Tytuł artykułu

Distributed generation’s integration planning involving growth load models by means of genetic algorithm

Tytuł czasopisma

Archives of Electrical Engineering




vol. 67


No 3

Autorzy publikacji

Słowa kluczowe

distributed generation ; genetic algorithm ; load models ; power loss ; load growth

Wydział PAN

Nauki Techniczne




ARCHIVES OF ELECTRICAL ENGINEERING (AEE) (previously Archiwum Elektrotechniki), quarterly journal of the Polish Academy of Sciences is OpenAccess (PAN Electronic Library, publishing original scientific articles and short communiques from all branches of Electrical Power Engineering exclusively in English. The main fields of interest are related to the theory & engineering of the components of an electrical power system: switching devices, arresters, reactors, conductors, etc. together with basic questions of their insulation, ampacity, switching capability etc.; electrical machines and transformers; modelling & calculation of circuits; electrical & magnetic fields problems; electromagnetic compatibility; control problems; power electronics; electrical power engineering; nondestructive testing & nondestructive evaluation.

Scoring assigned by the Polish Ministry of Science and Higher Education: 15 points

CiteScore metrics from Scopus, CiteScore 2017: 0.86

SCImago Journal Rank (SJR) 2017: 0.233

Source Normalized Impact per Paper (SNIP) 2017: 0.661

ICI Journal Master List 2017, Index Copernicus Value: 121.18


The growth in the system load accompanied by an increase of power loss in the distribution system. Distributed generation (DG) is an important identity in the electric power sector that substantially overcomes power loss and voltage drop problems when it is coordinated with a location and size properly. In this study, the DG integration into the network is optimally distributed by considering the load conditions in different load models used to surmount the impact of load growth. There are five load models tested namely constant, residential, industrial, commercial and mixed loads. The growth of the electrical load is modeled for the base year up to the fifth year as a short-term plan. Minimization of system power loss is taken as the main objective function considering voltage limits. Determination of the location and size of DG is optimally done by using the breeder genetic algorithm (BGA). The proposed studies were applied to the IEEE 30 radial distribution system with single and multiple placement DG scenarios. The results indicated that installing an optimal location and size DG could have a strong potential to reduce power loss and to secure future energy demand of load models. Also, commercial load requires the largest DG active injection power to maintain the voltage value within tolerable limits up to five years.


Polish Academy of Sciences




Artykuły / Articles


eISSN: 2300-2506 ; ISSN: 1427-4221