Operation Studies of the Power Systems Containing Combined Heat and Power ‎Plants‎

Document Type : Research paper

Authors

1 Department of Electrical Engineering, Dariun Branch, Islamic Azad University, Dariun, Iran

2 ‎Department of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran

3 Department of Computer Engineering, Sepidan Branch, Islamic Azad University, Sepidan, Iran‎

Abstract

In today's power systems, the use of methods that can increase the energy efficiency and reduce the cost of the generated energy has received much attention. One of these methods is the use of the combined heat and power (CHP) plants that simultaneously can generate the electric and thermal powers. In the conventional thermal power plants, the thermal energy of the working fluid coming out from the turbine is dissipated that result in low efficiency. However, it can be used for the heating purposes in the CHP units that result in the high efficiency of these plants. Due to the wide use of the CHP units in the power system, different aspects of the power system such as operation may be affected that must be studied. In this paper, the study of the power system operation integrated with the CHP plants is performed. For this purpose, the PJM method that considers the reliability-based indices such as unit commitment risk is utilized. Moreover, a four-state reliability model is developed different types of the CHP units including gas turbine, steam turbine, reciprocating engine, micro-turbine and fuel cell technologies. In the proposed model, both the failure of composed components and the participation of the CHP units in the thermal power generation are considered. To determine the probabilities of different states of the proposed model, matrix multiplication technique is used. Based on the PJM technique, the numerical results associated to the operation studies of the RBTS and IEEE-RTS that are given and the unit commitment risk and the required spinning reserve of these systems calculated considering the effect of the CHP units.  

Keywords

References

[1]     X. Zhang, G. Karady and S. Ariaratnam, “Optimal allocation of CHP-based distributed generation on urban energy distribution networks”, IEEE Trans. Sustainable Energy, vol. 5, pp. 246-53, 2014.
[2]     D. Xie, A. Chen, C. Gu and J. Tai, “Time-domain modeling of grid-connected CHP for its interaction with the power grid”, IEEE Trans. Power Syst., vol. 33, pp. 6430-40, 2018.
[3]     L. Ma et al., “Energy management for joint operation of CHP and PV prosumers inside a grid-connected microgrid: a game theoretic approach”, IEEE Trans. Ind. Inf., vol. 12, pp. 1930-42, 2016.
[4]     J. Tang et al., “Operational flexibility constrained intraday rolling dispatch strategy for CHP microgrid”, IEEE Access, vol. 7, pp. 96639-49, 2019.
[5]     P. Ivanova, A. Sauhats and O. Linkevics, “District heating technologies: Is it chance for CHP plants in variable and competitive operation conditions?”, IEEE Trans. Ind. Appl., vol. 55, pp. 35-42, 2018.
[6]     J. Morales, A. Hellmers, M. Zugno and A. Skajaa, “Operational strategies for a portfolio of wind farms and CHP plants in a two-price balancing market”, IEEE Power Energy Soc. Gen., 2016.
[7]     D. Xie et al., “Optimal operation of a combined heat and power system considering real-time energy prices”, IEEE Access, vol. 4, pp. 3005-15, 2016.
[8]     T. Sun et al., “Modeling combined heat and power systems for microgrid applications”, IEEE Trans. Smart Grid, vol. 9, pp. 4172-80, 2018.
[9]     M. Benam, S. Madani, S. Alavi and M. Ehsan, “Optimal configuration of the CHP system using stochastic programming”, IEEE Trans. Power Del., vol. 30, pp. 1048-56, 2015.
[10]   G. Zhang, Z. Shen and L. Wang, “Online energy management for microgrids with CHP co-generation and energy storage”, IEEE Trans. Control Syst. Technol., vol. 28, pp. 533-41, 2020.
[11]   R. Kazemzadeh and M. Moazen, “Unit commitment by a fast and new analytical non-iterative method using IPPD table and “λ-logic” algorithm”, J. Oper. Autom. Power Eng., vol. 7, pp. 27-39, 2019.
[12]   V. Amir, S. Jadid and M. Ehsan, “Operation of multi Carrier microgrid (MCMG) considering demand response”, J. Oper. Autom. Power Eng., vol. 7, pp. 119-28, 2019.
[13]   A. Dizaji, M. Saniei and K. Zare, “Resilient operation scheduling of microgrid using stochastic programming considering demand response and electric vehicles”, J. Oper. Autom. Power Eng., vol. 7, pp. 157-67, 2019.
[14]   H. Fateh, A. Safari, and S. Bahramara, “A bi-level optimization approach for optimal operation of distribution networks with retailers and micro-grids”, J. Oper. Autom. Power Eng., vol. 8, pp. 15- 21, 2020.
[15]   E. Shahryari et al., “Optimal energy management of microgrid in day-ahead and intra-day markets using a copula-based uncertainty modeling method”, J. Oper. Autom. Power Eng., vol. 8, pp. 86-96, 2020.
[16]   M. Behnamfar, H. Barati and M. Karami, “Stochastic short-term hydro-thermal scheduling based on mixed integer programming with volatile wind power generation”, J. Oper. Autom. Power Eng., vol. 8, pp. 195-208, 2020.
[17]   H. Siahkali, “Operation planning of wind farms with pumped storage plants based on interval type-2 fuzzy modeling of uncertainties”, J. Oper. Autom. Power Eng., vol. 8, pp. 182-94, 2020.
[18]   R. Billinton and R. Allan, “Reliability evaluation of power systems”, 2nd edition, New York, NY, USA and London, U.K.: Plenum, 1994.
[19]   R. Billinton et al., “A reliability test system for educational purposes-basic data”, Power Eng. Rev., vol.9, pp. 67-68, 1989.
[20]   R. Billinton and W. Li, “Reliability assessment of electric power system using monte carlo”, Plenum Press, New York, 1994.
Journal of Operation and Automation in Power Engineering
Volume 9, Issue 2
August 2021
Pages 160-171

Files

History

  • Receive Date: 23 August 2020
  • Revise Date: 18 October 2020
  • Accept Date: 17 November 2020
  • First Publish Date: 12 December 2020

Share

How to cite

Statistics