Abstract
The progressive development of renewable energy technologies is attributed to the growing energy demand and the depletion of non-renewable resources. Renewable energy technologies are usually characterized by intermittent availability of resources, affecting the capability of energy systems to meet projected energy demands. Tri-generation, or the simultaneous generation of three energy types, becomes a potential solution wherein integration of renewable energy technologies is used to maximize resource efficiency. Synthesizing these systems will require the consideration of techno-economic data and the use of computer-aided techniques to facilitate optimization and design. Mixed-Integer Linear Programming is a commonly used technique for Process Network Synthesis, but its application to complex problems becomes problematic due to numerous alternatives and parameter variations. The Process graph framework offers a less laborious option with its unambiguous representation of process systems, utilizing three algorithms in generating all combinatorially feasible solutions that present the user with both optimal and near-optimal solutions. These become helpful in decision-making especially when factors such as those impossible to be captured mathematically need to be considered. This work presents a P-graph model developed for the synthesis and design of multi-period, biomass-fired, tri-generation systems with a case study for power generation in the Philippines to demonstrate its capabilities.
Highlights
Efforts to mitigate global environmental problems have resulted in the development of energy-saving and resource-conserving systems
Process systems engineering (PSE), or alternatively known as computer aided process engineering (CAPE), employs computer-aided tools in solving process network synthesis and design problems (PNS) that deal with process selection which constitutes complex industrial design [2]
P-graph modelling is an approach developed by Friedler et al [3,4] to serve as a convenient and comparable alternative to conventional Mixed Integer Linear Programming (MILP)
Summary
Efforts to mitigate global environmental problems have resulted in the development of energy-saving and resource-conserving systems. Polygeneration is one of numerous established and developing technologies that aim to conserve already sparingly available resources, and utilize them to their maximum thermodynamic potential [1] In doing so, these technologies work to generate two or more energy products, making them appreciably beneficial for areas that are characterized by insufficient resources. These technologies work to generate two or more energy products, making them appreciably beneficial for areas that are characterized by insufficient resources Utilizing these systems to their maximum potential constitutes proper process integration techniques that take into consideration both technical and economic aspects in synthesis and design. The technique boasts of high computational efficiency in coping with desired process objectives and defining the process system’s combinatorially feasible structures [3,4,5]
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