Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm

This paper proposes a reconfiguration methodology based on a cuckoo search algorithm (CSA) for minimizing active power loss and the maximizing voltage magnitude. The CSA method is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species which lay their eggs in the nests of other host birds of other species for solving optimization problems. Compared to other methods, CSA method has fewer control parameters and is more effective in optimization problems. The effectiveness of the proposed CSA has been tested on three different distribution network systems and the obtained test results have been compared to those from other methods in the literature. The simulation results show that the proposed CSA can be an efficient and promising method for distribution network reconfiguration problems.     

Optimal Allocation and Operating Point of DG Units in Radial Distribution Network Considering Load Pattern

Distributed generation (DG) is a new approach for solving some problems of older power networks. Due to the increasing power demand in recent power systems, the importance of power loss reduction and maintaining system voltages within an acceptable range has given rise to the wide use of DG units in power systems. On the other hand, unplanned and non-optimal application such as installation and operation of DG units might cause other technical problems. In addition, it is important to consider the load pattern in the network, and the best decision for DG unit's operation must be chosen accordingly. In this paper, a method is introduced in order to make the optimal placement and find an optimal operating point for the DG units, which means the power output of DG units, considering the load pattern of the network. This load pattern has an average load of 24 hr a day, four seasons a year. In the proposed method, optimization has two goals: first, is optimizing the DG unit's placement based on improvement of the voltage profile, and the second is operating DG units with optimum power factor, minimizing power loss, and improving voltage profile, with regard to the load pattern. In order to solve this problem, the gravitational search algorithm and genetic algorithm are used. The proposed method is applied on the IEEE 33-bus test system, and the result shows the effectiveness of the proposed method. In order to solve the optimization problem, MATLAB software is used.     

基于两种仿生算法的低碳主动配电网规划

分布式电源（DG）为未来配电网的规划问题带来了许多新的挑战。在传统配电网规划基本要求的基础上,结合主动配电网相关标准,对主动配电网进行了新的规划。规划过程中,将选择投入运行的电网网架和分布式电源出力大小作为优化变量,将电网的碳排放环境成本作为评判标准。以14节点网络系统为例,将遗传算法（GA）和布谷鸟搜索（CS）算法相结合,并根据电网规划实际情况对算法做了改进。最终在MATLAB环境下,结合MATPOWER潮流计算工具,实现了主动配电网的低碳规划。算例结果表明,该规划方法简单有效,能够为低碳经济下主动配电网的进一步发展提供参考和依据。     

Simultaneous placement of distributed generation and capacitors in distribution networks considering voltage stability index

With regard to widespread use of distributed generation in distribution network, its technical impacts in distribution network should be thoroughly analyzed. In this paper simultaneous placement of distributed generation (DG) and capacitor is considered in radial distribution network with different load levels. The objectives of the problem are reduction of active and reactive power loss, reduction of energy loss and improvement of voltage profile. Also effect of capacitor and DG on voltage stability improvement has been considered in the objective function. Memetic algorithm is used to find optimal solutions. This algorithm is combinatorial form of local search and genetic algorithm. The performance of the proposed method is assessed on a test distribution network.     

Optimal location and sizing of real power DG units to improve the voltage stability in the distribution system using ABC algorithm united with chaos

The introduction of a Distributed Generation (DG) unit in the distribution system improves the voltage profile and reduces the system losses. Optimal placement and sizing of DG units play a major role in reducing system losses and in improving voltage profile and voltage stability. This paper presents in determination of optimal location and sizing of DG units using multi objective performance index (MOPI) for enhancing the voltage stability of the radial distribution system. The different technical issues are combined using weighting coefficients and solved under various operating constraints using a Chaotic Artificial Bee Colony (CABC) algorithm. In this paper, real power DG units and constant power load model and other voltage dependent load models such as industrial, residential, and commercial are considered. The effectiveness of the proposed algorithm is validated by testing it on a 38-node and 69-node radial distribution system.     

A novel method for optimal DG units capacity and location in Microgrids

Distributed generation (DG) has an overall positive impact on Microgrids. These DGs are usually located close to the load centers which lead to some benefits such as; system power loss and energy cost reduction; voltage profile and stability improvement; environmental friendliness, postponement system upgrading and reliability enhancement. In this paper, a novel combined method based on Genetic Algorithm (GA) and Intelligent Water Drops (IWD) is proposed to find location and capacity of DG in Microgrids for optimizing some objective functions. The objectives are minimizing network power losses, improving voltage regulation and increasing the voltage stability within the framework of system operation and security constraints in Microgrids. In this paper, DG units are modeled as generators that are able to inject just active power to network. The Intelligent Water Drops (IWD) algorithm is a new swarm-based optimization algorithm inspired by observing natural water drops that flow in rivers. A detailed performance analysis is carried out on 69-bus and 33-bus Microgrids to demonstrate the effectiveness of the proposed methodology.     

Optimal Installation of Different DG Types in Radial Distribution System Considering Load Growth

In power distribution network, the gradual increase in system load is a natural process, and it results in increased real and reactive power losses and reduced voltage profile. In this paper, optimal single and multiple installations of different types of distributed generation (DG) units are used to handle annual growth in system load, while satisfying system operational constraints. For load growth study, a predetermined growth in system annual load is considered. Minimization of system total real power loss is taken as the main objective, and optimal location and sizing of different DG types are determined using a hybrid configuration of weight-improved particle swarm optimization (WIPSO) with gravitational search algorithm (GSA) called hybrid WIPSO-GSA algorithm. The effect of load growth is studied using standard 33-bus radial distribution system, and the results illustrate significant reduction in system real and reactive power losses, enhancement in system voltage profile, and improvement in load carrying capacity of distribution feeder sections. Moreover, the economic benefits of DG on system annual load growth are also established. Also, the effectiveness of the proposed algorithm is demonstrated by comparing the results with other evolutionary optimization techniques.     

Optimal allocation and sizing of DG units considering voltage stability,losses and load variations

This paper proposes a new index to determine the optimal size and location of DG units, in order to minimize active power losses and enhance voltage stability margin considering load variations. A modified form of Imperialistic Competitive Algorithm (ICA) method is used to solve the optimization problem. To provide a comprehensive perspective for network scheduling, the load variations are considered. The load linear changes are from 50% to 150% of the base load (in 1% steps). At each step, the optimal size and location of the DG unit are determined and then, general expressions for DG sizes as a function of load level are concluded through curve fitting technique. These general expressions can be used as a suitable tool for network planning.The proposed method is applied to 34-bus and 69-bus test systems and the results are compared with the results obtained from cuckoo search algorithm in order to validate the proposed methodology.     

Influence of phasor adjustment of harmonic sources on the allowable penetration level of distributed generation

Harmonic distortion caused by increasing size of inverter-based distributed generation (DG) can give rise to power quality problems in distribution power networks. Therefore, it is very important to determine allowable DG penetration level by considering the harmonic related problems. In this study, an optimization methodology is proposed for maximizing the penetration level of DG while minimizing harmonic distortions considering different load profiles. The methodology is based on updating the voltage magnitude and angle at point of common coupling depending on the size of DG to be utilized in the harmonic power flow modeling. The harmonic parameters are determined by using decoupled harmonic power flow method, in which the harmonic source modeling with harmonic current spectrum angle adjustment is embedded, while the nonlinear loads and inverter-based DGs are connected to the distribution power network. The allowable penetration level of DGs is determined based on power quality constraints including total harmonic voltage distortion, individual harmonic voltage distortion, and RMS bus voltage limits in the optimization framework. Fuzzy-c means clustering method is also applied to decrease the computational effort of the optimization process in the long-term load profile. The effectiveness of the proposed method is illustrated on the IEEE 33-bus radial distribution network for different scenarios.     

Maximal optimal benefits of distributed generation using genetic algorithms

Recently, the distributed power generation (DG) takes more attention, because of the constraints on the traditional power generation besides the great development in the DG technologies. To accommodate this new type of generation, the existing network should be utilized and developed in an optimal manner. This paper presents an optimal proposed approach (OPA) to determine the optimal sitting and sizing of DG with multi-system constraints to achieve a single or multi-objectives using genetic algorithm (GA). The linear programming (LP) is used not only to confirm the optimization results obtained by GA but also to investigate the influences of varying ratings and locations of DG on the objective functions. A real section of the West Delta sub-transmission network, as a part of Egypt network, is used to test the capability of the OPA. The results demonstrate that the proper sitting and sizing of DG are important to improve the voltage profile, increase the spinning reserve, reduce the power flows in critical lines and reduce the system power losses.     

Distributed generation as Voltage support for single wire Earth return systems

Key issues for distributed generation (DG) inclusion in a distribution system include operation, control, protection, harmonics, and transients. This paper analyzes two of the main issues: operation and control for DG installation. Inclusion of DG in distribution networks has the potential to adversely affect the control of voltage. Both DG and tap changers aim to improve voltage profile of the network, and hence they can interact causing unstable operation or increased losses. Simulations show that a fast responding DG with appropriate voltage references is capable of reduction of such problems in the network. A DG control model is developed based on voltage sensitivity of lines and evaluated on a single wire earth return (SWER) system. An investigation of voltage interaction between DG controllers is conducted and interaction-index is developed to predict the degree of interaction. From the simulation it is found that the best power factor for DG injection to achieve voltage correction becomes higher for high resistance lines. A drastic reduction in power losses can be achieved in SWER systems if DG is installed. Multiple DG can aid voltage profile of feeder and should provide higher reliability. Setting the voltage references of separate DGs can provide a graduated response to voltage correction.     

含固态变压器新型配电网动态无功多目标优化

风机和光伏电池等分布式电源(distributed generator, DG)大量接入配电网会导致电压波动和网损增大等问题,需要对动态无功进行优化。但是由于风光存在的不确定性会影响动态无功优化的效果,因此提出了一种含固态变压器新型配电网动态无功多目标优化方法。首先,通过 Weibull 分布和 Beta 分布对风速和光照强度进行曲线拟合,再采用风机和光伏电池出力公式生成 DG 出力模型。其次,通过蒙特卡洛仿真抽样法对上述模型进行抽样,生成上千个DG日出力场景,并采用k-means 聚类算法将上千个场景聚类成k个典型场景,以缩短随机潮流计算时间。再次,以IEEE33 节点系统为基础,建立含固态变压器有源配电网方案和含有载调压变压器有源配电网方案,以日内网损和电压波动最小为目标,采用改进型多目标灰狼算法对两种方案的相关参数进行优化。最后,以优化后的相关参数进行仿真和对比,证明了所提方法在降低配电网网损和维持节点电压稳定方面的优越性。     

含分布式电源的三相不平衡配电网潮流计算

根据配电网三相不平衡的实际情况,为准确计算各种分布式电源(distributed generation,DG)并入配电网后的潮流问题,文章基于前推回代法,提出了可处理PV和PQ节点模型DG的三相不平衡潮流算法。按照配电网拓扑结构,利用支路分层技术,加快了潮流计算速度。在处理PV节点模型DG时,将电压正序分量幅值作为电压调节参数,计算电压正序分量幅值和额定电压幅值差,得到PV节点的无功补偿量,将DG由PV节点运行模型转换为PQ节点运行模型。IEEE 34节点系统算例结果验证了该算法的正确性。最后,通过分析DG对电压的调节和无功补偿能力,研究了不同类型DG对配电网电压的影响。     

Determination of optimal output power and location for multiple distributed generation sources simultaneously by using artificial bee colony

Transformation of a distribution network into an intelligent and efficient system meets with many difficulties. One of most important challenges for engineers is to achieve a more economical distribution network. In addition, fluctuation in the price of oil and gas makes this task more complex. Therefore, the introduction of distributed generation (DG) in the system promises to be a good solution to reduce the dependency on oil and gas sources. However, the location and output power of DG are still an issue that needs to be solved by the utility. In previous studies, determination of DG output power and DG location are executed separately, which means a different technique is applied to each of them. Thus, it will lead the solution getting trapped in a local minimum because the calculation of optimal DG output power does not depend on the optimal DG location. This paper presents a solution to determine the location and output power of DGs simultaneously by using simultaneous artificial bee colony (SABC) to reduce the total power losses. The performance of SABC is compared with that of separate analysis, which is a combination of a single DG placement algorithm and artificial bee colony (ABC). The analysis shows that determining simultaneously the DG's location and the output gives lower total power losses and better voltage profile compared to separately analyzing the two. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

以低碳为目标的分布式发电选址定容方法研究

针对分布式电源选址定容中新能源发电容量的受限问题,提出了分布式电源的两轮规划方法,即首先对新能源发电进行选址定容,然后在此基础上优化配置其他类型的分布式电源。在考虑系统运行费用最低、电压质量最好的基础上,创新地加入了系统等效碳排放量最小这一节能目标,并将目标函数设为规划前后成本和收益之差,直观反映了配电网的经济效益。采用改进的自适应惯性权重粒子群算法,对IEEE33节点标准算例进行求解,最终给出了该网络的最优DG配置方案,分别以图、表的形式表明各种分布式电源的接入节点和接入容量,其中光伏发电占到了分布式电源总量的60%,结果分析表明网损、电压和碳排放指标均有较大改观。     

分布式电源接入下配电网电压无功控制效果分析

分布式电源的接入对配电网的运行状况会有很大的影响,尤其是配电网的电压分布以及网络损耗方面。首先给出了分布式电源和负荷的详细模型,通过准确建模真实模拟电网潮流变化情况。然后引入一种基于规则的电压无功控制方法,以加入分布式电源和具体负荷的IEEE13节点典型馈线系统作为仿真算例,通过电压变化曲线和系统消耗功率等指标验证该算法在分布式电源接入情况下的有效性,并分析接入分布式电源的配电网的电压无功连续控制效果。     

Assessment of energy distribution losses for increasing penetration of distributed generation

High levels of penetration of distributed generation (DG) are a new challenge for traditional electric power systems. Power injections from DGs change network power flows modifying energy losses. Although it is considered that DG reduce losses, this paper shows that this is not always true. This paper presents an approach to compute annual energy losses variations when different penetration and concentration levels of DG are connected to a distribution network. In addition, the impact on losses of different DG technologies, such as combined heat and power, wind power, photovoltaic, and fuel-cells, is analyzed. Results show that energy losses variation, as a function of the DG penetration level, presents a characteristic U-shape trajectory. Moreover, when DG units are more dispersed along network feeders, higher losses reduction can be expected. Regarding DG technologies, it should be noted that wind power is the one that shows the worst behavior in losses reduction. Finally, DG units with reactive power control provide a better network voltage profile and lower losses.     

考虑静态安全约束的分布式电源准入容量计算

分布式电源的接入给配电网带来了一系列影响,在大量分布式电源亟待并网运行的趋势下,研究一个系统能够承受的分布式电源容量具有重要意义。该文分析了分布式电源对配电网电压分布和线路潮流的影响以及分布式电源并网位置和功率因数对准入容量的影响,从电力系统静态安全约束的角度出发,建立了计算分布式电源准入容量的数学模型。对于多个分布式电源的情况,提出了准入容量计算的双层优化模型和相应的优化求解算法,并通过对实际配电系统进行分析,验证了该方法的正确性和有效性。     

Technical and economic impacts of active management on distribution network

With the deregulation of energy market and the appeal for environment protection, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called “fit and forget” policy and the capacity of DG is limited rigidly by distribution network operator (DNO) to avoid the negative effects of high level penetration. Therefore active management (AM) is put forward as an effective method to network reinforcement for the connection and operation of DG. In this paper, the concept and principle of AM are introduced, and several indices are proposed to evaluate both technical and economic impacts of AM on distribution network with DG. To simplify the simulation fuzzy C-means clustering (FCM) algorithm is introduced. The test results on a sample system represent that AM will lead to decrease of power generation of DG, but it can reduce energy losses and improve voltage profile effectively. Furthermore, AM will take great economic incentives to DG developer as well as DNO with reasonable policy.     

Planning for distributed wind generation under active management mode

In the smart grid (SG), the active management (AM) mode will be applied for the connection and operation of distributed generation (DG), which means real time control and management of DG units and distribution network devices based on real time measurements of primary system parameters. In this paper, a novel bi-level programming model for distributed wind generation (DWG) planning under AM mode is put forward. The model takes the maximum expectation of net benefit of DWG as the upper level program objective, and takes the minimum expectation of generation curtailment as the lower level program objective. The impact of active management algorithm on improvement of branch power flow and node voltage is taken into account. A hybrid algorithm combining the plant growth simulation algorithm (PGSA) with probabilistic optimal power flow (POPF) algorithm is presented to solve the optimal planning of DWG under AM mode. The case studies have been carried out on a 33-node distribution network, and the results verify the rationality of the planning model and the effectiveness of the proposed method.