A multi-objective optimization and multi-criteria evaluation integrated framework for distributed energy system optimal planning
•Propose an optimization and evaluation integrated framework.•Establish a Mixed Integer Non-linear Programming optimal planning model.•Conduct multi-objective optimization by Ɛ-constraint method.•Identify Pareto-optimal solution through three decision making methods.•An Analytic Hierarchy Process an...
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| Published in: | Energy conversion and management Vol. 166; pp. 445 - 462 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Oxford
Elsevier Ltd
15.06.2018
Elsevier Science Ltd |
| Subjects: | |
| ISSN: | 0196-8904, 1879-2227 |
| Online Access: | Get full text |
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| Abstract | •Propose an optimization and evaluation integrated framework.•Establish a Mixed Integer Non-linear Programming optimal planning model.•Conduct multi-objective optimization by Ɛ-constraint method.•Identify Pareto-optimal solution through three decision making methods.•An Analytic Hierarchy Process and Gray Relation Analysis combined evaluation.
This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria evaluation issues simultaneously. The framework can be decomposed into two stages. At the optimization stage, the system design and dispatch are optimized considering multiple objectives by Ɛ-constraint method. Three decision making approaches are applied to identify the Pareto optimal solution. At the evaluation stage, a combined Analytic Hierarchy Process and Gray Relation Analysis method is proposed to evaluate and rank various optimal solutions when different objectives and cases are considered. Two stages of work are integrated by introducing the baseline conditions. As an illustrative example, an optimal planning model for a solar-assisted Solid Oxide Fuel Cell distributed energy system is proposed by Mixed Integer Non-linear Programming approach firstly. Then, the system is applied to different cases considering two types of buildings located in three climate zones. The obtained optimal solutions are further evaluated by the proposed multi-criteria evaluation method. Therefore, the overall optimal system design and dispatch strategy, as well as the best demonstration site can be identified comprehensively considering multiple objectives. In general, the results have verified the effectiveness of the proposed framework. |
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| AbstractList | This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria evaluation issues simultaneously. The framework can be decomposed into two stages. At the optimization stage, the system design and dispatch are optimized considering multiple objectives by Ɛ-constraint method. Three decision making approaches are applied to identify the Pareto optimal solution. At the evaluation stage, a combined Analytic Hierarchy Process and Gray Relation Analysis method is proposed to evaluate and rank various optimal solutions when different objectives and cases are considered. Two stages of work are integrated by introducing the baseline conditions. As an illustrative example, an optimal planning model for a solar-assisted Solid Oxide Fuel Cell distributed energy system is proposed by Mixed Integer Non-linear Programming approach firstly. Then, the system is applied to different cases considering two types of buildings located in three climate zones. The obtained optimal solutions are further evaluated by the proposed multi-criteria evaluation method. Therefore, the overall optimal system design and dispatch strategy, as well as the best demonstration site can be identified comprehensively considering multiple objectives. In general, the results have verified the effectiveness of the proposed framework. •Propose an optimization and evaluation integrated framework.•Establish a Mixed Integer Non-linear Programming optimal planning model.•Conduct multi-objective optimization by Ɛ-constraint method.•Identify Pareto-optimal solution through three decision making methods.•An Analytic Hierarchy Process and Gray Relation Analysis combined evaluation. This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria evaluation issues simultaneously. The framework can be decomposed into two stages. At the optimization stage, the system design and dispatch are optimized considering multiple objectives by Ɛ-constraint method. Three decision making approaches are applied to identify the Pareto optimal solution. At the evaluation stage, a combined Analytic Hierarchy Process and Gray Relation Analysis method is proposed to evaluate and rank various optimal solutions when different objectives and cases are considered. Two stages of work are integrated by introducing the baseline conditions. As an illustrative example, an optimal planning model for a solar-assisted Solid Oxide Fuel Cell distributed energy system is proposed by Mixed Integer Non-linear Programming approach firstly. Then, the system is applied to different cases considering two types of buildings located in three climate zones. The obtained optimal solutions are further evaluated by the proposed multi-criteria evaluation method. Therefore, the overall optimal system design and dispatch strategy, as well as the best demonstration site can be identified comprehensively considering multiple objectives. In general, the results have verified the effectiveness of the proposed framework. |
| Author | Zhu, Xingyi Li, Ning Wang, Wei Shah, Nilay Jing, Rui Zhu, Zhiyi Meng, Chao Zhao, Yingru |
| Author_xml | – sequence: 1 givenname: Rui surname: Jing fullname: Jing, Rui organization: College of Energy, Xiamen University, Xiamen, China – sequence: 2 givenname: Xingyi surname: Zhu fullname: Zhu, Xingyi organization: College of Energy, Xiamen University, Xiamen, China – sequence: 3 givenname: Zhiyi surname: Zhu fullname: Zhu, Zhiyi organization: East & West Region, CLP Power Hong Kong Limited, Hong Kong Special Administrative Region – sequence: 4 givenname: Wei surname: Wang fullname: Wang, Wei organization: College of Energy, Xiamen University, Xiamen, China – sequence: 5 givenname: Chao surname: Meng fullname: Meng, Chao organization: College of Energy, Xiamen University, Xiamen, China – sequence: 6 givenname: Nilay surname: Shah fullname: Shah, Nilay organization: Department of Chemical Engineering, Imperial College London, London, UK – sequence: 7 givenname: Ning surname: Li fullname: Li, Ning organization: College of Energy, Xiamen University, Xiamen, China – sequence: 8 givenname: Yingru orcidid: 0000-0003-3513-9451 surname: Zhao fullname: Zhao, Yingru email: yrzhao@xmu.edu.cn organization: College of Energy, Xiamen University, Xiamen, China |
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| Keywords | Distributed energy system Multi-objective optimization Solid Oxide Fuel Cell Mixed Integer Non-linear Programming Multi-criteria evaluation Decision making |
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| Snippet | •Propose an optimization and evaluation integrated framework.•Establish a Mixed Integer Non-linear Programming optimal planning model.•Conduct multi-objective... This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria... |
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| SubjectTerms | Analytic hierarchy process buildings climatic zones Criteria Decision making Design engineering Design optimization Distributed control systems Distributed energy system Energy Energy management fuel cells Mixed integer Mixed Integer Non-linear Programming Multi-criteria evaluation Multi-objective optimization Multiple criteria decision making Multiple objective analysis Nonlinear programming Optimization planning Solid Oxide Fuel Cell Solid oxide fuel cells Systems design systems engineering |
| Title | A multi-objective optimization and multi-criteria evaluation integrated framework for distributed energy system optimal planning |
| URI | https://dx.doi.org/10.1016/j.enconman.2018.04.054 https://www.proquest.com/docview/2076368682 https://www.proquest.com/docview/2220842361 |
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