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Generation, Transmission & Distribution, IET

Issue 2 • Date February 2012

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Displaying Results 1 - 9 of 9
  • Coordinated primary frequency control among non-synchronous systems connected by a multi-terminal high-voltage direct current grid

    Page(s): 99 - 108
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (417 KB)  

    The authors consider a power system composed of several non-synchronous AC areas connected by a multi-terminal high-voltage direct current (HVDC) grid. In this context, the authors propose a distributed control scheme that modifies the power injections from the different AC areas into the DC grid so as to make the system collectively react to load imbalances. This collective reaction allows each individual AC area to downscale its primary reserves. The scheme is inspired by algorithms for the consensus problem extensively studied by the control theory community. It modifies the power injections based on frequency deviations of the AC areas so as to make them stay close to each other. A stability analysis of the closed-loop system is reported as well as simulation results on a benchmark power system with five AC areas. These results show that with proper tuning, the control scheme makes the frequency deviations converge rapidly to a common value following a load imbalance in an area. View full abstract»

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  • New network sensitivity-based approach for real-time complex power flow calculation

    Page(s): 109 - 120
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (509 KB)  

    This study proposes a novel network sensitivity-based approach to solving complex power flow calculation problems in real time. A new sensitivity factor, named Jacobian-based distribution factor (JBDF), is used for the calculation of active and reactive power flow in transmission systems. It is derived from the Jacobian matrix of the base case Newton-Raphson power flow solution, and kept constant during real-time line flow calculation. Unlike well-known distribution factors, such as generation shift distribution factor (GSDF), generalised generation shift distribution factor (GGDF) and Z-bus distribution factor (ZBD), this approach reflects changes in complex injection power. Changes in load conditions from base case loads, with either conforming or non-conforming changes in complex power in each bus, can be used to rapidly compute active and reactive power flow without iterations. The proposed approach was tested on IEEE 14-Bus and 30-Bus systems. Numerical results demonstrate that the proposed approach is not only superior to previous distribution factors, but also compares favourably with the Newton-Raphson power flow method. It is well suited to real-time applications in steady-state security control and optimal dispatch. View full abstract»

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  • Design of differential evolution algorithm-based robust fuzzy logic power system stabiliser using minimum rule base

    Page(s): 121 - 132
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (765 KB)  

    Power system stabiliser must be capable of providing appropriate stabilisation signals over a broad range of operating conditions and disturbances. Literature shows that a fuzzy logic power system stabiliser (FLPSS) is a controller to cover a wider range of operating conditions. Differential evolution algorithm technique is employed in this study to systematically tune the optimal parameters of the proposed fuzzy logic controller. The decisions in fuzzy logic approach are made by forming a series of control rules. The number of control rules to cover all possible combinations of the `m'-input variables with 'n'-membership functions will be of 'nm' in number. But more number of rules requires more memory storage and evaluation time. In the proposed work, for a three-input each with three membership functions, the rules are reduced to three rules from 27 rules. The proposed reduced rule-based differential evolution FLPSS not only reduces the memory storage but also reduces the evaluation time. The proposed controller is designed for a linearised model of single machine infinite bus bar system under various operating conditions. The efficacy of the proposed controllers is tested on single machine connected to infinite bus for a three-phase fault and also in multi-machine environment. View full abstract»

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  • Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine

    Page(s): 133 - 141
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (874 KB)  

    This study presents a new method for reactive power tracing in a pool-based power system by introducing the hybrid genetic algorithm and least squares support vector machine (GA-LSSVM). The idea is to use GA to obtain the optimal values of regularisation parameter, -, and kernel radial basis function (RBF) parameter, -2, and adopt a supervised learning approach to train the LSSVM model. The technique that uses proportional sharing method (PSM) is used as a teacher. To obtain a lossless system, the concept of virtual load is proposed. Prior to that, the equivalent transmission line model is introduced. It integrates the nodal reactive power with the power produced by shunt admittances. Based on power-flow solution and reactive power tracing procedure by PSM, the description of inputs and outputs for training and testing data is created. The generators' shares to reactive loads in the test system are expected can be determined accurately by proposed GA'LSSVM model. In this study, five-bus system is used to illustrate the concept of virtual load and equivalent transmission line model whereas the 25-bus equivalent system of southern Malaysia is used to illustrate the effectiveness of the proposed GA'LSSVM model compared to PSM and artificial neural network. View full abstract»

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  • Forecasting dissolved gases content in power transformer oil based on weakening buffer operator and least square support vector machine–Markov

    Page(s): 142 - 151
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (386 KB)  

    The early detection of potential power transformer failures can ensure the safe operation of transformers. So it is practical to develop the early-fault-forecasting technology for transformers. Dissolved gas analysis (DGA) in power transformer is a significant basis for transformer insulation fault diagnosis, which provides full evidence for general internal transformer hidden dangers. But because of the stochastic growth and the small quantity of time-sequence data, forecasting the accurate dissolved gases content in power transformer oil is a complicated problem until now. Least square support vector machine (LSSVM) has been successfully employed to solve regression problem of nonlinearity and small sample. Aiming at improving the primitive shock and disturbance of time-sequence data, this paper firstly introduces the weakening buffer operator to attenuate its randomness. Then, in order to decrease the forecasting error and maximize the total forecasting precision, the Markov chain, which can well reflect the randomness produced by the system involved with many complex factors, is presented to modify the values forecasted by LSSVM. The experimental results indicate that the proposed model can achieve greater forecasting accuracy than GRNN and LSSVM model under the circumstances of small sample. View full abstract»

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  • Improved phase-locked loop for robust and fast tracking of three phases under unbalanced electric grid conditions

    Page(s): 152 - 160
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (767 KB)  

    Modern electric power transmission and distribution systems need accurate phase information on three-phase grid voltages and/or currents. Conventional three-phase synchronous reference frame-based phase-locked loop (SRF-PLL) is generally sufficient for phase tracking during balanced operating conditions. However, SRF-PLL becomes inadequate when unbalance exists in the three-phase input signal. Because, unbalance in input signal set causes a double-frequency ripple and as a result, an ideal output signal cannot be obtained. Previous studies have focused on improving the SRF-PLL performance by removing this ripple with using delayed signals methods such as delayed signal cancellation (DSC)-PLL methods. Although these methods give ideal output signals, a certain time delay is occurred. In this study, an effective method DIF-PLL based on adding another signal, which has reverse polarity ripple is proposed for obtaining ideal output signal and fast tracking of phase angle. Performance of the DIF-PLL is compared with the performances of SRF-PLL and DSC-PLL methods. The performances of these methods are also examined for the presence of the harmonics. The results show that the proposed method has a better three-phase tracking performance than the others under balanced and unbalanced electric grid conditions. View full abstract»

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  • Transient algorithm based on earth capacitance estimation for earth-fault detection in medium-voltage networks

    Page(s): 161 - 166
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (492 KB)  

    This study presents a new earth-fault detection algorithm for both unearthed and compensated neutral medium-voltage networks. The proposed algorithm is based on the transient estimation of the earth capacitance of the background network during the first one-eighth of the power frequency period. The effects of feeder impedances and the Petersen coil (in compensated networks) are compensated using proposed compensation factors. The estimated capacitance accurately indicates if the feeder is faulted or not. The capacitance can be estimated with a maximum error of ±10 %. The algorithm is not reliant on the fault resistance and the faulted feeder parameters; it mainly depends on the background network. The network is simulated using the ATP/EMTP program. Different fault conditions are covered in the simulation process, including different fault inception angles and high fault resistances. View full abstract»

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  • Security-constrained unit commitment with wind generation and compressed air energy storage

    Page(s): 167 - 175
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (355 KB)  

    Wind power is one of the fastest growing renewable sources of generation in the U.S. and many other countries. As wind-generated electricity continues to grow, electric utilities increasingly grapple with the challenges of connecting that power to the grid although maintaining system security. It is difficult to predict and control the output of wind generation because of wind intermittency and a reserve capacity is required to deal with inherent uncertainty. This study presents an approach for security-constrained unit commitment (SCUC) with integration of an energy storage system (ESS) and wind generation. Compressed air energy storage (CAES) is considered as an alternative solution to store energy. For economical operation and control purposes, utilities with CAES are interested in the availability and the dispatch of CAES on an hourly basis, given the specific characteristics of CAES. The main contribution of this study is the development of enhanced SCUC formulation and solution techniques with wind power, CAES and multiple constraints including fuel and emission limit. Proposed approach allows simultaneous optimisation of the energy and the ancillary services (AS). Case studies with eight-bus and 118-bus systems are presented to validate the proposed model. This study also contributes by conducting comprehensive studies to analyse the impact of CAES system on locational pricing, economics, peak-load shaving, transmission congestion management, wind curtailment and environmental perspective. View full abstract»

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  • Reconfiguration of distribution systems for loss reduction using the hyper-cube ant colony optimisation algorithm

    Page(s): 176 - 187
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (767 KB)  

    This study introduces the ant colony optimisation (ACO) algorithm implemented in the hyper-cube (HC) framework to solve the distribution network minimum loss reconfiguration problem. The ACO is a relatively new and powerful intelligence evolution method for solving optimisation problems. It is a population-based approach inspired from natural behaviour of real ant colonies. In contrast to the usual ways of implementing ACO algorithms, the HC framework limits the pheromone values by introducing changes in the pheromone updating rules resulting in a more robust and easier to implement version of the ACO procedure. The optimisation problem is formulated taking into account the operational constraints of the distribution systems. Results of numerical tests carried out on three test systems from literature are presented to show the effectiveness of the proposed approach. View full abstract»

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IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution.

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