March 15, 2019 article Open access Data-Driven Local Control Design for Active Distribution Grids Using Off-Line Optimal Power Flow and Machine Learning Techniques IEEE Transactions on Smart Grid DOI: 10.1109/tsg.2019.2905348 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 166 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Deep Reinforcement Learning for Modeling Market-Oriented Grid User Behavior in Active Distribution Grids 2021 IEEE PES Innovative Smart Grid Technologies Europe conference-paper Engineering Smart Grid Energy Management 3 citations Distributed Optimal Power Flow with Data-Driven Sensitivity Computation 2021 conference-paper Engineering Optimal Power Flow Distribution 5 citations Kernel‐based online learning for real‐time voltage control in distribution networks 2020 IET Smart Grid article Engineering Optimal Power Flow Distribution Open access 4 citations 3 results References 0