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Demand response scheduling by stochastic SCUC

Parvania, M ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/TSG.2010.2046430
  3. Publisher: 2010
  4. Abstract:
  5. Considerable developments in the real-time telemetry of demand-side systems allow independent system operators (ISOs) to use reserves provided by demand response (DR) in ancillary service markets. Currently, many ISOs have designed programs to utilize the reserve provided by DR in electricity markets. This paper presents a stochastic model to schedule reserves provided by DR in the wholesale electricity markets. Demand-side reserve is supplied by demand response providers (DRPs), which have the responsibility of aggregating and managing customer responses. A mixed-integer representation of reserve provided by DRPs and its associated cost function are used in the proposed stochastic model. The proposed stochastic model is formulated as a two-stage stochastic mixed-integer programming (SMIP) problem. The first-stage involves network-constrained unit commitment in the base case and the second-stage investigates security assurance in system scenarios. The proposed model would schedule reserves provided by DRPs and determine commitment states of generating units and their scheduled energy and spinning reserves in the scheduling horizon. The proposed approach is applied to two test systems to illustrate the benefits of implementing demand-side reserve in electricity markets
  6. Keywords:
  7. Security cost ; Stochastic security-constrained unit commitment ; Uncertainty ; Ancillary service markets ; Associated costs ; Customer response ; Demand response ; Demand-side ; Electricity market ; Generating unit ; Independent system operators ; Integer representation ; Mixed-Integer Programming ; Security assurance ; Security constrained unit commitment ; Spinning reserves ; Stochastic mixed integer programming ; Test systems ; Two stage ; Unit commitments ; Wholesale electricity markets ; Commerce ; Electric utilities ; Integer programming ; Real time systems ; Scheduling ; Stochastic systems ; Stochastic models
  8. Source: IEEE Transactions on Smart Grid ; Volume 1, Issue 1 , May , 2010 , Pages 89-98 ; 19493053 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/5464384