A Systematic Approach for the Optimal Design of an Off-Grid Polygeneration System using Fuzzy Linear Programming Model

Aristotle T. Ubando, Isidro Antonio Marfori, Alvin B. Culaba, Jonathan R. Dungca, Michael Angelo B. Promentilla, Kathleen B. Aviso, Raymond R. Tan

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)


Polygeneration systems provide an avenue for the production of clean energy. It consists of interdependent processes which seek opportunities to reuse by-products of processes to increase the thermodynamic efficiency of the system further, hence, making it challenging to design. This study looks into designing a polygeneration system for an off-grid community which considers the use of a micro-hydro power plant as the base technology, and a biomass-based Sterling engine together with a diesel engine plant as potential backup power generating technology. In addition to electricity, the community also intends to generate purified water through a water treatment facility and manufacture ice through an ice plant. A fuzzy linear programming model is used to identify the best polygeneration system design which simultaneously maximizes the product output, maximizes the profit, and minimizes the capital costs. A hypothetical but realistic case study of an off-grid polygeneration system is used to demonstrate the developed model consisting of a micro-hydro plant, an ice plant, and a water treatment facility for the community. The model selects an appropriate backup power generating technology. The results show two optimal configurations of polygeneration plants given varying scenarios. Furthermore, sensitivity analysis is conducted to highlight the overall degree of satisfaction across the various values of profit and capital costs. This developed model shall aid the national and local government officials together with engineers in the design of a polygeneration system for off-grid communities.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Number of pages6
Publication statusPublished - 2017 Oct

Publication series

NameComputer Aided Chemical Engineering
ISSN (Print)1570-7946

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications


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