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Occupant behavior can significantly influence the operation and performance of buildings. Many occupant-centric key performance indicators (KPIs) rely on having accurate counts of the number of occupants in a building, which is very different to how occupancy information is currently collected in the majority of buildings today. To address this gap, the authors develop a standardized methodology for the calculation of percent space utilization for buildings, which is formulated with respect to two prevalent operational data schemas: the Brick Schema and Project Haystack. The methodology is scalable across different levels of spatial granularity and irrespective of sensor placement. Moreover, the methods are intended to make use of typical occupancy sensors that capture presence level occupancy and not counts of people. Since occupant-hours is a preferable metric to use in KPI calculations, a method to convert between percent space utilization and occupant-hours using the design occupancy for a space is also developed. The methodology is demonstrated on a small commercial office space in Boulder, Colorado using data collected between June 2018 and February 2019. A multiple linear regression is performed that shows strong evidence for a relationship between building energy consumption and percent space utilization.
Cory Mosiman; Gregor Henze; Herbert Els. Development and Application of Schema Based Occupant-Centric Building Performance Metrics. Energies 2021, 14, 3513 .
AMA StyleCory Mosiman, Gregor Henze, Herbert Els. Development and Application of Schema Based Occupant-Centric Building Performance Metrics. Energies. 2021; 14 (12):3513.
Chicago/Turabian StyleCory Mosiman; Gregor Henze; Herbert Els. 2021. "Development and Application of Schema Based Occupant-Centric Building Performance Metrics." Energies 14, no. 12: 3513.
Typical commercial construction inherently contains large surface areas of relatively thin mass located in the floor slabs. This research asks how effective this mass could be for passive cooling, relative to other mass depths, if it were to be exposed and used as thermal mass. Although much of the rich literature on thermal mass has been conducted with far greater mass depths, a more limited amount of research suggests that because the surface heat transfer rate is limited, the focus should be on the surface area of exposed mass, not its depth. This presents an opportunity for more buildings to behave more thermally massively, if the mass inherent in typical floor slabs contains utility, particularly over diurnal cycles. In all climates analyzed, it was found that there is a pronounced shoulder where energy savings from passive cooling of increasing mass depths was steep until roughly 7.5–10 cm, and beyond this point the achieved energy savings diminished rapidly. When considering the embodied energy of concrete, the incremental benefit of added mass beyond a typical topping slab of 10 cm does not justify the incremental embodied energy cost from a total energy standpoint alone.
John Nelson; Gregor Henze. Evaluation of the Passive Cooling Potential of Thermal Mass Inherent in Medium to Large Commercial Buildings. Journal of Architectural Engineering 2021, 27, 04021007 .
AMA StyleJohn Nelson, Gregor Henze. Evaluation of the Passive Cooling Potential of Thermal Mass Inherent in Medium to Large Commercial Buildings. Journal of Architectural Engineering. 2021; 27 (2):04021007.
Chicago/Turabian StyleJohn Nelson; Gregor Henze. 2021. "Evaluation of the Passive Cooling Potential of Thermal Mass Inherent in Medium to Large Commercial Buildings." Journal of Architectural Engineering 27, no. 2: 04021007.
As the United States continues its progress toward sustainable construction, net zero building design is becoming an increasingly important and popular topic. Two definitions of net zero energy performance, monthly and annual, provide different levels of energy autonomy and efficiency within a building. This article analyzes the viability and incremental cost for two-, three-, and four-story multifamily apartment buildings to reach both annual and monthly net zero energy performance throughout four climate zones in the United States using baseline reference buildings that represent current construction practices. Building size plays a large role in determining the capability for a building model to reach annual or monthly net zero. Two-story buildings are capable of reaching annual net zero with an increase in construction cost of about 4.4–5.6%. Three-story buildings in warmer climates can achieve annual net zero with an increase of about 5.1%, but models in colder climates cannot reach annual net zero performance. Four-story buildings cannot achieve net zero, owing to insufficient building area for solar arrays to produce electricity. Monthly net zero energy performance was significantly harder to achieve, with the only case reaching this goal being the two-story Houston based model, at an added cost of 8.2%. Generally speaking, only small buildings in warm climates will be able to achieve monthly net zero without vastly oversizing photovoltaic systems and increasing costs without adequate payback.
Adam R. McKittrick; Gregor P. Henze. Cost Analysis of Annual and Monthly Net Zero Energy Performance for Multifamily Buildings in the United States. Journal of Architectural Engineering 2021, 27, 04021003 .
AMA StyleAdam R. McKittrick, Gregor P. Henze. Cost Analysis of Annual and Monthly Net Zero Energy Performance for Multifamily Buildings in the United States. Journal of Architectural Engineering. 2021; 27 (2):04021003.
Chicago/Turabian StyleAdam R. McKittrick; Gregor P. Henze. 2021. "Cost Analysis of Annual and Monthly Net Zero Energy Performance for Multifamily Buildings in the United States." Journal of Architectural Engineering 27, no. 2: 04021003.
Price-based demand response (PBDR) has recently been attributed great economic but also environmental potential. However, the determination of its short-term effects on carbon emissions requires the knowledge of marginal emission factors (MEFs), which compared to grid mix emission factors (XEFs), are cumbersome to calculate due to the complex characteristics of national electricity markets. This study, therefore, proposes two merit order-based methods to approximate hourly MEFs and applies them to readily available datasets from 20 European countries for the years 2017–2019. Based on the calculated electricity prices, standardized daily load shifts were simulated which indicated that carbon emissions increased for 8 of the 20 countries and by 2.1% on average. Thus, under specific circumstances, PBDR leads to carbon emissions increases, mainly due to the economic advantage fuel sources such as lignite and coal have in the merit order. MEF-based load shifts reduced the mean resulting carbon emissions by 35%, albeit with 56% lower monetary cost savings compared to price-based load shifts. Finally, by repeating the load shift simulations for different carbon price levels, the impact of the carbon price on the resulting carbon emissions was analyzed. The Spearman correlation coefficient between carbon intensity and marginal cost along the German merit order substantially increased with increasing carbon price. The coefficients were -0.13 for the 2019 carbon price of 24.9 €/t, 0 for 42.6 €/t, and 0.4 for 100.0 €/t. Therefore, with adequate carbon prices, PBDR can be an effective tool for both economical and environmental improvement.
Markus Fleschutz; Markus Bohlayer; Marco Braun; Gregor Henze; Michael D. Murphy. The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices. Applied Energy 2021, 295, 117040 .
AMA StyleMarkus Fleschutz, Markus Bohlayer, Marco Braun, Gregor Henze, Michael D. Murphy. The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices. Applied Energy. 2021; 295 ():117040.
Chicago/Turabian StyleMarkus Fleschutz; Markus Bohlayer; Marco Braun; Gregor Henze; Michael D. Murphy. 2021. "The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices." Applied Energy 295, no. : 117040.
Fully defined physics-based building energy models can accurately represent building systems; however, generating models based on high-level parameters is time consuming and simulation time of complex models can be slow. This article discusses the development of a Metamodelling Framework to create metamodels from a building energy modelling dataset. The framework generates metamodels using either linear regression, random forests, or support vector regressions. A fifth-generation district heating and cooling system analysis use case was used to motivate the development of the framework. The use case required quick and accurate representations of annual building loads reported hourly. Typical annual building modelling approaches can result in a runtime of 10 min. The metamodels runtime was reduced to less than 10 s to load and run an annual simulation with user-defined covariates. The results of the metamodel performance and an abbreviated topology analysis based on the motivating use case will be presented.
Nicholas Long; Fatema Almajed; Justus von Rhein; Gregor Henze. Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks. Journal of Building Performance Simulation 2021, 14, 203 -225.
AMA StyleNicholas Long, Fatema Almajed, Justus von Rhein, Gregor Henze. Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks. Journal of Building Performance Simulation. 2021; 14 (2):203-225.
Chicago/Turabian StyleNicholas Long; Fatema Almajed; Justus von Rhein; Gregor Henze. 2021. "Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks." Journal of Building Performance Simulation 14, no. 2: 203-225.
The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.
C Turley; M Jacoby; G Henze; G Pavlak. Development and evaluation of occupancy-aware model predictive control for residential building energy efficiency and occupant comfort. IOP Conference Series: Earth and Environmental Science 2020, 588, 022043 .
AMA StyleC Turley, M Jacoby, G Henze, G Pavlak. Development and evaluation of occupancy-aware model predictive control for residential building energy efficiency and occupant comfort. IOP Conference Series: Earth and Environmental Science. 2020; 588 (2):022043.
Chicago/Turabian StyleC Turley; M Jacoby; G Henze; G Pavlak. 2020. "Development and evaluation of occupancy-aware model predictive control for residential building energy efficiency and occupant comfort." IOP Conference Series: Earth and Environmental Science 588, no. 2: 022043.
Advanced district thermal energy systems, which circulate water at temperatures near ambient conditions, and facilitate the utilization of waste heat and renewable thermal sources, can lower the carbon-intensity of urban districts, advancing the U.N. Sustainable Development Goals. Optimization of the network topology — the selection of the best subset of buildings and the best network to connect them, to minimize life cycle cost — can increase adoption of these system in appropriate applications. The potential "solution space" of the topology optimization problem grows factorially with the number of buildings in the district, motivating the consideration of a design heuristic. In this study, a heuristic for the network selection was evaluated with an exhaustive search, for a prototypical four-building district. For the prototypical district considered, the heuristic was effective in selecting an optimal network topology. Additionally, it was found that, in this case, the selection of the subset of buildings was more influential on the life cycle cost than the selection of the network topology. This work is part of a larger effort to develop a topology optimization framework for district thermal energy systems, which is anticipated to address barriers to adoption of ambient-temperature systems.
Amy Allen; Gregor Henze; Kyri Baker; Gregory Pavlak; Nicholas Long; Yangyang Fu. A topology optimization framework to facilitate adoption of advanced district thermal energy systems. IOP Conference Series: Earth and Environmental Science 2020, 588, 022054 .
AMA StyleAmy Allen, Gregor Henze, Kyri Baker, Gregory Pavlak, Nicholas Long, Yangyang Fu. A topology optimization framework to facilitate adoption of advanced district thermal energy systems. IOP Conference Series: Earth and Environmental Science. 2020; 588 (2):022054.
Chicago/Turabian StyleAmy Allen; Gregor Henze; Kyri Baker; Gregory Pavlak; Nicholas Long; Yangyang Fu. 2020. "A topology optimization framework to facilitate adoption of advanced district thermal energy systems." IOP Conference Series: Earth and Environmental Science 588, no. 2: 022054.
Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.
Christina Turley; Margarite Jacoby; Gregory Pavlak; Gregor Henze. Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort. Energies 2020, 13, 5396 .
AMA StyleChristina Turley, Margarite Jacoby, Gregory Pavlak, Gregor Henze. Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort. Energies. 2020; 13 (20):5396.
Chicago/Turabian StyleChristina Turley; Margarite Jacoby; Gregory Pavlak; Gregor Henze. 2020. "Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort." Energies 13, no. 20: 5396.
District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.
Simone Buffa; Anton Soppelsa; Mauro Pipiciello; Gregor Henze; Roberto Fedrizzi. Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control. Energies 2020, 13, 4339 .
AMA StyleSimone Buffa, Anton Soppelsa, Mauro Pipiciello, Gregor Henze, Roberto Fedrizzi. Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control. Energies. 2020; 13 (17):4339.
Chicago/Turabian StyleSimone Buffa; Anton Soppelsa; Mauro Pipiciello; Gregor Henze; Roberto Fedrizzi. 2020. "Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control." Energies 13, no. 17: 4339.
District energy systems have the potential to achieve deep energy savings by leveraging the density and diversity of loads in urban districts. However, planning and adoption of district thermal energy systems is hindered by the analytical burden and high infrastructure costs. It is hypothesized that network topology optimization would enable wider adoption of advanced (ambient temperature) district thermal energy systems, resulting in energy savings. In this study, energy modeling is used to compare the energy performance of “conventional” and “advanced” district thermal energy systems at the urban district level, and a partial exhaustive search is used to evaluate a heuristic for the topology optimization problem. For the prototypical district considered, advanced district thermal energy systems mated with low-exergy building heating and cooling systems achieved a source energy use intensity that was 49% lower than that of conventional systems. The minimal spanning tree heuristic was demonstrated to be effective for the network topology optimization problem in the context of a prototypical district, and contributes to mitigating the problem’s computational complexity. The work presented in this paper demonstrates the potential of advanced district thermal energy systems to achieve deep energy savings, and advances to addressing barriers to their adoption through topology optimization.
Amy Allen; Gregor Henze; Kyri Baker; Gregory Pavlak. Evaluation of low-exergy heating and cooling systems and topology optimization for deep energy savings at the urban district level. Energy Conversion and Management 2020, 222, 113106 .
AMA StyleAmy Allen, Gregor Henze, Kyri Baker, Gregory Pavlak. Evaluation of low-exergy heating and cooling systems and topology optimization for deep energy savings at the urban district level. Energy Conversion and Management. 2020; 222 ():113106.
Chicago/Turabian StyleAmy Allen; Gregor Henze; Kyri Baker; Gregory Pavlak. 2020. "Evaluation of low-exergy heating and cooling systems and topology optimization for deep energy savings at the urban district level." Energy Conversion and Management 222, no. : 113106.
This paper evaluates the potential for automated lighting control as a resource for frequency regulation of the electric grid system in the context of current energy policies, economic incentives, and technological trends. The growing prevalence of renewable energy has increased the need for ancillary services to maintain grid frequency and stability. While demand side resources like heating, ventilating, and air-conditioning systems, as well as water treatment plants are already evaluated as regulation service providers, the potential application to electrical lighting systems has largely been ignored. Yet, aggregations of lighting systems that are retrofitted with intelligent controls could conceivably contribute to frequency regulation services with little impact on user comfort. To further explore the feasibility of lighting potential, this paper explores (1) how lighting control systems are limited by visual comfort perception and acceptability, (2) how such limitations impact the performance of the lighting system as an frequency regulation resource, and (3) how the market potential of lighting systems as demand side resources compares in different regional transmission organizations. Finally, the impact of developing technologies on the application of lighting systems for frequency regulation is discussed.
Alexandra Karpilow; Gregor Henze; Walter Beamer. Assessment of Commercial Building Lighting as a Frequency Regulation Resource. Energies 2020, 13, 613 .
AMA StyleAlexandra Karpilow, Gregor Henze, Walter Beamer. Assessment of Commercial Building Lighting as a Frequency Regulation Resource. Energies. 2020; 13 (3):613.
Chicago/Turabian StyleAlexandra Karpilow; Gregor Henze; Walter Beamer. 2020. "Assessment of Commercial Building Lighting as a Frequency Regulation Resource." Energies 13, no. 3: 613.
Clustering is an unsupervised learning technique that is useful when working with a large volume of unlabeled data. Complex dynamical systems in real life often entail data streaming from a large number of sources. Although it is desirable to use all source variables to form accurate state estimates, it is often impractical due to large computational power requirements, and sufficiently robust algorithms to handle these cases are not common. We propose a hierarchical time series clustering technique based on symbolic dynamic filtering and Granger causality, which serves as a dimensionality reduction and noise-rejection tool. Our process forms a hierarchy of variables in the multivariate time series with clustering of relevant variables at each level, thus separating out noise and less relevant variables. A new distance metric based on Granger causality is proposed and used for the time series clustering, as well as validated on empirical data sets. Experimental results from occupancy detection and building temperature estimation tasks shows fidelity to the empirical data sets while maintaining state-prediction accuracy with substantially reduced data dimensionality.
Sin Yong Tan; Homagni Saha; Margarite Jacoby; Gregor Henze; Soumik Sarkar. Granger Causality Based Hierarchical Time Series Clustering for State Estimation. IFAC-PapersOnLine 2020, 53, 524 -529.
AMA StyleSin Yong Tan, Homagni Saha, Margarite Jacoby, Gregor Henze, Soumik Sarkar. Granger Causality Based Hierarchical Time Series Clustering for State Estimation. IFAC-PapersOnLine. 2020; 53 (2):524-529.
Chicago/Turabian StyleSin Yong Tan; Homagni Saha; Margarite Jacoby; Gregor Henze; Soumik Sarkar. 2020. "Granger Causality Based Hierarchical Time Series Clustering for State Estimation." IFAC-PapersOnLine 53, no. 2: 524-529.
Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separate sensible and latent cooling (SSLC) systems. However, a sophisticated control technique is needed to coordinate the control of multiple cooling coils in such systems. This paper presents a novel model predictive control (MPC) developed for a DOAS-assisted SSLC system. The MPC adopts a linear state-space model that captures building thermodynamics, thermal comfort and ACMV for building response prediction and optimization. Subsequently, a multi-objective cost function is employed to optimize energy use and thermal comfort while fulfilling constraints of predicted mean vote (PMV) (-0.5, 0.5) and relative humidity (0%, 65%) in buildings. The performance of the MPC for controlling a conventional single-coil air-handling unit (AHU) system and a DOAS-assisted SSLC system is experimentally investigated and compared to a conventional feedback-control-based building management system (BMS). The MPC system achieved 18% and 20% electricity savings for the single-coil AHU and DOAS-assisted SSLC, respectively, as compared to the BMS controlled single-coil AHU. Furthermore, indoor thermal comfort is significantly improved, compared to the BMS. DOAS-assisted SSLC is shown to be advantageous compared to single-coil AHU to achieve better indoor environment in terms of thermal comfort and humidity, when both systems are controlled by MPC.
Shiyu Yang; Man Pun Wan; Bing Feng Ng; Swapnil Dubey; Gregor Henze; Wanyu Chen; Krishnamoorthy Baskaran. Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system. Applied Energy 2019, 257, 113920 .
AMA StyleShiyu Yang, Man Pun Wan, Bing Feng Ng, Swapnil Dubey, Gregor Henze, Wanyu Chen, Krishnamoorthy Baskaran. Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system. Applied Energy. 2019; 257 ():113920.
Chicago/Turabian StyleShiyu Yang; Man Pun Wan; Bing Feng Ng; Swapnil Dubey; Gregor Henze; Wanyu Chen; Krishnamoorthy Baskaran. 2019. "Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system." Applied Energy 257, no. : 113920.
Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of electricity. One way to shape load and introduce elasticity is to broadcast forecasts of dynamic electricity prices that orchestrate electricity supply and demand in order to maximize the efficiency of conventional generation and the use of renewable resources including wind and solar energy. A binary control algorithm that influences the on and off states of end uses was developed and applied to empirical time series data to estimate price-based instantaneous opportunities for shedding and adding electric load. To overcome the limitations of traditional stochastic methods in quantifying diverse, non-Gaussian, non-stationary distributions of observed appliance behaviour, recent developments in wavelet-based analysis were applied to capture and simulate time-frequency domain behaviour. The performance of autoregressive and spectral reconstruction methods was compared, with phase reconstruction providing the best simulation ensembles. Results show spatiotemporal differences in the amount of load that can be shed and added, which suggest further investigation is warranted in estimating the benefits anticipated from the wide-scale deployment of continuous automatic residential load shaping. Empirical data and documented software code are included to assist in reproducing and extending this work.
Robert Cruickshank; Gregor Henze; Rajagopalan Balaji; Bri-Mathias Hodge; Anthony Florita. Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping. Energies 2019, 12, 3204 .
AMA StyleRobert Cruickshank, Gregor Henze, Rajagopalan Balaji, Bri-Mathias Hodge, Anthony Florita. Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping. Energies. 2019; 12 (17):3204.
Chicago/Turabian StyleRobert Cruickshank; Gregor Henze; Rajagopalan Balaji; Bri-Mathias Hodge; Anthony Florita. 2019. "Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping." Energies 12, no. 17: 3204.
Buildings are widely regarded as potential sources for demand flexibility. The flexibility of thermal and electric load in buildings is a result of their interactive nature and its impact on the building’s performance. In this paper, the interaction of a building with the three interaction counterparts of the physical environment, civil infrastructure networks and other buildings is investigated. The literature review presents a wide variety of pathways of interaction and their associated potential impacts on building performance metrics such as net energy use, emissions, occupant comfort and operational cost. It is demonstrated that all of these counterparts of interaction should be considered to harness the flexibility potential of the buildings while maintaining other buildings performance metrics at a desired level. Juxtaposed with the upside potential for providing demand flexibility, numerous implementation challenges are identified that are associated with the evaluation and financial valuation of the capacity for demand flexibility, the aggregated flexibility potential, as well as the control and communication to facilitate the interactions.
Zahra Fallahi; Gregor Henze. Interactive Buildings: A Review. Sustainability 2019, 11, 3988 .
AMA StyleZahra Fallahi, Gregor Henze. Interactive Buildings: A Review. Sustainability. 2019; 11 (14):3988.
Chicago/Turabian StyleZahra Fallahi; Gregor Henze. 2019. "Interactive Buildings: A Review." Sustainability 11, no. 14: 3988.
Fifth generation district heating and cooling networks are characterized by supply temperatures in the ambient range of 15–25 °C, which not only reduces heat loss but also allows for integrating various kinds of low-temperature waste heat sources. The ability of these networks to absorb waste heat that is normally unrecoverable makes them an attractive solution for the future energy supply of urban areas. To enhance the adoption of these networks, this paper describes the development of a software tool to analyze the feasibility of fifth-generation of district heating and cooling systems in both new and existing districts. The research attempts to answer the question: ”Which buildings should be connected to a low-temperature hydraulic network given both the incremental benefits and costs relative to the scenario of decentralized (dedicated) heating and cooling systems for each building?” Therefore, all possible network layouts of the buildings are considered where the heating and cooling demands of each building are met by the fifth-generation of district heating and cooling network. For the heating and cooling load characterization of the buildings, reduced-order models are used while renewable energy and waste heat sources are included in the network. The focus of the research lies in the development of a hydraulic model for flexible use in the urban energy modeling and the optimization of the fifth-generation of district heating and cooling network topology for a given urban district. Simulation results quantify the performance of the fifth-generation of district heating and cooling network based on various output metrics, including primary energy usage, carbon dioxide emissions, and network implementation cost.
Justus von Rhein; Gregor P. Henze; Nicholas Long; Yangyang Fu. Development of a topology analysis tool for fifth-generation district heating and cooling networks. Energy Conversion and Management 2019, 196, 705 -716.
AMA StyleJustus von Rhein, Gregor P. Henze, Nicholas Long, Yangyang Fu. Development of a topology analysis tool for fifth-generation district heating and cooling networks. Energy Conversion and Management. 2019; 196 ():705-716.
Chicago/Turabian StyleJustus von Rhein; Gregor P. Henze; Nicholas Long; Yangyang Fu. 2019. "Development of a topology analysis tool for fifth-generation district heating and cooling networks." Energy Conversion and Management 196, no. : 705-716.
Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi‐energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building‐to‐grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions. This article is categorized under: Wind Power > Systems and Infrastructure Energy Policy and Planning > Systems and Infrastructure Energy Efficiency > Systems and Infrastructure
Kate Doubleday; Faeza Hafiz; Andrew Parker; Tarek Elgindy; Anthony Florita; Gregor Henze; Graziano Salvalai; Shanti Pless; Bri-Mathias Hodge. Integrated distribution system and urban district planning with high renewable penetrations. WIREs Energy and Environment 2019, 8, 1 .
AMA StyleKate Doubleday, Faeza Hafiz, Andrew Parker, Tarek Elgindy, Anthony Florita, Gregor Henze, Graziano Salvalai, Shanti Pless, Bri-Mathias Hodge. Integrated distribution system and urban district planning with high renewable penetrations. WIREs Energy and Environment. 2019; 8 (5):1.
Chicago/Turabian StyleKate Doubleday; Faeza Hafiz; Andrew Parker; Tarek Elgindy; Anthony Florita; Gregor Henze; Graziano Salvalai; Shanti Pless; Bri-Mathias Hodge. 2019. "Integrated distribution system and urban district planning with high renewable penetrations." WIREs Energy and Environment 8, no. 5: 1.
Energy modelling for the prediction of energy use in buildings, especially under novel energy management strategies, is of great importance. In buildings there are several flexible electrical loads which can be shifted in time such as thermostatically controllable loads. The main novelty of this paper is to apply an aggregation method to effectively characterize the electrical energy demand of air-conditioning (AC) systems in residential buildings under flexible operation during demand response and demand shaping programs. The method is based on clustering techniques to aggregate a large and diverse building stock of residential buildings to a smaller, representative ensemble of buildings. The methodology is tested against a detailed simulation model of building stocks in Houston, New York and Los Angeles. Results show good agreement between the energy demand predicted by the aggregated model and by the full model during normal operation (normalized mean absolute error, NMAE, below 10%), even with a small number of clusters (sample size of 1%). During flexible operation, the NMAE rises (around 20%) and a higher number of representative buildings become necessary (sample size at least 10%). Multiple cases for the input data series were considered, namely by varying the time resolution of the input data and the type of input data. These characteristics of the input time series data are shown to play a crucial role in the aggregation performance. The aggregated model showed lower NMAE compared to the original model when clustering is based on a hybrid signal resolved at 60-minute time intervals, which is a combination of the electricity demand profile and AC modulation level.
Dieter Patteeuw; Gregor P. Henze; Alessia Arteconi; Charles D. Corbin; Lieve Helsen. Clustering a building stock towards representative buildings in the context of air-conditioning electricity demand flexibility. Journal of Building Performance Simulation 2018, 12, 56 -67.
AMA StyleDieter Patteeuw, Gregor P. Henze, Alessia Arteconi, Charles D. Corbin, Lieve Helsen. Clustering a building stock towards representative buildings in the context of air-conditioning electricity demand flexibility. Journal of Building Performance Simulation. 2018; 12 (1):56-67.
Chicago/Turabian StyleDieter Patteeuw; Gregor P. Henze; Alessia Arteconi; Charles D. Corbin; Lieve Helsen. 2018. "Clustering a building stock towards representative buildings in the context of air-conditioning electricity demand flexibility." Journal of Building Performance Simulation 12, no. 1: 56-67.
In der Planungs‐ und Betriebspraxis herrscht im Bereich der Betriebsführung von thermisch aktivierten Bauteilsystemen und insbesondere der thermisch trägen Bauteilaktivierung noch große Unsicherheit. Trotz einer weiten Verbreitung dieser Systeme im Neubau von Nichtwohngebäuden hat sich bis heute keine einheitliche Betriebsführungsstrategie durchgesetzt. Vielmehr kritisieren Bauherren und Nutzer regelmäßig zu hohe bzw. niedrige Raumtemperaturen in den Übergangsjahreszeiten und bei Wetterwechsel sowie generell eine mangelhafte Regelbarkeit. Demgegenüber weisen Monitoringprojekte immer wieder einen hohen thermischen Komfort in diesen Gebäuden nach. Offensichtlich unterscheiden sich hier subjektiv empfundene Behaglichkeit und objektiv gemessener Komfort. Gleichzeitig sind Heiz‐ und Kühlkonzepte mit Flächentemperierung dann besonders energieeffi zient, wenn das Regelkonzept auf deren thermische Trägheit angepasst ist. Eine gute Regelung gewährleistet also einen hohen thermischen Komfort und sorgt für einen möglichst niedrigen Energieeinsatz. Das Rechenverfahren mit Anlagenaufwandszahlen (in Anlehnung an DIN V 18599) bietet eine gute Möglichkeit, Anlagenkonzepte inklusive deren Betriebsführungsstrategie zu bewerten. Damit ist es möglich, eine auf das Gebäude angepasste Betriebsführungsstrategie für die Bauteilaktivierung zu finden und einheitlich zu bewerten.
Dr.‐Ing. Jens Pfafferott; Dr.‐Ing. Gregor P. Henze; Tobias Lang. Anlagenaufwandszahlen für die Bauteilaktivierung in Abhängigkeit des Regelkonzeptes. Bauphysik 2017, 39, 279 -290.
AMA StyleDr.‐Ing. Jens Pfafferott, Dr.‐Ing. Gregor P. Henze, Tobias Lang. Anlagenaufwandszahlen für die Bauteilaktivierung in Abhängigkeit des Regelkonzeptes. Bauphysik. 2017; 39 (5):279-290.
Chicago/Turabian StyleDr.‐Ing. Jens Pfafferott; Dr.‐Ing. Gregor P. Henze; Tobias Lang. 2017. "Anlagenaufwandszahlen für die Bauteilaktivierung in Abhängigkeit des Regelkonzeptes." Bauphysik 39, no. 5: 279-290.
This paper aims at assessing the value of load shifting and demand side flexibility for improving electric grid system operations. In particular, this study investigates to what extent residential heat pumps participating in load shifting can contribute to reducing operational costs and CO2CO2 emissions associated with electric power generation and how home owners with heat pump systems can be best motivated to achieve these flexibility benefits. Residential heat pumps, when intelligently orchestrated in their operation, can lower operational costs and CO2CO2 emissions by performing load shifting in order to reduce curtailment of electricity from renewable energy sources and improve the efficiency of dispatchable power plants. In order to study the interaction, both the electricity generation system and residences with heat pumps are modeled. In a first step, an integrated modeling approach is presented which represents the idealized case where the electrical grid operation in terms of unit commitment and dispatch is concurrently optimized with that of a large number of residential heat pumps located in homes designed to low-energy design standards. While this joint optimization approach does not lend itself for real-time implementation, it serves as an upper bound for the achievable operational cost savings. The main focus of this paper is to assess to what extent load shifting incentives are able to achieve the aforementioned savings potential. Two types of incentives are studied: direct load control and dynamic time-of-use pricing. Since both the electricity generation supply system and the residential building stock with heat pumps had been modeled for the joint optimization, the performance of both load shifting incentives can be compared by separately assessing the supply and demand side. Superior performance is noted for the direct-load control scenario, achieving 60–90% of the cost savings attained in the jointly optimized best-case scenario. In dynamic time-of-use pricing, poor performance in terms of reduced cost and emissions is noted when the heat pumps response is not taken into account. When the heat pumps response is taken into account, dynamic time-of-use pricing performs better. However, both dynamic time-of-use pricing schemes show inferior performance at high levels of residential heat pump penetration.
Dieter Patteeuw; Gregor P. Henze; Lieve Helsen. Comparison of load shifting incentives for low-energy buildings with heat pumps to attain grid flexibility benefits. Applied Energy 2016, 167, 80 -92.
AMA StyleDieter Patteeuw, Gregor P. Henze, Lieve Helsen. Comparison of load shifting incentives for low-energy buildings with heat pumps to attain grid flexibility benefits. Applied Energy. 2016; 167 ():80-92.
Chicago/Turabian StyleDieter Patteeuw; Gregor P. Henze; Lieve Helsen. 2016. "Comparison of load shifting incentives for low-energy buildings with heat pumps to attain grid flexibility benefits." Applied Energy 167, no. : 80-92.