Digital power plant is the theory and method to improve the operating quality of power plant by quantifying, analyzing, controlling and deciding the physical and working objects of power plants in the whole life cycle. Signals and management information of power plants will be digitized, so as to realize information exchange reliably and accurately and large-scale distributed resource sharing based on the network technology. Then optimization decisions and scientific guidance for plant operation will be proposed by intelligent expert system based on the digital resources. Therefore, the foundation of digital power plant is system modeling and performance analysis. However, there are some problems in the process of the modeling performance analysis of digital power plant. For instance, each unit of the system model has different dimensions and different type of mathematical description, and the data or information used for modeling are defined differently and belong to different enterprises, who do not want to share their information. Metamodeling is potential to solve these problems. It defines the specification to describe a unit and the relationship between different elements. Compared with traditional modeling methodologies for thermal systems, metamodeling makes the model more standardized, and the relationship of the model elements is more explicit and better understood by the co-simulation partners. In this paper, the collaborative modeling and simulation platform for digital power plant has been established based on the metamodeling method and the performance of the target plant has been analyzed from different aspects via field data. The metamodeling method consists of three parts: syntax definition, model development and algorithm definition. The result shows that the collaborate modeling and simulation platform can be used to reduce costs, decrease equipment failure rate, and improve plant output, so as to guarantee the safety and increase economics.
Performance analysis of organic solar cells: Opto-electrical modeling and simulation
