Near‐real‐time loss allocation methodology based on the power system states. Issue 5 (18th January 2017)

• Record Type: Journal Article
• Authors: Yiasemi, Yiasoumis; Ciornei, Irina; Asprou, Markos; Kyriakides, Elias
• Is Part Of: IET generation, transmission & distribution. Volume 11:Issue 5(2017)
• Page Start: 1243
• Page End: 1250
• Publication Date: 2017-01-18
• Subjects: power transmission economics -- power markets -- smart power grids -- state estimation -- power system management; near‐real‐time loss allocation methodology -- power system states -- power losses -- transmission systems -- transmission loss allocation -- congestion management -- loss cost allocation methods -- smart grid context -- generator buses -- power network states -- state estimation -- economic dispatch procedure -- transmission congestion; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2016.1166
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Power losses in transmission systems are most of the time seen as a small amount (2–5%) from the total power carried over the network. However, transmission loss allocation may play a crucial role in the congestion management of balancing markets. Several loss allocation and loss cost allocation methods have been proposed and implemented in different markets. Most of these methods are intended to be used post‐market. This study presents a novel near‐real‐time loss allocation method suitable to be applied in real‐time markets as envisioned in the smart grid context. The proposed method allocates the total system losses fairly to all the demand and generator buses, by taking into account the dynamical changes of the power network states, which are provided by an accurate state estimation. The power flows required to determine the allocated losses are executed after an economic dispatch procedure that ignores losses, making the choice of the slack bus an independent factor. The proposed method can be used as an accurate real‐time pricing for network usage while the resolving of transmission congestion can be more reliable.