An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm

Nowadays due to development of distribution systems and increase in electricity demand, the use of distributed generation (DG) sources and capacitors banks in parallel are increased. Determining the installation location and capacity are two significant factors affecting network loss reduction and improving network performance. This paper, proposes an efficient hybrid method based on Imperialist Competitive Algorithm (ICA) and genetic algorithm (GA) which can greatly envisaged with problems for optimal placement and sizing of DG sources and capacitor banks simultaneously. The objective function is power loss reduction, improving system voltage profile, increasing voltage stability index, load balancing and transmission and distribution relief capacity for both utilities and the customers.The proposed method is implemented on IEEE 33 bus and 69 bus radial distribution systems and the results are compared with GA/Particle swarm optimization (PSO) method. Test results show that the proposed method is more effective and has higher capability in finding optimum solutions.     

A Multi-objective Shuffled Bat algorithm for optimal placement and sizing of multi distributed generations with different load models

In this paper a new and efficient hybrid multi-objective optimization algorithm is proposed for optimal placement and sizing of the Distributed generations (DGs) in radial distribution systems. A Multi-objective Shuffled Bat algorithm is proposed to evaluate the impact of DG placement and sizing for an optimal improvement of the distribution system with different load models. In this study, the ideal sizes and locations of DG units are found by considering the power losses, cost and voltage deviation as objective functions to minimize. Furthermore, the study is verified with voltage dependent load models like industrial, residential, commercial and mixed load models. The feasibility of the proposed technique is verified with the 33 bus distribution network and also the qualitative comparisons against a well-known technique, known as Non-dominated Sorting Genetic Algorithm II (NSGA-II) is done and results are presented.     

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.     

基于改进粒子群优化算法的DG准入容量与优化布置

为进一步优化配电网中分布式电源（distributed generation,DG）的准入容量和优化布置问题,以节点电压和线路载流量为约束条件建立了单电源和多电源准入容量的数学模型,以有功网损最小为目标函数建立了DG优化布置模型。为有效求解该模型,采用了基于粒子群优化（particle swarm optimization,PSO）算法和二次插值相结合的改进PSO算法,将该改进方法应用于IEEE 33节点标准算例,分别进行了DG的最优接入位置与最优容量的仿真,并与粒子群算法优化结果进行了对比,同时还分析了优化布置下的潮流分布。算例仿真结果表明该方法可有效减少DG接入后配电网的网损,提高配电网的供电质量。     

Optimal DG Allocation in Radial Distribution Systems with High Penetration of Non-linear Loads

This paper addresses the optimal distributed generation sizing and siting for voltage profile improvement, power losses, and total harmonic distortion (THD) reduction in a distribution network with high penetration of non-linear loads. The proposed planning methodology takes into consideration the load profile, the frequency spectrum of non-linear loads, and the technical constraints such as voltage limits at different buses (slack and load buses) of the system, feeder capacity, THD limits, and maximum penetration limit of DG units. The optimization process is based on the Genetic Algorithm (GA) method with three scenarios of objective function: system power losses, THD, and multi-objective function-based power losses and THD. This method is executed on the IEEE 31-bus system under sinusoidal and non-sinusoidal (harmonics) operating conditions including load variations within the 24-hr period. The simulation results using Matlab environment show the robustness of this method in optimal sizing and siting of DG, efficiency for improvement of voltage profile, reduction of power losses, and THD. A comparison with particle swarm optimization (PSO) method shows that the proposed method is better than PSO in reducing the power losses and THD in all suggested scenarios.     

Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth

This paper presents a comparison of Novel Power Loss Sensitivity, Power Stability Index (PSI), and proposed voltage stability index (VSI) methods for optimal location and sizing of distributed generation (DG) in radial distribution network. The main contribution of the paper is: (i) optimal placement of DGs based on Novel Power Loss Sensitivity and PSI methods, (ii) proposed voltage stability index method for optimal DG placement, (iii) comparison of sensitivity methods for DG location and their size calculations, (iv) optimal placement of DG in the presence of load growth, (v) impact of DG placement at combined load power factor, (vii) impact of DG on voltage stability margin improvement. Voltage profile, the real and reactive powers intake by the grid, real and reactive power flow patterns, cost of energy losses, savings in cost of energy loss and cost of power obtained from DGs are determined. The results show the importance of installing the suitable size of DG at the suitable location. The results are obtained with all sensitivity based methods on the IEEE 12-bus, modified 12-bus, 69-bus and 85-bus test systems.     

Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm

A Particle Swarm Optimization algorithm for finding the optimal location and sizing of Distributed Generation and Distribution STATicCOMpensator (DSTATCOM) with the aim of reducing the total power loss along with voltage profile improvement of Radial Distribution System is proposed in this paper. The new-fangled formulation projected is inspired by the idea that the optimum placement of the DG and DSTATCOM can facilitate in minimization of the line loss and voltage dips in Radial Distribution Systems. A complete performance analysis is carried out on 12, 34 and 69 bus radial distribution test systems and each test system has five different cases. The results analyzed using Loss Sensitivity Factor shows the optimal placement and sizing of DG and DSTATCOM in Radial Distribution System effectively improves the voltage profile and reduces the total power losses of the system.     

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.     

Optimum placement and sizing of DGs considering average hourly variations of load

This paper presents a multiobjective technique for obtaining optimal sizing of Distributed Generation (DG) units considering both technical and economical factors of the distribution system. The technical factors include real power loss reduction, line load reduction and voltage profile improvement and the economical factors consider optimal DG investment cost. Three different Distributed Generation systems solar photovoltaic, biomass and wind system are considered for integration with the existing distribution system. Since solar photovoltaic system is not available at night time, only biomass and wind systems are operated and for day time operation all the three distribution generation systems are considered. A new sensitivity index based on voltage sensitivity and apparent load power is proposed for identification of optimal locations for DG placement. The optimum sizing of DG units operating at unity power factor and lagging power factor is obtained using GA for different load levels considering daily average hourly loading aiming at improving the technical performance of the distribution system with optimum investment on DG units. Simulation results are presented to show the advantage of the proposed methodology in terms of technical performance and annual economical savings of the distribution system.     

An efficient optimal capacitor allocation in DG embedded distribution networks with islanding operation capability of micro-grid using a new genetic based algorithm

Capacitor banks are commonly used in electric distribution networks as a kind of reactive power sources. These sources are located in distribution networks for power factor correction, loss reduction, and voltage profile improvement. For these purposes optimal capacitor placement is needed to determine capacitors types, sizes and locations. Distribution system with Distributed Generation (DG) can have micro-grid that it will operate in both grid-connected and islanded modes of operation. The aim of this paper is to provide a method for optimal capacitor (fixed and switchable) placement in such a distribution network. The effect of different operation modes of DGs on the network is also investigated. The proposed method can guarantee the benefits of capacitor installation at different load levels. It is based on genetic algorithm (GA) with new coding and operators. Switching table of the allocated capacitors can be found through the proposed structure of the chromosome. Some case studies developed to illustrate the efficiency of the proposed method.     

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。     

含分布式发电的配电网有功—无功综合优化

为克服配电网中风力发电机和光伏电池出力随机波动、负荷变化带来的电压变动,研究了多种分布式电源接入配网后的电压控制问题。以分布式电源出力随机波动和负荷变化时每个时段的电压偏差和网损最小,以及尽量减少大电网向配电网输送有功为目标函数建立电压控制模型,采用粒子群优化算法对微型燃气轮机和燃料电池等出力稳定的分布式电源进行有功和无功综合优化,在保证电压质量的情况下减少对环境的污染。通过对IEEE33节点系统和一个实际算例系统分别进行仿真计算,结果表明该控制方案能在有效提高配电网电压水平的基础上提高环境效益。     

基于DG和多端VSC协调控制的交直流配电网优化运行

分布式电源(DG)大规模并网不仅带来了消纳问题,还使交直流网络的经济安全运行面临巨大挑战。基于此,文中提出一种基于DG选址和多端电压源换流器(VSC)协调控制的交直流混合配电网优化运行方法。针对DG选址,基于灵敏度分析方法提出一种节点网损灵敏度指标,利用网络中不同位置的负荷节点对网损敏感度不同的规律进行交流网侧的DG选址。进而建立以网络有功总损耗、节点电压偏移量和DG盈余量最小为目标的多目标优化模型,对多端VSC不同控制策略下的端口功率电压变量和DG的有功出力进行协调控制。仿真结果表明,所提优化运行方法能够提高网络运行经济性和安全性,并兼顾配电网对DG的消纳水平,为实际工程中的决策人员提供重要的参考。     

分布式电源并网动态无功优化调度的研究

根据分布式电源并网的控制特性,将分布式电源设计为电压控制型和无功补偿型,考虑其与地区电网的电压无功控制手段相结合,参与地区电网动态无功优化调度。建立以降低地区电网网损、抑制电压波动为综合目标的地区电网模糊动态无功优化调度模型。在该模型中,通过构造模糊评价函数,将目标函数转化为对优化结果的满意度,并利用自适应权重法将综合目标进行归一化处理。最后采用改进遗传算法有效求解含分布式电源的地区电网动态无功优化调度策略。算例表明,提出的模型和方法是合理的,具有一定参考价值。     

Long term scheduling for optimal allocation and sizing of DG unit considering load variations and DG type

This paper proposes a new long term scheduling for optimal allocation and sizing of different types of Distributed Generation (DG) units in the distribution networks in order to minimize power losses. The optimization process is implemented by continuously changing the load of the system in the planning time horizon. In order to make the analysis more practical, the loads are linearly changed in small steps of 1% from 50% to 150% of the actual value. In each load step, the optimal size and location for different types of DG units are evaluated. The proposed approach will help the distribution network operators (DNOs) to have a long term planning for the optimal management of DG units and reach the maximum efficiency. On the other hand, since the optimization process is implemented for the entire time period, the short term scheduling is also possible. The proposed method is applied to IEEE 33-bus test system using both the analytical approach and particle swarm optimization (PSO) algorithm. The simulation results show the effectiveness and acceptable performance of the proposed method.     

含分布式电源的配电网分区和主导节点选取方法研究

为了应对分布式电源及柔性负荷大规模接入给配电网电压控制带来的困难,提出一种基于改进的粒子群优化算法的配电网分区方法,通过分区使分布式电源主动参与到配电网的控制过程中。引入评价分区结果优劣的四个指标,综合考虑分区内无功/有功储备、区域内强耦合和区域间弱耦合,并结合无功/有功可控性和电压可观性,构建主导节点选取公式。该方法将分区转化为优化求解问题,使得分区结果能根据分布式电源运行参数和配电网结构的变化进行灵活调整。通过仿真证明了该分区科学合理,在该方法基础上的分布式电压控制能有效缓解柔性负荷大规模接入所带来的节点电压越限等问题,具有实际应用价值。     

Optimal wind turbine sizing to minimize energy loss

The integration of renewable distributed generation (DG) in power systems has been increasing day by day. One of the most promising DG technologies is wind turbine among the renewable sources. Therefore, the optimization of DG whose the output power is varying with time is very crucial for the future power systems. However, it is difficult to establish a suitable objective function by taking into account of time varying characteristics. In this paper, a methodology based on weighting factors is proposed in order to minimize energy loss by finding the optimal sizes of wind turbines. The optimization is carried out by using the genetic algorithm with utilizing power flow analysis. The contribution of this paper is to allow considering the time varying characteristics of both load and wind-generation profile in a pairwise manner without violating the harmony of correspondence between load and generation profile. In addition, the proposed methodology is merged with the fuzzy-c means clustering to reduce execution time and allow long term planning due to the fact that the computational burden of the genetic algorithm is substantially high. The proposed methodology is applied to the IEEE-30 bus test system for 4 days and annual energy loss minimization scenarios. The results show that energy loss can be reduced significantly by using the proposed methodology.     

分布式电源并网的配电网改进潮流算法

分布式电源(DG)的并网,不可避免地对配电网运行和安全产生很大影响,因此必须对含DG的配电网潮流进行计算调整.在分析常见的几种DG基础上,给出它们各自在潮流计算中的模型以及处理方法,并提出一种改进型前推回代潮流算法,来计算含DG的配电系统潮流.考虑到前推回代法处理PV节点的能力较差,引入注入无功修正法.此外,分析PV节点型DG无功初值选取对潮流收敛性的影响,以及DG并网对系统电压和网损的影响.设计不同类型DG并网的测试方案,在IEEE 33节点配电网络中反复检验,结果表明该方法是有效的.     

Optimal reactive power control of DGs for voltage regulation of MV distribution systems using sensitivity analysis method and PSO algorithm

This paper addresses the problem of reactive power control of distributed generation (DG) units in the medium voltage (MV) distribution systems to maintain the system voltages within the predefined limits. An efficient approach for the load flow calculation is used here which is based on the topological structure of the network. It has been formulated for the radial distribution systems. A direct voltage sensitivity analysis method is developed in this paper which is also based on the topological structure of the network and independent of the network operating points. Thus, the sensitivity matrix is calculated once with the load flow program and it is used in all the system working conditions. The problem of DGs reactive power control is formulated as an optimization problem which uses the sensitivity analysis for linearizing the system around its operating points. The objective of the optimization problem is to return the system voltages inside the permitted range by using the reactive power of DGs in an optimal way. The optimal solutions are obtained by implementing particle swarm optimization (PSO) algorithm. Then, the results are verified by running a load flow considering new values of DGs reactive power. The procedure is repeated as long as a voltage violation is observed. Simulation results reveal that the proposed algorithm is capable of keeping the system voltages within the permitted limits.     

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。