An innovative biomass-driven energy systems for green energy and freshwater production with less CO2 emission: Environmental and technical approaches

Considering the current crisis of fossil energies, the exploitation of renewables and green technologies is necessary and unavoidable. Additionally, the design and development of integrated energy systems with two or more output products and the maximum usage of thermal losses in order to improve efficiency can boost the yield and acceptability of the energy system. In this regard, this paper develops a comprehensive multi-aspect assessment of the operation of a new solar and biomass energies-driven multigeneration system (MGS). The main units installed in MGS are three electric energy generation units based on a gas turbine process, a solid oxide fuel cell unit (SOFCU) and an organic Rankine cycle unit (ORCU), a biomass energy conversion unit to useful thermal energy, a seawater conversion unit into useable freshwater, a unit for converting water and electricity into hydrogen energy and oxygen gas, a unit for converting solar energy into useful thermal energy (based on Fresnel collector), and a cooling load generation unit. The planned MGS has a novel configuration and layout that has not been considered by researchers recently. The current article is based on presenting a multi-aspect evaluation to study thermodynamic-conceptual, environmental and exergoeconomic analyzes. The outcomes indicated that the planned MGS can produce about 6.31 MW of electrical power and 0.49 MW of thermal power. Furthermore, MGS is able to produce various products such as potable water (∼0.977 kg/s), cooling load (∼0.16 MW), hydrogen energy (∼1.578 g/s) and sanitary water (∼0.957 kg/s). The total thermodynamic indexes were calculated as 78.13% and 47.72%, respectively. Also, the total investment and unit exergy costs were 47.16 USD per hour and 11.07 USD per GJ, respectively. Further, the content of CO₂ emitted from the desgined system was equal to 10.59 kmol per MWh. A parametric study has been also developed to identify influencing parameters.