A hybrid RBFNN–BBMO methodology for robust energy management in grid‐Connected microgrid

[1]  Hongseok Kim,et al.  Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost , 2016 .

[2]  Zhaohao Ding,et al.  Integrated Stochastic Energy Management for Data Center Microgrid Considering Waste Heat Recovery , 2019, 2018 IEEE Industry Applications Society Annual Meeting (IAS).

[3]  Y Riffonneau,et al.  Optimal Power Flow Management for Grid Connected PV Systems With Batteries , 2011, IEEE Transactions on Sustainable Energy.

[4]  Tao Jiang,et al.  Distributed energy management for community microgrids considering network operational constraints and building thermal dynamics , 2019, Applied Energy.

[5]  Andreas Sumper,et al.  Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets , 2013 .

[6]  Derong Liu,et al.  Residential energy system control and management using adaptive dynamic programming , 2011, The 2011 International Joint Conference on Neural Networks.

[7]  Yongqian Liu,et al.  Real-time energy management for a smart-community microgrid with battery swapping and renewables , 2019, Applied Energy.

[8]  Majid Shahabi,et al.  Comprehensive analysis of risk-based energy management for dependent micro-grid under normal and emergency operations , 2019, Energy.

[9]  Guangzhong Dong,et al.  Data-Driven Energy Management in a Home Microgrid Based on Bayesian Optimal Algorithm , 2019, IEEE Transactions on Industrial Informatics.

[10]  Jianguo Zhu,et al.  A magnetically coupled multi-port, multi-operation-mode micro-grid with a predictive dynamic programming-based energy management for residential applications , 2019 .

[11]  D. Bui,et al.  A hybrid machine learning ensemble approach based on a Radial Basis Function neural network and Rotation Forest for landslide susceptibility modeling: A case study in the Himalayan area, India , 2017, International Journal of Sediment Research.

[12]  T. Praveen Kumar,et al.  Power Flow Management of the Grid-Connected Hybrid Renewable Energy System: A PLSANN Control Approach , 2019 .

[13]  Hongmin Meng,et al.  Cooperative energy management optimization based on distributed MPC in grid-connected microgrids community , 2019, International Journal of Electrical Power & Energy Systems.

[14]  Hak-Man Kim,et al.  An internal trading strategy for optimal energy management of combined cooling, heat and power in building microgrids , 2019, Applied Energy.

[15]  Mohammad Nasir Uddin,et al.  Microgrid control methods toward achieving sustainable energy management , 2019, Applied Energy.

[16]  Adi Soeprijanto,et al.  Operation optimization stand-alone microgrid using firefly algorithm considering lifetime characteristics of battery , 2016, 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA).

[17]  Haibo He,et al.  Interactive Energy Management for Enhancing Power Balances in Multi-Microgrids , 2019, IEEE Transactions on Smart Grid.

[18]  Bo Yang,et al.  Adaptive deep dynamic programming for integrated frequency control of multi-area multi-microgrid systems , 2019, Neurocomputing.

[19]  Hemanshu R. Pota,et al.  Modified PSO algorithm for real-time energy management in grid-connected microgrids , 2018, Renewable Energy.

[20]  Maheswarapu Sydulu,et al.  CMBSNN for Power Flow Management of the Hybrid Renewable Energy – Storage System-Based Distribution Generation , 2018, IETE Technical Review.

[21]  K. Sureshkumar,et al.  Power flow management in micro grid through renewable energy sources using a hybrid modified dragonfly algorithm with bat search algorithm , 2019, Energy.

[22]  Junwei Cao,et al.  Optimal energy management strategies for energy Internet via deep reinforcement learning approach , 2019, Applied Energy.

[23]  Hoay Beng Gooi,et al.  A Secure Distributed Transactive Energy Management Scheme for Multiple Interconnected Microgrids Considering Misbehaviors , 2019, IEEE Transactions on Smart Grid.

[24]  S. S. Darly,et al.  Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system , 2020 .

[25]  Kallol Roy,et al.  Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system , 2019, Energy.

[26]  Thomas Morstyn,et al.  Incentivizing Prosumer Coalitions With Energy Management Using Cooperative Game Theory , 2019, IEEE Transactions on Power Systems.

[27]  Francesco Piazza,et al.  Optimal Home Energy Management Under Dynamic Electrical and Thermal Constraints , 2013, IEEE Transactions on Industrial Informatics.

[28]  Jun Zeng,et al.  A Potential Game Approach to Distributed Operational Optimization for Microgrid Energy Management With Renewable Energy and Demand Response , 2019, IEEE Transactions on Industrial Electronics.

[29]  Subhashish Bhattacharya,et al.  Rule-Based Control of Battery Energy Storage for Dispatching Intermittent Renewable Sources , 2010, IEEE Transactions on Sustainable Energy.

[30]  Ryohei Yokoyama,et al.  Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks , 2019, Energy.

[31]  Naresh Kumari,et al.  An Efficient Technique-Based Distributed Energy Management for Hybrid MG System: A Hybrid RFCFA Technique , 2020 .

[32]  Seyed Hossein Hosseinian,et al.  Risk‐averse energy management system for isolated microgrids considering generation and demand uncertainties based on information gap decision theory , 2019, IET Renewable Power Generation.

[33]  M Durairasan,et al.  An efficient control strategy for optimal power flow management from a renewable energy source to a generalized three-phase microgrid system: A hybrid squirrel search algorithm with whale optimization algorithm approach , 2020, Trans. Inst. Meas. Control.