Open AccessPlacement of large‐scale utility‐owned wind distributed generation based on probabilistic forecasting of line congestion
Author(s) -
Masaud Tarek Medalel,
Deepak Mistry Ronak,
Sen P.K.
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2016.0944
Subject(s) - probabilistic logic , congestion management , electric power transmission , computer science , reliability engineering , reliability (semiconductor) , distributed generation , grid , transmission line , line (geometry) , network congestion , transmission (telecommunications) , wind power , electric power system , real time computing , simulation , engineering , power (physics) , telecommunications , computer network , renewable energy , electrical engineering , mathematics , artificial intelligence , physics , geometry , quantum mechanics , network packet
Integration of large‐scale utility‐owned distributed generation (DG) units can be a vital technique in relieving transmission line congestion and improving the reliability of the power grid. However, the impact of DG installation on line congestion management is significant at locations where transmission lines are most heavily loaded. This study presents a novel probabilistic method to forecast the most heavily loaded lines in the transmission network that might be at a higher risk of congestion. The proposed method can be utilised for determining candidate lines to install DG with the objective of relieving line congestion. The proposed method adopts the cumulative probability distribution function that accounts for the uncertainty of line loading. Furthermore, a congestion improvement ratio is developed to investigate the DG location impact on line congestion. The forecasting method is tested on a small modified IEEE 5‐Bus system. In order to demonstrate the proposed forecasting method on a larger and more complex system with several generators, the method is also tested on IEEE 30‐Bus test system. The simulation results have confirmed the effectiveness of the proposed method.