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In a typical operation of palm oil mill, oil palm residues and palm oil mill effluent (POME) would be produced. While the oil palm residues have been well harnessed as biomass fuel, regional planning of efficient POME utilisation via biogas recovery and upgrading, coupled with possible biogas compressed natural gas (bioCNG) transshipment among the palm oil mill cluster, deserves more research and development. In this study, the objective is to design a modelling tool for optimising the oil palm biomass and POME utilisation pathway as well as bioCNG distribution network for a palm oil mill cluster with maximum simultaneous economic satisfaction level. Fuzzy optimisation approach was applied for this proposed multiple-objective modelling problem. Two case studies were simulated by the developed mathematical tool to examine the economic benefit of POME utilisation pathway in multiple-site palm oil processing complex (POPC) design. Moreover, the impact of feed-in-tariff (FIT) quota variation on POPC and bioCNG transshipment pathway designs was examined. From the simulation, it was found that POME utilisation pathway incorporation had increased the overall annual worth by MYR 15,049,096 per year due to additional revenues from bioCNG and biogas-derived electricity sales as well as utility saving. [ABSTRACT FROM AUTHOR]

The application of on-grid hybrid power system (HPS) has been effective for harnessing renewable energy resources and ensuring environmental sustainability. A number of algebraic and mathematical modeling approaches have been introduced for the optimisation of on-grid HPS. While algebraic power pinch analysis (PoPA) tools have been developed to enable the selection of cost-effective energy storage technology, the available mathematical modeling approaches have yet to consider the economics and storage system selection in the design of an optimal on-grid HPS. This work presents a mixed-integer linear programming (MILP) for the optimal design of an on-grid HPS with the minimum net present value (NPV) of the overall electricity production cost and the selection of the optimum energy storage technology. Two case studies are presented in this work. In the former, the differences between the developed MILP model and previous methods are highlighted, with sensitivity analysis to investigate the impact of electricity tariff on the on-grid HPS. In the second case study, the developed MILP model was applied to an Eco-Industrial Park (EIP) case study with energy storage technology selection. Lead-acid battery system was found to be the optimal choice due to its low investment requirement. [ABSTRACT FROM AUTHOR]