Bi-Level Optimization Model for Calculation of LMP Intervals Considering the Joint Uncertainty of Wind Power and Demand
Main Article Content
Abstract
In the electricity market operation, electricity prices or Locational Marginal Prices (LMP) vary according to both electric demand and the penetration level of the wind power. The variable domain identification of LMP plays a very important role for market participants to assess and mitigate the risk on account of the combined uncertainty of wind power and demand. Traditionally, the Monte Carlo simulation (MCS) method can be used in order to determine the variable intervals of LMP. However, in this paper, author deploys a bi-level optimization model to calculate the upper and lower bounds of LMP when considering the combined uncertainty of wind power generation and demand. The objective function of the upper-level optimization problem is to maximize (or minimize) LMP at a node whereas the objective function of the lower-level optimization problems is to calculate the optimal power generation of the units participating in supplying the load.
Keywords
electricity market, mathematical program with equilibrium constraints (MPEC), mixed-integer linear programming (MILP), joint uncertainty of wind power and demand, Locational Marginal Prices (LMP)
Article Details
References
[1] Pham Nang Van, Nguyen Duc Huy, Nguyen Van Duong, Nguyen The Huu, “A tool for unit commitment schedule in day-ahead pool-based electricity markets”, Journal of Science and Technology, The University of Danang, 6 (2016) 21-25.
[2] Pham Nang Van, Nguyen Dong Hung, Nguyen Duc Huy, “The impact of TCSC on transmission costs in wholesale power markets considering bilateral transactions and active power reserves”, Journal of Science and Technology, The University of Danang, 12 (2016) 24-28.
[3] Zou J, Lai X, Wang N, Time series model of stochastic wind power generation, Power System Technology, (2014) 2416-2421.
[4] Zhang Y, Ka WC, “The impact of wind forecasting in power system reliability”, Third international electric utility deregulation and restructuring and power technologies, Nanjing.
[5] Tuohy A, Meibom P, Denny E, “Unit commitment for systems with significant wind penetration”, IEEE Trans. Power Syst., 24 (2009) 592-601.
[6] Kroposki B, Sen PK, Malmedal K, “Selection of distribution feeders for implementing distributed and renewable energy applications”, IEEE Rural electric power conference, Fort Collins, CO, 2009.
[7] Yan Y, Wen F, Yang S, “Generation scheduling with fluctuating wind power”, Automation of Electric Power Systems, 34 (2010) 79-88.
[8] Juan M. Morales, Antonio J. Conejo and Juan Perez-Ruiz, “Simulating the impact of wind production on locational marginal prices”, IEEE Trans. Power Systems, 26 (2011) 820-828.
[9] Hu Y, Study on wind power storage technology and the intelligent dispatch model, Master thesis, Lanzhou University of Technology, 2013.
[10] Xin Fang, Qinran Hu, Fangxing Li, Beibei Wang and Yang Li, “Coupon-based demand response considering wind power uncertainty: a strategic bidding model for load serving entities”, IEEE Trans. Power Syst., 31 (2016) 1025-1037.
[11] Hongyuan Li, Leigh Tesfatsion, “ISO Net surplus collection and allocation in wholesale power markets under LMP”, IEEE Trans. Power Systems, 26 (2011) 627-641.
[12] V. Sarkar and S. A. Khaparde, “Optimal LMP Decomposition for the ACOPF Calculation”, IEEE Trans. Power Systems, 26 (2011) 1714-1723.
[13] F. Li and R. Bo, “Congestion and price prediction under load variation”, IEEE Trans. Power Syst., 24 (2009) 911-922.
[14] L.Baringo and A. J. Conejo, “Strategic offering for a wind power producer”, IEEE Trans. Power Syst., 28 (2013) 1645-1654.
[15] Zhi-Quan Luo, Jong-Shi Pang and Daniel Ralph, Mathematical Programs with Equilibrium constraints, Cambridge University Press, 2004.
[16] C Grigg et al., “The IEEE Reliability Test System 1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee”, IEEE Trans. Power Syst., 14 (1999) 1010-1020.
[17] CPLEX optimization studio.
[2] Pham Nang Van, Nguyen Dong Hung, Nguyen Duc Huy, “The impact of TCSC on transmission costs in wholesale power markets considering bilateral transactions and active power reserves”, Journal of Science and Technology, The University of Danang, 12 (2016) 24-28.
[3] Zou J, Lai X, Wang N, Time series model of stochastic wind power generation, Power System Technology, (2014) 2416-2421.
[4] Zhang Y, Ka WC, “The impact of wind forecasting in power system reliability”, Third international electric utility deregulation and restructuring and power technologies, Nanjing.
[5] Tuohy A, Meibom P, Denny E, “Unit commitment for systems with significant wind penetration”, IEEE Trans. Power Syst., 24 (2009) 592-601.
[6] Kroposki B, Sen PK, Malmedal K, “Selection of distribution feeders for implementing distributed and renewable energy applications”, IEEE Rural electric power conference, Fort Collins, CO, 2009.
[7] Yan Y, Wen F, Yang S, “Generation scheduling with fluctuating wind power”, Automation of Electric Power Systems, 34 (2010) 79-88.
[8] Juan M. Morales, Antonio J. Conejo and Juan Perez-Ruiz, “Simulating the impact of wind production on locational marginal prices”, IEEE Trans. Power Systems, 26 (2011) 820-828.
[9] Hu Y, Study on wind power storage technology and the intelligent dispatch model, Master thesis, Lanzhou University of Technology, 2013.
[10] Xin Fang, Qinran Hu, Fangxing Li, Beibei Wang and Yang Li, “Coupon-based demand response considering wind power uncertainty: a strategic bidding model for load serving entities”, IEEE Trans. Power Syst., 31 (2016) 1025-1037.
[11] Hongyuan Li, Leigh Tesfatsion, “ISO Net surplus collection and allocation in wholesale power markets under LMP”, IEEE Trans. Power Systems, 26 (2011) 627-641.
[12] V. Sarkar and S. A. Khaparde, “Optimal LMP Decomposition for the ACOPF Calculation”, IEEE Trans. Power Systems, 26 (2011) 1714-1723.
[13] F. Li and R. Bo, “Congestion and price prediction under load variation”, IEEE Trans. Power Syst., 24 (2009) 911-922.
[14] L.Baringo and A. J. Conejo, “Strategic offering for a wind power producer”, IEEE Trans. Power Syst., 28 (2013) 1645-1654.
[15] Zhi-Quan Luo, Jong-Shi Pang and Daniel Ralph, Mathematical Programs with Equilibrium constraints, Cambridge University Press, 2004.
[16] C Grigg et al., “The IEEE Reliability Test System 1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee”, IEEE Trans. Power Syst., 14 (1999) 1010-1020.
[17] CPLEX optimization studio.