Multi-Scenario scheduling optimisation for a novel Double-Stage ammonia absorption refrigeration system incorporating an organic Rankine cycle

Multi-Scenario scheduling optimisation for a novel Double-Stage ammonia absorption refrigeration system incorporating an organic Rankine cycle

Článek WoS

The coal chemical industry is facing severe challenges in energy conservation and emission reduction. High-value utilisation of waste heat is an effective method to solve the problem. However, the bottleneck is the utilisation of surplus low-grade waste heat full of uncertainty, challenging in its scale configuration and stable operation. This research firstly proposed a double-stage ammonia absorption refrigeration system incorporating an organic Rankine cycle. The proposed system can utilise waste heat as low as 52 degrees C to produce -40 degrees C cold energy. The lowest heat sink temperature in the refrigeration section could be 95 degrees C, with a coefficient of performance exceeding 0.30. With respect to waste heat fluctuation, a data-driven distributionally robust optimisation framework was proposed. By executing this method, multiple scenarios with similar data features could be generated. The uncertainty set was established in each scenario according to the probability density of the uncertain parameters. The uncertainty set was transformed into constraints of an adaptive genetic algorithm to create a balance between energy saving and operational stability. The proposed system and optimisation algorithm were then verified by a coal-to-SNG process. It was found that the unit cost of the waste heat refrigeration was 85% smaller than that of the original system and that the operational stability was improved to 97%. The waste heat utilisation for the whole process reduced the operating cost and carbon emission by 15% and 14%. Techno-economic analysis proved the feasibility of waste heat utilisation in economic performance, environmental protection and operational stability.

The coal chemical industry is facing severe challenges in energy conservation and emission reduction. High-value utilisation of waste heat is an effective method to solve the problem. However, the bottleneck is the utilisation of surplus low-grade waste heat full of uncertainty, challenging in its scale configuration and stable operation. This research firstly proposed a double-stage ammonia absorption refrigeration system incorporating an organic Rankine cycle. The proposed system can utilise waste heat as low as 52 degrees C to produce -40 degrees C cold energy. The lowest heat sink temperature in the refrigeration section could be 95 degrees C, with a coefficient of performance exceeding 0.30. With respect to waste heat fluctuation, a data-driven distributionally robust optimisation framework was proposed. By executing this method, multiple scenarios with similar data features could be generated. The uncertainty set was established in each scenario according to the probability density of the uncertain parameters. The uncertainty set was transformed into constraints of an adaptive genetic algorithm to create a balance between energy saving and operational stability. The proposed system and optimisation algorithm were then verified by a coal-to-SNG process. It was found that the unit cost of the waste heat refrigeration was 85% smaller than that of the original system and that the operational stability was improved to 97%. The waste heat utilisation for the whole process reduced the operating cost and carbon emission by 15% and 14%. Techno-economic analysis proved the feasibility of waste heat utilisation in economic performance, environmental protection and operational stability.

Waste heat refrigeration; Uncertainty; Multi -scenario scheduling optimisation

Waste heat refrigeration; Uncertainty; Multi -scenario scheduling optimisation

Liu, S., Qian, Y., Li, D., Klemeš, J.J., Yang, S.

2023

15.10.2022

PERGAMON-ELSEVIER SCIENCE LTD

OXFORD

0196-8904

ENERGY CONVERSION AND MANAGEMENT

270

Spojené království Velké Británie a Severního Irska

18

https://www.sciencedirect.com/science/article/pii/S0196890422009505