Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

Seyyed Mostafa Nosratabadi, Rahmat-Allah Hooshmand and Eskandar Gholipour

Applied Energy, 2016, vol. 164, issue C, 590-606

Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

Keywords: Virtual power plant; Stochastic scheduling; Industrial microgrid; Demand response load; Mixed integer non-linear programming (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (32)

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DOI: 10.1016/j.apenergy.2015.12.024

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