Document Type : Research paper


Engineering Faculty, Islamic Azad University-South Tehran Branch, Ahang Ave., Tehran, Iran.


The operation planning problem encounters several uncertainties in terms of the power system’s parameters such as load, operating reserve and wind power generation. The modeling of those uncertainties is an important issue in power system operation. The system operators can implement different approaches to manage these uncertainties such as stochastic and fuzzy methods. In this paper, new fuzzy based modeling approach is implemented to develop the new formulation of power system problems under an uncertain environment with energy storage systems. Interval type-2 fuzzy membership function (MF) is implemented to model the uncertainty of available wind power generation and the type-1 fuzzy MF is used to model the other parameters in weekly unit commitment (UC) problem. The proposed approach is applied to two different test systems which have conventional generating units, wind farms and pumped storage plants to consider differences between the type-1 and type-2 fuzzy approaches for uncertainty modeling. The results show that the total profit of UC problem using type-2 fuzzy MF is better than type-1 fuzzy MF.


Main Subjects

[1]    C. L. Chen, “Optimal wind–thermal generating unit commitment”, IEEE Trans. Energy Conver., Vol. 23, No. 1, pp. 273-280, 2008.
[2]    J. Garcia-Gonzalez, R. de laMuela, L. Santos and A. Gonzalez, “Stochastic joint optimization of wind generation and pumped storage units in an electricity market”, IEEE Trans. Power Syst., Vol. 23, No. 2, pp. 460-468, 2008.
[3]    S. Saneifard, N. Prasad and H. Smolleck, “A fuzzy logic approach to unit commitment”, IEEE Trans. Power Syst., Vol. 12, No. 2, pp. 988-995, 1997.
[4]    H. Y. Yamin, “Fuzzy self-scheduling for Gencos,” IEEE Trans. Power Syst., Vol. 20, No. 1, pp. 503-505, 2005.
[5]    H. Siahkali and M. Vakilian, “Integrating large scale wind farms in fuzzy mid-term unit commitment using PSO”, IEEE Int. Conf. Eur. Electr. Markets, Portugal, 2008.
[6]    L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning-1”, Info. Sci., Vol. 8, No. 4, pp. 199-249, 1975.
[7]    Q. Liang and J. Mendel, “Interval type-2 fuzzy logic systems: theory and design”, IEEE Trans. Fuzzy Syst., Vol. 8, No. 5, pp. 535-550, 2000.
[8]    M. Wagenknecht and K. Hartmann, “Application of fuzzy sets of type 2 to the solution of fuzzy equations systems”, Fuzzy Sets and Syst., Vol. 25, No. 2, pp. 183-190, 1988.
[9]    N. N. Karnik and J. M. Mendel, “Operations on type-2 fuzzy sets”, Fuzzy Sets and Syst., Vol. 122, No. 2, pp. 327-348, 2001.
[10]    N. N. Karnik and J. M. Mendel, “Type-2 fuzzy logic systems: type-reduction”, IEEE Syst. Man Cybern. Conf., San Diego, CA, pp. 2046-2051, 1998.
[11]    J. M. Mendel and R. I. John, “Type-2 fuzzy sets made simple”, IEEE Trans. Fuzzy Syst., Vol. 10, No. 2, pp. 117-127, 2001.
[12]    M. Mizumoto and K. Tanaka, “Fuzzy sets of type-2 under algebraic product and algebraic sum”, Fuzzy Sets and Syst., Vol. 5, No. 3, pp. 277-290, 1981.
[13]    O. Castillo and P. Melin, “Type-2 fuzzy logic: theory and applications”, Springer, Germany, 2008.
[14]    J. M Mendel, “Uncertain rule-based fuzzy logic systems: introduction and new directions”, Prentice-Hall, 2001.
[15]    M. Majidi, S. nojavan and K. Zare, “Optimal sizing of energy storage system in a renewable-based microgrid under flexible demand side management considering reliability and uncertainties”, J. Oper. Autom. Power Eng., Vol. 5, No. 2, pp. 205-214, 2017.
[16]    E. Heydarian-Forushani and H. A. Aalami, “Multi objective scheduling of utility-scale energy storages and demand response programs portfolio for grid integration of wind power”, J. Oper. Autom. Power Eng., Vol. 4, No. 2, pp. 104-116, 2016.
[17]    A. Tuohy and M. O’Malley, “Pumped storage in systems with very high wind penetration”, Energy Policy, Vol. 39, pp. 1956-1974, 2011.
[18]    B. C. Ummels, E. Pelgrum and W. L. Kling, “Integration of large-scale wind power and use of energy storage in the Netherlands’ electricity supply”, IET Renewable Power Gener., Vol. 2, No. 1, pp. 34–46, 2008.
[19]    B. Ummels, M. Gibescu, E. Pelgrum, W. Kling and A.  Brand, “Impacts of wind power on thermal generation unit commitment and dispatch”, IEEE Trans. Energy Convers., Vol. 22, No. 1, pp. 44–51, 2007.
[20]    M. Black, V. Silva and G. Strbac, “The role of storage in integrating wind energy”, Int. Conf. Future Power Syst., pp. 1-6, 2005.
[21]    P. Denholm and M. Hand, “Grid flexibility and storage required to achieve very high penetration of variable renewable electricity”, Energy Policy, Vol. 39, pp. 1817–1830, 2011.
[22]    G. Qin, G. Liu, Z. Jing and Y. Zhang, “A preliminary research on the optimal daily operation mode of pumped-storage power plants under electricity market environment”, IEEE/PES Trans. Dist. Conf. Exhib., Asia and Pacific, China, 2005.
[23]    M. E. Nazari and M. M. Ardehali, “Optimal scheduling of coordinated wind-pumped storage-thermal system considering environmental emission based on GA based heuristic optimization algorithm”, Int. J. Smart Electr. Eng., Vol. 6, No. 4, pp. 135-142, 2017.
[24]    M. Vatanpour and A. S. Yazdankhah, “The impact of energy storage modeling in coordination with wind farm and thermal units on security and reliability in a stochastic unit commitment”, Energy, Vol. 162, pp. 476-490, 2018.
[25]    A. Tuohy and M. O’Malley, “Impact of pumped storage on power systems with increasing wind penetration”, IEEE Power Energy Soc. Gen. Meeting, Canada, 2009.
[26]    N. Shi, S. Zhu, X. Su, R. Yang and X. Zhu, “Unit commitment and multi-objective optimal dispatch model for wind-hydro-thermal power system with pumped storage”, IEEE Int. Power Elect. Motion Control Conf., 2016.
[27]    P. Brown, J. Lopes and M. Matos, “Optimization of pumped storage capacity in an isolated power system with large renewable penetration”, IEEE Trans. Power Syst., Vol. 23, No. 2, pp. 523-531, 2008.
[28]    B. Bagen, “Reliability and cost/worth evaluation of generating systems utilizing wind and solar energy”, PhD thesis, University of Saskatchewan, Canada, 2005.
[29]    N. Lu, J. Chow and A. Desrochers, “Pumped-storage hydro-turbine bidding strategies in a competitive electricity market”, IEEE Trans. Power Syst., Vol. 19, No. 2, pp. 885-895, 2004.
[30]    S. Coupland and R. John, “Geometric type-1 and type-2 fuzzy logic systems,” IEEE Trans. Fuzzy Syst., Vol. 15, No. 1, pp. 3-15, 2007.
[31]    GAMS Release 2.50, “A user’s guide”, GAMS, Development Corporation, 1999.
[32]    IEEE Reliability Test System Task Force, “The IEEE reliability test system - 1996”, IEEE Trans. Power Syst., Vol. 14, No. 3, pp. 1010-1020, 1999.
[33]    S. Wang, S. shahidehpour, D. Kirschen, S. Mokhtari and G. Irisarri, “Short term generation scheduling with transmission and environmental constraints using an augmented lagrangian relaxation”, IEEE Trans. Power Syst., Vol. 10, No. 3, pp. 1294-1301, 1995.
[34]    H. Siahkali and M. Vakilian, “Electricity generation scheduling with large-scale wind farms using particle swarm optimization”, Electr. Power Syst. Res., Vol. 79, pp. 826-836, 2009.