[Poster Presentation]Multi-objective Two-level Planning Strategy for the Integrated Energy-Intelligent Transportation System Coupling Network

Multi-objective Two-level Planning Strategy for the Integrated Energy-Intelligent Transportation System Coupling Network
ID:211 Submission ID:20 View Protection:PUBLIC Updated Time:2020-10-29 15:01:48 Hits:269 Poster Presentation

Start Time:2020-11-04 14:35 (Asia/Shanghai)

Duration:5min

Session:[G] Poster session » [G1] Poster Session 1 and Poster Session 6

Abstract
Based on the solution of mathematical models of distribution network, natural gas network and transportation network, combined with timing characteristics and multi-scenario technology, the output and load typical values of various power sources in multiple scenarios are obtained, and the operation optimization strategy of the components in the integrated energy-intelligent transportation system (IE-ITS) coupling network is proposed. On this basis, a two-level programming model is established. The upper-level model discusses the planning plan, and makes investment decisions, load regulation, and charging pile location with the goal of the lowest cost, highest reliability, and best voltage quality, using an improved NSGA-Ⅱ algorithm. The lower-level model considers the operating strategy, manages the upper-level scheme with the smallest amount of DG waste, using an improved particle swarm algorithm and TOPSIS method. The digital simulation results of an improved IEEE 33-node distribution network, 11-node natural gas network and 34-community transportation network verifies the effectiveness of the proposed bi-level programming model.
Keywords
Multi-network coupling,timing characteristics,multi-objective bi-level programming,electric vehicles,active management
Speaker
tiange li
Room 3513; School of Electrical Engineering and Automation; Wuhan University

Submission Author
tiange li Room 3513; School of Electrical Engineering and Automation; Wuhan University
zhijian hu Room 3513; School of Electrical Engineering and Automation; Wuhan University
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