Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Congestion management with demand response considering uncertainties of distributed generation outputs and market prices
Author:
Affiliation:

1. School of Electrical Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China; 2. Department of Electrical and Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei; 3. Electric Power Research Institute of Guangdong Power Grid Co. Ltd., Guangzhou 510600, Guangdong, China

Fund Project:

National Basic Research Program of China (973 Program) (No. 2013CB228202), National Natural Science Foundsation of China (No. 51477151), Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120101110112), and a Project by China Southern Power Grid Company (No. K-GD2014-192).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
    Abstract:

    In recent years, much attention has been devoted to the development and applications of smart grid technologies, with special emphasis on flexible resources such as distributed generations (DGs), energy storages, active loads, and electric vehicles (EVs). Demand response (DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations. Despite their potential contributions to power system secure and economic operation, uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned. In addition, the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments. In this context, this paper aims to propose a DR based congestion management strategy for smart distribution systems. The general framework and procedures for distribution congestion management is first presented. A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established. Subsequently, the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices. The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: January 09,2017
  • Published: