Occupant-oriented mixed-mode EnergyPlus predictive control simulation

Zhao, Jie; Lam, Khee Poh; Ydstie, B. Erik; Loftness, Vivian

doi:10.1016/j.enbuild.2015.09.027

Cited by 67 publications

(30 citation statements)

References 17 publications

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“…Figure 7 depicts the chronological evolution of the main milestones reviewed in this investigation, as well as the impacted energy uses in a building. affects occupant behaviour and energy use [94,96,97]; energy-related occupant behaviour surveys [98,99]; etc. Finally, Hong et al [13] discussed the ten main questions affecting occupant behaviour.…”

Section: Discussionmentioning

confidence: 99%

“…They underlined the recommendation of a deeper understanding and interconnection in these fields. Other authors developed studies not only to deepen the knowledge but also to develop new research studies in order to support the different subtasks that are defined by the IEA, represented in Table 2, of the predictability of presence and movement of occupant in buildings [89][90][91]; window opening behaviour in the residential sector [92][93][94] and light switching action [95]; indoor comfort and how it affects occupant behaviour and energy use [94,96,97]; energy-related occupant behaviour surveys [98,99]; etc.…”

Section: Recent Researchmentioning

confidence: 99%

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Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

2018

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Abstract:It is essential to understand how significantly occupants' actions impact the performance of a building, as a whole, in terms of energy use. Consequently, this paper reviews the available resources on energy-related occupant behaviour and its implications in energy use in a building. A chronological review on energy-related occupant behaviour and its implications in energy use has been conducted. As a main existing gap, it was identified by researchers the difference between real energy performance and the one that is predicted during the design stage of a building. The energy predicted during the design stage of a building may be over twice the energy used in the operation stage. Buildings are one of the most energy intensive features in a country. They are affected by the interaction and correlation of several different variables, such as: its physical characteristics, technical systems, equipment, occupants, etc. Therefore, buildings are considered to be complex systems that require a careful and intensive analysis. Moreover, one of the key variables impacting real building energy use is occupant behaviour. The way occupants behave and their motivations are some of the main aspects that need to be considered in a building life-cycle.

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Section: Discussionmentioning

confidence: 99%

Section: Recent Researchmentioning

confidence: 99%

Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

2018

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“…In a recent work [18], Jazizadeh et al implemented a complementary control strategy for the HVAC control based on a fuzzy predictive model to learn occupant comfort profiles. Zhao et al used a simulation study, against a baseline rule-based algorithm, to tie occupant subjective thermal comfort feedback with MPC control algorithm for the active HVAC system [19]. Vellei et al [20] conducted a six week study to establish the feasibility of enhanced occupant and energy savings based on comfort feedback.…”

Section: Introductionmentioning

confidence: 99%

Singular Perturbation Method for Smart Building Temperature Control Using Occupant Feedback

Gupta

Kar

Mishra

et al. 2017

Asian Journal of Control

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In this work we propose a framework for incorporating occupant feedback towards temperature control of multi-occupant spaces, and analyze it using singular perturbation theory. Such a system would typically have to accommodate occupants with different temperature preferences, and incorporate that with thermal correlation among multiple zones to obtain optimal control for minimization of occupant discomfort and energy cost. In current practice, an acceptable temperature set point for the occupancy level of the zone is estimated, and the control law is designed to maintain temperature at the corresponding set point irrespective of the changes in occupancy and the preferences of multiple occupants. Proposed algorithm incorporates active occupant feedback to minimize aggregate user discomfort and total energy cost. Occupant binary feedback in the form of hot/cold or thermal comfort preference input is used by the control algorithm. The control algorithm also takes the energy cost into account, trading it off optimally with the aggregate occupant discomfort. For convergence to the optimal, sufficient separation between the occupant feedback frequency and the temperature dynamics of system is necessary; in absence of which, the occupant feedback provided do not correctly reflect the effect of current control input value on occupant discomfort. Under sufficient time scale separation, using singular perturbation theory, we establish the stability condition of the system and show convergence of the proposed solution to the desired temperature that minimizes energy cost plus occupant discomfort. The occupants are only assumed to be rational in that they choose their own comfort range to minimize individual thermal discomfort. Optimization for a multi-zone building also takes into account the thermal correlation among different zones. Simulation study with parameters based on our test facility, and experimental study conducted in the same building demonstrates performance of the algorithm under different occupancy and ambient conditions.

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“…A variety of existing HIL applications in the energy sector can be classified based on the level of integration of human control over system functioning-as active, passive, or hybrid active-passive sensing and control systems. In such advanced HIL processes, two-way communication occupancy-based MPCs [60,113,139] have been demonstrated to be capable of supporting building operators and energy managers in achieving two-way comfort and energy cost optimization goals. With such tools, building operators can correct undesired control logic on the fly in accordance with occupant feedback and requests-minimizing building energy consumption and waste while maximizing occupant comfort.…”

Section: 32supporting Research Advancementsmentioning

confidence: 99%

“…obFMU functions as a solver for occupant behavior models that are represented in obXML.  Model predictive controls (MPC) have been developed combining building emulation model with occupant behavior models (via co-simulation or embedded Modelica code) that predict the likelihood and effect of occupancy and adaptive actions over time [60,113,114].…”

Section: 12supporting Research Advancementsmentioning

confidence: 99%

The human dimensions of energy use in buildings: A review

D’Oca

Hong

Langevin

2018

Renewable and Sustainable Energy Reviews

274

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The "human dimensions" of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's life cycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights.Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners; enhanced comfort conditions and productivity for building occupants; more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.

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Occupant-oriented mixed-mode EnergyPlus predictive control simulation

Cited by 67 publications

References 17 publications

Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

Singular Perturbation Method for Smart Building Temperature Control Using Occupant Feedback

The human dimensions of energy use in buildings: A review

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