State-of-the-Art Techniques and Challenges Ahead for Distributed Generation Planning and Optimization

Keane, A.; Ochoa, L.F.; Borges, C.L.T.; Ault, G.W.; Alarcon-Rodriguez, A.D.; Currie, R.A.F.; Pilo, F.; Dent, C.J.; Harrison, G.P.

Abstract

It is difficult to estimate how much distributed generation (DG) capacity will be connected to distribution systems in the coming years; however, it is certain that increasing penetration levels require robust tools that help assess the capabilities and requirements of the networks in order to produce the best planning and control strategies. The work of this Task Force is focused on the numerous strategies and methods that have been developed in recent years to address DG integration and planning. This paper contains a critical review of the work in this field. Although there have been numerous publications in this area, widespread implementation of the methods has not taken place. The barriers to implementation of the advanced techniques are outlined, highlighting why network operators have been slow to pick up on the research to date. Furthermore, key challenges ahead which remain to be tackled are also described, many of which have come into clear focus with the current drive towards smarter distribution networks.

Citation

Keane, A., Ochoa, L., Borges, C., Ault, G., Alarcon-Rodriguez, A., Currie, R., …Harrison, G. (2013). State-of-the-Art Techniques and Challenges Ahead for Distributed Generation Planning and Optimization. IEEE Transactions on Power Systems, 28(2), 1493-1502. https://doi.org/10.1109/tpwrs.2012.2214406

• Journal Article Type: Article
• Publication Date: May 1, 2013
• Deposit Date: May 8, 2013
• Publicly Available Date: Jan 29, 2014
• Journal: IEEE Transactions on Power Systems
• Print ISSN: 0885-8950
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 28
• Issue: 2
• Pages: 1493-1502
• DOI: https://doi.org/10.1109/tpwrs.2012.2214406
• Keywords: AC optimal power flow, Active network management, Distributed generation, Distribution networks, Linear and multi-objective programming, Wind power.
• Public URL: https://durham-repository.worktribe.com/output/1457168