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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Vydáno v:Energy conversion and management Ročník 166; s. 445 - 462
Hlavní autoři: Jing, Rui, Zhu, Xingyi, Zhu, Zhiyi, Wang, Wei, Meng, Chao, Shah, Nilay, Li, Ning, Zhao, Yingru
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 15.06.2018
Elsevier Science Ltd
Témata:
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
Distributed energy system
Multi-objective optimization
Solid Oxide Fuel Cell
Mixed Integer Non-linear Programming
Multi-criteria evaluation
Decision making
ISSN:0196-8904, 1879-2227
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Shrnutí:•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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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2018.04.054