Optimal Allocation of Inverter-Based WTGS Complying with their DSTATCOM Functionality and PEV Requirements

Abdelfatah Ali, Karar Mahmoud, David Raisz, Matti Lehtonen

Research output: Contribution to journalArticleScientificpeer-review

20 Citations (Scopus)
71 Downloads (Pure)


Recently, the integration of inverter-based wind turbine generation systems (WTGS) and plug-in electric vehicles (PEV) has remarkably been expanded into distribution systems throughout the world. These distributed resources could have various technical benefits to the grid. However, they are also associated with potential operation problems due to their stochastic nature, such as high power losses and voltage deviations. An optimization-based approach is introduced in this paper to properly allocate multiple WTGS in distribution systems in the presence of PEVs. The proposed approach considers 1) uncertainty models of WTGS, PEV, and loads, 2) DSTATCOM functionality of WTGS, and 3) various system constraints. Besides, the realistic operational requirements of PEVs are addressed, including initial and preset conditions of their state of charge (SOC), arriving and departing times, and various controlled/uncontrolled charging schemes. The WTGS planning paradigm is established as a bi-level optimization problem which guarantees the optimal integration of multiple WTGS, besides optimized PEV charging in a simultaneous manner. For this purpose, a bi-level metaheuristic algorithm is developed for solving the planning model. Intensive simulations and comparisons with various approaches on the 69-bus distribution system interconnected with four PEV charging stations are deeply presented considering annual datasets. The results reveal the effectiveness of the proposed approach.
Original languageEnglish
Article number9036991
Pages (from-to)4763-4772
Number of pages10
JournalIEEE Transactions on Vehicular Technology
Issue number5
Publication statusPublished - 2020
MoE publication typeA1 Journal article-refereed


  • Distribution systems
  • PEV charging
  • Energy losses
  • System constraints
  • WTGS allocation


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