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Optimal dispatching of electric-thermal interconnected virtual power plant considering market trading mechanism
Journal of Cleaner Production ( IF 9.7 ) Pub Date : 2020-08-05 , DOI: 10.1016/j.jclepro.2020.123446
Weishang Guo , Pingkuo Liu , Xiaole Shu

With the development of energy internet technology, electric-thermal interconnected virtual power plant, a new integrated demand response entity, tends to become an effective solution to solve the high reliability and efficient utilization of distributed energy systems. Based on this, a new optimal dispatching method for electric-thermal interconnected virtual power plants considering market trading mechanism is established, which can effectively solve the operation and market transaction problems of complex energy systems including electricity, thermal, natural gas and other energy sources. In this paper, the structure and market trading mechanism of electric-thermal coupled virtual power plants are firstly studied. Secondly, a two-stage optimization model of virtual power plant is constructed. In the first stage, a multi-bid day-ahead market bidding model considering both economic and social benefits is constructed, which is aiming at formulating the strategy and bidding value of virtual power plant participating in energy market dispatching. In the second stage, the intra-day scheduling model is constructed, which takes the minimum penalty cost including abandoned wind penalty cost and bidding penalty cost as the optimization objective, and the output of virtual power plant is adjusted to ensure the operation efficiency of the system. Finally, an electric-thermal coupled virtual power plant in Tianjin, China, is taken as an example for analysis. The results show that the two-stage optimization model presented in this paper can significantly improve the volatility of renewable energy output and the economy of the system operation under the conditions of ensuring the comprehensive benefits of virtual power plant and participating in energy market bidding efficiently.

更新日期:2020-08-27
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