Thermodynamic modeling and multi-objective evolutionary-based optimization of a new multigeneration energy system

Performance assessment and optimization of a novel integrated multigeneration system for residential buildings

Exergoeconomic assessment and multi-objective optimization of a solar chimney integrated with waste-to-energy

Multi-objective optimization and exergo-economic assessment of a solar-biomass multi-generation system based on externally-fired gas turbine, steam and organic Rankine cycle, absorption chiller and multi-effect desalination

Proposal and assessment of a novel geothermal combined cooling and power cycle based on Kalina and ejector refrigeration cycles

Thermodynamic and exergoeconomic analysis of a novel solar-assisted multigenerational system utilizing high temperature phase change material and hybrid nanofluid

Green hydrogen & electricity production via geothermal-driven multi-generation system: Thermodynamic modeling and optimization

This paper presents a novel design for a solar-powered desalination system utilizing a single-effect absorption refrigeration cycle with a flat-plate solar collector. The NH3-H2O working fluid pair in the refrigeration subsystem produces chilled water while the rejected heat from the condenser drives a humidification-dehumidification (HDH) subsystem for freshwater generation. This cycle has been analyzed thermodynamically and exergetically to understand its key performance parameters. Furthermore, for a detailed examination and optimization, an exergoeconomic analysis was also conducted. Design parameters for this study include the tilt angle of the solar collector, Volume fraction of nanoparticles in the CuO nanofluid, Solar collector area, Base fluid mass flow rate in the collector, Mass flow rate of the strong solution, Absorber and condenser temperatures, Mass ratio and Humidifier effectiveness. The Objective functions used to evaluate the system, performance are the Cooling effect of performance (COP), Energy performance (EP), Exergy efficiency (μExe), and the Total product cost rate of the system (Ċp,Tot). The genetic algorithm optimization is employed to find the best system performance using two sets of three objective functions. The effectiveness of multi-objective optimization using LINMAP, TOPSIS, and Shannon Entropy methods is demonstrated. LINMAP and TOPSIS consistently achieved improvements in COP (32–42 %), exergy efficiency (33–48 %), and reduced total cost (89–90 %) compared to the base point, while Shannon Entropy offered slightly lower gains. These methods consistently identify superior system configurations, achieving significant improvements in performance while minimizing the total product cost rate.

Optimization of a new renewable energy system for producing electricity, hydrogen and ammonia

The effects of the disulfide bonds of neuropsin on the enzyme activity and neurite outgrowth

• Novel system uses LNG cooling, CO₂ capture, and waste heat recovery. • Compared PEME, Alkaline, and Vanadium Chloride methane production methods. • Vanadium Chloride method shows highest exergy efficiency and lowest cost. • Methane and hydrogen yields are highest in Vanadium Chloride configuration. • Multi-criteria analyses and Grey Wolf optimization are performed. This work proposes and evaluates a novel integrated energy system for renewable methane synthesis, offering a comparative analysis of three hydrogen production routes: alkaline electrolysis, proton exchange membrane electrolysis, and the vanadium chloride thermochemical cycle. The study’s core focus lies in seeking the best method for hydrogen and subsequently methane production while incorporating LNG as the exclusive cooling and CO₂ capture medium to mitigate water-based thermal pollution to enhance process integration. Through a detailed techno-economic and multi-objective optimization via the Gray Wolf Optimizer, the system’s performance was assessed in terms of exergy efficiency, methane production rate, output power, levelized cost of products, and environmental impact. The findings reveal that while all configurations achieve high integration efficiency, the vanadium chloride-based system significantly outperforms the electrolysis alternatives, achieving superior exergy efficiency, lower product cost, and markedly higher methane yields. The integrated comparative framework and novel system configuration presented here offer valuable insights for future deployment of multi-product renewable energy systems. Under optimal conditions, the proton exchange membrane electrolysis system achieves an exergy efficiency of 31.65 %, a levelized cost of 0.131 $/kWh, and an emission index of 0.533 kg/kWh. The alkaline system shows similar performance, with an exergy efficiency of 31.84 %, a levelized cost of 0.130 $/kWh, and an emission index of 0.531 kg/kWh. Among the three systems, the vanadium chloride system demonstrates the best performance, achieving an exergy efficiency of 38.82 %, the lowest levelized cost of 0.106 $/kWh, and an emission index of 0.474 kg/kWh. Moreover, the vanadium chloride system achieves the shortest payback period at 5.96 years. This work highlights the strategic potential of renewable methane as a long-term, storable, and grid-compatible energy carrier, supporting the transition to decarbonized energy systems.

Feasibility study of green ammonia and electricity production via an innovative wind-solar-biomass polygeneration system

Risk and 4E analyses and optimization of a novel solar-natural gas-driven polygeneration system based on Integration of Gas Turbine–SCO2–ORC-solar PV-PEM electrolyzer

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

Multi-objective exergy-based optimization of a continuous photobioreactor applied to produce hydrogen using a novel combination of soft computing techniques

A solar-powered combined cooling, heating, and power (CCHP) plant integrated with a water electrolysis unit is investigated in terms of energy, exergy, and exergo-economic (3E) assessments. A comprehensive parametric study and optimization is conducted following the thermodynamic and exergo-economic assessment of the proposed system to evaluate the key performance parameters of the system for efficiency and economic factors. This system employs a heliostat field and a receiver tower by taking advantage of thermal energy from the sun and produces a continuous energy supply with an integrated phase-change material (PCM) tank to store the heat. In addition, a supercritical CO2 Rankine cycle (RC), an ejector refrigeration cooling (ERC) system, and a PEM water electrolyzer are coupled to produce cooling, heating, power, and hydrogen. Thermodynamic analysis indicates that the system exergy efficiency and energy efficiency are improved to 33.50% and 40.61%, respectively, while the total cost rate is 2875.74 USD/h and the total product cost per exergy unit is 25.65 USD/GJ. Additionally, the system produces a net generated power, heating load, and cooling load of 11.70, 13.92, and 2.60 MW, respectively, and a hydrogen production rate of 12.95 g/s. A two-objective optimization approach utilizing a non-dominated sorting genetic algorithm (NSGA) was performed, demonstrating that the system’s ideal design point offers a cost rate of 1263.35 USD/h and an exergetic efficiency of 34.17%.