Multi‐objective optimisation‐based active distribution system planning with reconfiguration, intermittent RES, and DSTATCOM

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...

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Veröffentlicht in:IET renewable power generation Jg. 13; H. 13; S. 2418 - 2429
Hauptverfasser: Sannigrahi, Surajit, Roy Ghatak, Sriparna, Acharjee, Parimal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 07.10.2019
Schlagworte:
33‐bus ADS
accurate system planning
comprehensive planning
different consumers
different critical situations
different planning schemes
distributed power generation
distribution companies
DSTATCOM
enormous load growth
genetic algorithms
intermittent power generation
intermittent RES
multiobjective algorithms
multiobjective optimisation‐based active distribution system planning
multiobjective particle swarm optimisation technique
novel nondominant sorting strategy
Pareto optimisation
particle swarm optimisation
power distribution economics
power distribution planning
realistic planning model
recent times
reconfiguration
renewable energy sources
RES units
restructured power system
static VAr compensators
suitable planning scheme
time‐variant load demand
time‐varying system load
yearly load growth
ISSN:1752-1424, 1752-1416, 1752-1424
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Zusammenfassung: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.
ISSN:1752-1424
1752-1416
1752-1424
DOI:10.1049/iet-rpg.2018.6060