap for achieving the SETO 2030 residential PV target. Because the 2030 target likely will not be achieved under business-as-usual trends (NREL 2017), we examine two key market segments that demonstrate significant opportunities for cost savings and market growth: installing PV at the time of roof replacement and installing PV as part of the new home construction process. Within both market segments, we identify four key cost-reduction opportunities: market maturation, business model integration, product innovation, and economies of scale. To assess the potential impact of these cost reductions, we compare modeled residential PV system prices in 2030 to the National Renewable Energy Laboratory's (NREL's) quarter one 2017 (Q1 2017) residential PV system price benchmark (Fu et al. 2017). We use a bottom-up accounting framework to model all component and project-development costs incurred when installing a PV system. The result is a granular accounting for 11 direct and indirect costs associated with installing a residential PV system in 2030. All four modeled pathways demonstrate significant installed-system price savings over the Q1 2017 benchmark, with the visionary pathways yielding the greatest price benefits. The largest modeled cost savings are in the supply chain, sales and marketing, overhead, and installation labor cost categories. When we translate these installed-system costs into LCOE, we find that the less-aggressive pathways achieve significant cost reductions, but may not achieve the 2030 LCOE target. On the other hand, both visionary pathways could get very close to (for roof replacement) or achieve (for new construction) the 2030 target. Our analysis has two key implications. First, because installed-system soft cost reductions account for about 65 percent of the LCOE reductions in 2030 for both visionary pathways, residential PV stakeholders may need to emphasize these soft cost reductions to achieve the 2030 target. Second, capturing these savings will likely require considerable innovation in the technologies and business practices employed by the PV industry.
14 SOLAR ENERGY↗
VOLTTRON-Based System for Providing Ancillary Services with Residential Building Loads
Ancillary services entail controlled modulation of building equipment to maintain a stable balance of generation and load in the power system. Ancillary services include frequency regulation and contingency reserves, whose acting time ranges from several seconds to several minutes. Many pilot studies have been implemented to use industrial loads to provide ancillary services, and some have explored services from commercial building loads or electric vehicle charging loads. Residential loads, such as space conditioning and water heating, represent a largely untapped resource for providing ancillary services. The residential building sector accounts for a significant fraction of the total electricity use in the United States. Many loads in residential buildings are flexible and could potentially be curtailed or shifted at the request of the grid. However, there are many barriers that prevent residential loads being widely used for ancillary services. One of the major technical barriers is the lack of communication capabilities between end-use devices and the grid. End-use devices need to be able to receive the automatic generation control (AGC) signal from the grid operator and supply certain types of telemetry to verify response. With the advance of consumer electronics, communication-enabled, or 'connected,' residential equipment has emerged to overcome the communication barrier. However, these end-use devices have introduced a new interoperability challenge due to the existence of numerous standards and communication protocols among different end devices. In this paper, we present a VOLTTRON-based system that overcomes these technical challenges and provides ancillary services with residential loads. VOLTTRON is an open-source control and sensing platform for building energy management, facilitating interoperability solutions for end devices. We have developed drivers to communicate and control different types of end devices through standard-based interfaces, manufacturer-provided application programming interfaces, and proprietary communication interfaces. We document the ability to manage nine appliances, using four different standards or proprietary communication methods. A hardware-in-the-loop test was performed in a laboratory environment where the loads of a laboratory home and a large number of simulated homes are controlled by an aggregator. Upon receipt of an AGC signal, the VOLTTRON home energy management system (HEMS) of the laboratory home adjusts the end-device controls based on the comfort criteria set by the end users and sends telemetry to the aggregator to verify response. The aggregator then sends the AGC signal to other simulated homes in attempts to match the utility request as closely as possible. Frequency regulation is generally considered a higher value service than other ancillary services but it is also more challenging due to the constraint of short response time. A frequency regulation use case has been implemented with the regulation signals sent every 10 seconds. Experimental results indicate that the VOLTTRON-controlled residential loads are able to be controlled with sufficient fidelity to enable an aggregator to meet frequency regulation requirements. Future work is warranted, such as understanding the impact of this type of control on equipment life, and market requirements needed to open up residential loads to ancillary service aggregators.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Exploring the potential of non-residential solar to tackle energy injustice
Despite the observed disparities in US residential solar deployment, there is limited insight into whether these disparities exist for the non-residential sector. Here we use DeepSolar, a comprehensive photovoltaic database constructed with satellite imagery, to assess solar deployment equity based on the US Justice40’s disadvantaged community measure. We find that disadvantaged communities have less non-residential solar (–38%), but this disparity is notably higher for residential solar (–67%). Across-state variations are consistent for residential solar (–81% to –49%) yet highly heterogeneous for non-residential solar (–66% to +34%). Using scenarios to explore the potential for microgrids powered by solar on building rooftops larger than 1,000 square metres, we estimate that 63% of disadvantaged communities could meet at least 20% of annual residential electricity demand. Furthermore, our research argues for a new focus on non-residential solar as a way to strengthen resilience and accelerate local deployment of clean energy resources to promote energy justice.
14 SOLAR ENERGY↗
Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage
A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.
14 SOLAR ENERGY↗
What is the Controllable Electrical Demand from Non-Residential Electric Vehicle Supply Equipment in the San Diego Region?
The EVSE deployed by The EV Project included both residential and non-residential units. Approximately 4,000 non-residential AC Level 2 (ACL2) EVSE were installed in workplace environments, fleet applications and publicly accessible locations near retail centers, parking lots, and similar locations. The power required to recharge a plug-in electric vehicle (PEV) can be a significant additional electrical load to electric grid but may also provide a controllable resource for mitigating grid overload issues. Electric utilities seek ways to reduce their generating costs by controlling the maximum (peak) load on their system, their generating resources, and frequency and voltage control on the system. This management may be achieved indirectly, through rates that incentivize their customers (including PEV owners) to manage the charging of their vehicles, or may take the form of direct utility control of non-residential EVSE. What insight can The EV Project data provide related to the magnitude of this impact and the potential controllable demand? The paper What is the Controllable Electrical Demand from Residential EVSE in the San Diego Region?1 addressed this question for residential EVSE. This paper quantifies the total controllable electrical load imposed on the electric grid by non-residential PEV charging in the San Diego region of The EV Project.
33 ADVANCED PROPULSION SYSTEMS↗
Effects of incomplete residential histories on studies of environmental exposure with application to childhood leukaemia and background radiation
Highlights: • Residential exposures are most important for many environmental carcinogens. • Direct measurement in all occupied homes is the gold standard but may be impractical. • About half of cases of childhood cancer have not moved between birth and diagnosis. • Most house movements are short-range; exposures in successive houses are correlated. • Analyses using exposure estimation from a single address are informative. When evaluating environmental exposures, residential exposures are often most relevant. In most countries, it is impossible to establish full residential histories. In recent publications, childhood leukaemia and background radiation have been studied with and without full residential histories. This paper investigates the consequences of lacking such full data. Data from a nationwide Finnish Case-Control study of Childhood Leukaemia and gamma rays were analysed. This included 1093 children diagnosed with leukaemia in Finland in 1990–2011. Each case was matched by gender and year of birth to three controls. Full residential histories were available. The dose estimates were based on outdoor background radiation measurements. The indoor dose rates were obtained with a dwelling type specific conversion coefficient and the individual time-weighted mean red bone marrow dose rates were calculated using age-specific indoor occupancy and the age and gender of the child. Radiation from Chernobyl fallout was included and a 2-year latency period assumed. The median separation between successive dwellings was 3.4 km and median difference in red bone marrow dose 2.9 nSv/h. The Pearson correlation between the indoor red bone marrow dose rates of successive dwellings was 0.62 (95% CI 0.60, 0.64). The odds ratio for a 10 nSv/h increase in dose rate with full residential histories was 1.01 (95% CI 0.97, 1.05). Similar odds ratios were calculated with dose rates based on only the first dwelling (1.02, 95% CI 0.99, 1.05) and only the last dwelling (1.00, 95% CI 0.98, 1.03) and for subjects who had lived only in a single dwelling (1.05, 95% CI 0.98, 1.10). Knowledge of full residential histories would always be the option of choice. However, due to the strong correlation between exposure estimates in successive dwellings and the uncertainty about the most relevant exposure period, estimation of overall exposure level from a single address is also informative. Error in dose estimation is likely to cause some degree of classical measurement error resulting in bias towards the null.
63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
Valuing Residential Energy Efficiency: Analysis for a Prototypical Southeastern Utility [Slides]
The increasing amount of variable renewable energy resources and shifts towards more end-use and vehicle electrification suggests profound changes to power system planning and operation. Specifically, renewable energy is expected to shift net peak demand from late afternoon to early evening and end-use electrification may significantly increase winter peak demand. Residential energy efficiency is likely to align well with these shifts as it tends to produce savings in the early evening (e.g., from lighting measures) and coincident with heating loads (e.g., from envelope and space conditioning measures). Despite the opportunity to decrease system costs and emissions, residential energy efficiency is often limited by static valuation methods and its economic potential is considerably less than its technical potential. Using hourly residential energy efficiency characterizations, utility program cost data, and a capacity expansion model, we estimate the benefits of residential energy efficiency for a prototypical, summer-peaking utility in the Southeastern region. We first establish the cost-effective residential energy efficiency portfolio through “competition” with supply-side resources in a forward-looking capacity expansion model. Importantly, we then evaluate several scenarios intended to drive an increasing amount of cost-effective residential energy efficiency through measure cost reductions, increased customer adoption, policy goals (e.g., carbon price), and delivery of an integrated package of measures. The results quantify total system cost and emissions reductions, fossil-fuel plant retirements, and peak demand reductions. Results suggest the design and prioritization of policies and programs to access the untapped amount of cost-effective residential energy efficiency.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
High Performance Residential Housing Units at U.S. Coast Guard Base Kodiak: Preprint
The United States Coast Guard (USCG) constructs residential housing throughout the country using a basic template that must meet the minimum Leadership in Energy and Environmental Design (LEED) Silver criteria or better for the units. In Kodiak, Alaska, USCG is procuring between 24 and 100 residential multi-family housing units. Priorities for the Kodiak project were to reduce overall energyconsumption by at least 20% over existing units, improve envelope construction, and evaluate space heating options. USCG is challenged with maintaining similar existing units that have complicated residential diesel boilers. Additionally, fuel and material costs are high in Kodiak. While USCG has worked to optimize the performance of the housing units with principles of improved buildingenvelope, the engineers realize there are still opportunities for improvement, especially within the heating, ventilation, and air conditioning (HVAC) system and different envelope measures. USCG staff also desires to balance higher upfront project costs for significantly reduced life-cycle costs of the residential units that have an expected lifetime of 50 or more years. To answer thesequestions, this analysis used the residential modeling tool BEoptE+ to examine potential energy- saving opportunities for the climate. The results suggest criteria for achieving optimized housing performance at the lowest cost. USCG will integrate the criteria into their procurement process. To achieve greater than 50% energy savings, USCG will need to specify full 2x 6 wood stud R-21 insulationwith two 2 inches of exterior foam, R-38 ceiling insulation or even wall insulation in the crawl space, and R-49 fiberglass batts in a the vented attic. The air barrier should be improved to ensure a tight envelope with minimal infiltration to the goal of 2.0 ACH50. With the implementation of an air source heat pump for space heating requirements, the combination of HVAC and envelope savings inthe residential unit can save up to 58% in source energy over existing residential units.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States
Note: This dataset has been superseded by the dataset found at "End-Use Load Profiles for the U.S. Building Stock" (submission 4520; linked in the submission resources), which is a comprehensive and validated representation of hourly load profiles in the U.S. commercial and residential building stock. The End-Use Load Profiles project website includes links to data viewers for this new dataset. For documentation of dataset validation, model calibration, and uncertainty quantification, see Wilson et al. (2022). These data were first created around 2012 as a byproduct of various analyses of solar photovoltaics and solar water heating (see references below for are two examples). This dataset contains several errors and limitations. It is recommended that users of this dataset transition to the updated version of the dataset posted in the resources. This dataset contains weather data, commercial load profile data, and residential load profile data. Weather The Typical Meteorological Year 3 (TMY3) provides one year of hourly data for around 1,000 locations. The TMY weather represents 30-year normals, which are typical weather conditions over a 30-year period. Commercial The commercial load profiles included are the 16 ASHRAE 90.1-2004 DOE Commercial Prototype Models simulated in all TMY3 locations, with building insulation levels changing based on ASHRAE 90.1-2004 requirements in each climate zone. The folder names within each resource represent the weather station location of the profiles, whereas the file names represent the building type and the representative city for the ASHRAE climate zone that was used to determine code compliance insulation levels. As indicated by the file names, all building models represent construction that complied with the ASHRAE 90.1-2004 building energy code requirements. No older or newer vintages of buildings are represented. Residential The BASE residential load profiles are five EnergyPlus models (one per climate region) representing 2009 IECC construction single-family detached homes simulated in all TMY3 locations. No older or newer vintages of buildings are represented. Each of the five climate regions include only one heating fuel type; electric heating is only found in the Hot-Humid climate. Air conditioning is not found in the Marine climate region. One major issue with the residential profiles is that for each of the five climate zones, certain location-specific algorithms from one city were applied to entire climate zones. For example, in the Hot-Humid files, the heating season calculated for Tampa, FL (December 1 - March 31) was unknowingly applied to all other locations in the Hot-Humid zone, which restricts heating operation outside of those days (for example, heating is disabled in Dallas, TX during cold weather in November). This causes the heating energy to be artificially low in colder parts of that climate zone, and conversely the cooling season restriction leads to artificially low cooling energy use in hotter parts of each climate zone. Additionally, the ground temperatures for the representative city were used across the entire climate zone. This affects water heating energy use (because inlet cold water temperature depends on ground temperature) and heating/cooling energy use (because of ground heat transfer through foundation walls and floors). Representative cities were Tampa, FL (Hot-Humid), El Paso, TX (Mixed-Dry/Hot-Dry), Memphis, TN (Mixed-Humid), Arcata, CA (Marine), and Billings, MT (Cold/Very-Cold). The residential dataset includes a HIGH building load profile that was intended to provide a rough approximation of older home vintages, but it combines poor thermal insulation with larger house size, tighter thermostat setpoints, and less efficient HVAC equipment. Conversely, the LOW building combines excellent thermal insulation with smaller house size, wider thermostat setpoints, and more efficient HVAC equipment. However, it is not known how well these ...
Array↗
Impacts of COVID-19 related stay-at-home restrictions on residential electricity use and implications for future grid stability
“Stay-at-home” orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. Here, we conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apartment’s consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a possible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is predicted to be 15% – 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% – 53% higher than that under pre-pandemic conditions. We conclude that the projected increase in peak demand - which might arise if stay-at-home guidelines coincided with hot weather conditions - could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Determinants of residential mobility: an adaptive retrospective survey method
This study introduces a survey instrument to collect retrospective life-course events, focusing on residential relocation, and it utilizes the survey to evaluate determinants of residential mobility. Here, the survey consists of seven modules collecting information about household structure and household demographics, latest residential relocation, current and previous home, employment, education, vehicle ownership, and travel behavior. The time window of the life-course calendar in the survey is customized according to the latest residential relocation as an anchor point to assist with memory recollection and balance the required input from participants. The survey is used to collect data from a sample of 514 respondents in Sydney, Australia, and another sample of 404 respondents in Chicago, Illinois, in the US. The Cox proportional hazard model is used to analyze residential mobility. The results show primary school commencement is a salient determinant of residential relocation, but its impact is significantly higher in Chicago compared to Sydney.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗