Abstract
Reliable isolated energy systems are necessary for supplying energy to remote areas where grid extension is not feasible. It may also be required to harness renewable energy to reduce the use of conventional fuel that involves potentially high transportation cost and carbon emissions. Polygeneration systems are suitable for distributed energy supply in remote areas with the advantages of compactness and operational flexibility. Also, the simultaneous production of multiple utilities and products provides the opportunity for process integration, hence increased fuel efficiency and reduced carbon emissions. The challenge is to identify the optimal design of the processes such that the system remains in operation regardless of anticipated changes in raw material supply and product demand during multi-period operations. Graph theoretic models in the form of a P-graph (process graph) have previously been developed for synthesizing single period polygeneration systems. This work aims to develop a P-graph model to handle multi-period operations of isolated energy systems. The resulting network is thus more robust since it is able to operate amidst changes in the availability of raw material supply and/or variations in product demand. In addition, the P-graph model is also capable of generating near-optimal solutions which provide insights into other intangible parameters that may be significant to decision-makers. A case study will be presented to demonstrate the proposed approach.
| Original language | English |
|---|---|
| Title of host publication | Chemical Engineering Transactions |
| Editors | Petar Sabev Varbanov, Jun-Yow Yong, Jiri Jaromir Klemes, Peng-Yen Liew, Hon Loong Lam |
| Publisher | Italian Association of Chemical Engineering - AIDIC |
| Pages | 865-870 |
| Number of pages | 6 |
| Volume | 52 |
| ISBN (Electronic) | 9788895608426 |
| DOIs | |
| Publication status | Published - 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- General Chemical Engineering
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