Document Type : Original Article

Authors

Department of mechanical engineering, Imam Hossein Comprehensive University.

Abstract

This paper is dealt with energy hub systems in order to evaluate the sensitivity analysis of output power carriers in terms of input electricity and natural gas. Unlike the recent works which were solitary concentrated at operational cost minimization, in this research not only the energy carriers of proposed hub are being modeled, but also the sensitivity analysis of each power supplier are investigated. Since some of input power carriers in the hub, are decreased slightly or immediately according to unsolicited situations, the output electrical or thermal profile may not be supplied completely. Therefore the network operator must make a proper decision to utilize the best carriers not to reduce the system efficiency if possible. In this regard, the objective function including the energy costs for electrical, thermal and cooling demand carriers is optimized and the best solution will be extracted based on conditional value at risk (CAVR) of electricity market actors, using GAMS/CPLEX software, results in the higher the risk the network operator takes, the higher the profit from futures contracts. In the next step, the electricity price is predicted using ARIMA approach for the next four weeks and the sensitivity analysis for the future of the energy hub will be examined. The simulation results and changes in the share of energy carriers show that the importance of passive defense must be considered in the planning for energy supply of office buildings and the percentage of unsupplied energy must be studied.

Keywords

Main Subjects

[1] Alayi, S. R. Seydnouri, M. Jahangeri, and A. Maarif, "Optimization, Sensitivity Analysis, and Techno-Economic Evaluation of a Multi-source System for an Urban Community: a Case Study." in Renewable Energy Research and Application, 2021.
[2] Nikoukar, S. Momen, and M. Gandomkar, "Determining the Optimal Arrangement of Distributed Generations in Micro-grids to Supply the Electrical and Thermal Demands using the Improved Shuffled Frog Leaping Algorithm." in Renewable Energy Research and Applications, 2021.
[3] M. Mirlohi, M. Sadeghzadeh, R. Kumar, and M. Ghassemieh, "Implementation of a Zero-energy Building Scheme for a Hot and Dry Climate Region in Iran (a Case Study, Yazd)." in Renewable Energy Research and Application, Vol. 1, No. 1, pp. 65-74, 2020.
[4] Mokaramian, H. Shayeghi, F. Sedaghati, A. Safari, and H. H. Alhelou, "A CVaR-Robust-Based Multi-objective Optimization Model for Energy Hub considering Uncertainty and E-Fuel Energy Storage in Energy and Reserve Markets," in IEEE Access, Vol. 9, pp. 109447-109464, 2021.
[5] Hu, X. Liu, M. Shahidehpour, and S. Xia, "Optimal Operation of Energy Hubs with Large-scale Distributed Energy Resources for Distribution Network Congestion Management," in IEEE Transactions on Sustainable Energy, vol. 12, no. 3, pp. 1755-1765, July 2021.
[5] Jadidbonab, B. Mohammadi-Ivatloo, M. Marzband, and P. Siano, "Short-term Self-scheduling of Virtual Energy Hub Plant Within Thermal Energy Market," in IEEE Transactions on Industrial Electronics, Vol. 68, No. 4, pp. 3124-3136, April 2021.
[6] Geng, M. Vrakopoulou, and I. A. Hiskens, "Optimal Capacity Design and Operation of Energy Hub Systems," in Proceedings of the IEEE, Vol. 108, No. 9, pp. 1475-1495, Sept. 2020.
[7] Zhong, C. Yang, K. Xie, S. Xie, and Y. Zhang, "ADMM-based Distributed Auction Mechanism for Energy Hub Scheduling in Smart Buildings," in IEEE Access, Vol. 6, pp. 45635-45645, 2018.
[8] Z. Oskouei, B. Mohammadi-Ivatloo, M. Abapour, M. Shafiee, and A. Anvari-Moghaddam, "Strategic Operation of a Virtual Energy Hub with the Provision of Advanced Ancillary Services in Industrial Parks," in IEEE Transactions on Sustainable Energy, Vol. 12, No. 4, pp. 2062-2073, Oct. 2021.
[9] Li, W. Sheng, Q. Duan, Z. Li, C. Zhu, and X. Zhang, "A Lyapunov Optimization-based Energy Management Strategy for Energy Hub with Energy Router," in IEEE Transactions on Smart Grid, Vol. 11, No. 6, pp. 4860-4870, Nov. 2020.
[10] Luo, X. Zhang, D. Yang, and Q. Sun, "Emission Trading-based Optimal Scheduling Strategy of Energy Hub with Energy Storage and Integrated Electric Vehicles," in Journal of Modern Power Systems and Clean Energy, Vol. 8, No. 2, pp. 267-275, March 2020.
[11] Ma, N. Liu, J. Zhang, and L. Wang, "Real-time Rolling Horizon Energy Management for the Energy-Hub-Coordinated Prosumer Community from a Cooperative Perspective," in IEEE Transactions on Power Systems, Vol. 34, No. 2, pp. 1227-1242, March 2019.
[12] Liang, W. Wei, and C. Wang, "A Generalized Nash Equilibrium Approach for Autonomous Energy Management of Residential Energy Hubs," in IEEE Transactions on Industrial Informatics, vol. 15, No. 11, pp. 5892-5905, Nov. 2019.
[13] G. Moghaddam, M. Saniei, and E. Mashhour, “A comprehensive model for self-scheduling an energy hub to supply cooling, heating, and electrical demands of a building,” Energy, Vol. 94, pp. 157–170, 2016.
[14] Najafi, H. Falaghi, J. Contreras, and M. Ramezani, “Medium-term energy hub management subject to electricity price and wind uncertainty,” Applied Energy, Vol. 168, pp. 418–433, Apr. 2016.
[15] Najafi, H. Falaghi, J. Contreras, and M. Ramezani, “A Stochastic Bilevel Model for the Energy Hub Manager Problem,” IEEE Transactions on Smart Grid, Vol. 8, No. 5, pp. 2394–2404, Sep. 2017.
[16] Wang, N. Zhang, Z. Zhuo, C. Kang, and D. Kirschen, “Mixed-integer linear programming-based optimal configuration planning for energy hub: starting from scratch,” Applied Energy, Vol. 210, pp. 1141–1150, Jan. 2018.
[17] Setlhaolo, S. Sichilalu, and J. Zhang, “Residential load management in an energy hub with heat pump water heater,” Applied Energy, Vol. 208, pp. 551–560, Dec. 2017.
[18] Dolatabadi and B. Mohammadi-Ivatloo, “Stochastic risk-constrained scheduling of smart energy hub in the presence of wind power and demand response,” Applied Thermal Engineering, Vol. 123, pp. 40–49, Aug. 2017.
[19] AlRafea, M. Fowler, A. Elkamel, and A. Hajimiragha, “Integration of renewable energy sources into combined cycle power plants through electrolysis-generated hydrogen in a new designed energy hub,” International Journal of Hydrogen Energy, Vol. 41, No. 38, pp. 16718–16728, Oct. 2016.
[20] Ahmadisedigh and L. Gosselin, “Combined heating and cooling networks with waste heat recovery based on energy hub concept,” Applied Energy, Vol. 253, p. 113495, Nov. 2019.
[21] Hemmati, “Stochastic energy investment in off-grid renewable energy hub for autonomous building,” IET Renewable Power Generation, Vol. 13, No. 12, pp. 2232–2239, Sep. 2019.
[22] Rahmani-Andebili, “Stochastic, adaptive, and dynamic control of energy storage systems integrated with renewable energy sources for power loss minimization,” Renewable Energy, Vol. 113, pp. 1462–1471, Dec. 2017.
[23] Maroufmashat, S. Sattari, R. Roshandel, M. Fowler, and A. Elkamel, “Multi-objective Optimization for Design and Operation of Distributed Energy Systems through the Multi-energy Hub Network Approach,” Industrial and Engineering Chemistry Research, Vol. 55, No. 33, pp. 8950–8966, Aug. 2016.
[24] Cao, W. Wei, J. Wang, S. Mei, M. Shafie-khah, and J. P. S. Catalao, “Capacity Planning of Energy Hub in Multi-carrier Energy Networks: a Data-driven Robust Stochastic Programming Approach,” IEEE Transactions on Sustainable Energy, p 1, 2018.
[25] W. Tian et al., “Risk-based stochastic scheduling of energy hub system in the presence of heating network and thermal energy management,” Applied Thermal Engineering, Vol. 159, p. 113825, Aug. 2019.