Cost-Effectiveness and Resiliency Evaluation of Net-Zero Energy U.S. Residential Communities

Thompson, J.R.; Krarti, Moncef

doi:10.1115/1.4051656

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…For this analysis, the sequential search technique is used to determine the Pareto path, revealing the optimal solutions that achieve NZE designs. The sequential search technique is efficient computationally [47] and has been applied for various building energy applications, including optimally designing individual NZE housing units [48,49] and resilient residential communities [50,51], as well as retrofitting existing buildings and communities to be NZE [52,53]. For this study, NZE homes are defined as those housing units that can generate enough onsite electricity from solar panels to meet their own annual energy consumption requirements [54,55].…”

Section: Optimization Analysismentioning

confidence: 99%

Cost Benefits of Net Zero Energy Homes in Australia

Krarti,

Karrech

2024

Buildings

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This paper presents a systematic analysis of energy savings and cost benefits associated with several options for integrating energy efficiency and renewable energy technologies. The primary goal of this study is to assess the cost-effectiveness of achieving optimal net-zero energy (NZE) designs for residential buildings in Australia. Specifically, the analysis combines a series of sensitivity analyses and multi-objective optimizations to account for a wide range of design strategies for detached homes in four cities representing different Australian climates. The results indicate that not only are NZE designs technically feasible for all the considered Australian cities, but they are also highly cost-effective. This cost-effectiveness is attributed to the lower installation costs of rooftop PV systems as well as the beneficial interactive effects of proven energy efficiency strategies. Indeed, it is found that the deployment costs of rooftop PV systems can be recovered in less than 4 years. Moreover, the addition of thermal insulation in walls and ceilings can reduce both HVAC capacities and annual energy end-use by up to 59%. Based on an optimization-based design, NZE homes in Australia can have lower construction costs and, ultimately, lower life cycle costs than dwellings built to meet current energy efficiency standards based primarily on stringent building envelope thermal performance.

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Section: Optimization Analysismentioning

confidence: 99%

Cost Benefits of Net Zero Energy Homes in Australia

Krarti,

Karrech

2024

Buildings

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Practical Method for Optimizing Capacities of Private Generators Installed in Hospital Buildings During Power Outages

Uemichi¹,

Kaito²,

Yamasaki³

et al. 2022

Journal of Energy Resources Technology

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In stand-alone operations, on-site generators must balance and meet demand at any time for second-by-second fluctuations in output and load demand. However, the previous optimization tool for private generator configuration in hospital buildings did not consider demand sufficiency. Herein, this qualitative electricity problem was solved by proposing a new optimization method that considers the balance of power supply and demand in the stand-alone operation of on-site generators during power outages. As a demand sufficiency condition, a power balance simulator obtained available configurations of private generators that can be operated within the standard alternating current (AC) frequency range of 49-51 Hz. We also compared case study results by applying these constraints to the findings of previous studies. The same case study from a previous paper reported that the optimal amount of photovoltaic systems installed is approximately the upper limit (set at 600 m2 in this calculation) and the optimal solution. In contrast, the optimization results with additional constraints to keep frequency fluctuations within specified limits yielded an optimal value of much less than the previous optimization; one case study showed that the optimal installation amount of photovoltaics was 0 m2. On the other hand, the key equipment in this study was the emergency diesel generator. The emergency generator compensates for power shortages and balances supply and demand under the power outage. The result suggests that case studies with demand-satisfying conditions tend to select equipment configurations that effectively improve the expected power-shortage rate.

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Neural Network-Based Building Energy Models for Adapting to Post-Occupancy Conditions: A Case Study for Florida

Migliori

Najafi

Fabregas

et al. 2022

ASME Journal of Engineering for Sustainable Buildings and Cities

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Building energy models (BEMs) are developed by subject matter experts during the design phase to help with decision making for achieving a more energy-efficient design. A BEM that is created based on “as-designed” condition to predict building energy consumption can become much less accurate during the lifetime of the building given the potential changes to the “in-operation” conditions. While BEMs can be adjusted to address operational changes, the end-user (i.e. building owners) usually do not possess the knowledge to update physics-based models (e.g., eQuest) and therefore the initial BEM may no longer be useful to them. In the present paper, an approach is proposed and assessed through which a physics-based model is developed using eQuest and simulated for several different operating conditions. The resulting data are then used for training an artificial neural network (ANN) which serves as a simple and data-driven model for prediction of building energy consumption in response to changes in operating conditions. A case study is performed for a building in Melbourne, FL to explore the changes occurred in the building schedule of operation during COVID-19 pandemic and it's impact on the performance of BEM. The trained ANN is tested against the actual measured data for energy consumption under different scenarios and good agreement between the results are found. The approach presented can be used to establish data-driven BEMs that remain accurate in response to sudden changes in building operating conditions.

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Cost-Effectiveness and Resiliency Evaluation of Net-Zero Energy U.S. Residential Communities

Cited by 3 publications

References 13 publications

Cost Benefits of Net Zero Energy Homes in Australia

Cost Benefits of Net Zero Energy Homes in Australia

Practical Method for Optimizing Capacities of Private Generators Installed in Hospital Buildings During Power Outages

Neural Network-Based Building Energy Models for Adapting to Post-Occupancy Conditions: A Case Study for Florida

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