A P-graph model for multi-period optimization of sustainable energy systems

被引:29
|
作者
Aviso, Kathleen B. [1 ]
Lee, Jui-Yuan [2 ]
Dulatre, Jonathan Carlo [1 ]
Madria, Venn Royce [1 ]
Okusa, James [1 ]
Tan, Raymond R. [1 ]
机构
[1] De La Salle Univ, Chem Engn Dept, 2401 Taft Ave, Manila 0922, Philippines
[2] Natl Taipei Univ Technol, Dept Chem Engn & Biotechnol, 1 Sec 3,Zhongxiao E Rd, Taipei 10608, Taiwan
关键词
Sustainable energy system; Process integration; Process network synthesis; P-graph; Hybrid renewable energy system; Polygeneration system; TRIGENERATION SYSTEMS; NETWORK SYNTHESIS; RENEWABLE ENERGY; SUPPLY CHAINS; EFFICIENT USE; POLYGENERATION; DESIGN;
D O I
10.1016/j.jclepro.2017.06.044
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Deployment of efficient, integrated energy systems can make a substantial contribution to reduction in greenhouse gas emissions. Such systems are suitable for the provision of distributed energy supply in remote areas, and offer the advantages of compactness and operational flexibility. Also, the simultaneous production of multiple products provides the opportunity for Process Integration, thus leading to improved fuel efficiency and reduced carbon emissions. Process Systems Engineering methods can be applied for the synthesis of such sustainable energy systems. For example, process graph (or P-graph) models have previously been developed for synthesizing single-period polygeneration systems based on the Process Network Synthesis framework. In this work, a P-graph model for multi-period optimization of sustainable energy systems is developed. The model is able to synthesize flexible systems that can cope with changes in the availability of raw material supply and variations in product demand. In addition, the P-graph model is also capable of generating near-optimal solutions, which provide insights that may be significant to decision-makers, such as structural features that are common to a range of good solutions. Two case studies are presented to demonstrate the approach developed in this work. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1338 / 1351
页数:14
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