| Author: | Li, Hangxin |
| Title: | Robust optimal design and online optimal control of zero/low energy buildings |
| Advisors: | Wang, Shengwei (BSE) |
| Degree: | Ph.D. |
| Year: | 2020 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Sustainable buildings -- Design and construction Buildings -- Environmental engineering |
| Department: | Department of Building Services Engineering |
| Pages: | xxvii, 192 pages : color illustrations |
| Language: | English |
| Abstract: | Energy conservation and environmental protection are among the most critical issues faced by the sustainable development of human societies. Zero and low energy buildings, as efficient means, are attracting increasing attentions from the society, government and professionals. Design and control play significant roles in achieving the zero/low energy goal and high energy efficiency for zero/low energy buildings. However, an effective design optimization method is still absent to identify global optimal design solutions for the entire zero/low energy buildings, including building envelope and energy systems, when a large number of design variables are involved. The impacts of uncertainties, which exist throughout building life cycle and probably lead to the failure of achieving zero/low energy goal, are ignored in current design practice. In addition, real-time multi-objective optimal control of energy systems is seldom studied. An effective approach is needed to achieve online multi-objective optimization for online multi-objective optimal controls. This study therefore aims to develop an effective and comprehensive optimal design method for zero/low energy buildings concerning uncertainties, and to develop an online multi-objective optimal control strategy for energy systems in zero/low energy buildings. A coordinated optimal design method is proposed for the entire zero/low energy buildings on the basis of the existing multi-stage design optimization methods to effectively identify the global optimal design solutions, which need to consider the design optimization of building envelope and energy systems as a whole. It considers the interactions between design optimizations of building envelope and energy systems using an iterative approach. The results and experiences of the case studies show that the proposed coordinated design method can provide global optimal designs with robust performance efficiently. The life cycle "cost" of the optimal designs is 4% less and unmet cooling load is over 22% less compared with that given by existing multi-stage design optimization methods. The impacts of alternative objective functions for robust optimal design concerning uncertainties are studied. A proper objective function for robust design optimization in building energy field is identified by analyzing and comparing the commonly-used objective functions in pioneer fields. Results show that the commonly-used objective functions in pioneer fields are not suitable if applied in building energy field directly without proper revisions. Revisions to objective functions, particularly the involvement of variance of performance indicator, are proposed for robust design optimization of buildings. A coordinated robust design optimization method is proposed for the entire zero/low energy buildings by considering uncertainties and the interactions between robust design optimizations of building envelope and energy systems, based on the coordinated optimal design method and robust optimal design method proposed. Point estimate method is used to quantify the uncertainties in the design inputs. The results of the case study show that the coordinated robust optimal design method is most robust in sustaining possible uncertainties in operation followed by coordinated optimal design method, compared with the existing multi-stage design methods. The coordinated robust optimal design achieved has 97% less accumulated unmet cooling load and 42% less system design objective value in average under possible uncertain scenarios, compared with that given by existing multi-stage design optimization methods. A coordinated online multi-objective optimal control strategy consisting of two control optimization schemes are proposed for the predictive scheduling and real-time optimal control of energy systems in zero/low energy buildings. A cooperative game theory-based method is adopted for the online multi-objective optimizations. The control strategy and schemes are tested and evaluated on the energy systems with battery storage in the reference building. The test results show that it is essential and beneficial to coordinate the predictive scheduling and real-time optimal control in actual operation. The cooperative game theory-based method is effective for the online multi-objective optimization without the need of setting weights of different objectives. |
| Rights: | All rights reserved |
| Access: | open access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022378658903411.pdf | For All Users | 2.77 MB | Adobe PDF | View/Open |
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