Hierarchical optimal scheduling method of heat-electricity integrated energy system based on Power Internet of Things. (1st November 2020)

• Record Type: Journal Article
• Authors: Kong, Xiangyu; Sun, Fangyuan; Huo, Xianxu; Li, Xue; Shen, Yu
• Is Part Of: Energy. Volume 210(2020)
• Publication Date: 2020-11-01
• Subjects: Integrated energy system -- Power internet of things -- Bi-level optimization -- Demand response; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118590
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: To guarantee the heat demand during winter, most combined heat and power (CHP) units in the integrated energy system (IES) usually work under following heat load (FTL) mode, and the renewable energy accommodation is limited. With the development of Power Internet of Things (PIoT), the information exchange in IES become more frequent. Through flexible interaction between different networks in IES, the accommodation capacity of renewable energy can increase significantly. Therefore, this paper focus on the optimization of IES under the background of PIoT. Firstly, based on the influence of PIoT on IES, a novel integrated demand response (DR) way and the model of the critical components in IES are established. Secondly, a Bi-level economic dispatching method for regional IES is developed, considering the cyber-physical infrastructure of PIoT and IES. The upper level of the dispatching method is used to optimize the overall IES operation; the lower level is to optimize the output of demand-side facilities and integrated DR. Thirdly, with adaptive particle swarm optimization (APSO) algorithm, the solution method for the Bi-level dispatch is established. Finally, the feasibility and effectiveness of the proposed method are verified in a standard IES and a real system in northern China. Highlights: Dispatching method of integrated energy system (IES) under Power Internet of Things (PIoT) background is proposed. The proposed method can utilize the flexibility of the demand side under PIoT background. Bi-level optimization model is used for the proposed method. The proposed method can facilitate the accommodation of renewable energy and reduce the operation cost of IES.