Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle (ORC) based combined systems

Zhou, Jianzhao; Chu, Yin Ting; Ren, Jingzheng; Shen, Weifeng; He, Chang

doi:10.1016/j.energy.2023.128218

Cited by 19 publications

(1 citation statement)

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“…Zhou and colleagues undertook an extensive study comparing optimization times between ANN and mechanistic models. The findings reveal that ANN achieves an optimization time of approximately 0.135 s, whereas mechanistic models require over 10 h. Notably, the accuracy rate of ANN impressively reaches 99% [39]. By leveraging an ANN-based model, remarkable levels of optimization and design detail were attained by Chen et al, the results demonstrating that the model reduces calculation time by more than 50% [40].…”

Section: Literature Reviewmentioning

confidence: 97%

Optimizing Solar Energy Harvesting through Integrated Organic Rankine Cycle–Reverse Osmosis Systems: A Techno–Economic Analysis

Wang,

Zhou,

Rahbari

2023

Sustainability

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When it comes to seawater desalination in the small- to medium-electricity ranges, the organic Rankine cycle (ORC) powered by solar energy stands out as the most energy-efficient technology currently available. Various solar techniques have been developed to capture and absorb solar energy. Among them, the parabolic trough collector (PTC) has gained recognition as a low-cost solar thermal collector with a long operating life. This study investigates the thermodynamic performance and economic parameters of a PTC-powered ORC using Dowtherm A and toluene as working fluids for the solar cycle and ORC cycle, respectively. Thermo-economic multi-objective optimization and decision-making techniques are applied to assess the system’s performance. Four key parameters are analyzed for their impact on exergy efficiency and total hourly cost. Using TOPSIS decision-making, the best solution from the Pareto frontier is identified, featuring an ORC exergy efficiency of 30.39% and a total hourly cost of 39.38 US$/h. The system parameters include a mass flow rate of fresh water at 137.7 m3/h, a total output net power of 577.9 kJ/kg, and a district heating supply of 1074 kJ/kg. The cost analysis reveals that the solar collector represents approximately 68% of the total hourly cost at 26.77 US$/h, followed by the turbine, thermoelectric generator, and reverse osmosis (RO) unit.

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Section: Literature Reviewmentioning

confidence: 97%