Showing papers in "Electric Power Components and Systems in 2011"
TL;DR: The results show that the new quasi-oppositional biogeography-based optimization algorithm outperforms the other techniques in terms of convergence speed and global search ability.
Abstract: This article develops an efficient and reliable evolutionary programming algorithm, namely quasi-oppositional biogeography-based optimization, for solving optimal power flow problems. To improve the simulation results as well as the speed of convergence, opposition-based learning is incorporated in the original biogeography-based optimization algorithm. In order to investigate the performance, the proposed scheme is applied on optimal power flow problems of standard 26-bus, IEEE 118-bus, and IEEE 300-bus systems; and comparisons among mixed-integer particle swarm optimization, evolutionary programming, the genetic algorithm, original biogeography-based optimization, and quasi-oppositional biogeography-based optimization are presented. The results show that the new quasi-oppositional biogeography-based optimization algorithm outperforms the other techniques in terms of convergence speed and global search ability.
76 citations
TL;DR: A novel methodology that employs fuzzy set theory and the genetic algorithm for formulation and evaluation of a multi-objective function, respectively, for optimal planning of distributed generator units is proposed.
Abstract: This article proposes a novel methodology that employs fuzzy set theory and the genetic algorithm for formulation and evaluation of a multi-objective function, respectively, for optimal planning of distributed generator units. The effectiveness of the proposed method is tested using various systems of different sizes and configurations and is validated by comparing the results with that of the weighted sum method. The dependence of existing methods on global preference information of decision maker is overcome in this method. Further, different types of distributed generator models are also employed to demonstrate the importance of the use of a precise distributed generator model and the adaptability of the proposed method in distributed generator planning studies.
75 citations
TL;DR: This work is an attempt to utilize the velocity-based particle updating process from particle swarm optimization in the improvisation process of the harmony search algorithm for a better convergence of the proposed algorithm.
Abstract: This article presents a novel stochastic optimization approach to solve the constrained economic load dispatch problem using a hybridization of the harmony search algorithm and particle swarm optimization, named hybrid harmony search based on the swarm intelligence principle. Harmony search is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work is an attempt to utilize the velocity-based particle updating process from particle swarm optimization in the improvisation process of the harmony search algorithm for a better convergence of the proposed algorithm. The proposed methodology also easily takes care of solving non-convex economic load dispatch problems along with different constraints, such as power balance, ramp rate limits of the generators, and prohibited operating zones. Simulations were performed over four various standard test systems with different numbers of...
59 citations
TL;DR: In this paper, a multi-objective formulation for determining the best location and size of distributed generation is presented, which includes reliability of service, system operational efficiency, cost of purchased energy, power quality, and system security.
Abstract: This article presents a multi-objective formulation for determining the best location and size of distributed generation. This multi-objective formulation includes reliability of service, system operational efficiency, cost of purchased energy, power quality, and system security as objective functions that are the primary concern of system planners. These objectives contradict each other and have trade-off relations. Conventional approaches for optimizing a single objective yield an uncompromised solution for such multi-objective problems. The multi-objective formulation is solved using an interactive trade-off algorithm to obtain compromised or most satisfactory non-inferior solutions. The system planner has a choice to include his/her preference on each objective through interactive steps. The practical situations, such as voltage rise phenomenon and voltage dependency of loads, are addressed, incorporating certain voltage constraints and appropriate load models. The test system is an existing ...
57 citations
TL;DR: Results indicate that the proposed probabilistic neural network based islanding detection technique can reliably detect islanding conditions in the power distribution network with multiple distributed generation interface.
Abstract: This article proposes a probabilistic neural network based islanding detection technique for distributed generation considering multiple parameters in order to secure the detection of islanding for any possible network topology. This approach utilizes different parameters (features), such as rate of change of frequency, rate of change of voltage, rate of change of power, rate of change of frequency over power, total harmonic distortion (current), and rate of change of power factor, derived at the target distributed generation location and fed to the probabilistic neural network for automatic islanding detection. While comparing with other techniques, such as the radial basis function neural network and decision tree, the probabilistic neural network based technique is found to be highly effective in islanding detection. The proposed algorithm has been tested for simulation model, as well as the real-time digital simulator, and results indicate that the proposed method can reliably detect islandin...
57 citations
TL;DR: In this article, a new method for reconfiguration of radial distribution systems for minimization of real power loss using adaptive particle swarm optimization without involving any additional cost for the installation of tap changing transformers, capacitors, and concerned switching equipment.
Abstract: This article presents a new method for reconfiguration of radial distribution systems for minimization of real power loss using adaptive particle swarm optimization without involving any additional cost for the installation of tap changing transformers, capacitors, and concerned switching equipment. The initial population for particle swarm optimization is created using a heuristic approach, and the particles are adapted with the help of graph theory to generate feasible individuals. This not only avoids tedious mesh check but also reduces the computational burden. The effectiveness of the proposed method is demonstrated on two different test systems. The application results show that the proposed method is efficient and promising for the minimization of real power loss of radial distribution systems.
51 citations
TL;DR: In this paper, a battery-based control method was proposed to reduce the photovoltaic output power fluctuations, which, in turn, will reduce the frequency deviations of the power system.
Abstract: This article explains a battery-based control method to reduce the photovoltaic output power fluctuations, which, in turn, will reduce the frequency deviations of the power system. The battery control method introduced here will maintain the state of charge near 50%. Therefore, it will increase the lifetime of the battery, as well as decreasing the maintenance cost. A local search algorithm is provided with this battery control method to search the optimal capacity of the battery required for smoothing the photovoltaic output power fluctuations. Then, a cost comparison is provided to realize the performance of the search algorithm. To verify the effectiveness of the proposed method, simulation results are presented using the actual insolation and load data.
48 citations
TL;DR: In this article, a biogeography-based optimization algorithm is proposed to solve the optimal reactive power dispatch problem incorporating a flexible AC transmission system, and the proposed approach results have been compared to those of particle swarm optimization with inertia weight approach, real coded genetic algorithm, and differential evolution.
Abstract: This study presents biogeography-based optimization to solve the optimal reactive power dispatch problem incorporating a flexible AC transmission system. The purpose of optimal reactive power dispatch is to provide a solution that improves voltage profile and reduces transmission loss for every practical power system. The proposed biogeography-based optimization algorithm is implemented and tested on the IEEE 30-bus system with multiple flexible AC transmission system devices, such as a thyristor control series compensator and a thyristor control phase shifter. The proposed approach results have been compared to those of particle swarm optimization with inertia weight approach, real-coded genetic algorithm, and differential evolution. The comparison of the results with other methods shows the superiority of the proposed biogeography-based optimization.
46 citations
TL;DR: In this article, a closed-loop inductance capacitance inductance-T (LCL-T) series parallel resonant converter has been simulated and presented in a MATLAB environment.
Abstract: A closed-loop inductance capacitance inductance-T (LCL-T) series parallel resonant converter has been simulated and presented in this article. The fuzzy logic controller has been used for closed-loop operation, and the performance of the proposed converter has been estimated with a closed-loop condition. The steady-state stability analysis of the LCL-T series parallel resonant converter has been analyzed using the state-space model and simulated using MATLAB (The MathWorks, Natick, Massachusetts, USA). The proposed approach is expected to provide better voltage regulation for dynamic load conditions. A prototype 300-W, 100-kHz converter is designed and built for experimental demonstrations, and transient and steady-state performances for the LCL-T series parallel resonant converter are compared from the simulation studies.
39 citations
TL;DR: In this paper, a two-level hierarchical hybrid control is proposed based on the hybrid system control theory in terms of interactive adjustment between the continuous controller at the lower level and discrete management at the upper level.
Abstract: The increased penetration of distributed generations introduces considerable complexity in the network operation, as well reliability if the distributed generations are effectively controlled and managed. Hence, the issues of management and control for smart microgrids become more significant. With respect to a large power system, a microgrid shows more conspicuous interactive hybrid dynamic behaviors. In this study, a novel hybrid model is first founded to clearly explain the hybrid interactive behaviors of microgrids. On the basis of the model, a two-level hierarchical hybrid control is proposed based on the hybrid system control theory in terms of interactive adjustment between the continuous controller at the lower level and discrete management at the upper level. The upper-level discrete management strategies are responsible for guaranteeing stability and security of the overall microgrid while constraining it to meet the load demand during significant disturbances, as well as minimizing the...
34 citations
TL;DR: In this paper, a multi-class support vector machine (SVM) was used to classify the type of discharge in a ternary plot, where each discharge has a unique location.
Abstract: Ultra-high-frequency signals are generated due to particle movement, floating conductors, corona, and surface discharges in gas-insulated switchgear. The ultra-high-frequency signal generated due to particle movement is independent of operating pressure and applied voltage. The bandwidth of the ultra-high-frequency signal formed due to corona and surface discharges vary with applied voltage. In a ternary plot, each type of discharge has a unique location. If a variety of discharge occurs simultaneously, it is difficult to classify the type of discharges through the ternary plot. It is demonstrated that the type of discharge can be classified efficiently by adopting a multi-class support vector machine.
TL;DR: In this article, an extensive set of test data of artificially aged transformer oil under various temperatures was given, and the aging effect of test temperature on various properties of the oil was quantified.
Abstract: This article presents research results on electrical and physic-chemical properties of insulating oil used for high-voltage applications under accelerated artificial thermal aging. Unlike in previously published work, this article gives an extensive set of test data of artificially aged transformer oil under various temperatures. In addition, the aging effect of test temperature on various properties of the oil was quantified. Continuous thermal aging tests were made on transformer oil (Borak 22, Sonelgaz, Nynas, Austria) using a 5000-hr test at four different temperatures of 80, 100, 120, and 140°C. First, the electrical properties of transformer oil, such as the dielectric dissipation factor and the breakdown voltage, are measured after every 500 hr of aging. Next, the physicochemical parameters, including the acidity degree, water content, color factor, kinematic viscosity, density, and flash point, are quantified in order to find the changes in the chemical composition of the insulating oil. The results show that thermal aging significantly affects the properties of transformer oil by the formation of acidic products and the formation of water in oil, which lead to the degradation of the oil's electrical and physicochemical properties.
TL;DR: In this article, a new approach is proposed to optimize conductor size selection in radial distribution network planning for the purpose of minimization of real power loss and enhancement of voltage profile, where the objective function is modeled as a problem that minimizes the sum of capital investment and capitalized energy loss cost.
Abstract: In this article, a new approach is proposed to optimize conductor size selection in radial distribution network planning for the purpose of minimization of real power loss and enhancement of voltage profile. The objective function is modeled as a problem that minimizes the sum of capital investment and capitalized energy loss cost. Voltage constraints and the maximum current carrying capacity of the conductors are also considered in the evaluation of the objective function. The harmony search algorithm with a differential operator is used to solve the optimal conductor size selection problem and to determine the size and type of the conductors. The effectiveness of the proposed method is demonstrated through simulations on 16- and 85-bus systems, and the results obtained are encouraging.
TL;DR: In this paper, a state-space model is derived from the netlist of the equivalent qd microgrid circuit model, and the model may be used to conduct time-domain simulations and analyze system response to large transients.
Abstract: A systematic, automatable, unified methodology is presented for the modeling of non-linear large-signal dynamics and eigenvalue analysis of microgrid systems. Unlike nodal-based simulators and typical state-variable methods that require Kirchhoff's current law analysis, a state-space model is systematically derived from the netlist of the equivalent qd microgrid circuit model. The model may be used to conduct time-domain simulations and analyze system response to large transients. Additionally, system eigenvalues may be analyzed with respect to inverter control gains and system parameters to assess small-signal stability and sensitivity. The dynamic model is verified against existing experimental results, and small-signal stability results are presented.
TL;DR: In this paper, the authors proposed a new generation worth index for each load level to evaluate whether or not the distributed generation in that load level is worthwhile, which regards the impact of a distributed generation operation strategy on generation cost and reliability of the network.
Abstract: This article proposes a new generation worth index for each load level to evaluate whether or not the distributed generation in that load level is worthwhile. The proposed index regards the impact of a distributed generation operation strategy on generation cost and reliability of the network. Based on the proposed generation worth index, the annual optimal operation strategy of distributed generation can also be estimated. Obviously, there is a mutual impact between the optimal operation strategy and the optimal site and size of distributed generations in the network. Hence, in the second part of the article, the proposed generation worth index and annual distributed generation operation strategy are utilized to determine the optimal size and location of distributed generations and the optimal location of remote controllable switches. The generation worth index is calculated to reduce the network energy loss, energy cost, and expected energy not supplied. The annual load is considered to be mult...
TL;DR: In this article, a particle swarm optimization algorithm was proposed to optimize the design of the single-tuned passive filters for industrial plants in distribution networks, where the main objective is to minimize the load voltage total harmonic distortion, taking into account the source voltage harmonics.
Abstract: Single-tuned passive filters are considered one of the most effective and economical means of harmonic mitigation. One important factor to consider while designing passive filters is the source voltage harmonics. This article presents a novel approach based on a particle swarm technique to optimize the design of the single-tuned passive filters for industrial plants in distribution networks. The filter design problem is formulated as a non-linear programming problem, where the main objective is to minimize the load voltage total harmonic distortion, taking into account the source voltage harmonics. The optimal filter parameters are determined using particle swarm optimization with the static penalty constraint handling approach. The particle swarm optimization algorithm performance is tested on ten constrained non-linear programming benchmark cases and a previous filter design problem. Initial results show that single-tuned passive filters can fail to maintain harmonic levels within standard leve...
TL;DR: A novel load flow method of radial distribution systems is presented that has a good convergence pattern and execution time for all types of realistic loads and sizes of the networks.
Abstract: The need for fast load flow algorithms for radial distribution networks that take advantage of their particular structure has been increasing for planning and optimization. In this article, a novel load flow method of radial distribution systems is presented. In the proposed method, different realistic loads have been considered, as loads are voltage dependent in distribution systems. The effect of load growth is investigated with the proposed method, as it is required for system expansion, planning, and operation. The proposed method has a good convergence pattern and execution time for all types of realistic loads and sizes of the networks. The efficacy of the proposed method is tested with different radial distribution systems and compared with other existing methods.
TL;DR: In this article, the influence of temperature and accelerated aging factors, such as accelerated thermal aging factor and accelerated electrical aging factor, on dielectric properties of transformer oil was analyzed experimentally for a fresh oil sample and for samples subjected to accelerated aging.
Abstract: This article deals with the experimental analysis to measure the influence of temperature and accelerated aging factors, such as accelerated thermal aging factor and accelerated electrical aging factor, on dielectric properties, such as resistivity and dielectric dissipation factor or tan delta, of transformer oil. A number of vital decisions, such as oil reconditioning, oil replacement, etc., are based on these parameters. These parameters were determined experimentally for a fresh oil sample and for samples subjected to accelerated aging.
TL;DR: In this paper, a dynamic model for a microgrid according to the difference in transient processes between the microgrid and the traditional grid is proposed and expressed as a differential-algebraic equation system, so the structure of the micro grid and the physical meaning of original variables are preserved.
Abstract: Microgrids can provide a more reliable power supply and can enable the interconnection of renewable energy. The microgrid has been recognized as one of the most important directions of power systems. The transient characteristics of the microgrid are very important for the planning and operation of the whole power system. However, its mechanism still needs further exploration because the circuit structure, control feature, and even the operation mode of the microgrid are quite different from those of the traditional power system. In this article, a dynamic model is proposed for a microgrid according to the difference in transient processes between the microgrid and the traditional grid. The model is expressed as a differential-algebraic equation system, so the structure of the microgrid and the physical meaning of original variables are preserved. The focal point in this article is the fast control function of the inverter and the strong coupling between inverter and grid. The inverter is modeled...
TL;DR: In this paper, a load frequency control technique for an isolated small hydro power plant based on a multiple flow control system is proposed, which employs a dump load whose rating is equal to the rated power output of the plant.
Abstract: In this article, a load frequency control technique for an isolated small hydro power plant based on a multiple flow control system is proposed. In general, the frequency of the system is controlled by employing a dump load whose rating is equal to the rated power output of the plant. The proposed scheme reduces the size of the dump load to 50%, as 50% input power of the hydro plant is controlled by an on/off control. A generalized transfer function model for the system is developed with on/off control logic, and the parameters were optimized using the integral time absolute error technique. The on/off control linearly raises or lowers the generation. Finally, transient responses are shown for low, medium, and high head installations with different loading conditions.
TL;DR: The investigation reveals that the proposed fuzzified particle swarm optimization algorithm can provide an accurate solution with fast convergence and has the potential to be applied to other power system optimization problems.
Abstract: This article presents a new computationally efficient fuzzified particle swarm optimization algorithm for solving the security-constrained multi-area economic dispatch of an interconnected power system. The core objective of the security-constrained multi-area economic dispatch is to determine the generation allocation of each committed unit in the system and the power exchange between areas so as to minimize the total generation cost without violating the tie-line constraint. The proposed fuzzified particle swarm optimization algorithm is based on the combined application of fuzzy logic strategy incorporated in the particle swarm optimization algorithm. The proposed method was tested on a system of three interconnected areas. The investigation reveals that the proposed method can provide an accurate solution with fast convergence and has the potential to be applied to other power system optimization problems.
TL;DR: In this article, the authors proposed an expansion method to perform load flow analysis with consideration of multiple distributed generation integration and load uncertainties, and the proposed approach offers a method to handle the impacts of all possible allocations of distributed generation units without increasing computational efforts.
Abstract: Distributed generation is becoming a part of the strategic plans of electricity providers for effective system management. The proper planning of multiple distributed generation units plays an important role in modern power systems to offer a highly reliable system. Computation of power flows is one of the major tasks in system planning studies. Conventional load flow analysis methods are impractical to evaluate every possible or probable combination of loads and different allocations of distributed generation units because of the extremely large computational effort required. This article proposes an expansion method to perform load flow analysis with consideration of multiple distributed generation integration and load uncertainties. The proposed approach offers a method to handle the impacts of all possible allocations of distributed generation units without increasing computational efforts. The impacts of placement and penetration level of multiple distributed generation on power losses, volt...
TL;DR: In this article, an approach to find the optimal location of thyristor-controlled series compensators in a power system to improve the loadability of its lines and minimize its total loss is presented.
Abstract: This article presents an approach to find the optimal location of thyristor-controlled series compensators in a power system to improve the loadability of its lines and minimize its total loss. Also the proposed approach aims to find the optimal number of devices and their optimal compensation levels by using a genetic algorithm taking into consideration the thermal and voltage limits. Examination of the proposed approach is carried out on a modified IEEE 30-bus system.
TL;DR: In this paper, a new classification method for power quality disturbances was proposed using S-transform to extract the most severable features of the power quality waveforms and a decision-making scheme was performed using the logistic model tree.
Abstract: This article presents certain features and a new classification method for recognition of power quality disturbances. The proposed method uses S-transform to extract the most severable features of the power quality waveforms. The disturbances decision-making scheme is performed using the logistic model tree. This new algorithm requires fewer features compared to the wavelet based approach for the identification of power quality events. Thus, the required memory space and learning logistic model tree time are substantially reduced. The most common types of disturbances, including sag, swell, interruption, harmonics, transient, and flicker, are studied. Disturbances consisting of both sag and harmonics, as well as both swell and harmonics, are also considered. The result shows that the classifier can detect and classify different power quality events correctly. Sensitivity of the proposed algorithm under noisy condition is also investigated.
TL;DR: In this article, a new thermoelectric-photovoltaic hybrid energy system is proposed for hybrid electric vehicles, where the key is to newly develop the multiple-input single-ended primary inductor converter to simultaneously regulate the thermocouple and photocouple generators in such a way that the total output power can be maximized.
Abstract: In this article, a new thermoelectric-photovoltaic hybrid energy system is proposed for hybrid electric vehicles. The key is to newly develop the multiple-input single-ended primary inductor converter to simultaneously regulate the thermoelectric and photovoltaic generators in such a way that the total output power can be maximized. Both design and implementation of the proposed system are discussed. Experimental results are given to verify the whole system.
TL;DR: The proposed controller surpasses the best performance obtained by an optimized proportional-integral-derivative controller in improving the step response of an automatic voltage regulator system.
Abstract: A type-2 fuzzy logic controller is proposed in this article for an automatic voltage regulator system. For controller design, memberships of system variables are represented using interval value fuzzy sets. Fuzzy logic based on interval value sets is capable of modeling the uncertainty and imprecision in a better way. The proposed controller surpasses the best performance obtained by an optimized proportional-integral-derivative controller in improving the step response of an automatic voltage regulator system. Simulation results also reveal the robustness of the controller to system parameter changes.
TL;DR: It is shown that the probabilistic neural network approach can provide a fast and precise operation for various faults and can successfully be used as an effective tool for solving complicated classification problems.
Abstract: This article presents a classification methodology based on probabilistic neural networks. To automatically select the training data and obtain the performance evaluation results, the “K-fold” cross-validation method is used. Then, the probabilistic neural network is compared with the feed-forward neural network and the radial basis function network. The goal is to propose a classifier that is capable of recognizing 11 classes of three-phase distribution system faults to solve the complex fault (three-phase short-circuit) classification problem for reducing the multiple-estimation problem to estimate the fault location in radial distribution systems. The data for the fault classifier is produced by DigSilent Power Factory, Integrated Power System Analysis Software on an IEEE 13-node test feeder. A selection of features or descriptors obtained from voltages and currents measured in the substation are analyzed and used as input of the probabilistic neural network classifier. It is shown that the pr...
TL;DR: A probabilistic model that takes into account the random nature of solar irradiance and load is developed, and convergence is rapidly attained, and computational cost is low enough for that required for Monte Carlo simulation.
Abstract: This article shows that technical constraints must be considered in radial distribution networks, where voltage regulation is one of the primary problems in distributed generation photovoltaic systems. Loads and distributed generation production are modeled as random variables. Results prove that the proposed method can be applied for keeping voltages within desired limits at all load buses of a photovoltaic grid-connected system. To evaluate the performance of a photovoltaic system, this article has developed a probabilistic model that takes into account the random nature of solar irradiance and load. This work introduces a new method utilizing discrete particle swarm optimization and probabilistic radial load flow. Computer simulation reduction demonstrates better performance of the new probabilistic load flow in comparison to the Monte Carlo simulation. Acceptable solutions are reached in a smaller number of iterations. Therefore, convergence is rapidly attained, and computational cost is low ...
TL;DR: A four-step multi-objective mixed-integer non-linear programming technique that uses the genetic algorithm in combination with a sequential quadratic programming method is implemented in MATLAB to solve the problem of optimal reactive power procurement in pool electricity markets.
Abstract: This article presents a new algorithm for optimal reactive power procurement in pool electricity markets. Due to the significant impact of reactive power flow on the system voltage stability and transmission loss, the objective function of the proposed algorithm is minimization of the market payment for reactive power and system energy loss, simultaneously maximizing voltage stability margin. Moreover, as another object, the algorithm tries to decrease the probability of the transmission congestion during reactive power market clearing. A four-step multi-objective mixed-integer non-linear programming technique that uses the genetic algorithm in combination with a sequential quadratic programming method is implemented in MATLAB (The MathWorks, Natick, Massachusetts, USA) to solve the proposed problem. Numerical studies on the IEEE-RTS test system show the suitability of the proposed method.
TL;DR: In this article, a novel technique based on iterative stability-constrained optimum power flow is proposed to maximize the social welfare with consideration of static and dynamic functional operating constraints and dynamic loading margin requirements with respect to normal condition and contingencies.
Abstract: The dynamic security-constrained dispatch of an electric power network is a difficult task facing an independent system operator mandated to provide equitable and fair transmission services in an open-market environment. In this article, a novel technique based on iterative stability-constrained optimum power flow is proposed. The particle swarm optimization methodology is employed to maximize the social welfare with consideration of static and dynamic functional operating constraints and dynamic loading margin requirements with respect to normal condition and contingencies. Furthermore, since the pattern of load increase is difficult to predict in the new market environment, a new method for determining the sensitive loading direction associated with a dynamic loading margin is proposed. An IEEE 14-bus test system with both supply and demand bidding is used to illustrate and test the proposed technique.