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      SCIE SCOPUS KCI등재

      Risk-Based Allocation of Demand Response Resources Using Conditional Value-at Risk (CVaR) Assessment

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      https://www.riss.kr/link?id=A99959168

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      다국어 초록 (Multilingual Abstract)

      In a demand response (DR) market run by independent system operators (ISOs), load aggregators are important market participants who aggregate small retail customers through various DR programs. A load aggregator can minimize the allocation cost by eff...

      In a demand response (DR) market run by independent system operators (ISOs), load aggregators are important market participants who aggregate small retail customers through various DR programs. A load aggregator can minimize the allocation cost by efficiently allocating its demand response resources (DRRs) considering retail customers’ characteristics. However, the uncertain response behaviors of retail customers can influence the allocation strategy of its DRRs, increasing the economic risk of DRR allocation. This paper presents a risk-based DRR allocation method for the load aggregator that takes into account not only the physical characteristics of retail customers but also the risk due to the associated response uncertainties. In the paper, a conditional value-at-risk (CVaR) is applied to deal with the risk due to response uncertainties. Numerical results are presented to illustrate the effectiveness of the proposed method.

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      목차 (Table of Contents)

      • Abstract
      • 1. Introduction
      • 2. Problem Formulation
      • 3. Risk-Based DRR Allocation Method
      • 4. Numerical Example
      • Abstract
      • 1. Introduction
      • 2. Problem Formulation
      • 3. Risk-Based DRR Allocation Method
      • 4. Numerical Example
      • 5. Conclusion
      • References
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      참고문헌 (Reference) 논문관계도

      1 Y. Fu, "Security-Constrained Unit Commitment with AC Constraints" IEEE Trans. Power Syst 20 (3) : 1538 ~ 1550, 2005

      2 A. Khodaei, "SCUC with Hourly Demand Response Considering Intertemporal Load Characteristics" IEEE Trans. Smart Grid 2 (3) : 564 ~ 571, 2011

      3 M. Mazaheri, "Risk Budgeting Using Expected Shortfall(CVaR) : An Overview" SSRN, 2008

      4 P. Yi, "Real-Time Opportunistic Scheduling for Residential Demand Response" IEEE Trans. Smart Grid 4 (1) : 227 ~ 234, 2013

      5 John C. Hull, "Options, Futures, and Other Derivatives, vol. 6" PEARSON : 6 ~ 2006, 2006

      6 S. V. Bruno, "Optimization of Real Asset Portfolio Using a Coherent Risk Measure : Application to Oil and Energy Industries" Optimization Online : 1 ~ 8, 2008

      7 C. I. Fabrian, "Handling CVaR Objectives and Constraints in Two-Stage Stochastic Models" Eur. J. Oper. Res 191 (3) : 888 ~ 911, 2008

      8 K. Cuthbertson, "Financial Engineering: Derivatives and Risk Management" Wiley : 559 ~ 601, 2004

      9 J. Y. Joo, "Distributed Multi-Temporal Risk Management Approach to Designing Dynamic Pricing" IEEE Power & Energy Society General Meeting, 2012

      10 K. Dietrich, "Demand Response in an Isolated System with High Wind Integration" IEEE Trans. Power Syst 27 (1) : 20 ~ 29, 2012

      1 Y. Fu, "Security-Constrained Unit Commitment with AC Constraints" IEEE Trans. Power Syst 20 (3) : 1538 ~ 1550, 2005

      2 A. Khodaei, "SCUC with Hourly Demand Response Considering Intertemporal Load Characteristics" IEEE Trans. Smart Grid 2 (3) : 564 ~ 571, 2011

      3 M. Mazaheri, "Risk Budgeting Using Expected Shortfall(CVaR) : An Overview" SSRN, 2008

      4 P. Yi, "Real-Time Opportunistic Scheduling for Residential Demand Response" IEEE Trans. Smart Grid 4 (1) : 227 ~ 234, 2013

      5 John C. Hull, "Options, Futures, and Other Derivatives, vol. 6" PEARSON : 6 ~ 2006, 2006

      6 S. V. Bruno, "Optimization of Real Asset Portfolio Using a Coherent Risk Measure : Application to Oil and Energy Industries" Optimization Online : 1 ~ 8, 2008

      7 C. I. Fabrian, "Handling CVaR Objectives and Constraints in Two-Stage Stochastic Models" Eur. J. Oper. Res 191 (3) : 888 ~ 911, 2008

      8 K. Cuthbertson, "Financial Engineering: Derivatives and Risk Management" Wiley : 559 ~ 601, 2004

      9 J. Y. Joo, "Distributed Multi-Temporal Risk Management Approach to Designing Dynamic Pricing" IEEE Power & Energy Society General Meeting, 2012

      10 K. Dietrich, "Demand Response in an Isolated System with High Wind Integration" IEEE Trans. Power Syst 27 (1) : 20 ~ 29, 2012

      11 Korea Power Exchange, "Demand Response Market Operation Rules" 2013

      12 J. Soares, "Day-Ahead Resource Scheduling Including Demand Response for Electric Vehicles" IEEE Trans. Smart Grid 4 (1) : 596 ~ 605, 2013

      13 M. Shahidehpour, "Benders decomposition" IEEE Power Energy Mag 3 (2) : 20 ~ 21, 2005

      14 Federal Energy Regulatory Commission, "Assessment of Demand Response and Advanced Metering : Staff Report" 2012

      15 R. S. Tsay, "Analysis of Financial Time Series (3rd ed.)" Wiley : 333 ~ 338, 2010

      16 S. Shao, "An Approach for Demand Response to Alleviate Power System Stress Conditions" IEEE Power & Energy Society General Meeting, 2011

      17 Y. H. Huang, "A Comparison of Value at Risk Approaches and a New Method with Extreme Value Theory and Kernel Estimator" CUNY, 2006

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