Optimal energy management in a microgrid under uncertainties using novel hybrid metaheuristic algorithm
Tài liệu tham khảo
Vandezande, 2010, Well-functioning balancing markets: A prerequisite for wind power integration, Energy Policy, 38, 3146, 10.1016/j.enpol.2009.07.034
Mehdizadeh, 2018, Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management, Appl. Energy, 211, 617, 10.1016/j.apenergy.2017.11.084
Venkataramanan, 2008, A larger role for microgrids, IEEE Power Energy Mag., 6, 78, 10.1109/MPE.2008.918720
Hatefi einaddin, 2017, Power management in a utility connected micro-grid with multiple renewable energy sources, J. Oper. Autom. Power Eng., 5, 1
Rabiee, 2016, Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties, Renew. Sustain. Energy Rev., 57, 721, 10.1016/j.rser.2015.12.041
Alavi, 2015, Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method, Energy Convers. Manage., 95, 314, 10.1016/j.enconman.2015.02.042
Soroudi, 2011, A possibilistic–probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks—A case study, Renew. Sustain. Energy Rev., 15, 794, 10.1016/j.rser.2010.09.035
Kuznetsova, 2015, Analysis of robust optimization for decentralized microgrid energy management under uncertainty, Int. J. Electr. Power Energy Syst., 64, 815, 10.1016/j.ijepes.2014.07.064
Yukseltan, 2020, Hourly electricity demand forecasting using Fourier analysis with feedback, Energy Strategy Rev., 31, 10.1016/j.esr.2020.100524
Jagait, 2021, Load forecasting under concept drift: Online ensemble learning with recurrent neural network and ARIMA, IEEE Access, 9, 98992, 10.1109/ACCESS.2021.3095420
Guan, 2021, Customer load forecasting method based on the industry electricity consumption behavior portrait, Front. Energy Res., 9, 10.3389/fenrg.2021.742993
Karavas, 2015, A multi-agent decentralized energy management system based on distributed intelligence for the design and control of autonomous polygeneration microgrids, Energy Convers. Manage., 103, 166, 10.1016/j.enconman.2015.06.021
Adika, 2013, Energy management for a customer owned grid-tied photovoltaic micro generator, 1
Nguyen, 2014, Optimal energy management for building microgrid with constrained renewable energy utilization, 133
Tsikalakis, 2008, Centralized control for optimizing microgrids operation, IEEE Trans. Energy Convers., 23, 241, 10.1109/TEC.2007.914686
Merabet, 2017, Energy management and control system for laboratory scale microgrid based wind-PV-battery, IEEE Trans. Sustain. Energy, 8, 145, 10.1109/TSTE.2016.2587828
Pascual, 2015, Energy management strategy for a renewable-based residential microgrid with generation and demand forecasting, Appl. Energy, 158, 12, 10.1016/j.apenergy.2015.08.040
Song, 2015, Optimal energy management of multi-microgrids with sequentially coordinated operations, Energies, 8, 8371, 10.3390/en8088371
Shayeghi, 2017, Optimal operation management of grid-connected microgrid using multi-objective group search optimization algorithm, J. Oper. Autom. Power Eng., 5, 227
Shokri Gazafroudi, 2015, Assessing the operating reserves and costs with considering customer choice and wind power uncertainty in pool-based power market, Int. J. Electr. Power Energy Syst., 67, 202, 10.1016/j.ijepes.2014.11.007
Ghasemi, 2018, Coordination of pumped-storage unit and irrigation system with intermittent wind generation for intelligent energy management of an agricultural microgrid, Energy, 142, 1, 10.1016/j.energy.2017.09.146
Zia, 2018, Microgrids energy management systems: A critical review on methods, solutions, and prospects, Appl. Energy, 222, 1033, 10.1016/j.apenergy.2018.04.103
Chevy Volt website [Online], URL http://www.chevy-volt.net/chevrolet-volt-specs.htm.
Parks, 2007
S.W. Hadley, Impact of Plug-in Hybrid Vehicles on the Electric Grid.
Jabbari-Sabet, 2016, Microgrid operation and management using probabilistic reconfiguration and unit commitment, Int. J. Electr. Power Energy Syst., 75, 328, 10.1016/j.ijepes.2015.09.012
Silva, 2020, Futuristic sustainable energy management in smart environments: A review of peak load shaving and demand response strategies, challenges, and opportunities, Sustainability, 12, 10.3390/su12145561
Shao, 2010, Impact of TOU rates on distribution load shapes in a smart grid with PHEV penetration, 1
Moghaddam, 2012, Multi-operation management of a typical micro-grids using particle swarm optimization: A comparative study, Renew. Sustain. Energy Rev., 16, 1268, 10.1016/j.rser.2011.10.002
Karevan, 2020, Transductive LSTM for time-series prediction: An application to weather forecasting, Neural Netw., 125, 1, 10.1016/j.neunet.2019.12.030
Ding, 2020, Interpretable spatio-temporal attention LSTM model for flood forecasting, Neurocomputing, 403, 348, 10.1016/j.neucom.2020.04.110
Maragheh, 2022, A new hybrid based on long short-term memory network with spotted hyena optimization algorithm for multi-label text classification, Mathematics, 10, 488, 10.3390/math10030488
García, 2008, A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter Optimization, J. Heuristics, 15, 617, 10.1007/s10732-008-9080-4
Cuevas, 2020, Recent metaheuristics algorithms for parameter identification, Vol. XIV, 297, 10.1007/978-3-030-28917-1
Yousif, 2018, Application of particle swarm optimization to a scheduling strategy for microgrids coupled with natural gas networks, Energies, 11, 10.3390/en11123499
Sedighizadeh, 2019, A two-stage optimal energy management by using ADP and HBB-BC algorithms for microgrids with renewable energy sources and storages, J. Energy Storage, 21, 460, 10.1016/j.est.2018.12.010
Zakariazadeh, 2014, Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach, Energy Convers. Manage., 78, 151, 10.1016/j.enconman.2013.10.051
D.O.M. power Schedule 1T [Online], URL https://www.dominionenergy.com/virginia.htm.
DataUSA [Online], URL http://www.datausa.io.htm.
Zakariazadeh, 2014, Smart microgrid energy and reserve scheduling with demand response using stochastic optimization, Int. J. Electr. Power Energy Syst., 63, 523, 10.1016/j.ijepes.2014.06.037
Nait-Sidi-Moh, 2018, A prediction model of electric vehicle charging requests, Procedia Comput. Sci., 141, 127, 10.1016/j.procs.2018.10.158
Saremi, 2017, Grasshopper optimisation algorithm: Theory and application, Adv. Eng. Softw., 105, 30, 10.1016/j.advengsoft.2017.01.004
Yang, 2012, Flower pollination algorithm for global optimization, 240
Chechkin, 2008, Introduction to the theory of Lévy flights, 129
Demand Response as a Solution to Electricity Shortages by WDW [Online], http://policyeconomist.wordpress.com/2006/05/19/demand-response-as-a-solution-to-electricity-shortages.