• DocumentCode
    3605239
  • Title

    Fully Distributed Social Welfare Optimization With Line Flow Constraint Consideration

  • Author

    Ye Ma ; Wei Zhang ; Wenxin Liu ; Qinmin Yang

  • Author_Institution
    Klipsch Sch. of Electr. & Comput. Eng., New Mexico State Univ., Las Cruces, NM, USA
  • Volume
    11
  • Issue
    6
  • fYear
    2015
  • Firstpage
    1532
  • Lastpage
    1541
  • Abstract
    This paper proposes a fully distributed social welfare optimization solution that solves the economic dispatch and demand response problems in an integrated way. Compared with sequentially implementing these two operations one after another, the integrated solution can efficiently maximize the benefits of customers and minimize the generation cost of generators simultaneously. By adjusting both generations and dispatchable loads, line flow constraints and generation bounds can be satisfied easier. The proposed solution has two layers of operations for consensus-based information discovery and gradient-based generation or demand adjustment, respectively. It is fully distributed in the sense that there is no need for a specialized/central controller to coordinate the operations of the autonomous local controllers (agents). Compared with centralized solutions, the multiagent system-based distributed solution is more reliable against single-point failures and can better accommodate customer participation. The proposed solution has been tested with a 5-bus system and the IEEE 30-bus system under light- and heavy-load conditions. Both static optimization and dynamic simulation results are provided to demonstrate the performance of the proposed solution.
  • Keywords
    power generation dispatch; 5-bus system; IEEE 30-bus system; central controller; consensus-based information discovery; demand adjustment; demand response problems; dispatchable loads; distributed social welfare optimization; dynamic simulation; economic dispatch; generation cost; generators; gradient-based generation; line flow constraint consideration; line flow constraints; static optimization; Algorithm design and analysis; Communication networks; Convergence; Economics; Generators; Informatics; Optimization; Consensus; distributed gradient algorithm; line flow constraints; social welfare optimization; social welfare optimization (SWO);
  • fLanguage
    English
  • Journal_Title
    Industrial Informatics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1551-3203
  • Type

    jour

  • DOI
    10.1109/TII.2015.2475703
  • Filename
    7234895