Novel planning methodology for energy stations and networks in regional integrated energy systems. (1st February 2020)

• Record Type: Journal Article
• Authors: Yan, Rujing; Wang, Jiangjiang; Zhu, Sitong; Liu, Yi; Cheng, Youliang; Ma, Zherui
• Is Part Of: Energy conversion and management. Volume 205(2020)
• Publication Date: 2020-02-01
• Subjects: Regional integrated energy system (RIES) -- Energy planning -- Kernel density estimation -- Shortest path -- Energy stations -- Energy networks; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2019.112441
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A planning methodology of energy stations and networks is proposed. Kernel density estimation can be used to help to locate the energy station. The networks are optimized using the shortest path method. The potential benefits of the modified optimization are analyzed. Abstract: The effective planning of energy stations and networks is critical for improving the economic and energy performance of regional integrated energy systems. Based on the principle of minimizing investment cost and network losses, this study proposes a novel methodology involving both kernel density estimation and shortest path methods to optimize the transmission network. The optimal locations of energy supply and storage stations are determined according to the kernel density of the annual energy consumption of building groups and the annual energy output of energy stations in the kernel density estimation method, respectively. The shortest path method using the Astar search algorithm with a screening algorithm is used to optimize the distribution of energy networks. The proposed methodology is verified by a hypothetical region from literature. The modified energy station and network planning methodology based on kernel density hotspots can reduce the total network length by 21.3%. Moreover, the proposed methodology can be applied easily and effectively to select the locations of the energy stations and determine the distribution of the energy networks in a regional integrated energy system.