Abstract
It is a great challenge to identify optimum technologies for CHP systems that utilise biomass and convert it into heat and power. In this respect, industry decision makers are lacking in confidence to invest in biomass CHP due to economic risk from varying energy demand. This research work presents a linear programming systematic framework to design biomass CHP system based on potential loss of profit due to varying energy demand. Minimax Regret Criterion (MRC) approach was used to assess maximum regret between selections of the given biomass CHP design based on energy demand. Based on this, the model determined an optimal biomass CHP design with minimum regret in economic opportunity. As Feed-in Tariff (FiT) rates affects the revenue of the CHP plant, sensitivity analysis was then performed on FiT rates on the selection of biomass CHP design. Besides, design analysis on the trend of the optimum design selected by model was conducted. To demonstrate the proposed framework in this research, a case study was solved using the proposed approach. The case study focused on designing a biomass CHP system for a palm oil mill (POM) due to large energy potential of oil palm biomass in Malaysia.
Highlights
Global energy demands are projected to increase 48% from 2012 by 2040 [1, 2]
To select the optimum design of combined heat and power (CHP) plant throughout the wide range of power demand, Minimax Regret Criterion (MRC) approach was utilised as described in methodology
This research work had presented a linear programming systematic framework to design biomass CHP system based on potential loss of profitable opportunity due to varying energy demand
Summary
Global energy demands are projected to increase 48% from 2012 by 2040 [1, 2]. To meet this projected increase in energy demand, biomass energy is expected to play an imperative role over the coming years. Global biomass energy demands from 2000 to 2015 have seen a significant increase as compared to stable hydropower demands [3]. Such increase indicates that biomass is gaining attention in the renewable energy market. Biomass can be categorised into lignocellulose biomass, municipal waste and animal manure. These biomass resources can be obtained from agricultural residues, biomass plantations and organic wastes from residential areas [4]. Due to the high availability of lignocellulose biomass, recent studies on biomass utilisation focus on converting biomass into bioenergy and biofuels
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