دانشگاه تربیت دبیر شهید رجائی
انتشارات دانشگاه تربیت دبیر شهید رجائی

  اخبار و اعلانات

 آمار

تعداد نشریات11
تعداد شماره‌ها210
تعداد مقالات2,098
تعداد مشاهده مقاله2,877,198
تعداد دریافت فایل اصل مقاله2,085,000
Rashidinejad, M., Dorahaki, S., Zadsar, S. S., Salehizadeh, ‪M.R.. (1401). Robust Scheduling of Water and Energy Hub Considering CAES, Power-to-Gas Units, and Demand Response Programs. فناوری آموزش, 10(2), 371-380. doi: 10.22061/jecei.2022.8489.519
M. Rashidinejad; S. Dorahaki; S. S. Zadsar; ‪M.R. Salehizadeh. "Robust Scheduling of Water and Energy Hub Considering CAES, Power-to-Gas Units, and Demand Response Programs". فناوری آموزش, 10, 2, 1401, 371-380. doi: 10.22061/jecei.2022.8489.519
Rashidinejad, M., Dorahaki, S., Zadsar, S. S., Salehizadeh, ‪M.R.. (1401). 'Robust Scheduling of Water and Energy Hub Considering CAES, Power-to-Gas Units, and Demand Response Programs', فناوری آموزش, 10(2), pp. 371-380. doi: 10.22061/jecei.2022.8489.519
Rashidinejad, M., Dorahaki, S., Zadsar, S. S., Salehizadeh, ‪M.R.. Robust Scheduling of Water and Energy Hub Considering CAES, Power-to-Gas Units, and Demand Response Programs. فناوری آموزش, 1401; 10(2): 371-380. doi: 10.22061/jecei.2022.8489.519

Robust Scheduling of Water and Energy Hub Considering CAES, Power-to-Gas Units, and Demand Response Programs

Journal of Electrical and Computer Engineering Innovations (JECEI)
مقاله 10، دوره 10، شماره 2، مهر 2022، صفحه 371-380    اصل مقاله (963.4 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2022.8489.519
نویسندگان
M. Rashidinejad* 1؛ S. Dorahaki1؛ S. S. Zadsar1؛ ‪M.R. Salehizadeh2
1Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
2Department of Electrical Engineering, Islamic Azad University, Marvdasht Branch, Marvdasht, Iran.
تاریخ دریافت: 25 آبان 1400،  تاریخ بازنگری: 08 بهمن 1400،  تاریخ پذیرش: 12 بهمن 1400 
چکیده
Background and Objectives: The smart energy hub framework encompasses physical assets such as thermal storage, boiler, wind turbine, PV panel, water storage and, water desalination unit to ensure continuity of electricity, water, thermal, and gas provision in the case of unexpected outages in the upstream networks. In this regard, the smart energy hub as an integrated structure provides a suitable platform for energy supply. Considering the drinking water resources in the smart hub structure can cause operational efficiency improvement.
Methods: This paper proposes an integrated scheduling model for energy and water supply. To address the issue of increasing operational flexibility, a set of new technologies such as Compressed Air Energy Storage (CAES) and Power-to-Gas (P2G) system are provided. Also, the energy price is modeled as an uncertain parameter using a robust optimization approach. The proposed model is established as a Mixed Integer Linear Function (MILP). The mentioned model is implemented using the CPLEX solver in GAMS software. The proposed model is simulated in different scenarios in the energy hub and the optimization results are compared with each other to validate the proposed method.
Results: The results show that using CAES technology and the P2G system can lead to reducing the operating costs to a desirable level. Moreover, the impact of the P2G unit on the operation cost is more than the CAES unit.
Conclusion: The energy hub operator should tradeoff between robustness and operation cost of the system. The obtained results ensured that the proposed methodology was robust, optimal, and economical for energy hub schedules.
کلیدواژه‌ها
Energy Hub؛ Demand Response Programs؛ Power-to-Gas (P2G)؛ Compressed Air Energy Storage؛ Robust Optimization
مراجع
[1] M. MollahassaniPour, I. Taheri, M. Hasani Marzooni, “Assessment of transmission outage Contingencies’ effects on bidding strategies of electricity suppliers,” Int. J. Electr. Power Energy Syst., 120: 106053, 2020.

[2] S. Dorahaki, M. Rashidinejad, M. Mollahassani-pour, A. Bakhshai, “An efficient hybrid structure to solve economic-environmental energy scheduling integrated with demand side management programs,” Electr. Eng., 101(4): 1249–1260, 2019.

[3] M. Mohammadi, Y. Noorollahi, B. Mohammadi-ivatloo, H. Yousefi, “Energy hub: From a model to a concept – A review,” Renew. Sustain. Energy Rev., 80: 1512–1527, 2017.

[4] W.S. Ho, S. Macchietto, J.S. Lim, H. Hashim, Z.A. Muis, W.H. Liu, “Optimal scheduling of energy storage for renewable energy distributed energy generation system,” Renew. Sustain. Energy Rev., 58: 1100–1107, 2016.

[5] S. Dorahaki, R. Dashti, H.R. Shaker, “The optimal energy management in the smart microgrid considering demand response program and energy storage,” in Proc. 2019 International Symposium on Advanced Electrical and Communication Technologies (ISAECT): 1–6, 2019.

[6] S. Dorahaki, M. Rashidinejad, S.F. Fatemi Ardestani, A. Abdollahi, M.R. Salehizadeh, “A home energy management model considering energy storage and smart flexible appliances: A modified time-driven prospect theory approach,” J. Energy Storage, 48: 104049, 2022.

[7] I.T. Emami, M. MollahassaniPour, M.R.N. Kalhori, M.S. Deilami, “Short-run economic–environmental impacts of carbon tax on bulk electric systems,” Sustain. Energy, Grids Networks, 26:  100480, 2021.

[8] S. Dorahaki, M. Rashidinejad, H. Farahmand, M. MollahassaniPour, M. Pourakbari-Kasmaei, J.P.S. Catalao, “An optimal flexible partitioning of smart distribution system considering electrical and gas infrastructure,” in Proc. 2021 IEEE Madrid PowerTech, 2021.

[9] M.A. Mirzaei et al., “An integrated energy hub system based on power-to-gas and compressed air energy storage technologies in presence of multiple shiftable loads,” IET Gener. Transm. Distrib., 2020.

[10] M. Mollahassani-pour, M. Rashidinejad, A. Abdollahi, “Spinning reserve contribution using unit responsibility criterion incorporating preventive maintenance scheduling,” Int. J. Electr. Power Energy Syst., 73: 508–515, 2015.

[11] A. Dini, A. Hassankashi, S. Pirouzi, M. Lehtonen, B. Arandian, A.A. Baziar, “A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response,” Energy, 239: 121923, 2022.

[12] Y. Cao, Q. Wang, J. Du, S. Nojavan, K. Jermsittiparsert, N. Ghadimi, “Optimal operation of CCHP and renewable generation-based energy hub considering environmental perspective: An epsilon constraint and fuzzy methods,” Sustain. Energy, Grids Networks, 20: 100274, 2019.

[13] Z. Zeng, T. Ding, Y. Xu, Y. Yang, Z. Dong, “Reliability evaluation for integrated power-gas systems with power-to-gas and gas storages,” IEEE Trans. Power Syst., 35(1): 571–583, 2020.

[14] L. Chen, T. Zheng, S. Mei, X. Xue, B. Liu, Q. Lu, “Review and prospect of compressed air energy storage system,” J. Mod. Power Syst. Clean Energy, 4(4): 529–541, 2016.

[15] M. Ban, J. Yu, M. Shahidehpour, Y. Yao, “Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration,” J. Mod. Power Syst. Clean Energy, 5(3): 337–349, 2017.

[16] A. Mazza, F. Salomone, F. Arrigo, S. Bensaid, E. Bompard, G. Chicco, “Impact of Power-to-Gas on distribution systems with large renewable energy penetration,” Energy Convers. Manag. X, 7: 100053, 2020.

[17] C. Wulf, J. Linssen, P. Zapp, “Power-to-gas—concepts, demonstration, and prospects,” Hydrog. Supply Chain Des. Deploy. Oper., 2018: 309–345, 2018.

[18] S. Clegg and P. Mancarella, “Storing renewables in the gas network: modelling of power-to-gas seasonal storage flexibility in low-carbon power systems,” IET Gener. Transm. Distrib., 10(3):  566–575, 2016.

[19] Z. Soltani, M. Ghaljehei, G.B. Gharehpetian, H.A. Aalami, “Integration of smart grid technologies in stochastic multi-objective unit commitment: An economic emission analysis,” Int. J. Electr. Power Energy Syst., 100: 565–590, 2018.

[20] X. Luo, J. Wang, M. Dooner, J. Clarke, C. Krupke, “Overview of Current development in compressed air energy storage technology,” Energy Procedia, 62: 603–611, 2014.

[21] W. Cai, R. Mohammaditab, G. Fathi, K. Wakil, A.G. Ebadi, N. Ghadimi, “Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach,” Renew. Energy, 143: 1–8, 2019.

[22] A.L. Soyster, “Technical note—convex programming with set-inclusive constraints and applications to inexact linear programming,” Oper. Res., 21(5): 1154–1157, 1973.

[23] Y. Zhang, N. Gatsis, G.B. Giannakis, “Robust energy management for microgrids with high-penetration renewables,” IEEE Trans. Sustain. Energy, 4(4): 944–953, 2013.

[24] M. Yan, N. Zhang, X. Ai, M. Shahidehpour, C. Kang, J. Wen, “Robust two-stage regional-district scheduling of multi-carrier energy systems with a large penetration of wind power,” IEEE Trans. Sustain. Energy, 10(3): 1227–1239, 2019.

[25] M. Alipour, K. Zare, H. Zareipour, H. Seyedi, “Hedging Strategies for heat and electricity consumers in the presence of real-time demand response programs,” IEEE Trans. Sustain. Energy, 10(3): 1262–1270, 2019.

[26] M. Nazari-Heris, B. Mohammadi-Ivatloo, G.B. Gharehpetian, M. Shahidehpour, “Robust short-term scheduling of integrated heat and power microgrids,” IEEE Syst. J., 13(3): 3295–3303, 2019.

[27] S. Dorahaki, R. Dashti, H.R. Shaker, “Optimal outage management model considering emergency demand response programs for a smart distribution system,” Appl. Sci., 10(21): 7406, 2020.

[28] S. Dorahaki, M. Rashidinejad, S.F.F. Ardestani, A. Abdollahi, M.R. Salehizadeh, “A Peer-to-Peer energy trading market model based on time-driven prospect theory in a smart and sustainable energy community,” Sustain. Energy, Grids Networks: 100542, 2021.

[29] S. Dorahaki, A. Abdollahi, M. Rashidinejad, M. Moghbeli, “The role of energy storage and demand response as energy democracy policies in the energy productivity of hybrid hub system considering social inconvenience cost,” J. Energy Storage, 33: 102022, 2021.

[30] M. Ghahramani, M. Nazari-Heris, K. Zare, B. Mohammadi-ivatloo, “Robust Short-term scheduling of smart distribution systems considering renewable sources and demand response programs,” Robust Optimal Planning and Operation of Electrical Energy Systems, Cham: Springer International Publishing, 2019, pp. 253–270.

آمار
تعداد مشاهده مقاله: 531
تعداد دریافت فایل اصل مقاله: 351


سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب