Hybrid solar irradiance now-casting by fusing Kalman filter and regressor
نویسنده
چکیده
In this work, a hybrid solar irradiance now-casting mechanism is proposed. The proposed hybrid predictor fuses the results from both Kalman filter predictor and regressor predictor to benefit from the advantages of both techniques. A time-varying adaptive system function for Kalman filter is designed to deal with ramp-down events for more accurate prediction. Three fusion alternatives based on local root mean square error computation are proposed and compared. The experimental results have validated the effectiveness of the proposed method on a challenging dataset. © 2016 Elsevier Ltd. All rights reserved.
منابع مشابه
Maximum Power Point Tracking Using Kalman Filter for Photovoltaic System
This thesis proposes a new maximum power point tracking (MPPT) method for photovoltaic (PV) systems using Kalman filter. The Perturbation & Observation (P&O) method is widely used due to its easy implementation and simplicity. The P&O usually requires a dithering scheme to reduce noise effects, but the dithering scheme slows the tracking response time. Tracking speed is the most important facto...
متن کاملHybrid Bayesian Approach for Fusing Range-based and Sourceless Localization Estimates Under Non-Stationary Observability
The paper proposes a hybrid Bayesian approach for multi-sensor data fusion for 3D localization. The approach addresses the problem of fusing range-based and sourceless localization estimates under conditions of varying observability in the range-based sub-system. The proposed localization approach uses a mixture of Single-Hypothesis-Tracking (e.g. Kalman filter) and Multi-Hypothesis-Tracking (M...
متن کاملA New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems
This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...
متن کاملUbiquitous and Seamless Localization: Fusing GNSS Pseudoranges and WLAN Signal Strengths
Ubiquitous global positioning is not feasible by GNSS alone, as it lacks accurate position fixes in dense urban centres and indoors. Hybrid positioning methods have been developed to aid GNSS in those environments. Fingerprinting localization in wireless local area networks (WLANs) is a promising aiding system because of its availability, accuracy, and error mechanisms opposed to that of GNSS. ...
متن کاملImplementation of a Low- Cost Multi- IMU by Using Information Form of a Steady State Kalman Filter
In this paper, a homogenous multi-sensor fusion method is used to estimate the trueangular rate and acceleration with a combination of four low cost (< 10$) MEMS Inertial MeasurementUnits (IMU). An information form of steady state Kalman filter is designed to fuse the output of four lowaccuracy sensors to reduce the noise effect by the square root of the number of sensors. A hardware isimplemen...
متن کامل