scholarly journals How Smart Meter Data Analysis Can Support Understanding the Impact of Occupant Behavior on Building Energy Performance: A Comprehensive Review

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2502
Author(s):  
Jacqueline Nicole Adams ◽  
Zsófia Deme Bélafi ◽  
Miklós Horváth ◽  
János Balázs Kocsis ◽  
Tamás Csoknyai
Keyword(s):  
Western Europe ◽  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Smart Meter ◽  
Occupant Behavior ◽  
Psychological Determinants ◽  
Data Limitations ◽  
Holistic Understanding ◽  
The Impact

The goal of this literature review was to outline the research currently conducted on smart meter (SM) adoption and its connection to building occupant behavior to better understand both SM technology and SM customers. We compiled our findings from the existing literature and developed a holistic understanding of the socio-demographic factors that lead to more or less energy use, the methods used to group and cluster occupants on the basis of energy use, how occupant energy use profiles are developed, and which socio-psychological determinants may influence SM adoption. Our results highlight 11 demographic variables that impact building energy use, find 9 methods commonly used to profile occupants on the basis of energy usage, and highlight 13 socio-psychological variables than can be utilized to better understand SM adoption intentions. The review findings two major deficiencies in the existing literature. First, this review highlights the lack of existing interdisciplinary research that combines occupant behavior with SM data and a clear socio-psychological framework. Second, this review underscores certain data limitations in existing SM research, with most research being conducted only on residential or office buildings and geographically in North America or Western Europe. Final policy recommendations center on increased need for interdisciplinary SM research and the need for an expanded understanding of occupant behavior and SM research across different geographies.

scholarly journals Evaluation of Urban-Scale Building Energy-Use Models and Tools—Application for the City of Fribourg, Switzerland

2021 ◽  
Vol 13 (4) ◽  
pp. 1595
Author(s):  
Valeria Todeschi ◽  
Roberto Boghetti ◽  
Jérôme H. Kämpf ◽  
Guglielmina Mutani
Keyword(s):  
Machine Learning ◽  
Energy Use ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Space Heating ◽  
Engineering Model ◽  
Building Energy Use ◽  
The Impact ◽  
The City

Building energy-use models and tools can simulate and represent the distribution of energy consumption of buildings located in an urban area. The aim of these models is to simulate the energy performance of buildings at multiple temporal and spatial scales, taking into account both the building shape and the surrounding urban context. This paper investigates existing models by simulating the hourly space heating consumption of residential buildings in an urban environment. Existing bottom-up urban-energy models were applied to the city of Fribourg in order to evaluate the accuracy and flexibility of energy simulations. Two common energy-use models—a machine learning model and a GIS-based engineering model—were compared and evaluated against anonymized monitoring data. The study shows that the simulations were quite precise with an annual mean absolute percentage error of 12.8 and 19.3% for the machine learning and the GIS-based engineering model, respectively, on residential buildings built in different periods of construction. Moreover, a sensitivity analysis using the Morris method was carried out on the GIS-based engineering model in order to assess the impact of input variables on space heating consumption and to identify possible optimization opportunities of the existing model.

scholarly journals Impact of space layout on energy performance of office buildings coupling daylight with thermal simulation

2019 ◽  
Vol 111 ◽  
pp. 03077 ◽  
Author(s):  
Tiantian Du ◽  
Sabine Jansen ◽  
Michela Turrin ◽  
Andy van den Dobbelsteen
Keyword(s):  
Architectural Design ◽  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Thermal Simulation ◽  
Floor Plan ◽  
Building Energy Performance ◽  
Artificial Lighting ◽  
Space Layout ◽  
The Impact

Space layout design is one of the most important phases in architectural design, and current studies have shown that it can affect building energy performance. However, its influence has not been quantified. This paper aims at investigating the impact of space layouts on building energy performance. We use the floor plan of an office building in the Netherlands as reference, and propose eleven space layouts based on the reference. Calculations are performed with the tools Honeybee and Ladybug in Grasshopper, which are developed based on Daysim and EnergyPlus, to simulate lighting, cooling and heating demand of these layouts. In addition, we couple daylight with thermal simulation, by importing the artificial lighting schedule calculated in Daysim to EnergyPlus. The result shows that the heating demand of the worst layout is 12% higher than the best layout, the cooling demand of the worst layout is 10% higher than the best layout, and the lighting demand of the worst layout is 65% higher than the best layout. The total final energy use of the worst layout is 19% higher than the best layout.

scholarly journals Influence of User-Related Parameters on Calculated Energy Use in Low-Energy School Buildings

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2985 ◽  
Author(s):  
Branko Simanic ◽  
Birgitta Nordquist ◽  
Hans Bagge ◽  
Dennis Johansson
Keyword(s):  
Energy Use ◽  
Ventilation System ◽  
Building Energy ◽  
Energy Performance ◽  
Hot Water ◽  
Low Energy ◽  
Building Energy Use ◽  
Low Energy Buildings ◽  
Demand Controlled Ventilation ◽  
The Impact

Literature and experience show that there are large discrepancies between the calculated and measured building energy usages, where user-related parameters are significant factors with regard to energy use in low-energy buildings. Furthermore, the difficulties encountered when quantifying these parameters compound these discrepancies. The main aim of this study was to provide feedback that would help the building industry and research communities to predict more accurately the impact of the user-related parameters on energy performance. The results of the study would, subsequently, contribute to minimizing the discrepancies between calculated and measured energy use. This article analyses simulated building energy use based on randomly chosen combinations of measured user-related parameters in three recently built low-energy schools in Sweden. The results show that energy performance can span from 30 to 160 kWh/(m² y) simply by varying the combination of previously measured user-related parameters in building energy simulations. The study shows that the set points for indoor air temperatures during the heating season and the energy required to run a demand-controlled ventilation system have an extensive influence, while tenant electricity use has a slightly lower influence on building energy use. Variations in occupancy rates and energy for hot water usage have the smallest influences on building energy use.

scholarly journals Investigating the Impact of Actual and Modeled Occupant Behavior Information Input to Building Performance Simulation

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Mengda Jia ◽  
Ravi Srinivasan ◽  
Robert J. Ries ◽  
Gnana Bharathy ◽  
Nathan Weyer
Keyword(s):  
Energy Use ◽  
Building Design ◽  
System Optimization ◽  
Building Energy ◽  
Building Performance ◽  
Occupant Behavior ◽  
Commercial Building ◽  
Multiple Perspectives ◽  
Human In The Loop ◽  
The Impact

Occupant behaviors are one of the most dominant factors that influence building energy use. Understanding the influences from building occupants can promote the development of energy–efficient buildings. This paper quantifies the impact of different occupant behavior information on building energy model (BEM) from multiple perspectives. For this purpose, an occupant behavior model that uses agent–based modeling (ABM) approach is implemented via co-simulation with a BEM of an existing commercial building. Then, actual occupant behavior data in correspondence to ABM output, including operations on window, door, and blinds in selected thermal zones of the building are recorded using survey logs. A simulation experiment is conducted by creating three BEMs with constant, actual, and modeled occupant behavioral inputs. The analysis of the simulation results among these scenarios helps us gain an in–depth understanding of how occupant behaviors influence building performance. This study aims to facilitate robust building design and operation with human–in–the–loop system optimization.

scholarly journals Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 749
Author(s):  
John H. Scofield ◽  
Susannah Brodnitz ◽  
Jakob Cornell ◽  
Tian Liang ◽  
Thomas Scofield
Keyword(s):  
Greenhouse Gas ◽  
Energy Use ◽  
Energy Savings ◽  
Electric Energy ◽  
Building Energy ◽  
Energy Performance ◽  
Office Buildings ◽  
Ghg Emission ◽  
Site Energy ◽  
New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

The impact of window opening and other occupant behavior on simulated energy performance in residence halls

2017 ◽  
Vol 10 (6) ◽  
pp. 963-976 ◽  
Author(s):  
Jose G. Cedeno Laurent ◽  
Holly Wasilowski Samuelson ◽  
Yujiao Chen
Keyword(s):  
Residence Halls ◽  
Energy Performance ◽  
Occupant Behavior ◽  
Window Opening ◽  
The Impact

scholarly journals An Optimization-Based Supervisory Control and Coordination Approach for Solar-Load Balancing in Building Energy Management

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1215
Author(s):  
James Allen ◽  
Ari Halberstadt ◽  
John Powers ◽  
Nael H. El-Farra
Keyword(s):  
Solar Energy ◽  
Energy Use ◽  
Weather Forecasting ◽  
Energy Generation ◽  
Building Energy ◽  
Objective Functions ◽  
Forecasting Accuracy ◽  
Electricity Cost ◽  
The Impact ◽  
Building Loads

This work considers the problem of reducing the cost of electricity to a grid-connected commercial building that integrates on-site solar energy generation, while at the same time reducing the impact of the building loads on the grid. This is achieved through local management of the building’s energy generation-load balance in an effort to increase the feasibility of wide-scale deployment and integration of solar power generation into commercial buildings. To realize this goal, a simulated building model that accounts for on-site solar energy generation, battery storage, electrical vehicle (EV) charging, controllable lighting, and air conditioning is considered, and a supervisory model predictive control (MPC) system is developed to coordinate the building’s generation, loads and storage systems. The main aim of this optimization-based approach is to find a reasonable solution that minimizes the economic cost to the electricity user, while at the same time reducing the impact of the building loads on the grid. To assess this goal, three objective functions are selected, including the peak building load, the net building energy use, and a weighted sum of both the peak load and net energy use. Based on these objective functions, three MPC systems are implemented on the simulated building under scenarios with varying degrees of weather forecasting accuracy. The peak demand, energy cost, and electricity cost are compared for various forecast scenarios for each MPC system formulation, and evaluated in relation to a rules-based control scheme. The MPC systems tested the rules-based scheme based on simulations of a month-long electricity consumption. The performance differences between the individual MPC system formulations are discussed in the context of weather forecasting accuracy, operational costs, and how these impact the potential of on-site solar generation and potential wide-spread solar penetration.

scholarly journals The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1480 ◽  
Author(s):  
Qadeer Ali ◽  
Muhammad Jamaluddin Thaheem ◽  
Fahim Ullah ◽  
Samad M. E. Sepasgozar
Keyword(s):  
Energy Efficient ◽  
Behavioral Interventions ◽  
Energy Use ◽  
Energy Savings ◽  
Energy Performance ◽  
Office Buildings ◽  
Occupant Behavior ◽  
Energy Usage ◽  
Performance Gap ◽  
Energy Efficient Buildings

Rising demand and limited production of electricity are instrumental in spreading the awareness of cautious energy use, leading to the global demand for energy-efficient buildings. This compels the construction industry to smartly design and effectively construct these buildings to ensure energy performance as per design expectations. However, the research tells a different tale: energy-efficient buildings have performance issues. Among several reasons behind the energy performance gap, occupant behavior is critical. The occupant behavior is dynamic and changes over time under formal and informal influences, but the traditional energy simulation programs assume it as static throughout the occupancy. Effective behavioral interventions can lead to optimized energy use. To find out the energy-saving potential based on simulated modified behavior, this study gathers primary building and occupant data from three energy-efficient office buildings in major cities of Pakistan and categorizes the occupants into high, medium, and low energy consumers. Additionally, agent-based modeling simulates the change in occupant behavior under the direct and indirect interventions over a three-year period. Finally, energy savings are quantified to highlight a 25.4% potential over the simulation period. This is a unique attempt at quantifying the potential impact on energy usage due to behavior modification which will help facility managers to plan and execute necessary interventions and software experts to develop effective tools to model the dynamic usage behavior. This will also help policymakers in devising subtle but effective behavior training strategies to reduce energy usage. Such behavioral retrofitting comes at a much lower cost than the physical or technological retrofit options to achieve the same purpose and this study establishes the foundation for it.

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