Zobrazeno 1 - 10
of 195
pro vyhledávání: '"Qi, Junjian"'
Publikováno v:
In Electric Power Systems Research March 2024 228
We study the interdependence between transportation and power systems considering decentralized renewable generators and electric vehicles (EVs). We formulate the problem in a stochastic multi-agent optimization framework considering the complex inte
Externí odkaz:
http://arxiv.org/abs/2101.00908
In this paper, a novel Q-learning based approach is proposed for estimating the parameters of synchronous generators using PMU measurements. Event playback is used to generate model outputs under different parameters for training the agent in Q-learn
Externí odkaz:
http://arxiv.org/abs/2012.00803
Phasor measurement units (PMUs) enable better system monitoring and security enhancement in smart grids. In order to enhance power system resilience against outages and blackouts caused by extreme weather events or man-made attacks, it remains a majo
Externí odkaz:
http://arxiv.org/abs/2010.07540
In this paper, we propose an AC power flow based cascading failure model that explicitly considers external weather conditions, extreme temperatures in particular, and evaluates the impact of extreme temperature on the initiation and propagation of c
Externí odkaz:
http://arxiv.org/abs/2009.14155
Publikováno v:
In Electric Power Systems Research October 2023 223
A robust observer for performing power system dynamic state estimation (DSE) of a synchronous generator is proposed. The observer is developed using the concept of $\mathcal{L}_{\infty}$ stability for uncertain, nonlinear dynamic generator models. We
Externí odkaz:
http://arxiv.org/abs/1910.09487
Publikováno v:
Transactions of China Electrotechnical Society 34 (2019) 3651-3660
Cubature Kalman Filter (CKF) has good performance when handling nonlinear dynamic state estimations. However, it cannot work well in non-Gaussian noise and bad data environment due to the lack of auto-adaptive ability to measure noise statistics on l
Externí odkaz:
http://arxiv.org/abs/1907.08951
Publikováno v:
IEEE Access 7 (2019) 29139-29148
Kalman-type filtering techniques including cubature Kalman filter (CKF) does not work well in non-Gaussian environments, especially in the presence of outliers. To solve this problem, Huber's M-estimation based robust CKF (RCKF) is proposed for synch
Externí odkaz:
http://arxiv.org/abs/1902.07213