Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Weakly meshed distribution networks with distributed generation — power flow analysis using improved impedance matrix based algorithm

Authors: Dejan Ivic; Drazenko Macanovic; Darko Sosic; Predrag Stefanov;

Weakly meshed distribution networks with distributed generation — power flow analysis using improved impedance matrix based algorithm

Abstract

From the viewpoint of the emerging concept of smart grid, distribution network will require fast power flow solution that must be resolved as efficiently as possible. Presence of distributed generators and power electronic based compensating devices, in modern medium and low voltage distribution networks, additionaly expands requirements for performances of algorithms for power flow calculations which are an essential part of effective smart distribution system analysis tools. The solution which can respond to most of defined requirements is proposed in this paper. This paper presents improved algorithm for power flow calculations for radial and weakly meshed distribution network with distributed generation and compensating devices. Proposed algorithm is based on the classical implicit impedance matrix (Z bus ) Gauss method. Algorithm, presented in this paper, is enforceable to any one-sided supplied distribution network topology and can calculate the impact of distributed generation from renewable energy sources on electrical power losses and voltage magnitudes. Algorithm is applied to IEEE 33 bus test distribution network, modified by adding tie lines to get meshed network. Efficiency of proposed algorithm is confirmed by calculations for different switching scenarios within analysis of system abilities made to meet requirements for integration of distributed generators in defined system nodes. Described analysis were carried out for both systems, with and without compensation devices included.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!