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Multi-criteria optimization for a biomass gasification-integrated combined cooling, heating, and power system based on life-cycle assessment

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Abstract A multi-criteria optimization for a biomass gasification-integrated combined cooling, heating, and power (CCHP) system based on life-cycle assessment is carried out. The criteria comprise primary energy saving ratio (PESR),… Click to show full abstract

Abstract A multi-criteria optimization for a biomass gasification-integrated combined cooling, heating, and power (CCHP) system based on life-cycle assessment is carried out. The criteria comprise primary energy saving ratio (PESR), total cost saving ratio (TCSR), and CO2 emission reduction ratio (CERR). The overall-performance criterion, Cl, is obtained with Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS). Results show that the Cl reaches its maximum when the nominal electric output is 1572.8 kW, the biomass feedstock type is wood pellet, and the operation strategy is following the electric load (FEL). The PESR, TCSR, CERR, and Cl are 0.101, 0.271, 0.498, and 0.867, respectively. By comparing with reference systems, it is found that in FEL mode, the system is improved because of higher energy utilization efficiency and better use of economic and environmental advantages of biomass. In following the thermal load (FTL) mode, economic performance is compromised for optimal overall performance. Sensitivity analysis is carried out to find out the effect of variation of various parameters on optimization results. It is found that the variation of a single-aspect parameter could affect the system performance on all aspects. The variation of primary energy consumption per unit electricity from the grid (pecen,g) has the greatest effect on optimization results. The corresponding variation ranges of PESR, TCSR, and CERR owing to its variation are from −0.063/0.231/0.473 to 0.284/0.295/0.624 and from −0.029/0.101/0.314 to 0.194/0.123/0.379 in FEL and FTL modes.

Keywords: multi criteria; system; variation; biomass; optimization; criteria optimization

Journal Title: Energy Conversion and Management
Year Published: 2018

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