Other

State Grid Corporation of China

State Grid Jiangsu Electric Power Company

State Grid Corporation of China Co., Ltd

Global Energy Interconnection Research Institute Co. Ltd

State Grid Beijing Electric Power Company

Global Energy Interconnection Research Institute

State Grid Shandong Electric Power Company

State Grid Jiangxi Electric Power Co.

Global Energy Interconnection Research Institute North America

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

Geiri Co., Ltd

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

Geiri North America

State Grid Jiangsu Electric Power Co., Ltd., Information and Communication Branch

Zhiwei Wang

Di Shi

Haifeng Li

Xiao Lu

Chunlei Xu

Zhehan Yi

Yishen Wang

Zhe Yu

Xueming Li

Xiaohu Zhang

Qibing Zhang

Shiming Xu

Jiangpeng Dai

Xiaoying Zhao

Yingmeng Xiang

Wei Li

Jing Cao

Jianyu Luo

Ruisheng Diao

Siqi Wang

Jiajun Duan

Feng Xue

Zhengyang Ding

Huimin Peng

Bo Guo

Jiangchao Qin

Haiyun Han

You Lin

Chang Fu

Chaoyang Jing

Bibin Huang

Tingting Hou

Xinan Wang

Systems and methods for generating a load model having composite load components for electric power systems are disclosed which include acquiring state information at a bus of the electric power system, acquiring a training event record, and generating the load model by sequentially executing steps of determining a final load component composition for a predetermined composite load model structure referencing to both the state information and the training event record, and determining a plurality of final load parameters corresponding to the final load component composition and the predetermined load model structure also referencing to both the state information and the training event record.

Systems and methods of composite load modeling for electric power systems

A method to simulate a circuit includes receiving at least one circuit requirement and at least one Modular Multilevel Converter (MMC) parameter; determining an operating mode and switching states of an arm circuit; determining each capacitor current based on the switching states and an arm current; determining capacitor voltage and arm voltage; and generating an equivalent circuit model to simulate MMC-based HVDC systems and DC grids in a hybrid AC and DC power system.

Generalized equivalent circuit model of MMC-HVDC for power system simulation

Systems and methods manage electrical loads in a grid by applying Robust principal component analysis (R-PCA) to decompose annual load profiles into low-rank components and sparse components; extracting one or more predetermined features; constructing a similarity graph; selecting submodular cluster centers through the constructed similarity graph; determining a cluster assignment based on selected centers; and applying the clustering assignment for load analysis.

Submodular load clustering with robust principal component analysis

A method for managing a power load of a grid includes performing a statistic-based distribution estimation of a composite load model using static and dynamic models with Gibbs sampling; deriving a distribution estimation of load model coefficients; and controlling grid power based on a simulation, a prediction, a stability analysis or a reliability analysis with the load model coefficients.

Bayesian estimation based parameter estimation for composite load model

Systems and methods are disclosed for power management by estimating power contingency of a grid at a cloud control center; performing decentralized real-time measurement and making local decisions at one more computer controlled outlets connected to the grid; and aggregating distributed loads to provide emergency frequency support to the grid.

Adaptive method for aggregation of distributed loads to provide emergency frequency support

Systems and methods are disclosed to control the power grid frequency by capturing the frequency change using an extended Kalman filter method with the distributed smart outlet devices at the low-voltage distribution level; and locally control the relay that provides power to the appliance by comparing the captured frequency with the threshold sent from the cloud control center.

Smart outlet system with fast frequency tracking for power system frequency control using distributed appliances

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 manage a microgrid with a hybrid energy storage system (HESS) includes deriving a dynamic model of a bidirectional-power-converter (BPC)-interfaced HESS; applying a first neural network (NN) to estimate a system dynamic; and applying a second NN to calculate an optimal control input for the HESS through online learning based on the estimated system dynamics.

Optimal charging and discharging control for hybrid energy storage system based on reinforcement learning

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

A control system is disclosed with a control strategy for autonomous multi-bus hybrid microgrids based on Finite-Control-Set Model Predictive Control (FCS-MPC). The control loops are expedited by predicting the future states and determining the optimal control action before switching signals are sent to converters/inverters. The method eliminates PI and PWM components, and offers 1) accurate PV maximum power point tracking (MPPT) and battery charging/discharging control, 2) DC and AC bus voltage/frequency regulation, and 3) precise and flexible power sharing control among multiple DERs.

Model predictive controller for autonomous hybrid microgrids

Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This invention presents a novel framework for online error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for the energy management system (EMS) database and protective relay settings. Case studies are presented to demonstrate the effectiveness of the proposed method.

Data mining based approach for online calibration of phasor measurement unit (PMU)

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San Jose, CA, United States of America

Zhiwei Wang