The Experts below are selected from a list of 1047126 Experts worldwide ranked by ideXlab platform
Ali Ghasemi - One of the best experts on this subject based on the ideXlab platform.
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a fuzzified multi objective interactive honey bee mating optimization for environmental economic power dispatch with valve point effect
International Journal of Electrical Power & Energy Systems, 2013Co-Authors: Ali GhasemiAbstract:Abstract In this paper, an improved multi objective Interactive Honey Bee Mating Optimization (IHBMO) is Proposed to find the feasible optimal solution of the Environmental/Economic Power Dispatch (EED) problem with considering operational constraints of the generators. The EED problem is an important issue in power industry with considered the production of environmental pollution caused by fossil fuel consumption such as dangerous gases and carbon monoxide. The EED problem is formulated as a nonlinear constrained multi objective optimization problem which is solved by multi objective IHBMO techniques that has a strong ability to find the most optimal results. The three conflicting and non-commensurable: fuel cost, pollutant emissions and system loss, should be minimized simultaneously while satisfying certain system constraints. For achieve a good design with different solutions in a multi objective optimization problem, Pareto dominance concept is used to generate and sort the dominated and non-dominated solutions. Also, fuzzy set theory is employed to extract the best compromise solution. The Propose Method has been individually examined and applied to the standard IEEE 30-bus 6-generator, IEEE 180-bus fourteen generator and 40 generating unit (with valve point effect) test systems. The effectiveness of the Proposed approach is demonstrated by comparing its performance with other evolutionary multi-objective optimization algorithms such as NSGA, NPGA, SPEA, MOPSO, MODE and MOHBMO. The computational results reveal that the multi objective IHBMO algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms. Also, the results confirm its great potential in handling the multi-objective problems in power systems.
Myongchul Shin - One of the best experts on this subject based on the ideXlab platform.
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generator fault detection technique using detailed coefficients ratio by daubechies wavelet transform
Power and Energy Society General Meeting, 2009Co-Authors: Chulwon Park, Kwangchul Shin, Sangseung Lee, Jongkeun Park, Myongchul ShinAbstract:An AC (alternating current) generator is one of the important components in producing a electric power and so it requires highly reliable protection relays to minimize the possiblity of demage occurring under fault conditions. Conventionally, a RDR (ratio differential relaying) based on DFT (discrete Fourier transform) has been used for protecting the stator winding of a generator. However, when DFTs based on Fourier analysis are used, it has been pointed out that defects can occur during the process of transforming a time domain signal into a frequency domain one which can lead to loss of time domain information. This paper Proposes the adoption of a protection algorithm for the stator by applying a WT (wavelet transform) to overcome the defects in the DFT process. Moreover, a new ratio equation is Proposed for easy utilization of the detailed coefficients by DWT (Daubechies wavelet transform) through the course of MLD (multi-level decomposition) using MATLAB. For the case studies reported in the paper, a model system was established for the simulations utilizing the ATP (alternative transient program), and this verified the effectiveness of the Proposed technique through various off-line tests carried out on the collected data. The Propose Method is shown to be able to rapidly identify internal faults and did not operate a miss-operation for all the external faults tested.
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internal fault detection and fault type discrimination for ac generator using detail coefficient ratio of daubechies wavelet transform
The Transactions of the Korean Institute of Electrical Engineers, 2009Co-Authors: Chulwon Park, Kwangchul Shin, Myongchul ShinAbstract:An AC generator is an important components in producing a electric power and so it requires highly reliable protection relays to minimize the possibility of demage occurring under fault conditions. Conventionally, a DFT based RDR has been used for protecting the generator stator winding. However, when DFTs based on Fourier analysis are used, it has been pointed out that defects can occur during the process of transforming a time domain signal into a frequency domain one which can lead to loss of time domain information. This paper Proposes the internal fault detection and fault type discrimination for the stator winding by applying the detailed coefficients by Daubechies Wavelet Transform to overcome the defects in the DFT process. For the case studies reported in the paper, a model system was established for the simulations utilizing the ATP, and this verified the effectiveness of the Proposed technique through various off-line tests carried out on the collected data. The Propose Method is shown to be able to rapidly identify internal fault and did not operate a miss-operation for all the external fault tested.
David Thomas - One of the best experts on this subject based on the ideXlab platform.
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Sparse voltage amplitude measurement based fault location in large-scale photovoltaic power plants
Applied Energy, 2018Co-Authors: Ke Jia, Zhengwen Xuan, Tian-shu Bi, Chenjie Gu, Lun Li, David ThomasAbstract:Large-scale photovoltaic (PV) power plants contain numerous transmission line branches and laterals inside. When a fault occurs conventional fault location Methods face challenges due to the complex system structure and the diversity of PV inverter controls. Most of the published fault location Methods cannot be directly used in the PV power plant due to the following issues: (1) Most of the fault location Methods consider the PV inverter as a constant voltage source while the actual inverters have varied controls during faults. Without analysis of the unique fault transients of the PV, the fault location will suffer from errors. (2) In a complicated large-scale PV power plant with massive quantity of nodes, the synchronised measurements from all the nodes are almost impossible. A Method with sparse un-synchronized measurements is required. Therefore, a new negative-sequence voltage amplitude sparse measurement based fault location Method is Proposed for unbalanced faults. The improved Bayesian compressive sensing algorithm is used to recover the sparse fault current vector and then determine the faulted node. Both the field testing and the simulation results indicate that the Proposed Method can locate the faulted nodes accurately and effectively without synchronizing measurement requirements from all the nodes. This Method also presents a good performance for various unbalanced fault types, fault resistances, inverter controls and signal noise. All these factors make the Propose Method feasible for industrial applications.
Sancheng Peng - One of the best experts on this subject based on the ideXlab platform.
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a hybrid privacy protection scheme in cyber physical social networks
IEEE Transactions on Computational Social Systems, 2018Co-Authors: Longxiang Gao, Wanlei Zhou, Sancheng PengAbstract:The rapid proliferation of smart mobile devices has significantly enhanced the popularization of the cyber-physical social network, where users actively publish data with sensitive information. Adversaries can easily obtain these data and launch continuous attacks to breach privacy. However, existing works only focus on either location privacy or identity privacy with a static adversary. This results in privacy leakage and possible further damage. Motivated by this, we Propose a hybrid privacy-preserving scheme, which considers both location and identity privacy against a dynamic adversary. We study the privacy protection problem as the tradeoff between the users aiming at maximizing data utility with high-level privacy protection while adversaries possessing the opposite goal. We first establish a game-based Markov decision process model, in which the user and the adversary are regarded as two players in a dynamic multistage zero-sum game. To acquire the best strategy for users, we employ a modified state-action-reward-state-action reinforcement learning algorithm. Iteration times decrease because of cardinality reduction from $n$ to 2, which accelerates the convergence process. Our extensive experiments on real-world data sets demonstrate the efficiency and feasibility of the Propose Method.
Peng S - One of the best experts on this subject based on the ideXlab platform.
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A hybrid privacy protection scheme in cyber-physical social networks
'Institute of Electrical and Electronics Engineers (IEEE)', 2018Co-Authors: Qu Y, Yu S, Gao L, Zhou W, Peng SAbstract:© 2014 IEEE. The rapid proliferation of smart mobile devices has significantly enhanced the popularization of the cyber-physical social network, where users actively publish data with sensitive information. Adversaries can easily obtain these data and launch continuous attacks to breach privacy. However, existing works only focus on either location privacy or identity privacy with a static adversary. This results in privacy leakage and possible further damage. Motivated by this, we Propose a hybrid privacy-preserving scheme, which considers both location and identity privacy against a dynamic adversary. We study the privacy protection problem as the tradeoff between the users aiming at maximizing data utility with high-level privacy protection while adversaries possessing the opposite goal. We first establish a game-based Markov decision process model, in which the user and the adversary are regarded as two players in a dynamic multistage zero-sum game. To acquire the best strategy for users, we employ a modified state-action-reward-state-action reinforcement learning algorithm. Iteration times decrease because of cardinality reduction from n to 2, which accelerates the convergence process. Our extensive experiments on real-world data sets demonstrate the efficiency and feasibility of the Propose Method
