Optimal Operation Method for Distribution Systems Considering Distributed Generators Imparted with Reactive Power Incentive

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  • Ryuto Shigenobu
    Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
  • Mitsunaga Kinjo
    Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
  • Paras Mandal
    Department of Electrical and Computer Engineering, Power and Renewable Energy Systems (PRES) Lab, University of Texas at El Paso, El Paso, TX 79968, USA
  • Abdul Howlader
    Hawaii Natural Energy Institute, University of the Hawaii, Manoa, 1860 East-West Rasd, Honolulu, HI 96822, USA
  • Tomonobu Senjyu
    Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan

説明

<jats:p>In order to solve urgent energy and environmental problems, it is essential to carry out high installation of distributed generation using renewable energy sources (RESs) and environmentally-friendly storage technologies. However, a high penetration of RESs usually leads to a conventional power system unreliability, instability and low power quality. Therefore, this paper proposes a reactive power control method based on the demand response (DR) program to achieve a safe, reliable and stable power system. This program does not enforce a change in the active power usage of the customer, but provides a reactive power incentive to customers who participate in the cooperative control of the distribution company (DisCo). Customers can achieve a reduction in their total energy purchase by gaining a reactive power incentive, whilst the DisCo can achieve a reduction of its total procurement of equipment and distribution losses. An optimal control schedule is calculated using the particle swarm optimization (PSO) method, and also in order to avoid over-control, a modified scheduling method that is a dual scheduling method has been adopted in this paper. The effectiveness of the proposed method was verified by numerical simulation. Then, simulation results have been analyzed by case studies.</jats:p>

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