Design and implementation of a peer-to-peer energy trading scheme in multi-microgrid network with photovoltaics and wind energy

Year 2023, Volume: 7 Issue: 2, 158 - 172, 30.06.2023

Muhammad Ehjaz , Muhammad Iqbal Syed Sajjad Haider Zaidi Bilal Khan

https://doi.org/10.30521/jes.1042333

Cited By: 2

Abstract

Expected widespread deployment of Peer-to-Peer energy transactions through affective utilization of Renewable Energy Sources require efficient energy transaction mechanism among the microgrids. We propose a scheme to establish peer-to-peer energy trading in multi-microgrid network by considering photovoltaic and wind energy systems. The research objectives are to minimize overall cost of all microgrids in multi-microgrid network and minimize the loading on centralized power network. Various parameters of photovoltaics and wind energy systems are modeled to explore their impact on P2P energy trading. Energy Management Unit establishes the smart contracts among microgrids, manages power transactions and calculates the cost based on dynamic pricing scheme in the multi-microgrid network. Two different cases are considered with respect to the types of power transaction among the microgrids in the multi-microgrid network and main grid. The effectiveness of the proposed scheme is validated by implementing on local small-scale power distribution system.

Keywords

Energy management, Microgrid, Peer-to-Peer Energy Trading, power system optimization, Renewable energy resources

References

• [1] Aftab, L, Jamil, U. Integrated Energy Modeling-Present status of Pakistan vs. World. In: PGSRET 2018 International Conference on Power Generation Systems and Renewable Energy Technologies; 10 Sep 2018: IEEE, pp. 1-9.
• [2] Ejaz, S., Aamir, M., Khan, M.A. and Ashfaq, B., Modeling and analysis of CPEC energy power projects using LEAP model. In iCoMET 2018 International Conference on Computing, Mathematics and Engineering Technologies; March 2018: IEEE, pp. 1-8.
• [3] Khan, MA, Çamur, H, Kassem, Y. Modeling predictive assessment of wind energy potential as a power generation sources at some selected locations in Pakistan. Modeling Earth Systems and Environment 2018; 5(2): 555-569. DOI: 10.1007/s40808-018-0546-6
• [4] Baloch, MH, Wang, J, Kaloi, GS, Memon, AA, Larik, AS, Sharma, P. Techno‐economic analysis of power generation from a potential wind corridor of Pakistan: An overview. Environmental Progress & Sustainable Energy 2019; 38(2): 706-720. DOI: 10.1002/ep.13005.
• [5] Solangi, YA, Tan, Q, Khan, MWA, Mirjat, NH, Ahmed, I. The selection of wind power project location in the Southeastern Corridor of Pakistan: A factor analysis, AHP, and fuzzy-TOPSIS application. Energies 2018; 11(8): 1940. DOI: 10.3390/en11081940.
• [6] Mudeer, A, Noman Ali, M, Memon, IA. A review of wind energy potential in Sindh, Pakistan. AIP Conference Proceedings 2019; AIP Publishing LLC: 020017.
• [7] Mengal, A., Mirjat, N.H., Walasai, G.D., Khatri, S.A., Harijan, K., Uqaili, M.A.,. Modeling of future electricity generation and emissions assessment for Pakistan. Processes 2019, 7(4): 212. 10.3390/pr7040212.
• [8] Hussain Baloch, M, Ishak, D, Tahir Chaudary, S, Ali, B, Asghar Memon, A, Ahmed Jumani, T. Wind power integration: An experimental investigation for powering local communities. Energies 2019; 12(4): 621. 10.3390/en12040621.
• [9] Ahmad, SS, Al Rashid, A, Raza, SA, Zaidi, AA, Khan, SZ, Koç, M. Feasibility analysis of wind energy potential along the coastline of Pakistan. Ain Shams Engineering Journal 2022; 13(1): 101542. DOI: 10.1016/j.asej.2021.07.001.
• [10] Hemanand, T, Subramaniam, NP, Venkateshkumar, M. Comparative analysis of intelligent controller based microgrid integration of hybrid PV/wind power system. Journal of Ambient Intelligence and Humanized Computing 2018; 1-20. DOI: 10.1007/s12652-018-0961-6.
• [11] Arani, MF, Mohamed, YA. Cooperative control of wind power generator and electric vehicles for microgrid primary frequency regulation. IEEE Transactions on Smart Grid 2017; 9(6): 5677-5686. DOI: 10.1109/TSG.2017.2693992.
• [12] Sarshar, J., Moosapour, S.S., Joorabian, M., Multi-objective energy management of a micro-grid considering uncertainty in wind power forecasting. Energy 2017; 139: 680-693. DOI: 10.1016/j.energy.2017.07.138.
• [13] Zheng, D., Eseye, A.T., Zhang, J., Li, H., Short-term wind power forecasting using a double-stage hierarchical ANFIS approach for energy management in microgrids. Protection and Control of Modern Power Systems 2017; 2(1): 1-10. DOI: 10.1186/s41601-017-0041-5.
• [14] Sewwandi, KM, Senarathna, TS, Lakshika, KA, Wong, VY, Hemapala, KT, Lucas, JR. Porawagamage GD. Wind turbine emulator for a microgrid. In: i-PACT 2017 Innovations in Power and Advanced Computing Technologies; 21-22 April 2017: IEEE, pp. 1-6.
• [15] Tavakoli, M., Shokridehaki, F., Marzband, M., Godina, R., Pouresmaeil, E.,. A two stage hierarchical control approach for the optimal energy management in commercial building microgrids based on local wind power and PEVs. Sustainable Cities and Society 2018; 41: pp.332-340. DOI: 10.1016/j.scs.2018.05.035.
• [16] Dehnavi, G. and Ginn, H.L., Distributed load sharing among converters in an autonomous microgrid including PV and wind power units. IEEE Transactions on Smart Grid 2018; 10(4): 4289-4298. DOI: 10.1109/TSG.2018.2856480.
• [17] Zhou, Y, Zhai, Q, Zhou, M, Li, X. Generation scheduling of self-generation power plant in enterprise microgrid with wind power and gateway power bound limits. IEEE Transactions on Sustainable Energy 2019; 11(2): 758-70. DOI: 10.1109/TSTE.2019.2905280.
• [18] Liu, W., Li, N., Jiang, Z., Chen, Z., Wang, S., Han, J., Zhang, X., Liu, C., Smart micro-grid system with wind/PV/battery. Energy Procedia 2018; 152: pp.1212-1217. DOI: 10.1016/j.egypro.2018.09.171.
• [19] Li, Y., Xu, Z., Xiong, L., Song, G., Zhang, J., Qi, D., Yang, H., A cascading power sharing control for microgrid embedded with wind and solar generation. Renewable Energy 2019; 132: 846-860. DOI: 10.1016/j.renene.2018.07.150.
• [20] Imani, MH, Niknejad, P, Barzegaran, MR. Implementing Time-of-Use Demand Response Program in microgrid considering energy storage unit participation and different capacities of installed wind power. Electric Power Systems Research 2019; 175: 105916. DOI: 10.1016/j.epsr.2019.105916.
• [21] Jiang, Y, Guo, L. Research on wind power accommodation for an electricity-heat-gas integrated microgrid system with power-to-gas. IEEE Access 2019; 7: 87118-87126. DOI: 10.1109/ACCESS.2019.2924577.
• [22] Vahedipour-Dahraie, M, Rashidizadeh-Kermani, H, Anvari-Moghaddam, A. Risk-constrained stochastic scheduling of a grid-connected hybrid microgrid with variable wind power generation. Electronics 2019; 8(5): 577. DOI: 10.3390/electronics8050577.
• [23] Azeroual, M, Lamhamdi, T, El Moussaoui, H, El Markhi, H. Simulation tools for a smart grid and energy management for microgrid with wind power using multi-agent system. Wind Engineering 2020; 44(6): 661-672. DOI: 10.1177/0309524X19862755.
• [24] Mahmood, I, Mobeen, M, Rahman, AU, Younis, S, Malik, AW, Fraz, MM, Ullah, K. Modeling, simulation and forecasting of wind power plants using agent-based approach. Journal of Cleaner Production 2020; 276: 124172. DOI: 10.1016/j.jclepro.2020.124172.
• [25] Yoo, YS, Hwang, T, Kang, S, Newaz, SS, Lee, IW, Choi, JK. Peer-to-peer based energy trading system for heterogeneous small-scale DERs. In: ICTC International Conference on Information and Communication Technology Convergence; 18-20 October 2017: IEEE. pp. 813-816.
• [26] Denktas, B., Pekdemir, S, Soykan, G. Peer to peer business model approach for renewable energy cooperatives. In: ICRERA 7th International Conference on Renewable Energy Research and Applications; 5-8 December 2018: IEEE, pp. 1336-1339.
• [27] Ullah, Md Habib, Jae-Do, Park. Peer-to-peer energy arbitrage in prosumer-based smart residential distribution system. In: ECCE IEEE Energy Conversion Congress and Exposition; 29 September – 3 October 2019: IEEE, pp. 508-514.
• [28] Rao, B.H., Arun, SL, Selvan, MP. Framework of locality electricity trading system for profitable peer‐to‐peer power transaction in locality electricity market. IET Smart Grid 2020; 3(3): pp.318-330. DOI: 10.1049/iet-stg.2019.0131.
• [29] Deacon, S., Pisica, I, Taylor, G. A Brief Review of Methods to Simulate Peer-to-Peer Trading in Electricity Networks. In UPEC 2020 55th International Universities Power Engineering Conference; 1-4 September 2020: IEEE. pp. 1-6.
• [30] Vahedipour-Dahraie, M., Rashidizadeh-Kermani, H., Shafie-Khah, M. and Siano, P., Peer-to-peer energy trading between wind power producer and demand response aggregators for scheduling joint energy and reserve. IEEE Systems Journal 2020; 15(1):705-714. DOI: 10.1109/JSYST.2020.2983101.
• [31] Feng, Y, Fan, J, Wang, J, Li,Y. Peer-to-peer Energy Trading Platform Using Consortium Blockchain. In: APPEEC 12th IEEE PES Asia-Pacific Power and Energy Engineering Conference; 20-23 September 2020: IEEE, pp. 1-5.
• [32] Rashidizadeh-Kermani, H, Vahedipour-Dahraie, M, Shafie-khah, M, Catalão, JP. Joint Energy and Reserve Scheduling of a Wind Power Producer in a Peer-to-Peer Mechanism. IEEE Systems Journa 2020; 15: pp. 4315 – 4324. DOI: 10.1109/JSYST.2020.3026233.
• [33] Vieira, G, Zhang, J. Peer-to-peer energy trading in a microgrid leveraged by smart contracts. Renewable and Sustainable Energy Reviews 2021; 143:110900. DOI: 10.1016/j.rser.2021.110900.
• [34] Liu, J., Yang, H. and Zhou, Y., Peer-to-peer energy trading of net-zero energy communities with renewable energy systems integrating hydrogen vehicle storage. Applied Energy 2021; 298: 117206. DOI: 10.1016/j.apenergy.2021.117206.
• [35] Paudel, A. and Beng, G.H., A hierarchical peer-to-peer energy trading in community microgrid distribution systems. In: PESGM IEEE Power & Energy Society General Meeting; 5-9 August 2018: IEEE, pp. 1-5.
• [36] Wang, N, Xu, W, Xu, Z, Shao, W. Peer-to-peer energy trading among microgrids with multidimensional willingness. Energies 2018; 11(12): 3312. DOI: 10.3390/en11123312.
• [37] Xu, D., Zhou, B., Liu, N., Wu, Q., Voropai, N., Li, C. and Barakhtenko, E., Peer-to-Peer Multienergy and Communication Resource Trading for Interconnected Microgrids Microgrids. IEEE Transactions on Industrial Informatics 2020; 17(4): 2522-2533, DOI: 10.1109/TII.2020.3000906.
• [38] Ab-BelKhair, Adel, Javad Rahebi, Nureddin, A. A. M. A study of deep neural network controller-based power quality improvement of hybrid PV/Wind systems by using smart inverter. International Journal of Photoenergy 2020.
• [39] Nureddin, A. A. M., Rahebi, J., Ab-BelKhair, A. Power management controller for microgrid integration of hybrid PV/fuel cell system based on artificial deep neural network. International Journal of Photoenergy 2020; 2020: 8896412. https://doi.org/10.1155/2020/8896412.
• [40] Ehjaz, M, Iqbal, M, Zaidi, SSH. Khan, BM. A Novel Scheme for P2P Energy Trading Considering Energy Congestion in Microgrid. IEEE Access 2021; 9: 147649-147664. DOI: 10.1109/ACCESS.2021.3124792.