Design optimization of a hybrid solar-biomass plant to sustainably supply energy to industry: Methodology and case study

To gain the benefits of solar-biomass cogeneration plant, supplying energy to industry, the design optimization procedure is required to holistically integrate economical, technical and environmental aspects. This entails formulation of a performance criterion that maximizes solar fraction, reduces...

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Bibliographic Details
Published inEnergy (Oxford) Vol. 220; p. 119736
Main Authors Tilahun, Fitsum Bekele, Bhandari, Ramchandra, Mamo, Mengesha
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.04.2021
Elsevier BV
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Summary:To gain the benefits of solar-biomass cogeneration plant, supplying energy to industry, the design optimization procedure is required to holistically integrate economical, technical and environmental aspects. This entails formulation of a performance criterion that maximizes solar fraction, reduces investment cost, lowers thermal storage loss and puts less pressure on biomass resources. It is also necessary to consider factors influencing the plant’s performance while giving active role to industrial demand. This kind of optimization approach adaptively evolves as influences change and is not static. However, such a criterion is not yet part in many of the existing design optimization schemes. In this work, an alternative optimization approach that addresses the aforementioned issues is proposed. To this end, a molten salt biomass boiler is modeled in MATLAB and integrated to a solar plant model in TRNSYS. The resulting configuration is latter optimized in GenOpt to minimize biomass power utilization index (BPUI) and excess saturated steam generation (ESSG). Demonstrated by a case study, a plant efficiency of 31.5% with 23.5% solar gain is optimally designed resulting in about 0.094$/kWh levelized cost of generation. Furthermore, considering global power outage loss, the hybrid plant could be seen as a preferred industrial source of energy. •A holistic design optimization integrating technical, economic and environmental factors.•Designed and optimized in TRNSYS/MATLAB.•A case study conducted leading to 31.5% power plant efficiency with 0.13$/kWh LCOE.•Economically feasible only under power outage loss and/or improved electricity tariff.
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2020.119736