An evaluation of robust controls for passive building thermal mass and mechanical thermal energy storage under uncertainty

Kim, Sean Hay

doi:10.1016/j.apenergy.2013.05.030

Cited by 32 publications

(9 citation statements)

References 20 publications

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“…In addition, it is difficult to probabilistically define uncertainties in the future economy such as electricity prices and policy changes [22]. As such, one way to proceed is to use 'scenarios', which can be understood as formulated alternatives when probabilities of uncertainties are unknown [26,27] and can be used to integrate uncertainties into the performance robustness assessment [13,26]. Scenarios are used to present a range of possible alternatives so that the performance robustness of designs can be assessed based on how different designs perform in each of these alternatives [28].…”

Section: Performance Robustness Assessment Based On Scenario Analysismentioning

confidence: 99%

A methodology for performance robustness assessment of low-energy buildings using scenario analysis

2018

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• A novel methodology for performance robustness assessment is proposed.• Multi-criteria assessment is carried out using predicted performance and robustness.• The minimax regret method is used to identify robust designs.• A multi-criteria decision making strategy is implemented to select robust designs. A R T I C L E I N F O Keywords:Robust design Low-energy buildings Future scenarios Occupant behavior Performance assessment Robustness assessment Design decision making A B S T R A C T Uncertainties in building operation and external factors such as occupant behavior, climate change, policy changes etc. impact building performance, resulting in possible performance deviation during operation compared to the predicted performance in the design phase. Multiple low-energy building configurations can lead to similar optimal performance under deterministic conditions, but can have different magnitudes of performance deviation under these uncertainties. Low-energy buildings must be robust so that these uncertainties do not result in significant variations in energy use, cost and comfort. However, these uncertainties are rarely considered in the design of low-energy buildings and hence, the decision making process may result in designs that are sensitive to uncertainties and might not perform as intended. Therefore, to reduce this sensitivity, performance robustness assessment of low-energy buildings considering uncertainties should be assessed in the design phase. The probability of occurrences of these uncertainties are usually unknown and hence, scenarios are essential to assess the performance robustness of buildings. Therefore, a non-probabilistic robustness assessment methodology, based on scenario analysis, is developed to identify robust designs. Maximum performance regret calculated using the minimax regret method is used as the measure of performance robustness. In this approach, the preferred robust design is based on optimal performance and performance robustness.The proposed methodology is demonstrated using a case study with a policymaker as the decision maker. The proposed methodology can be used by designers and consultants to aid decision makers in the design phase to identify robust low-energy building designs that deliver preferred performance in the future operation.

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Section: Performance Robustness Assessment Based On Scenario Analysismentioning

confidence: 99%

A methodology for performance robustness assessment of low-energy buildings using scenario analysis

2018

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“…Other than utilizing building thermal mass, the operation strategies for TES which are derived by mathematical programming, model predictive control (MPC) and reinforcement learning approaches are demonstrated to outperform the conventional control strategy such as chiller-priority and storage-priority strategies [8][9][10][11][12][13][14]. The near-optimal TES control strategy proposed in [9] is comparable to optimal TES control strategy obtained by dynamic programming.…”

Section: Introductionmentioning

confidence: 75%

“…The near-optimal TES control strategy proposed in [9] is comparable to optimal TES control strategy obtained by dynamic programming. To significantly improve building energy performance and reduce energy cost, a robust MPC is proposed to obtain operation strategy for building thermal mass and TES [11]. A MPC algorithm is proposed in [14] to operate the chiller and TES systems which is able to achieve 5-20% cost savings compared to a modified storage-priority strategy and 20-30% cost savings compared to the chiller-priority strategy.…”

Section: Introductionmentioning

confidence: 99%

A data-driven feed-forward decision framework for building clusters operation under uncertainty

2015

Applied Energy

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“…The uncertainty-based control amalgamated into MPC can be considered one of the viable approaches for maintaining the system's operational stability, even under uncertain conditions [48]. Generically, the uncertainty can be referred to as the gap present between the certainty and the present state of information (obtained from decision making) as shown in Fig.…”

Section: Figure 1312mentioning

confidence: 99%

Control and Optimization of Thermal Energy Storage Systems

Kalaiselvam

Parameshwaran

2014

Thermal Energy Storage Technologies for Sustainability

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An evaluation of robust controls for passive building thermal mass and mechanical thermal energy storage under uncertainty

Cited by 32 publications

References 20 publications

A methodology for performance robustness assessment of low-energy buildings using scenario analysis

A methodology for performance robustness assessment of low-energy buildings using scenario analysis

A data-driven feed-forward decision framework for building clusters operation under uncertainty

Control and Optimization of Thermal Energy Storage Systems

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