Optimal location-allocation of storage devices and renewable-based DG in distribution systems

Juan M. Home-Ortiz*, Mahdi Pourakbari-Kasmaei, Matti Lehtonen, José Roberto Sanches Mantovani

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

42 Citations (Scopus)


This paper proposes a mixed integer conic programming (MICP) model to find the optimal type, size, and place of distributed generators (DG) over a multistage planning horizon in radial distribution systems. The proposed planning framework focuses on the optimal siting and sizing of wind turbines, photovoltaic panels, gas turbines, and energy storage devices (ESD). Inherently, renewable energy sources and electricity demands are subject to uncertainty. To handle such probabilistic situations in decision-making, the MICP model is extended into a two-stage stochastic programming model. To obtain more practical results, annual historical data are used to generate the scenarios. For the sake of tractability, the k-means clustering technique is used to reduce the number of scenarios while keeping the correlation between the uncertain data. Due to convexity, the proposed MICP model guarantees to find the global optimal solution. To show the potential and performance of the proposed model a 69-bus radial distribution system under different conditions is dully studied and a sensitivity analysis is conducted. Results and comparisons approve its effectiveness and usefulness.

Original languageEnglish
Pages (from-to)11-21
Number of pages11
JournalElectric Power Systems Research
Publication statusPublished - 1 Jul 2019
MoE publication typeA1 Journal article-refereed


  • Conic programming
  • Distributed generation
  • Energy storage
  • Multistage distribution system planning
  • Renewable energy sources
  • Stochastic programming


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