Global Energy Interconnection Research Institute Co. Ltd

State Grid Beijing Electric Power Company

State Grid Corporation of China Co., Ltd

Global Energy Interconnection Research Institute North America

Geiri Co Ltd, State Grid Jiangxi Electric Power Co, State Grid Corp of China, Geirina Inc.

Xiaohu Zhang

Di Shi

Zhiwei Wang

Ruisheng Diao

Zhehan Yi

Haifeng Li

Xiao Lu

Qibing Zhang

Siqi Wang

Xiaoying Zhao

Desong Bian

Zheming Liang

A system with deep reinforcement learning based control determines optimal actions for major components in a commercial building to minimize operation costs while maximizing comprehensive comfort levels of occupants. An unsupervised deep Q-network method is introduced to handle the energy management problem by evaluating the influence of operation costs on comfort levels considering the environment factors at each time slot. An optimum control decision can be derived that targets both immediate and long-term goals, where exploration and exploitation are considered simultaneously.

Deep reinforcement learning based real-time scheduling of Energy Storage System (ESS) in commercial campus

Systems and method are disclosed for monitor long-term voltage stability in a power system by estimating post-contingency operating point(s) considering PV-PQ transitions based on the current operating point; predicting a sensitivity based Thevenin index (STI) for each contingency using the estimated operating condition; and determining a voltage stability assessment (VSA) considering N&#x2212;1 contingency.

Sensitivity based Thevenin index for voltage stability assessment considering N-1 contingency

Systems and methods are disclosed to control a power inverter by extracting photovoltaic (PV) maximum power under a plurality of operating conditions as one or more reference variables; predicting the future behaviors of a PV output voltage as one or more controlled variables based on a current operational condition; generating one or more control signals for the H5 inverter that minimizes an error between the reference variable and the controlled variables; and controlling the power inverter with the one or more control signals.

MPC-based PV maximum power point tracker for transformerless H5 inverter with leakage current reduction

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San Jose, CA, United States of America

Xiaohu Zhang