4.7 Article

Simulation and experiment investigation of a heating and power double function system with multi-objective optimization

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Publisher

ELSEVIER
DOI: 10.1016/j.seta.2021.101768

Keywords

Double function system; Power generation; Heat pump; Mathematical model; Multi-objective optimization

Funding

  1. National Key R&D Program of China [2020YFD110030]

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This study proposes a novel RCC and ORC double function system for district heating and power output. The system's thermal performance is analyzed using an energy model and verified with a test rig. Economic and environmental analysis is conducted, and multi-objective optimization is used to solve conflicting problems. Results show that the system has good feasibility and stability, providing efficient power output and heating capacity.
As conventional organic Rankine cycle (ORC) power generation and reverse Carnot cycle (RCC) heat pump systems have some limitations for a fixed heat source. This study proposed a novel RCC and ORC double function system which can work in the ORC power generation mode and RCC heat pump mode for district heating and power output, respectively. The energy model is firstly established to analyze the system thermal performance and then a test rig is built to verify the performance of the system and validate the mathematical model. The economic and environmental analysis are conducted and the multi-objective optimization (MOP) method has been conducted to solve the conflicting problem between the capital cost and payback period under the different operating conditions. Results indicate that the system has good feasibility and stability which can provide 5.96 kW power output with the thermal efficiency of 5.23 % and 60.02 kW heating capacity with the COP of 2.85. The errors of the experiment to simulation COP and the error of experiment to simulation thermal efficiency value are all less than 10%. The optimization consequences based on the TOPSIS decision-making and NSGA-II technology indicate that the MOP solution has a better performance compared with the single-objective optimization.

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