Learning-Based Hierarchical Distributed HVAC Scheduling With Operational Constraints

Radhakrishnan, Nikitha; Srinivasan, Seshadhri; Su, Rong; Poolla, Kameshwar

doi:10.1109/tcst.2017.2728004

Cited by 38 publications

(21 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [26], to protect privacy, a decentralized method based on a multi-level virtual market was proposed. Different from the above works where the heat transfer between neighbouring thermal zones is ignored, [2], [27] regarded the heat transfer from the adjacent zone as external thermal disturbances that are measured through sensors or learned from data at the beginning of each planning horizon. To cope with the difficulties and challenges to solve the problem, a hierarchical distributed method was proposed, in which the original optimization problem was divided into three-level subproblems and each corresponds to a part of the global objective function.…”

Section: Related Workmentioning

confidence: 99%

“…In this case study, we assume there exist heat transfer between any two of the zones. Without loss of generality, the initial temperature for the I = 5 zones are set as [26,28,28,27,27] • C, respectively. Similarly, the thermal load curves for the I = 5 zones are randomly generated according to the uniform distribution, which are shown in Fig.…”

Section: A Performance Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

HVAC Energy Cost Optimization for a Multizone Building via a Decentralized Approach

Yong

Spanos

2020

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

It has been well acknowledged that buildings account for a large proportion of the worlds energy consumption. However, the energy use of buildings, especially the heating, ventilation and air-conditioning (HVAC), is far from being efficient. There still exists a dramatic potential to save energy through improving building energy efficiency. Therefore, this paper studies the control of HVAC system for multi-zone buildings with the objective to reduce energy consumption cost while satisfying thermal comfort. In particular, the thermal couplings due to the heat transfer between the adjacent zones are incorporated in the optimization. Considering that a centralized method is generally computationally prohibitive for large buildings, an efficient decentralized approach is developed, based on the Accelerated Distributed Augmented Lagrangian (ADAL) method [1]. To evaluate the performance of the proposed method, we first compare it with a centralized method, in which the optimal solution of a small-scale problem can be obtained. We find that this decentralized approach can almost approach the optimal solution of the problem. Further, this decentralized approach is compared with the Distributed Token-Based Scheduling Strategy (DTBSS) [2]. The numeric results reveal that when the number of zones is relatively small (less than 20), the two decentralized methods can achieve a comparable performance regarding the cost of the HVAC system. However, with an increase of the number of zones in the building, the proposed decentralized approach demonstrates better performance with a considerable reduction of the total cost. Moreover, the decentralized approach proposed in this paper demonstrate better scalability with less average computation required.Note to Practitioners-Buildings accounts for a large proportion of the worlds energy consumption, especially the HVAC system. How to improve the energy efficiency of HVAC system has been recognized as an important and urgent problem for a sustainable future. Motivated by this important problem, this paper is focused on the intelligent control of HVAC system for multi-zone buildings with the objective to reduce energy consumption cost for the HVAC system while maintaining zone thermal comfort. Considering that a centralized method usually encounters computation difficulties with a large number of zones, this paper aims to develop an efficient decentralized solution. In terms of the problem, there usually exist various couplings between different zones, which both arise from the heat transfer between the neighbouring zones and the operation limits of ).the HVAC system. Moreover, this problem is nonconvex and nonlinear. Therefore, it is generally difficult to find an existing decentralized or distributed method, which are mostly established for convex optimization problems. Motivated by the recent progress on decentralized or distributed optimization for nonconvex problems, this paper proposes an efficient decentralized approach, which mainly contains three steps. In the first step, the o...

show abstract

Section: Related Workmentioning

confidence: 99%

Section: A Performance Evaluationmentioning

confidence: 99%

HVAC Energy Cost Optimization for a Multizone Building via a Decentralized Approach

Yong

Spanos

2020

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…In fact, there exist many evolutionary and swarm intelligent algorithms for coordination and combinatorial optimization in engineering [23,24], but they might not be applicable to decentralized pumps control system due to a number of reasons. Firstly, the existing evolutionary or swarm intelligent algorithm refers to quite identical individualities.…”

Section: Decentralized Optimization Based On Probability Parallel Varmentioning

confidence: 99%

Decentralized Optimization Algorithms for Variable Speed Pumps Operation Based on Local Interaction Game

Wang

Xing

Jiang

et al. 2018

Journal of Control Science and Engineering

View full text Add to dashboard Cite

A fully distributed optimal control strategy for the parallel variable speed pumps in heating, ventilation, and air-conditioning (HVAC) systems is proposed. Compared with the traditional centralized method, the efficient control and coordination are scattered to every updated smart pump without the need for a monitoring host. Similar to the structure, mechanism, and characteristics of biological communities, a smart pump can communicate with adjacent nodes and operate collaboratively to complete pumps group operation with the least total power consumption under load demand and system constraints. And a decentralized optimization method that is decentralized estimation of distribution algorithm (DEDA) under local interaction games framework has been transplanted to the proposed structure to optimize the pumps working in parallel mode. Besides, convergence property of the two novel mechanisms is analyzed theoretically. Finally, simulation studies have been conducted based on the models of a physical pumps system, and the performance of the proposed algorithm is compared with centralized algorithms in terms of both effectiveness and stability. The results provide support for the validity of the proposed algorithms and control structure.

show abstract

“…Statistics suggest that space cooling alone contributes to about 40-45% of the total building energy consumption in India. Consequently, energy optimization for space cooling maintaining thermal comfort has attracted significant attention recently (see [2,3] and references therein). While the importance of energy consumption is often exacerbated, the indoor air quality (IAQ) is not usually discussed [4].…”

Section: Introductionmentioning

confidence: 99%

“…Over the years, several control approaches for maintaining both IAQ and thermal comfort have been studied but with certain limitations. Among those, few studies implemented model predictive control (MPC) to investigate the combined (i) thermal comfort and CO 2 optimization by regulating fresh air [10], (ii) IAQ (particle concentration) and energy optimization [11], (iii) multi-objective optimization of IAQ (particulate matter) and energy consumption in subway ventilation system [12], (iv) optimization energy and IAQ with focus on CO 2 [13], and (v) energy optimization and air-quality through fresh air induction [3]. More recently, the role of demand controlled ventilation(DCV) on IAQ and energy savings was studied [14].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings

et al. 2020

Self Cite

View full text Add to dashboard Cite

Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors.

show abstract

Learning-Based Hierarchical Distributed HVAC Scheduling With Operational Constraints

Cited by 38 publications

References 16 publications

HVAC Energy Cost Optimization for a Multizone Building via a Decentralized Approach

HVAC Energy Cost Optimization for a Multizone Building via a Decentralized Approach

Decentralized Optimization Algorithms for Variable Speed Pumps Operation Based on Local Interaction Game

Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings

Contact Info

Product

Resources

About