Alternating direction method of multipliers; Electric vehicles; Local electricity market; Robust optimization; Stochastic programming; Wholesale electricity market; % reductions; Alternating directions method of multipliers; Distribution companies; Market price; Second level; Smart charging; Third level; Wholesale electricity markets; Energy Engineering and Power Technology; Electrical and Electronic Engineering
Abstract :
[en] This study investigates a tri-level optimal market strategy for the integrated electric vehicle fleets and solar distributed generations (IEVSDG) to engage in the local electricity market (LEM) as a strategic price-maker. The distribution company (Disco) which operates the LEM, participates in the wholesale electricity market (WEM) to provide its consumers, is also a strategic price-maker. For this purpose, the IEVSDGs are integrated at the first level of the optimization problem, while the Disco operator and WEM operator form the second and third levels, respectively. In other words, Disco acts as an intermediary retailer that links the LEM (modelled by IEEE 69-bus distribution system) to WEM (modelled by an IEEE 24-bus transmission network). The study puts forward a novel solution strategy, where the second and third level problems are conjoined through the Karush–Kuhn–Tucker (KKT) conditions. Moreover, the equilibrium point between the first level and this conjoined problem is achieved through the alternating direction method of multipliers (ADMM). In a hybrid robust optimization (RO) and stochastic programming (SP) approach, the uncertain specifications, such as the arrival/departure times and daily travelled miles are modelled through the SP scenarios. On other hand, the RO was deployed to handle solar power forecasting uncertainties. Different case studies of dumb and smart charging were devised to evaluate the method. The outcomes show that the proposed three-level approach leads to 57.21% reduction in the LEM price, and 0.86% reduction in the WEM price. Furthermore, the smart charging strategy eliminated 105 MWh of load interruptions.
Disciplines :
Energy
Author, co-author :
ZEINALI, Saeid ✱; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
This work was supported by the Luxembourg National Research Fund (FNR) LightGridSEED Project , ref. C21/IS/16215802/LightGridSEED . For the purpose of open access, and in fulfilment of the obligations arising from the grant agreement , the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.
Milošević, N.D., Popović, Ž.N., Kovački, N.V., A multi-period multi-criteria replacement and rejuvenation planning of underground cables in urban distribution networks. Int J Electr Power Energy Syst, 149, 2023, 109018.
Li, Y., Wei, X., Lin, J., Niu, G., A robust fault location method for active distribution network based on self-adaptive switching function. Int J Electr Power Energy Syst, 148, 2023, 109007.
Esmaeili, M., Shafie-khah, M., Catalao, J.P., A system dynamics approach to study the long-term interaction of the natural gas market and electricity market comprising high penetration of renewable energy resources. Int J Electr Power Energy Syst, 139, 2022, 108021.
IRENA, M., Renewable energy policies in a time of transition. Int J Prod Res, 53(9), 2018.
Navas-Anguita, Z., García-Gusano, D., Iribarren, D., A review of techno-economic data for road transportation fuels. Renew Sustain Energy Rev 112:April (2019), 11–26, 10.1016/j.rser.2019.05.041.
IRENA, Z., IRENA (2019) global energy transformation: A roadmap to 2050. 2019.
Nasiri, N., Zeynali, S., Ravadanegh, S.N., Kubler, S., Economic-environmental convex network-constrained decision-making for integrated multi-energy distribution systems under electrified transportation fleets. J Clean Prod, 379, 2022, 134582.
Patel, M., Roy, S., Roskilly, A.P., Smallbone, A., The techno-economics potential of hydrogen interconnectors for electrical energy transmission and storage. J Clean Prod, 335, 2022, 130045.
Parlikar, A., Schott, M., Godse, K., Kucevic, D., Jossen, A., Hesse, H., High-power electric vehicle charging: Low-carbon grid integration pathways with stationary lithium-ion battery systems and renewable generation. Appl Energy, 333, 2023, 120541.
Ullah, Z., Wang, S., Wu, G., Hasanien, H.M., Rehman, A.U., Turky, R.A., et al. Optimal scheduling and techno-economic analysis of electric vehicles by implementing solar-based grid-tied charging station. Energy, 267, 2023, 126560.
Mohammad, A., Zamora, R., Lie, T.T., Energy management for EV participation in local energy markets. 2022 IEEE transportation electrification conference & expo, ITEC, 2022, IEEE, 1327–1331.
de la Torre, S., Aguado, J., Sauma, E., Optimal scheduling of ancillary services provided by an electric vehicle aggregator. Energy, 265, 2023, 126147.
Vijayan, V., Mohapatra, A., Singh, S., Dewangan, C.L., An efficient modular optimization scheme for unbalanced active distribution networks with uncertain EV and PV penetrations. IEEE Trans Smart Grid, 2023.
Shi, X., Xu, Y., Guo, Q., Sun, H., Optimal dispatch based on Aggregated Operation Region of EV considering spatio-temporal distribution. IEEE Trans Sustain Energy 13:2 (2021), 715–731.
Gao, X., Chan, K.W., Xia, S., Zhang, X., Zhang, K., Zhou, J., A multiagent competitive bidding strategy in a pool-based electricity market with price-maker participants of WPPs and EV aggregators. IEEE Trans Ind Inform 17:11 (2021), 7256–7268.
Sangswang, A., Konghirun, M., Optimal strategies in home energy management system integrating solar power, energy storage, and vehicle-to-grid for grid support and energy efficiency. IEEE Trans Ind Appl 56:5 (2020), 5716–5728, 10.1109/TIA.2020.2991652.
Das, S., Acharjee, P., Bhattacharya, A., Charging scheduling of electric vehicle incorporating grid-to-vehicle and vehicle-to-grid technology considering in smart grid. IEEE Trans Ind Appl 57:2 (2021), 1688–1702, 10.1109/TIA.2020.3041808.
Patnam, B.S.K., Pindoriya, N.M., DLMP calculation and congestion minimization with EV aggregator loading in a distribution network using bilevel program. IEEE Syst J, 2020, 1–12, 10.1109/jsyst.2020.2997189.
Deb, S., Goswami, A.K., Harsh, P., Sahoo, J.P., Chetri, R.L., Roy, R., et al. Charging coordination of plug-in electric vehicle for congestion management in distribution system integrated with renewable energy sources. IEEE Trans Ind Appl 56:5 (2020), 5452–5462, 10.1109/TIA.2020.3010897.
Li, Y., Han, M., Yang, Z., Li, G., Coordinating flexible demand response and renewable uncertainties for scheduling of community integrated energy systems with an electric vehicle charging station: A bi-level approach. IEEE Trans Sustain Energy, 2021, 10.1109/TSTE.2021.3090463.
Liu, W., Chen, S., Hou, Y., Yang, Z., Optimal reserve management of electric vehicle aggregator: Discrete bilevel optimization model and exact algorithm. IEEE Trans Smart Grid 12:5 (2021), 4003–4015, 10.1109/TSG.2021.3075710.
Hajebrahimi, A., Kamwa, I., Abdelaziz, M.M.A., Moeini, A., Scenario-wise distributionally robust optimization for collaborative intermittent resources and electric vehicle aggregator bidding strategy. IEEE Trans Power Syst 35:5 (2020), 3706–3718, 10.1109/TPWRS.2020.2985572.
Li, Y., Ni, Z., Zhao, T., Yu, M., Liu, Y., Wu, L., et al. Coordinated scheduling for improving uncertain wind power adsorption in electric vehicles - wind integrated power systems by multiobjective optimization approach. IEEE Trans Ind Appl 56:3 (2020), 2238–2250, 10.1109/TIA.2020.2976909.
Sharma, S., Jain, P., Risk-averse integrated DR and dynamic V2G scheduling of parking lot operator for enhanced market efficiency. Energy, 275, 2023, 127428.
Najafi, A., Jasiński, M., Leonowicz, Z., A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem. Energy, 249, 2022, 123674.
Zare, M., Chabok, H., Niknam, T., Azizipanah-Abarghooee, R., Smart coordinated management of distribution networks with high penetration of PEVs using FLC. IET Gener, Transm Distribution 14:3 (2020), 476–485.
Mobaraki, A.H., Salyani, P., Safari, A., Quteishat, A., Younis, M.A., A hybrid robust-stochastic optimization model for planned outage based day-ahead scheduling of a plug-in electric vehicles parking lot. Sustain Energy Technol Assess, 54, 2022, 102831.
Sheikhahmadi, P., Bahramara, S., Mazza, A., Chicco, G., Catalão, J.P., Bi-level optimization model for the coordination between transmission and distribution systems interacting with local energy markets. Int J Electr Power Energy Syst, 124, 2021, 106392, 10.1016/j.ijepes.2020.106392.
Mohiti, M., Monsef, H., Anvari-moghaddam, A., Guerrero, J., Lesani, H., A decentralized robust model for optimal operation of distribution companies with private microgrids. Int J Electr Power Energy Syst 106 (2019), 105–123, 10.1016/J.IJEPES.2018.09.031.
Hu, B., Gong, Y., Chung, C., Noble, B., Poelzer, G., Price-maker bidding and offering strategies for networked microgrids in day-ahead electricity markets. IEEE Trans Smart Grid, 2021, 1, 10.1109/TSG.2021.3109111.
Zhang, C., Wang, Q., Wang, J., Korpås, M., Pinson, P., Østergaard, J., et al. Trading strategies for distribution company with stochastic distributed energy resources. Appl Energy 177 (2016), 625–635.
Xia, Y., Xu, Q., Tao, S., Du, P., Ding, Y., Fang, J., Preserving operation privacy of peer-to-peer energy transaction based on enhanced benders decomposition considering uncertainty of renewable energy generations. Energy, 250, 2022, 123567.
Xia, Y., Xu, Q., Tao, S., Du, P., Ding, Y., Fang, J., Preserving operation privacy of peer-to-peer energy transaction based on enhanced benders decomposition considering uncertainty of renewable energy generations. Energy, 250, 2022, 123567.
Karimi, H., Jadid, S., Modeling of transactive energy in multi-microgrid systems by hybrid of competitive-cooperative games. Electr Power Syst Res, 201, 2021, 107546.
Nasiri, N., Zeynali, S., Ravadanegh, S.N., Kubler, S., Moment-based distributionally robust peer-to-peer transactive energy trading framework between networked microgrids, smart parking lots and electricity distribution network. IEEE Trans Smart Grid, 2023.
Nasiri, N., Zeynali, S., Ravadanegh, S.N., A tactical transactive energy scheduling for the electric vehicle-integrated networked microgrids. Sustainable Cities Soc, 83, 2022, 103943.
Zeynali, S., Nasiri, N., Ravadanegh, S.N., Marzband, M., The role of smart electric vehicle charging in optimal decision-making of the active distribution network. Electric vehicle integration via smart charging: technology, standards, implementation, and applications, 2022, Springer, 201–222.
Nasiri, N., Zeynali, S., Ravadanegh, S.N., Kubler, S., Economic-environmental convex network-constrained decision-making for integrated multi-energy distribution systems under electrified transportation fleets. J Clean Prod, 379, 2022, 134582.
Cao, Y., Li, D., Zhang, Y., Tang, Q., Khodaei, A., Zhang, H., et al. Optimal energy management for multi-microgrid under a transactive energy framework with distributionally robust optimization. IEEE Trans Smart Grid 13:1 (2021), 599–612.
Nasiri, N., Zeynali, S., Ravadanegh, S.N., Marzband, M., A hybrid robust-stochastic approach for strategic scheduling of a multi-energy system as a price-maker player in day-ahead wholesale market. Energy, 235, 2021, 121398, 10.1016/J.ENERGY.2021.121398.
Zeynali, S., Nasiri, N., Marzband, M., Ravadanegh, S.N., A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets. Appl Energy, 300, 2021, 117432, 10.1016/J.APENERGY.2021.117432.
Xu, B., Zhao, J., Zheng, T., Litvinov, E., Kirschen, D.S., Factoring the cycle aging cost of batteries participating in electricity markets. IEEE Trans Power Syst 33:2 (2018), 2248–2259, 10.1109/TPWRS.2017.2733339.
Bisschop, J., AIMMS optimization modeling. 2006.
Bahramara, S., Sheikhahmadi, P., Mazza, A., Chicco, G., Shafie-Khah, M., Catalão, J.P., A risk-based decision framework for the distribution company in mutual interaction with the wholesale day-ahead market and microgrids. IEEE Trans Ind Inf 16:2 (2020), 764–778, 10.1109/TII.2019.2921790.
Xue, Y., Shahidehpour, M., Pan, Z., Wang, B., Zhou, Q., Guo, Q., et al. Reconfiguration of district heating network for operational flexibility enhancement in power system unit commitment. IEEE Trans Sustain Energy 12:2 (2021), 1161–1173, 10.1109/TSTE.2020.3036887.
Sheikhahmadi, P., Bahramara, S., Mazza, A., Chicco, G., Catalão, J.P., Bi-level optimization model for the coordination between transmission and distribution systems interacting with local energy markets. Int J Electr Power Energy Syst, 124, 2021, 106392.
Conejo, A.J., Carrión, M., Morales, J.M., Decision making under uncertainty in electricity markets. International series in operations research & management science, 2010, Springer US, Boston, MA, 10.1007/978-1-4419-7421-1.
Yan, M., Shahidehpour, M., Alabdulwahab, A., Abusorrah, A., Gurung, N., Zheng, H., et al. Blockchain for transacting energy and carbon allowance in networked microgrids. IEEE Trans Smart Grid, 2021, 1, 10.1109/TSG.2021.3109103.
Nikmehr, N., Zhang, P., Bragin, M., Quantum distributed unit commitment. IEEE Trans Power Syst, 2022.
National household travel survey: URL https://nhts.ornl.gov/.
Zeynali, S., Rostami, N., Feyzi, M., Multi-objective optimal short-term planning of renewable distributed generations and capacitor banks in power system considering different uncertainties including plug-in electric vehicles. Int J Electr Power Energy Syst, 119, 2020, 105885.
Data available at: URL http://motor.ece.iit.edu/data.
National household travel survey, URL https://nhts.ornl.gov/.
Data repository: URL https://uniluxembourg-my.sharepoint.com/:f:/g/personal/saeid_zeinali_uni_lu/ElUe5JPZi31Lkio3lhTwVBkBefQrQXQljcaj7AiNtoarxQ?e=IO4au9.
Fazlalipour, P., Ehsan, M., Mohammadi-Ivatloo, B., Risk-aware stochastic bidding strategy of renewable micro-grids in day-ahead and real-time markets. Energy 171 (2019), 689–700.
Apostolopoulou, D., De Greve, Z., McCulloch, M., Robust optimization for hydroelectric system operation under uncertainty. IEEE Trans Power Syst 33:3 (2018), 3337–3348.
Bertsimas, D., Sim, M., Robust discrete optimization and network flows. Math Program 98:1 (2003), 49–71.
