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Energy quality management for building clusters and districts (BCDs) through multi-objective optimization
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering.
2014 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 79, 525-533 p.Article in journal (Refereed) Published
Abstract [en]

Renewable energy systems entail a significant potential to meet the energy requirements of building clusters and districts (BCDs) provided that local energy sources are exploited efficiently. Besides improving the energy efficiency by reducing energy consumption and improving the match between energy supply and demand, energy quality issues have become a key topic of interest. Energy quality management is a technique that aims at optimally utilizing the exergy content of various renewable energy sources. In addition to minimizing life-cycle CO2 emissions related to exergy losses of an energy system, issues such as system reliability should be addressed. The present work contributes to the research by proposing a novel multi-objective design optimization scheme that minimizes the global warming potential during the life-cycle and maximizes the exergy performance, while the maximum allowable level of the loss of power supply probability (LPSP) is predefined by the user as a constraint. The optimization makes use of Genetic Algorithm (GA). Finally, a case study is presented, where the above methodology has been applied to an office BCD located in Norway. The proposed optimization scheme is proven to be efficient in finding the optimal design and can be easily enlarged to encompass more relevant objective functions.

Place, publisher, year, edition, pages
2014. Vol. 79, 525-533 p.
Keyword [en]
Building clusters and districts, Exergy efficiency, Genetic algorithm, Life cycle CO2 equivalent, LPSP, Renewable energy system
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-142337DOI: 10.1016/j.enconman.2013.12.051ISI: 000333946700055Scopus ID: 2-s2.0-84893061812OAI: oai:DiVA.org:kth-142337DiVA: diva2:699719
Note

QC 20140228

Available from: 2014-02-28 Created: 2014-02-28 Last updated: 2017-12-05Bibliographically approved
In thesis
1. Energy Quality Management for Building Clusters and Districts Using a Multi-Objective Optimization Approach
Open this publication in new window or tab >>Energy Quality Management for Building Clusters and Districts Using a Multi-Objective Optimization Approach
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

As society develops, energy needs and the warnings of global warming have become main areas of focus in many areas of human life. One such aspect, the building sector, needs to take responsibility for a significant portion of energy use. Researchers need to concentrate on applying innovative methods for controlling the growth of energy use. Apart from improving energy efficiency by reducing energy use and improving the match between energy supply and demand, energy quality issues have become a key topic of interest. Energy quality management (EQM) is a technique that aims to optimally utilize the exergy content of various renewable energy sources. The evaluation of the optimum energy systems for specific districts is an essential part of EQM.

The optimum energy system must follow the concept of “sustainability.” In other words, the optimization process should select the most suitable energy systems, which fulfill various sustainable requirements such as high energy/exergy performance, low environmental impacts and economic cost, as well as acceptable system reliability. A common approach to dealing with complex criteria involves multi-objective optimization, whereby multi-objective optimization is applied in the context of EQM of building clusters and districts (BCDs). In the present thesis, a multi-objective optimization process is proposed that applies a genetic algorithm (GA) to address non-linear optimization problems. Subsequently, four case studies are used to analyze how the multi-objective optimization process supports EQM of BCDs. Detailed information about these cases is provided below:

1. Basic case (UK): This case is used to investigate the application possibility of the approach in BCD energy system design and to analyze the optimal scenario changes, along with variations of optimization objective combinations. This approach is proven to be time-effective

2. Case 1 (Norway): The use of renewable energy sources can be highly intermittent and dependent on local climatic conditions; therefore, energy system reliability is a key parameter be considered for the renewable energy systems. This section defines system reliability as a constraint function and analyzes the system changes caused by the varying reliability constraints. According to the case, system reliability has been proven to be one of the most important objectives for the optimization of renewable energy systems.

3. Case 2 (China): In this section, the approach is applied in order to search for the optimal hybrid system candidates for a net-zero exergy district (NZEXD) in China. Economic analysis is included in this case study. Through the optimization process, the proposed approach is proven to be flexible and capable of evaluating distinct types of energy scenarios with different objective functions. Moreover, the approach is able to solve practical issues, such as identifying the most feasible options to the stepwise energy system transition for a specific case.

4. Case 3 (China): This section makes two major contributions. The first is to test the expansibility of inserting additional objectives into the approach; a parametric study is then applied to investigate the effects of different energy parameters. The second contribution is the conclusion that the optimum energy systems might vary significantly, depending on certain parameters.

According to the analyses in these case studies, the multi-objective optimization approach is capable of being a tool for future BCDs’ energy system design. It should also be noted that the findings from the case studies – especially the parametric study – might provide some interesting research topics for future work.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 79 p.
Series
TRITA-IES, 2015:06
National Category
Civil Engineering
Research subject
Civil and Architectural Engineering
Identifiers
urn:nbn:se:kth:diva-179063 (URN)978-91-7595-786-9 (ISBN)
Public defence
2016-01-14, SalF3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20151211

Available from: 2015-12-11 Created: 2015-12-10 Last updated: 2015-12-11Bibliographically approved

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