Accommodation of DG sources in a radial distribution system may result in reversal of current flow in some feeder sections of the system with a subsequent protection mis-coordination. To maintain the protection coordi...
详细信息
ISBN:
(纸本)9781728152899
Accommodation of DG sources in a radial distribution system may result in reversal of current flow in some feeder sections of the system with a subsequent protection mis-coordination. To maintain the protection coordination, DG sources are connected to the distribution system through fault current limiters (FCLs) whose impedances are unknowns. A method is proposed to formulate an optimization function to minimize power-loss and to ensure that the fault currents restore to their original values without DG sources. The proposed method is based on two approaches. In the two-stage approach, the sizes and locations of DG sources are determined in the first-stage followed by the determination of sizes of FCLs in the second-stage. In the single-stage approach, the sizes of FCLs as well as the sizes and locations of DG sources are determined simultaneously. Minimization of the objectivefunction is achieved using Particle Swarm Optimization (PSO) technique to obtain the optimum impedance values of the FCLs in addition to the sizes and locations of DG sources. The method is applied to the Canadian benchmark 9-bus and the IEEE 33-/69-bus distribution systems. The obtained impedances of the FCLs as well as the sizes and locations of DG sources are correlated with those reported in the literature for the same distribution system.
This paper is aimed at presenting the importance of DG sources in distribution systems and reviewing the published work on optimal planning through determination of optimal locations and sizes of DG sources by minimiz...
详细信息
ISBN:
(纸本)9781728152899
This paper is aimed at presenting the importance of DG sources in distribution systems and reviewing the published work on optimal planning through determination of optimal locations and sizes of DG sources by minimizing single-objectivefunction (SOF) and multi-objective function (MOF). The indices of the SOF include active power loss, reactive power loss, bus voltage deviation, voltage stability, cost and others. The MOF combines several indices through weighting coefficients depending on the importance of the indices. The optimization techniques are reviewed after being classified into conventional and artificial-intelligence based-ones. Particular attention is directed to genetic algorithm and its hybrids with other techniques for optimal sizing and location of DG sources.
This study introduces a new estimation approach that could be used in calculating the Weibull parameters for the estimation of wind power. This new approach, called the method of multi-objective moments (MUOM), propos...
详细信息
This study introduces a new estimation approach that could be used in calculating the Weibull parameters for the estimation of wind power. This new approach, called the method of multi-objective moments (MUOM), proposes minimization of the squared deviances between the first three population moments and corresponding sample moments. In the proposed MUOM, the third moment, which is used in the formula of wind power, is a key function since it provides a significant contribution to the correct prediction of wind energy. In order to demonstrate the performance of the proposed MUOM, it is compared with the well-known estimation methods such as the maximum likelihood, modified maximum likelihood, moment and energy pattern factor. In comparative analysis, the performance of the considered methods is evaluated on the actual wind speed data measured different time periods according to various goodness of fit criteria. The obtained results indicate that the MUOM definitely provides more accurate estimates than other well-known methods in estimating wind power based on the Weibull distribution. Thus, the MUOM can be used as an improved method in estimating wind power.
This article investigates a novel visualization-based fusion of hyperspectral image bands using an iterative approach. Given a multi-objective function and the pixel-based hyperspectral image fusion method, the optimi...
详细信息
This article investigates a novel visualization-based fusion of hyperspectral image bands using an iterative approach. Given a multi-objective function and the pixel-based hyperspectral image fusion method, the optimization process is described as finding the optimal fusion parameters to improve the fusion performance. Accordingly, an iterative-based approach is adopted. In the first step, the fusion process is developed using the pixel-based fusion technique. In the second step, the fused image is produced, and the fusion quality is assessed for multi-objective function construction. For multi-objective formulation, we focus three desired properties of the fused image such as entropy, variance, and smoothness. In the last step, fusion parameters are updated iteratively by examining the objectivefunction. Here, the self-adaptive learning particle swarm optimizer is used to refine the fusion parameters iteratively. Different hyperspectral images, such as Cuprite mining, AVIRIS Indian pines scene, are employed in the evaluation. Quantitative analysis of fused images is carried out through some efficient fusion metrics such as correlation coefficient, entropy, Q-average, ERGAS, SAM, and SID. Experimental results show that the proposed approach outperforms existing methods in terms of both objectivefunction criteria and visual effect.
This paper presents differential search algorithm in order to solve reliability optimization problem of radial distribution network. Remote control switches have been optimally allocated to improve reliability at a co...
详细信息
This paper presents differential search algorithm in order to solve reliability optimization problem of radial distribution network. Remote control switches have been optimally allocated to improve reliability at a compromised cost. A multi-objective problem has been formulated and solved using differential search algorithm. The test systems considered in this paper are an 8 bus radial distribution network and a 33 bus radial distribution network. Simulation results obtained using differential search algorithm when applied to the test cases, have been compared with those obtained by particle swarm optimization. Differential search algorithm has been found to provide superior results as compared to particle swarm optimization. (C) 2016 Production and hosting by Elsevier B.V. on behalf of Ain Shams University.
The adoption of the transferable load and energy storage system (ESS) makes the microgrid more suitable for the development of modern electricity. By means of energy storage equalization technology and transferable lo...
详细信息
The adoption of the transferable load and energy storage system (ESS) makes the microgrid more suitable for the development of modern electricity. By means of energy storage equalization technology and transferable load, this paper proposes a day-head optimal scheduling method for a grid-connected microgrid. In the proposed strategy, by solving the multi-objective function involving in the cost of electricity market demand, operating of BESS, and the residents' satisfaction, then the optimal control of transferable load and the charging/discharging power are achieved according to the strategy of ESS equalization and transferable load. Besides, the stability of charging/discharging power and the consistency of the battery units are analyzed. Finally, simulation results are provided by using the improved PSO to show that this proposed method can attain much stability and efficiency.
Distributed generation (DG) is a better alternative to meet power demand near the load centers than centralized power generation. Optimal placement and sizing of DGs plays a crucial role in improving the performance o...
详细信息
Distributed generation (DG) is a better alternative to meet power demand near the load centers than centralized power generation. Optimal placement and sizing of DGs plays a crucial role in improving the performance of distribution systems in terms of network loss reduction, voltage profile improvement, reliability of power supply and stability issues. This paper presents a comprehensive teaching learning-based optimization (CTLBO) technique for the optimal allocation of DGs in radial distribution systems to improve network loss reduction, voltage profile and annual energy savings. The proposed technique can handle mixed integer variables, is parameter independent and possesses immunity to local extrema trappings. The effectiveness of the proposed method is first validated on standard mathematical benchmark functions. It is observed to have better convergence characteristics than teaching learning-based optimization (TLBO) and quasi-oppositional teaching learning based optimization (QOTLBO). Subsequently, it is applied to optimal DG allocation in IEEE 33-bus, 69-bus and 118-bus radial distribution test systems. Both single and multi-objective formulations are considered. In addition, the selection of the optimal number of DGs in the distribution networks is also investigated and case studies are carried out. Results demonstrate that optimal allocation of DGs using the proposed technique results in marked improvement in the performance of distribution systems over TLBO and QOTLBO. The applicability of the proposed technique for DG allocation in distribution systems with practical load profiles results in further improvement in annual energy loss reduction and cost savings.
In this paper, a multi-objective optimization method is proposed to determine trade-off between conflicting operation objectives of wind farm (WF) systems, i.e., maximizing the output power and minimizing the output p...
详细信息
In this paper, a multi-objective optimization method is proposed to determine trade-off between conflicting operation objectives of wind farm (WF) systems, i.e., maximizing the output power and minimizing the output power fluctuation of the WF system. A detailed analysis of the effects of different objective's weight values and battery size on the operation of the WF system is also carried out. This helps the WF operator to decide on an optimal operation point for the whole system to increase its profit and improve output power quality. In order to find out the optimal solution, a two-stage optimization is also developed to determine the optimal output power of the entire system as well as the optimal set-points of wind turbine generators (WTGs). In stage 1, the WF operator performs multi-objective optimization to determine the optimal output power of the WF system based on the relevant information from WTGs' and battery's controllers. In stage 2, the WF operator performs optimization to determine the optimal set-points of WTGs for minimizing the power deviation and fulfilling the required output power from the previous stage. The minimization of the power deviation for the set-points of WTGs helps the output power of WTGs much smoother and therefore avoids unnecessary internal power fluctuations. Finally, different case studies are also analyzed to show the effectiveness of the proposed method.
As the power system continuously operates under stressed condition due to various constraints, i.e. economic, right of way and regulations etc. FACTS devices are used to provide flexible control of the power systems. ...
详细信息
ISBN:
(纸本)9781538649961
As the power system continuously operates under stressed condition due to various constraints, i.e. economic, right of way and regulations etc. FACTS devices are used to provide flexible control of the power systems. STATCOM is used to control the various parameters of the power system either by injecting or absorbing the reactive power but subjected to the cost. Therefore, this paper concerns with the optimal number, location and size of holomorphic embedded load-flow (HELF) model of STATCOM in the multi-bus power systems using improved sine cosine optimization algorithm (ISCA). The IEEE 30-bus test system is considered to validate the algorithm for optimal allocation of HELF model. The results are also compared with the sine-cosine algorithm (SCA) and grey wolf optimization (GWO).
Due to development of distribution systems and increase in electricity demand,the use of capacitor banks *** the other point of view,nonlinear loads generate and inject considerable harmonic currents into power *** th...
详细信息
Due to development of distribution systems and increase in electricity demand,the use of capacitor banks *** the other point of view,nonlinear loads generate and inject considerable harmonic currents into power *** this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable *** attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is *** the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion *** paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current *** algorithm is based on particle swarm optimization(PSO).The objectivefunction includes the cost of power losses,energy losses and those of the capacitor banks and APCs.
暂无评论