Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Optimal air-conditioning load control in distribution network with intermittent renewables
Author:
Affiliation:

1.Centre for Intelligent Electricity Networks, The University of Newcastle, Callaghan, NSW 2308, Australia; 2. College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China; 3. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia; 4. School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia

Fund Project:

Faculty of Engineering and IT Early Career Researcher and Newly Appointed Staff Development Scheme 2016, the Hong Kong RGC Theme Based Research Scheme (No. T23-407/13 N, No. T23-701/ 14 N), and the 2015 Science and Technology Project of China Southern Power Grid (No. WYKJ00000027).

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    Abstract:

    The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP (mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization (RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method.

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History
  • Received:
  • Revised:
  • Adopted:
  • Online: January 09,2017
  • Published: