Improved LSF method for loss estimation and its application in DG allocation. Issue 10 (1st July 2016)

• Record Type: Journal Article
• Authors: Fu, Xueqian; Chen, Haoyong; Cai, Runqing; Xuan, Peizheng
• Is Part Of: IET generation, transmission & distribution. Volume 10:Issue 10(2016)
• Page Start: 2512
• Page End: 2519
• Publication Date: 2016-07-01
• Subjects: distributed power generation -- losses -- statistical analysis; LSF method -- DG allocation -- loss factor calculation -- minimum load factor -- MLF -- quadratic equation -- statistical analysis -- energy losses estimation -- ILSF methods -- loss reduction -- distributed generation -- 43‐bus distribution network; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2015.1471
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Energy loss represents a traditional key objective in the optimal operation and planning of electrical networks, and various estimation methods have been studied. In this study, two formulas are proposed for calculation of the loss factor (LSF) to improve the classical LSF method based on the minimum load factor (MLF) and the LF. The former is an approximate formula, whose accuracy is good enough for engineering calculations. While the latter is an empirical quadratic equation determined by the statistical analysis, which is more accurate to estimate losses. To conduct a complete feasibility study for project practices, a large amount of measurement data is used to calculate energy losses in a district of Guangdong using the classical LSF method and the improved LSF (ILSF) method. Results of statistical analyses indicate that the real data fall in the proposed three‐dimensional region and the use of MLF can help improve accuracy in the energy losses estimation. The classical and ILSF methods are used to estimate the effect in loss reduction by inserting a distributed generation in a 43‐bus distribution network, and the candidate bus can be identified effectively.