Energy Scheduling in a Hybrid DC/AC Micro-Grid Considering Battery/Wind/Photovoltaic Power Sources using Heuristic Optimization Algorithm

Ebrahimi, Javad; Niknam, Taher; Bahmanifirouzi, Bahman

doi:10.29252/mjee.14.3.13

Document Type : Review Article

Authors

Department of Electrical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

https://doi.org/10.29252/mjee.14.3.13

Abstract

This paper is treated with optimum energy management in a DC/AC Microgrid (MG) containing hybrid power sources to supply the load within cost minimization. In this hybrid electrical networks, energy sources are exploited as DC and AC manner, in which the Independent System Operator (ISO) should provide a practical coordination between them in order to procure the demand load optimally. This paper presents a framework that all available resources are formulated mathematically in hybrid microgrid with full constraints along with Demand Response (DR) programs implementation. The network under consideration can operate both in grid-tied and autonomous modes to manage power exchanging. Uncertainty and intermittent of Photovoltaic (PV) with Maximum Power Point Tracker (MPPT) equipped, Wind Turbine (WT), Energy Storage Systems (ESS) and DR programs are also considered to achieve the optimal control and operation. The ESSs are capable to connect both DC and AC links and the State of Charge (SOC) is maintained within permissible range. The proposed DG control framework and operation scheduling has facilitated the energy management of renewables using dynamic programing approach. A 24-hour time horizon simulation and discussion through three scenarios verified on a IEEE 33 bus distribution network, is done to represent the effectiveness of proposed energy management strategy to keep the whole hybrid grid stable.

Keywords

References

[1] N. J. Swaroopan, “A novel combined economic and emission dispatch control by hybrid particle swarm optimization technique”. Majlesi journal of electrical engineering, Vol. 4, No. 2, pp. 19-24, 2010.

[2] F. Mohammadi, H. Abdi, “Solving dynamic economic emission dispatch problem by random drift particle swarm optimization considering valve-point and spinning reserve constraints”. Majlesi Journal of Energy Management, Vol. 5, No. 1, 2016.

[3] D. C. Secui, “A hybrid particle Swarm optimization algorithm for the economic dispatch problem.” Majlesi Journal of Electrical Engineering, Vol. 9, No. 1, pp. 37-53, 2016.

[4] B. Houari, L. Mohamed, B. Hamid, S. Abdallah, “Economic Dispatch Optimization Using Improved Dynamic Harmony Search Algorithm.” Majlesi Journal of Mechatronic Systems, Vol. 7, No. 1, pp. 45-52, 2018.

[5] X. Liu, Y. Liu, J. Liu, Y. Xiang and X. Yuan, "Optimal planning of AC-DC hybrid transmission and distributed energy resource system: Review and prospects," in CSEE Journal of Power and Energy Systems, Vol. 5, No. 3, pp. 409-422, Sept. 2019.

[6] S. B. Pandya, H. R. Jariwala, “Stochastic Wind-Thermal Power Plants Integrated Multi-Objective Optimal Power Flow.” Majlesi Journal of Electrical Engineering, Vol. 14, No. 2, pp. 93-110, 2020.

[7] Maulik and D. Das, "Optimal power dispatch considering load and renewable generation uncertainties in an AC–DC hybrid microgrid," in IET Generation, Transmission & Distribution, Vol. 13, No. 7, pp. 1164-1176, 9 4 2019.

[8] A. Hussain, V. Bui and H. Kim, "Robust Optimal Operation of AC/DC Hybrid Microgrids Under Market Price Uncertainties," in IEEE Access, Vol. 6, pp. 2654-2667, 2018.

[9] H. Haddadian and R. Noroozian, "Multi-Microgrid-Based Operation of Active Distribution Networks Considering Demand Response Programs," in IEEE Transactions on Sustainable Energy, Vol. 10, No. 4, pp. 1804-1812, Oct. 2019.

[10] Zhang, Y. Xu, Z. Y. Dong and K. P. Wong, "Robust Coordination of Distributed Generation and Price-Based Demand Response in Microgrids," in IEEE Transactions on Smart Grid, Vol. 9, No. 5, pp. 4236-4247, Sept. 2018.

[11] M. L. Little, S. F. Rabbi, K. Pope and J. E. Quaicoe, "Unified Probabilistic Modeling of Wind Reserves for Demand Response and Frequency Regulation in Islanded Microgrids," in IEEE Transactions on Industry Applications, Vol. 54, No. 6, pp. 5671-5681, Nov.-Dec. 2018.

[12] A. Aderibole, H. H. Zeineldin, M. Al Hosani and E. F. El-Saadany, "Demand Side Management Strategy for Droop-Based Autonomous Microgrids Through Voltage Reduction," in IEEE Transactions on Energy Conversion, Vol. 34, No. 2, pp. 878-888, June 2019.

[13] M. Bayat, K. Sheshyekani, M. Hamzeh and A. Rezazadeh, "Coordination of Distributed Energy Resources and Demand Response for Voltage and Frequency Support of MV Microgrids," in IEEE Transactions on Power Systems, Vol. 31, No. 2, pp. 1506-1516, March 2016.

[14] T. Nguyen and L. B. Le, "Risk-Constrained Profit Maximization for Microgrid Aggregators with Demand Response," in IEEE Transactions on Smart Grid, Vol. 6, No. 1, pp. 135-146, Jan. 2015.

[15] N. Liu, X. Yu, C. Wang, C. Li, L. Ma and J. Lei, "Energy-Sharing Model with Price-Based Demand Response for Microgrids of Peer-to-Peer Prosumers," in IEEE Transactions on Power Systems, Vol. 32, No. 5, pp. 3569-3583, Sept. 2017.

[16] Yang, J. Yao, W. Lou and S. Xie, "On Demand Response Management Performance Optimization for Microgrids Under Imperfect Communication Constraints," in IEEE Internet of Things Journal, Vol. 4, No. 4, pp. 881-893, Aug. 2017.

[17] A. Mohsenzadeh, C. Pang and M. Haghifam, "Determining Optimal Forming of Flexible Microgrids in the Presence of Demand Response in Smart Distribution Systems," in IEEE Systems Journal, Vol. 12, No. 4, pp. 3315-3323, Dec. 2018.

[18] T. Samad, E. Koch and P. Stluka, "Automated Demand Response for Smart Buildings and Microgrids: The State of the Practice and Research Challenges," in Proceedings of the IEEE, Vol. 104, No. 4, pp. 726-744, April 2016.

[19] W. E. Elamin and M. F. Shaaban, "New real-time demand-side management approach for energy management systems," in IET Smart Grid, Vol. 2, No. 2, pp. 183-191, 6 2019.

[20] N. Kinhekar, N. P. Padhy, F. Li and H. O. Gupta, "Utility Oriented Demand Side Management Using Smart AC and Micro DC Grid Cooperative," in IEEE Transactions on Power Systems, Vol. 31, No. 2, pp. 1151-1160, March 2016.

[21] L. Martirano et al., "Demand Side Management in Microgrids for Load Control in Nearly Zero Energy Buildings," in IEEE Transactions on Industry Applications, Vol. 53, No. 3, pp. 1769-1779, May-June 2017.

[22] M. H. Yaghmaee, M. Moghaddassian and A. Leon-Garcia, "Autonomous Two-Tier Cloud-Based Demand Side Management Approach with Microgrid," in IEEE Transactions on Industrial Informatics, Vol. 13, No. 3, pp. 1109-1120, June 2017.

[23] X. Yang, Y. Zhang, H. He, S. Ren and G. Weng, "Real-Time Demand Side Management for a Microgrid Considering Uncertainties," in IEEE Transactions on Smart Grid, Vol. 10, No. 3, pp. 3401-3414, May 2019.

[24] M. H. K. Tushar, A. W. Zeineddine and C. Assi, "Demand-Side Management by Regulating Charging and Discharging of the EV, ESS, and Utilizing Renewable Energy," in IEEE Transactions on Industrial Informatics, Vol. 14, No. 1, pp. 117-126, Jan. 2018.

[25] A. Mehdizadeh and N. Taghizadegan, "Robust optimisation approach for bidding strategy of renewable generation-based microgrid under demand side management," in IET Renewable Power Generation, Vol. 11, No. 11, pp. 1446-1455, 13 9 2017.

[26] H. Pashaei-Didani, H. Ahmadi-Nezamabad, A. Mohammadi, and S. Nojavan, “Stochastic-based energy management of hybrid AC/DC microgrid,” Risk-based Energy Management, pp. 203–227, 2020.

[27] S. Nojavan, H. Pashaei-Didani, A. Mohammadi, and H. Ahmadi-Nezamabad, “Deterministic-based energy management of hybrid AC/DC microgrid,” Risk-based Energy Management, pp. 177–202, 2020.

[28] P. Zeng, H. Li, H. He and S. Li, "Dynamic Energy Management of a Microgrid Using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning," in IEEE Transactions on Smart Grid, Vol. 10, No. 4, pp. 4435-4445, July 2019.

[29] Z. Ni, N. Malla and X. Zhong, "Prioritizing Useful Experience Replay for Heuristic Dynamic Programming-Based Learning Systems," in IEEE Transactions on Cybernetics, Vol. 49, No. 11, pp. 3911-3922, Nov. 2019.

Energy Scheduling in a Hybrid DC/AC Micro-Grid Considering Battery/Wind/Photovoltaic Power Sources using Heuristic Optimization Algorithm

References

References

Volume 14, Issue 3 - Serial Number 3September 2020Pages 101-110

Volume 14, Issue 3 - Serial Number 3
September 2020
Pages 101-110