Roel Dobbe An Integrative Approach To Data Driven Control In Electric Distribution Networks

Data Driven Control | PDF | Machine Learning | Artificial Intelligence

Data Driven Control | PDF | Machine Learning | Artificial Intelligence This dissertation works towards this vision by formulating a systematic control theoretic approach for integrating data driven monitoring and control in the operation of electric distribution networks. Roel dobbe, new york universityfeb 6, 2019title: an integrative approach to data driven control in electric distribution networkscompsust open graduate semin.

Robust Data-Driven Predictive Control Using Reachability Analysis | DeepAI

Robust Data-Driven Predictive Control Using Reachability Analysis | DeepAI Abstract an integrative approach to data driven monitoring and control of electric distribution networks by roel ignatius jacobus dobbe doctor of philosophy in engineering electrical engineering and computer sciences. This dissertation works towards this vision by formulating a systematic control theoretic approach for integrating data driven monitoring and control in the operation of electric distribution networks. How can data, modeling and algorithms be best combined to improve the spatial and temporal resolution of monitoring and control of voltage and power flow in distribution networks?. ∙ five data driven use cases in active distribution networks are summarized. ∙ data driven algorithms are categorized into four groups. ∙ comprehensive.

Comparison Of The Proposed Robust Data-driven Control And Controller... | Download Scientific ...

Comparison Of The Proposed Robust Data-driven Control And Controller... | Download Scientific ... How can data, modeling and algorithms be best combined to improve the spatial and temporal resolution of monitoring and control of voltage and power flow in distribution networks?. ∙ five data driven use cases in active distribution networks are summarized. ∙ data driven algorithms are categorized into four groups. ∙ comprehensive. We consider distribution systems with multiple controllable distributed energy resources (ders) and present a data driven approach to learn control policies for each der to reconstruct and mimic the solution to a centralized opf problem from solely locally available information. Author (s): dobbe, roel ignatius jacobus | advisor (s): tomlin, claire j.; callaway, duncan | abstract: the commodification of computing, sensors, actuators, data storage and algorithms has unleashed a new wave of automation throughout society. This work provides a model based control with regression trees algorithm (mbcrt), which allows us to perform closed loop control for dr strategy synthesis for large buildings and compares dr advisor with other data driven methods and rank 2nd on ashrae's benchmarking data set for energy prediction. The method is applied on both single and three phase test feeder networks using data from real loads and distributed generators. it provides a framework for distribution system operators to efficiently plan and operate the contributions of ders to active distribution networks.

(PDF) Robust Data-driven Control Design For Linear Systems Subject To Input Saturations

(PDF) Robust Data-driven Control Design For Linear Systems Subject To Input Saturations We consider distribution systems with multiple controllable distributed energy resources (ders) and present a data driven approach to learn control policies for each der to reconstruct and mimic the solution to a centralized opf problem from solely locally available information. Author (s): dobbe, roel ignatius jacobus | advisor (s): tomlin, claire j.; callaway, duncan | abstract: the commodification of computing, sensors, actuators, data storage and algorithms has unleashed a new wave of automation throughout society. This work provides a model based control with regression trees algorithm (mbcrt), which allows us to perform closed loop control for dr strategy synthesis for large buildings and compares dr advisor with other data driven methods and rank 2nd on ashrae's benchmarking data set for energy prediction. The method is applied on both single and three phase test feeder networks using data from real loads and distributed generators. it provides a framework for distribution system operators to efficiently plan and operate the contributions of ders to active distribution networks.

Roel Dobbe: An Integrative Approach to Data-Driven Control in Electric Distribution Networks