Title: Optimal placement and sizing of distributed generation in an unbalance distribution system using grey wolf optimisation method
Authors: Arjun Tyagi; Ashu Verma; Lokesh Kumar Panwar
Addresses: Centre for Energy Studies, Indian Institute of Technology Delhi, New Delhi-110016, India ' Centre for Energy Studies, Indian Institute of Technology Delhi, New Delhi-110016, India ' Centre for Energy Studies, Indian Institute of Technology Delhi, New Delhi-110016, India
Abstract: The distributed generation sources (DGs) are becoming increasingly attractive due to introduction of small scale renewable energy sources. They can be integrated in to low voltage distribution networks, to reduce the burden on transmission and sub transmission network. However, the number of DGs, their placement, and sizing can influence the advantages from the distribution network operation point of view. Also, most of the time the planning is done considering the peak load demand only. However, the losses obtained at peak load, may not give the realistic picture. This paper demonstrates the application of a grey wolf optimisation method for obtaining the optimal size and location of DGs (solar photovoltaic-based) in an unbalanced distribution network. The method proposed in this paper provides a set of solutions from the point of view of voltage stability enhancement and loss minimisation. The utility can prioritise either voltage stability enhancement or loss minimisation or both to choose the best compromised solution. Moreover, the losses are calculated by considering the seasonal load and PV generation patterns during the year to simulate the real picture of distribution system. Results on 33 bus balanced and 25 bus unbalanced distribution system are taken to demonstrate the potential of the proposed algorithm.
Keywords: distributed generator; energy loss; grey wolf optimiser; GWO; optimal size; optimal location.
International Journal of Power and Energy Conversion, 2019 Vol.10 No.2, pp.208 - 224
Received: 07 Jul 2016
Accepted: 03 Mar 2017
Published online: 29 Mar 2019 *