Search

This paper presents an integrated mathematical optimisation approach to synthesise a bioelectricity supply chain network with minimal costs. Detailed economic evaluation was performed to determine the optimum location of centralised or decentralised biomass pre-treatment and power plants. Once the optimum bioelectricity supply chain network is established, input-output modelling of the network is formed. Next, feasible operating range analysis is performed. A palm-based bioelectricity supply chain case study in Malaysia is used to illustrate the proposed approach. Based on the optimised results, a total of 80.90 MW of bioelectricity are generated with an estimated net present value of USD 123.94 million and a payback period of 5 years. Meanwhile, the feasible operating range analysis indicated that the synthesised bioelectricity supply chain network possessed multiple feasible operating ranges; 5.06–10.04 MW, 11.88–36.08 MW and 44.26–101.16 MW. Based on the result, the decision makers can determine the potential of the future bioelectricity projects according to different seasons of supply and demand variations.

Designing a biomass combined heat and power (CHP) system that fulfils uncertain energy demands is a challenging task. This task becomes increasingly complex when historical data and probability distributions are not well defined. This work presents a newly developed decision analysis design framework for biomass CHP system which considers three types of decision-makers, namely optimistic, pessimistic and cautious decision-makers. To illustrate the proposed framework, a palm-based biomass CHP case study is solved. In addition, sensitivity analysis is performed to evaluate the effect of Feed-in Tariff (FiT) rates towards the design of CHP system. The optimum biomass CHP design is then further analysed to determine the “must-have”, “optional” and “must-avoid” equipment within a given range of power demand. The proposed decision analysis design framework enables decision makers to make informed decisions.

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.