• DocumentCode
    6536
  • Title

    Stochastic DG Placement for Conservation Voltage Reduction Based on Multiple Replications Procedure

  • Author

    Zhaoyu Wang ; Bokan Chen ; Jianhui Wang ; Begovic, Miroslav M.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    30
  • Issue
    3
  • fYear
    2015
  • fDate
    Jun-15
  • Firstpage
    1039
  • Lastpage
    1047
  • Abstract
    Conservation voltage reduction (CVR) and distributed-generation (DG) integration are popular strategies implemented by utilities to improve energy efficiency. This paper investigates the interactions between CVR and DG placement to minimize load consumption in distribution networks, while keeping the lowest voltage level within the predefined range. The optimal placement of DG units is formulated as a stochastic optimization problem considering the uncertainty of DG outputs and load consumptions. A sample average approximation algorithm-based technique is developed to solve the formulated problem effectively. A multiple replications procedure is developed to test the stability of the solution and calculate the confidence interval of the gap between the candidate solution and optimal solution. The proposed method has been applied to the IEEE 37-bus distribution test system with different scenarios. The numerical results indicate that the implementations of CVR and DG, if combined, can achieve significant energy savings.
  • Keywords
    distributed power generation; distribution networks; energy conservation; stochastic programming; IEEE 37-bus distribution test system; conservation voltage reduction; distributed-generation integration; distribution networks; energy efficiency; load consumption; multiple replications procedure; stochastic DG placement; stochastic optimization problem; Equations; Load modeling; Materials requirements planning; Mathematical model; Reactive power; Stochastic processes; Voltage control; Conservation voltage reduction (CVR); Monte Carlo sampling; distributed generation (DG); multiple replications procedure (MRP); sample average approximation (SAA); stochastic programming (SP);
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2014.2331275
  • Filename
    7072569