Modeling of Energy Storage Systems in Microgrids with the Aim of Reducing Cost and Environmental Pollutants
Subject Areas : Power Engineering and Energy Management
1 - Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Keywords: Micro-grid, energy saver, cost, environmental pollution,
Abstract :
In this article, in order to improve the performance of a micro-grid, a complete and practical model for electric energy storage is presented. In order to optimize the energy in the micro-grid, a dual-purpose objective function has been considered, and the main purpose of this function is to simultaneously minimize the total operating costs and environmental pollutants by considering the uncertainty in the micro-grid. In the optimization part, due to the large search space of the above problem and its non-linearity, the proposed improved particle swarm algorithm has been used. Comparing the answers obtained through the above optimization algorithm with other optimization algorithms shows that the above algorithm is more efficient and has higher speed and accuracy. Finally, the proposed algorithm for managing the electrical energy of the entire micro-grid, the working points of all scattered production sources, how to charge and discharge electrical energy storage devices, as well as the amount of electrical power exchanged with the upstream network, in the condition that the total operating costs and environmental pollution Production is simultaneously minimized and optimized.
[1] G. Melath, S. Rangarajan and V. Agarwal, "Comprehensive power management scheme for the intelligent operation of photovoltaic-battery based hybrid microgrid system", IET Renew. Power Gener., vol. 14, no. 1, pp. 1688-1698, 2020#
[2] Z. Yi, W. Dong and A. H. Etemadi, "A unified control and power management scheme for PV-battery-based hybrid microgrids for both grid-connected and islanded modes", IEEE Trans. Smart Grid, vol. 9, no. 6, pp. 5975-5985, Nov. 2018.#
[3] S. Sen and V. Kumar, "Simplified modeling and HIL validation of solar PVs and storage-based islanded microgrid with generation uncertainties", IEEE Syst. J., vol. 14, no. 2, pp. 2653-2664, Jun. 2020.#
[4] X. Zhang, B. Wang, U. Manandhar, H. Beng Gooi and G. Foo, "A model predictive current controlled bidirectional three-level DC/DC converter for hybrid energy storage system in DC microgrids", IEEE Trans. Power Electron., vol. 34, no. 5, pp. 4025-4030, May 2019.#
[5] B. R. Ravada and N. R. Tummuru, "Control of a supercapacitor-battery-PV based stand-alone DC-microgrid", IEEE Trans. Energy Convers., vol. 35, no. 3, pp. 1268-1277, Sep. 2020.#
[6] . Shan, J. Hu, K. W. Chan, Q. Fu and J. M. Guerrero, "Model predictive control of bidirectional DC–DC converters and AC/DC interlinking converters—A new control method for PV-Wind-Battery microgrids", IEEE Trans. Sustain. Energy, vol. 10, no. 4, pp. 1823-1833, Oct. 2019.#
[7] O. Wallscheid and E.F.B. Ngoumtsa, "Investigation of disturbance observers for model predictive current control in electric drives", IEEE Trans. Power Electron., vol. 35, no. 12, pp. 13 563–13 572, Dec. 2020.#
[8] J. Guo, "Robust tracking control of variable stiffness joint based on feedback linearization and disturbance observer with estimation error compensation", IEEE Access, vol. 8, pp. 173 732–173 754, 2020.#
[9] H. Bakhshi Yamchi, H. Shahsavari, N. T. Kalantari, A. Safari and M. Farrokhifar, "A cost-efficient application of different battery energy storage technologies in microgrids considering load uncertainty", J. Energy Storage, vol. 22, pp. 17-26, Apr. 2019.#
[10] M. Faisal, M. A. Hannan, P. J. Ker, M. S. A. Rahman, R. A. Begum and T. M. I. Mahlia, "Particle swarm optimised fuzzy controller for charging–discharging and scheduling of battery energy storage system in MG applications", Energy Rep., vol. 6, pp. 215-228, Dec. 2020.#
[11] M. S. Reza, M. Mannan, S. B. Wali, M. A. Hannan, K. P. Jern, S. A. Rahman, et al., "Energy storage integration towards achieving grid decarbonization: A bibliometric analysis and future directions", J. Energy Storage, vol. 41, Sep. 2021.#
[12] E. Borri, A. Tafone, G. Zsembinszki, G. Comodi, A. Romagnoli and L. F. Cabeza, "Recent trends on liquid air energy storage: A bibliometric analysis", Appl. Sci., vol. 10, no. 8, pp. 2773, Apr. 2020.#
[13] S. B. Wali, M. A. Hannan, M. S. Reza, P. J. Ker, R. A. Begum, M. S. A. Rahman, et al., "Battery storage systems integrated renewable energy sources: A biblio metric analysis towards future directions", J. Energy Storage, vol. 35, Mar. 2021.#
[14] A. Q. Al-Shetwi, M. A. Hannan, K. P. Jern, M. Mansur and T. M. I. Mahlia, "Grid-connected renewable energy sources: Review of the recent integration requirements and control methods", J. Cleaner Prod., vol. 253, Apr. 2020.#
[15] M. A. Hannan, M. Faisal, P. Jern Ker, R. A. Begum, Z. Y. Dong and C. Zhang, "Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications", Renew. Sustain. Energy Rev., vol. 131, Oct. 2020.#
[16] V. V. S. N. Murty and A. Kumar, "Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems", Protection Control Mod. Power Syst., vol. 5, no. 1, pp. 1-20, 2020.#
[17] X. Wu, S. Qi, Z. Wang, C. Duan, X. Wang and F. Li, "Optimal scheduling for microgrids with hydrogen fueling stations considering uncertainty using data-driven approach", Appl. Energy, vol. 253, Nov. 2019.#
[18] A. Mansour-Saatloo et al., "Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots", Sustain. Cities Soc., vol. 74, Nov. 2021.#
[19] T. Ding, M. Qu, C. Huang, Z. Wang, P. Du and M. Shahidehpour, "Multi-period active distribution network planning using multi-stage stochastic programming and nested decomposition by SDDIP", IEEE Trans. Power Syst., vol. 36, no. 3, pp. 2281-2292, May 2021.#
[20] X. Cao, X. Sun, Z. Xu, B. Zeng and X. Guan, "Hydrogen-based networked microgrids planning through two-stage stochastic programming with mixed-integer conic recourse", IEEE Trans. Autom. Sci. Eng., vol. 19, no. 4, pp. 3672-3685, Oct. 2022.#
[21] Y. Liu, R. Sioshansi and A. J. Conejo, "Multistage stochastic investment planning with multiscale representation of uncertainties and decisions", IEEE Trans. Power Syst., vol. 33, no. 1, pp. 781-791, Jan. 2018.#
