A SSSC optimal configuration method to enhance available transfer capability considering multi‐wind farm access

Author:

Chen Yanbo1ORCID,Wang Deshuai1,Li Jiaqi1,Fan Haiwei2,Li Jinsong3,Luo Yadi3,Li Li3

Affiliation:

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, School of Electrical and Electronic Engineering North China Electric Power University Beijing China

2. State Grid Fujian Electric Power Company Fujian Province China

3. China Electric Power Research Institute Co Ltd Beijing China

Abstract

AbstractIn the context of electricity market, the heavy load of some inter‐provincial and intra‐provincial lines limits available transfer capability (ATC). As a series compensation device, static synchronous series compensator (SSSC) can reallocate the power flow of adjacent lines. In order to maximize the inter‐regional ATC, a two‐stage optimal SSSC allocation method considering the uncertainty and correlation of multi‐wind farm is proposed. Firstly, the initial wind power scenarios are generated based on latin hypercube sampling (LHS) and reduced by the improved iterative self‐organizing data analysis techniques algorithm (I‐ISODATA). Then, a multi‐objective optimization model is constructed with the maximum expected power flow transfer entropy (PFTE) and minimum expected SSSC investment cost in all typical wind power scenarios, and non‐dominated sorting genetic algorithm‐II (NSGA‐II) method is used to determine the location of SSSC. In addition, based on the reduced wind power scenarios, the ATC calculation model containing SSSC is constructed, and the modern interior point method is used to determine the control parameters and configuration capacity of SSSC. Finally, based on the improved IEEE39 and IEEE118 node systems, case study proves that the proposed model can determine the optimal SSSC configuration scheme and significantly improves the ATC.

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

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