Machine Learning Techniques for Improving Self-Consumption in Renewable Energy Communities
暂无分享,去创建一个
David Vangulick | Jean-François Toubeau | François Vallée | Zacharie De Greve | Adriano Arrigo | Jeremie Bottieau | Aurélien Wautier | Pierre-David Dapoz | Z. D. Greve | F. Vallée | J. Toubeau | J. Bottieau | D. Vangulick | Adriano Arrigo | Aurélien Wautier | Pierre-David Dapoz | Z. D. Grève
[1] Choong Seon Hong,et al. Day-ahead Energy Sharing Schedule for the P2P Prosumer Community Using LSTM and Swarm Intelligence , 2020, 2020 International Conference on Information Networking (ICOIN).
[2] Thorsten Staake,et al. Explaining and predicting annual electricity demand of enterprises – a case study from Switzerland , 2018, Energy Inform..
[3] Jean-François Toubeau,et al. Recalibration of recurrent neural networks for short-term wind power forecasting , 2021 .
[4] Juan M. Morales,et al. Real-Time Demand Response Model , 2010, IEEE Transactions on Smart Grid.
[5] Kuldip K. Paliwal,et al. Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..
[6] Nadia Oudjane,et al. Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management , 2017, IEEE Transactions on Smart Grid.
[7] Chris Eliasmith,et al. Hyperopt: a Python library for model selection and hyperparameter optimization , 2015 .
[8] Pierre Pinson,et al. Impact of Public Aggregate Wind Forecasts on Electricity Market Outcomes , 2017, IEEE Transactions on Sustainable Energy.
[9] Laurine Duchesne,et al. Sensitivity Analysis of a Local Market Model for Community Microgrids , 2019, 2019 IEEE Milan PowerTech.
[10] Thomas Morstyn,et al. Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences , 2019, IEEE Transactions on Power Systems.
[11] Ying Wah Teh,et al. Time-series clustering - A decade review , 2015, Inf. Syst..
[12] Benjamin Sovacool,et al. Electricity market design for the prosumer era , 2016, Nature Energy.
[13] Tarek AlSkaif,et al. Smart charging of community storage units using Markov chains , 2017, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).
[14] Jean-François Toubeau,et al. Deep Learning-Based Multivariate Probabilistic Forecasting for Short-Term Scheduling in Power Markets , 2019, IEEE Transactions on Power Systems.
[15] Daniel Pérez Palomar,et al. Demand-Side Management via Distributed Energy Generation and Storage Optimization , 2013, IEEE Transactions on Smart Grid.
[16] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[17] Jean-François Toubeau,et al. A New Cooperative Framework for a Fair and Cost-Optimal Allocation of Resources within a Low Voltage Electricity Community , 2020, ArXiv.
[18] Damien Ernst,et al. E-CLOUD, the open microgrid in existing network infrastructure , 2017 .
[19] Andreas Ehrenmann,et al. Unintended consequences: The snowball effect of energy communities , 2020 .
[20] Tianqi Chen,et al. XGBoost: A Scalable Tree Boosting System , 2016, KDD.
[21] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[22] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[23] R. Ramakumar,et al. A framework for intelligent control of SIRES for rural communities , 2017, 2017 IEEE Power & Energy Society General Meeting.
[24] P. Pinson,et al. Energy Collectives: A Community and Fairness Based Approach to Future Electricity Markets , 2019, IEEE Transactions on Power Systems.
[25] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[26] Paulin Jacquot,et al. Peer-to-Peer Electricity Market Analysis: From Variational to Generalized Nash Equilibrium , 2018, Eur. J. Oper. Res..
[27] Jean-François Toubeau,et al. Improved day-ahead predictions of load and renewable generation by optimally exploiting multi-scale dependencies , 2017, 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia).
[28] Tianshu Bi,et al. Smart control for battery energy storage system in a community grid , 2014, 2014 International Conference on Power System Technology.
[29] Luisa Jorge,et al. EDPD’s experience with data analytics and stochastic simulation methods for risk-controlled network planning , 2018 .
[30] Youbing Zhang,et al. Lyapunov Optimization Based Online Energy Flow Control for Multi-energy Community Microgrids , 2019, 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia).
[31] Alfredo Núñez,et al. Load profile generator and load forecasting for a renewable based microgrid using Self Organizing Maps and neural networks , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[32] Francois Vallee,et al. Cooperative demand‐side management scenario for the low‐voltage network in liberalised electricity markets , 2018, IET Generation, Transmission & Distribution.
[33] Xiaojun Shen,et al. A Combined Algorithm for Cleaning Abnormal Data of Wind Turbine Power Curve Based on Change Point Grouping Algorithm and Quartile Algorithm , 2019, IEEE Transactions on Sustainable Energy.
[34] S. Chiba,et al. Dynamic programming algorithm optimization for spoken word recognition , 1978 .
[35] Walid Saad,et al. Managing Price Uncertainty in Prosumer-Centric Energy Trading: A Prospect-Theoretic Stackelberg Game Approach , 2017, IEEE Transactions on Smart Grid.
[36] Shi You,et al. The Emergence of Consumer-centric Electricity Markets , 2017 .
[37] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[38] Tao Hong,et al. Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting , 2019, International Journal of Forecasting.
[39] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .