Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6680215 | Applied Energy | 2018 | 14 Pages |
Abstract
Pilot-scale distributed polygeneration system driven by solar energy and its effective simulation mechanism provides promising solutions for the technology promotion and implementation, as the emerging of smart grid concepts. In this regard, this study aims to preliminary test such a system based on organic Rankine cycle with the power output of 200â¯kW, which is combined with cooling and heating cycle. The developed pilot system is proven to sustain the power thermal efficiency of 10% with R123 and a self-made expansion valve. Targeting a whole optimized system in practical application, a multi-time scale mechanism is proposed and consists of long-, mid- and short-term simulation with yearly, hourly and second time step, respectively. The functionality of the concept is proven by showing the model-guided optimal sequential system with hexamethyldisiloxane working fluid. It achieves a high performance ratio, efficient cost, and less land occupation, corresponding to 67.61%, $0.12 million and 3774.2â¯m2, respectively, under the long-term simulation. Rated operation decisions are correspondingly determined and present acceptable supply-and-demand matching performance at the level of mid-term modeling, with the payback time of 7.41â¯years. Furthermore, the system dynamic behavior is analyzed in two typical sunny and cloudy days to understand and compare its running states. The short-term model shows a steady thermal efficiency of 9.6% within 15,000â¯s and capture a smaller period of safety state only within 6000â¯s under the sunny day condition. Although the peak irradiance in the cloudy day is higher than that in the sunny day, the performance degrades dramatically due to the irradiance fluctuation. It is expected that the proposed mechanism can be extended in analyzing operational security and control strategy.
Keywords
Related Topics
Physical Sciences and Engineering
Energy
Energy Engineering and Power Technology
Authors
Ying Zhang, Shuai Deng, Li Zhao, Shan Lin, Jiaxin Ni, Minglu Ma, Weicong Xu,