Open AccessMulti‐objective optimisation‐based active distribution system planning with reconfiguration, intermittent RES, and DSTATCOM
Author(s) -
Sannigrahi Surajit,
Roy Ghatak Sriparna,
Acharjee Parimal
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2018.6060
Subject(s) - control reconfiguration , computer science , control theory (sociology) , embedded system , control (management) , artificial intelligence
The enormous load growth in recent times has forced distribution companies to undertake comprehensive planning of the active distribution system (ADS) to maintain superior service to their consumers. Under different critical situations in the restructured power system, reconfiguration in combination with the incorporation of renewable energy sources (RESs) and distributed static compensator (DSTATCOM) must be utilised for accurate system planning. In addition, from a practical viewpoint, the time‐variant load demand of different consumers and the intermittency of RES units must be considered. This study proposes a modified multi‐objective particle swarm optimisation (m‐MOPSO) technique for ADS planning considering reconfiguration, RES, and DSTATCOM to enhance voltage stability, reduce pollution, improve reliability, and maximise financial benefits. In the proposed m‐MOPSO, a novel non‐dominant sorting strategy is used to maintain diversity among the non‐dominated solutions. The time‐varying system load, yearly load growth, and intermittent power generation of RES are considered to construct a realistic planning model. The proposed technique is tested on the 33‐bus ADS considering different planning schemes to provide the most suitable planning scheme to the ADS planners. Moreover, the accuracy of the proposed algorithm is confirmed by comparing it with other multi‐objective algorithms.