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Noninvasive Load Identification Method Based on Feature Similarity
The traditional power load identification is greatly restricted in application because of its high cost and low efficiency. In this paper, the similarity model is established to realize the noninvasive load identification of power by determining the feature database for the equipment. Firstly, the wavelet decomposition method and the wavelet threshold processing method are used to remove abnormal points and reduce noise of the original data, respectively. Secondly, the transient and steady-state characteristics of electrical equipment (active power and reactive power, harmonic current, and voltage-current trajectory) are extracted, and the feature database for the equipment is established. Thirdly, the feature similarity is defined to describe the similarity degree of any two devices under a certain feature, and the similarity model of automatic recognition of a single device is established. Finally, the device identification and calculation of power consumption are carried out for the part of data in annex 2 of question A in the 6th “teddy cup” data mining challenge competition.
Differential Evolution Optimized a Second-Order Divided Difference Particle Filter
In order to improve the estimation accuracy of particle filter algorithm in a nonlinear system state estimation problem, a new algorithm based on the second-order divided difference filter to generate the proposed distribution and the differential evolution algorithm for resampling is proposed. The second-order divided difference based on Strling’s interpolation formula is used to generate approximations to nonlinear dynamics, which avoids the evaluation of the Jacobian derivative matrix and is easy to implement. Cholesky factorization is used to ensure the positive definiteness of the covariance matrix. The truncated errors of the local linearization are reduced to a certain extent, and the approximation degree of the proposed distribution to the posterior probability of the system state is improved. The differential evolution algorithm is used to replace the traditional resampling algorithm, which effectively mitigates the problem of particle degradation. Monte Carlo simulation experiments show the effectiveness of the new algorithm.
Multi-Time Scale Optimal Dispatch for AC/DC Distribution Networks Based on a Markov Chain Dynamic Scenario Method and MPC
A multi-time scale optimal dispatch model based on the scenario method and model predictive control (MPC) in the AC/DC distribution network is established due to the uncertainty of wind and load. A Markov chain dynamic scenario method is proposed, which generates scenarios by characterizing the forecast error via empirical distribution. Considering the time correlation of the forecast error, Markov chain is adopted in the Markov chain dynamic method to simulate the uncertainty and variability in wind and load with time. A multi-time scale optimal dispatch strategy based on MPC is proposed. The operation scheduling of operation units is solved in day-ahead and intraday optimal dispatch by minimizing the expected value of total cost in each scenario. In the real-time optimal dispatch, the stability and robustness of system operation are considered. MPC is adopted in the real-time optimal dispatch, taking the intraday scheduling as reference and using the roll optimization method to compute real-time optimal dispatch scheduling to smooth the output power. The simulation results in a 50-node system with uncontrollable distributed energy demonstrate that the proposed model and strategy can effectively eliminate fluctuations in wind and load in AC/DC distribution networks.
FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization
Filter model reduction is an important optimization method in digital signal processing. A method of FIR to FIR model reduction using SDP optimization is proposed in this paper. At first, we use SDP to design an original FIR filter. Then we name a general K-order FIR digital filter with coefficient values equal to the first K + 1 filter coefficient values of . Finally, we design a new general K-order FIR digital filter connected in parallel with using SDP optimization. The experiment results show this method has good performance on the magnitude error and the linear phase in passband. Therefore, this method can be used in the field of digital signal processing.
A New Local Descriptor Based on Strings for Face Recognition
This paper proposes the use of strings as a new local descriptor for face recognition. The face image is first divided into nonoverlapping subregions from which the strings (words) are extracted using the principle of chain code algorithm and assigned into the nearest words in a dictionary of visual words (DoVW) with the Levenshtein distance (LD) by applying the bag of visual words (BoVW) paradigm. As a result, each region is represented by a histogram of dictionary words. The histograms are then assembled as a face descriptor. Our methodology depends on the path pursued from a starting pixel and do not require a model as the other approaches from the literature. Therefore, the information of the local and global properties of an object is obtained. The recognition is performed by using the nearest neighbor classifier with the Hellinger distance (HD) as a comparison between feature vectors. The experimental results on the ORL and Yale databases demonstrate the efficiency of the proposed approach in terms of preserving information and recognition rate compared to the existing face recognition methods.
Implementation of Optimal Protection Coordination for Microgrids with Distributed Generations Using Quaternary Protection Scheme
The flexible operation of microgrids, along with the availability of distributed generation (DG) units, causes a variety of changes in short-circuit current levels, magnitudes, and directions, which has undesirable effects on the operation of protection systems. Conventional protection schemes use typical directional overcurrent relays (DOCRs) with limited operating capability, unable to respond to microgrid operations in the manner of short-circuit current changes. In this paper, a quaternary protection scheme implemented with dual-directional overcurrent relays (dual-DOCR) and a protection control strategy is developed for protecting against faults in microgrids, taking into account the existence of DGs and connection and disconnection of DG units. The optimal dual-DOCRs setting and coordination are formulated as an optimization problem solved by evolutionary programming to minimize the relay operating times. The proposed protection scheme is implemented with a centralized protection control system based on the smart grid concept to increase the adaptability of the dual-DOCRs, which have multiple relay setting groups in accordance with system state changes. The simulation case studies are performed using the IEEE 14-bus test system, which is modified as a meshed microgrid operation. Test scenarios, including possible operations of microgrids, DGs availabilities, and different fault events, are analyzed and discussed. The comparative studies and simulation results show that the proposed scheme provides efficient coordination between the primary and backup relays and increases the responsibility of the protection system, which can be observed from the significant reduction in the relay operating times, resulting in the enhancement of selectivity, sensitivity, and speed of microgrid protection systems.