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

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • South Valley University
  • Budapest University of Technology and Economics

Abstract

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.

Details

Original languageEnglish
Number of pages10
JournalIEEE Transactions on Vehicular Technology
Publication statusE-pub ahead of print - 16 Mar 2020
MoE publication typeA1 Journal article-refereed

    Research areas

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

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