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Transition path towards hybrid systems in China: Obtaining net-zero exergy district using a multi-objective optimization method
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Building Service and Energy Systems. Electric Power Research Institute, Yunnan Electric Power and Research Institute (Group), Kunming, China .
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2014 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 85, 524-535 p.Article in journal (Refereed) Published
Abstract [en]

A hybrid energy system including both off-site and distributed energy sources, energy conversion technologies and operation methods, is a necessary step on a transition path towards a sustainable energy system. The challenge is to identify such a combination of design options that result in minimum life cycle cost (LCC) and maximum exergy efficiency (EE) at each phase of the transition path. In this paper, a time-effective multi-objective optimization method based on genetic algorithm (GA), is proposed for the transition path problem. The proposed model makes use of a fitness function approach to reduce the model into one objective function and to reduce the computational time. In a case study, the model is applied to a potential net-zero exergy district (NZEXD) in Hangzhou, China. Here, three possible hybrid energy scenarios and three preference treatment strategies are analyzed. The study suggests that the proposed approach is workable for the identification of the most feasible options to be gradually integrated in an NZEXD in a multi-stage process. In the Hangzhou case, with the reduction of investments in distributed energy components and escalating market prices of fossil fuels, distributed energy system (DES) may have more feasibility in the near future.

Place, publisher, year, edition, pages
2014. Vol. 85, 524-535 p.
Keyword [en]
Exergy efficiency, Genetic algorithm, Hybrid energy system, Life cycle cost, Net-zero exergy district, Transition path
National Category
Energy Engineering
URN: urn:nbn:se:kth:diva-161040DOI: 10.1016/j.enbuild.2014.09.074ISI: 000348880900052ScopusID: 2-s2.0-84908360984OAI: diva2:794615

QC 20150311

Available from: 2015-03-12 Created: 2015-03-06 Last updated: 2015-12-11Bibliographically 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.
TRITA-IES, 2015:06
National Category
Civil Engineering
Research subject
Civil and Architectural Engineering
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)

QC 20151211

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

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