Next Article in Journal
Structural Health Monitoring (SHM) of Civil Structures
Previous Article in Journal
Guest Editors’ Note—Special Issue on Spatial Audio
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(8), 787; doi:10.3390/app7080787

A Novel Reactive Power Optimization in Distribution Network Based on Typical Scenarios Partitioning and Load Distribution Matching Method

1
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2
Power Distribution Research Department, China Electric Power Research Institute, Beijing 100192, China
*
Authors to whom correspondence should be addressed.
Received: 8 June 2017 / Revised: 25 July 2017 / Accepted: 31 July 2017 / Published: 3 August 2017
(This article belongs to the Section Mechanical Engineering)
View Full-Text   |   Download PDF [2264 KB, uploaded 3 August 2017]   |  

Abstract

This paper proposed an entropy weight optimum seeking method (EWOSM) based on the typical scenarios partitioning and load distribution matching, to solve the reactive power optimization problem in distribution network under the background of big data. Firstly, the mathematic model of reactive power optimization is provided to analyze the relationship between the data source and the optimization schemes in distribution network, which illustrate the feasibility of using large amount of historical data to solve reactive power optimization. Then, the typical scenarios partitioning method and load distribution matching method are presented, which can select out some loads that have the same or similar distributions with the load to be optimized from historical database rapidly, and the corresponding historical optimization schemes are used as the alternatives. As the reactive power optimization is a multi-objective problem, the multi-attribute decision making method based on entropy weight method is used to select out the optimal scheme from the alternatives. The objective weights of evaluation indexes are determined by entropy weight method, and then the multi-attribute decision making problem is transformed to a single attribute decision making problem. Finally, the proposed method is tested on several systems with different scales and compared with existing methods to prove the validity and superiority. View Full-Text
Keywords: entropy weight optimum seeking method (EWOSM); big data; reactive power optimization in distribution network; typical scenarios partitioning; load distribution matching; multi-attribute decision making entropy weight optimum seeking method (EWOSM); big data; reactive power optimization in distribution network; typical scenarios partitioning; load distribution matching; multi-attribute decision making
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ji, Y.; Liu, K.; Geng, G.; Sheng, W.; Meng, X.; Jia, D.; He, K. A Novel Reactive Power Optimization in Distribution Network Based on Typical Scenarios Partitioning and Load Distribution Matching Method. Appl. Sci. 2017, 7, 787.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top