Risk-aware multi-objective planning of a renewable hybrid microgrid incorporating energy storage systems and responsive loads

Document Type : Original Article

Authors

1 University of Tabriz

2 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

10.22109/jemt.2022.337010.1377

Abstract

The environmental pollution problem is intensified in recent years due to increasing fossil fuel consumption. In this regard, deployment of renewable resources can be a practical solution to decrease greenhouse gases and global warming. This paper proposes a risk-aware multi-objective programming consisting of operation cost and pollution objective functions to optimize the operation of a renewable hybrid microgrid composed of biomass-based conventional generators, wind turbines, photovoltaics and electrical and heat storage systems. According to the presence of uncertainties in such infrastructures, fluctuations of wind speed, solar radiation, loads and market price are modeled through a scenario generation and reduction procedure and then, the conditional value-at-risk index is used to measure the risk of decisions. Moreover, the epsilon constraint and fuzzy logic approaches are utilized to solve the problem and select the best solution in the Pareto set, respectively. A demand response program is also implemented for electrical and heat loads to analyze the influence of responsive loads. The results validate that the operation cost and pollution increase by about 10.03% and 11.31% in the risk-averse strategy, in return, robustness in the worst-case scenarios improves. As well, responsive loads decrease operation cost by about 9.8% under the uncertainties, however, the pollution increases by about 0.88%.

Keywords

Main Subjects

References

1. M. A. Jirdehi, V. S. Tabar, S. Ghassemzadeh, and S. Tohidi, "Different aspects of microgrid management: A comprehensive review," Journal of Energy Storage, vol. 30, p. 101457, 2020.
2. V. S. Tabar and V. Abbasi, "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, vol. 189, p. 116264, 2019.
3. V. S. Tabar, M. T. Hagh, and M. A. Jirdehi, "Achieving a nearly zero energy structure by a novel framework including energy recovery and conversion, carbon capture and demand response," Energy and Buildings, vol. 230, p. 110563, 2021.
4. M. A. Jirdehi, V. S. Tabar, R. Hemmati, and P. Siano, "Multi objective stochastic microgrid scheduling incorporating dynamic voltage restorer," International Journal of Electrical Power & Energy Systems, vol. 93, pp. 316-327, 2017
5. V. S. Tabar, M. A. Jirdehi, and R. Hemmati, "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, vol. 118, pp. 827-839, 2017.
6. A. Ghasemi and M. Enayatzare, "Optimal energy management of a renewable-based isolated microgrid with pumped-storage unit and demand response," Renewable energy, vol. 123, pp. 460-474, 2018.
7. A. Zakariazadeh, S. Jadid, and P. Siano, "Stochastic multi-objective operational planning of smart distribution systems considering demand response programs," Electric Power Systems Research, vol. 111, pp. 156-168, 2014.
8. J. Shi, W. Huang, N. Tai, P. Qiu, and Y. Lu, "Energy management strategy for microgrids including heat pump air-conditioning and hybrid energy storage systems," The Journal of Engineering, vol. 2017, no. 13, pp. 2412-2416, 2017.
9. Y. Zheng, B. M. Jenkins, K. Kornbluth, A. Kendall, and C. Træholt, "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, vol. 230, pp. 836-844, 2018.
10. Y. Iwafune, J. Kanamori, and H. Sakakibara, "A comparison of the effects of energy management using heat pump water heaters and batteries in photovoltaic-installed houses," Energy Conversion and Management, vol. 148, pp. 146-160, 2017.
11. Y. Zheng, B. M. Jenkins, K. Kornbluth, and C. Træholt, "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable energy, vol. 123, pp. 204-217, 2018.
12. M. Caliano, N. Bianco, G. Graditi, and L. Mongibello, "Design optimization and sensitivity analysis of a biomass-fired combined cooling, heating and power system with thermal energy storage systems," Energy Conversion and Management, vol. 149, pp. 631-645, 2017.
13. F. Kalavani, B. Mohammadi-Ivatloo, and K. Zare, "Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program," Renewable Energy, vol. 130, pp. 268-280, 2019.
14. T. Beck, H. Kondziella, G. Huard, and T. Bruckner, "Optimal operation, configuration and sizing of generation and storage technologies for residential heat pump systems in the spotlight of self-consumption of photovoltaic electricity," Applied Energy, vol. 188, pp. 604-619, 2017.
15. J. Soares, M. A. F. Ghazvini, N. Borges, and Z. Vale, "A stochastic model for energy resources management considering demand response in smart grids," Electric Power Systems Research, vol. 143, pp. 599-610, 2017.
16. M. Alipour, H. Chitsaz, H. Zareipour, and D. Wood, "Microgrid energy management: how uncertainty modelling impacts economic performance," IET Generation, Transmission Distribution, vol. 13, no. 24, pp. 5504-5510, 2019.
17. P. Pourghasem, F. Sohrabi, M. Abapour, and B. Mohammadi-Ivatloo, "Stochastic multi-objective dynamic dispatch of renewable and CHPbased islanded microgrids," Electric Power Systems Research, vol. 173, pp. 193-201, 2019
18. M. Alipour, B. Mohammadi-Ivatloo, and K. Zare, "Stochastic Scheduling of Renewable and CHP-Based Microgrids," IEEE Transactions on Industrial Informatics, vol. 11, no. 5, pp. 1049-1058, 2015.
19. K. Masoudi and H. Abdi, "Optimal stochastic scheduling in microgrids under managed risk," Journal of Energy Management and Technology, vol. 6, no. 1, pp. 33-43, 2022.
20. M. Jadidbonab, S. Madadi, and B. Mohammadi-ivatloo, "Hybrid Strategy for Optimal Scheduling of Renewable Integrated Energy Hub Based on Stochastic/Robust Approach," Journal of Energy Management and Technology, vol. 2, no. 4, pp. 29-38, 2018.
21. F. K/bidi, C. Damour, D. Grondin, M. Hilairet, and M. Benne, "Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage," Applied Energy, vol. 323, pp.119549, 2022.
22. T. Chen, Y. Cao, X. Qing, J. Zhang, Y. Sun, and G. A. J. Amaratunga, "Multi-energy microgrid robust energy management with a novel decision-making strategy," Energy, vol. 239, p. 121840, 2022.
23. P. Harsh and D. Das, "Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid," Renewable and Sustainable Energy Reviews, vol. 160, p. 112251, 2022.
24. C. Guo, X. Wang, Y. Zheng, and F. Zhang, "Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning," Energy, vol. 238, p. 121873, 2022.
25. V. S. Tabar, S. Ghassemzadeh, and S. Tohidi, "Stochastic scheduling of multi-hub energy-water nexus in the presence of renewable resources and responsive loads towards achieving sustainability," Journal of Cleaner Production, vol. 346, p. 131230, 2022.
26. M. Abbaspour, M. Satkin, B. Mohammadi-Ivatloo, F. H. Lotfi, and Y. Noorollahi, "Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)," Renewable Energy, vol. 51, pp. 53-59, 2013.
27. V. S. Tabar, S. Ghassemzadeh, and S. Tohidi, "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, vol. 174, pp. 10-23, 2019.
28. T. Ostadi Azari, V. Sohrabi Tabar, and S. Tohidi, "Stochastic multiobjective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure," International Journal of Energy Research, vol. 46, no. 7, pp. 9667-9683, 2022.
29. A. Rezaee Jordehi, "Risk-aware two-stage stochastic programming for electricity procurement of a large consumer with storage system and demand response," Journal of Energy Storage, vol. 51, pp. 104478, 2022.
30. V. S. Tabar, S. Tohidi, S. Ghassemzadeh, and P. Siano, "Enhancing security and observability of distribution systems with optimal placement of µPMUs and firewalls," International Journal of Electrical Power & Energy Systems, vol. 135, p. 107601, 2022.
Journal of Energy Management and Technology
Volume 7, Issue 3
September 2023
Pages 125-133

Files

History

  • Receive Date: 10 April 2022
  • Revise Date: 21 August 2022
  • Accept Date: 27 August 2022

Share

How to cite

Statistics