Optimal location and sizing of Distribution Static Synchronous Series Compensator using Particle Swarm Optimization

This paper describes the power quality improvement using Particle Swarm Optimization for optimal placement and sizing of Distribution Static Synchronous Series Compensator in radial distribution networks. In this analysis, enhancement of power quality includes improvement of voltage and reduction of line losses. A complete performance analysis is carried out on 12 and 69 bus radial distribution systems to demonstrate the effectiveness of the proposed work. The results show that the placement of DSSSC in radial distribution systems effectively improves the voltage of a system and reduces the power losses. MATLAB, Version 7.10 software is used for simulation.     

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.     

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.     

Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method

A great number of methods have been proposed for distributed generation (DG) placement in distribution networks to minimize the power loss of Medium Voltage (MV) lines. However, very few researches have been done for network configuration in parallel with the DG siting and sizing for the maximum system loss reduction. In this paper, a heuristic method based on “uniform voltage distribution based constructive reconfiguration algorithm” (UVDA) is proposed for the simultaneous reconfiguration and DG siting and sizing. The results obtained from the application of the proposed method on two well-known distribution networks and a real network clearly verify the robustness of the contributed technique. The simulation results demonstrate that the proposed approach is able to find the best solution of the problem found so far. Also, the presented method is applicable to real large-scale distribution systems to find the optimal solution in a very short period of time.     

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.     

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.     

Optimal sitting and sizing of DGs in distribution system considering time sequence characteristics of loads and DGs

With the consideration of time sequence characteristics of load and distributed generator (DG) output, a novel method is presented for optimal sitting and sizing of DG in distributed system. Multi-objective functions have been formulated with the consideration of minimum investment and operational cost of DG, minimum purchasing electricity cost from main grid and minimum voltage deviation. To solve the multi-objective optimization problem, an improved Non-dominated Sorting Genetic Algorithm II has been proposed. The compromised solution is extracted from the Pareto set using the fuzzy theory method. Several experiments have been made on the modified PG&E 69-bus and multiple actual test cases with the consideration of multiple DGs. The computational result and comparisons indicate the proposed method for optimal placement and sizing of DG is feasible and effective.     

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.     

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 placement and sizing of distributed generators and shunt capacitors for power loss minimization in radial distribution networks using hybrid heuristic search optimization technique

This paper attempts to minimize power losses in radial distribution networks and facilitates an enhancement in bus voltage profile by determining optimal locations, optimally sized distributed generators and shunt capacitors by hybrid Harmony Search Algorithm approach. To overcome the drawback of premature and slow convergence of Harmony Search Algorithm (HSA) over multi model fitness landscape, the Particle Artificial Bee Colony algorithm (PABC) is utilized to enhance the harmony memory vector. In the first approach, the formulation echoes the determination of loss sensitivity factor to decide the sensitive nodes and thereafter decides on the optimal rating through the use of hybrid Algorithm. The second approach encircles the role of hybrid Algorithm to search for both the optimal candidate nodes and sizing of compensating devices by significant increase in loss reduction with the former approach. The procedure travels to examine the robustness of the proposed hybrid approach on 33 and 119 node test systems and the result outcomes are compared with the other techniques existing in the literature. The simulation results reveal the efficiency of the proposed hybrid algorithm in obtaining optimal solution for simultaneous placement of distributed generators and shunt capacitors in distribution networks.     

Optimal allocation of shunt Var compensators in power systems using a novel global harmony search algorithm

In this paper, a novel global harmony search algorithm (NGHS) is used to determine the optimal location and size of shunt reactive power compensators such as shunt capacitors, static Var compensators (SVCs), and static synchronous compensators (STATCOMs) in a transmission network. The problem is decomposed into two subproblems. The first deals with the optimal placement of shunt Var compensation devices using the modal analysis method. The second subproblem is the optimization of the load flow using the NGHS algorithm. A multi-criterion objective function is defined to enhance the voltage stability, improve the voltage profile, and minimize power loss while minimizing the total cost. The results from a 57-bus test system show that the NGHS algorithm causes lower power loss and has better voltage profile and greater voltage stability than the improved harmony search algorithm (IHS) and particle swarm optimization (PSO) techniques in solving the placement and sizing problem of shunt Var compensators. Finally, a comparison of the convergence characteristics of three optimization methods demonstrates the greater accuracy and higher speed of the proposed NGHS algorithm in finding better solutions compared with PSO and IHS.     

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.     

A novel optimal distribution system planning framework implementing distributed generation in a deregulated electricity market

This paper introduces a new framework included mathematical model and a new software package interfacing two powerful softwares (MATLAB and GAMS) for obtaining the optimal distributed generation (DG) capacity sizing and sitting investments with capability to simulate large distribution system planning. The proposed optimization model allows minimizing total system planning costs for DG investment, DG operation and maintenance, purchase of power by the distribution companies (DISCOs) from transmission companies (TRANSCOs) and system power losses. The proposed model provides not only the DG size and site but also the new market price as well. Three different cases depending on system conditions and three different scenarios depending on different planning alternatives and electrical market structures, have been considered. They have allowed validating the economical and electrical benefits of introducing DG by solving the distribution system planning problem and by improving power quality of distribution system. DG installation increases the feeders’ lifetime by reducing their loading and adds the benefit of using the existing distribution system for further load growth without the need for feeders upgrading. More, by investing in DG, the DISCO can minimize its total planning cost and reduce its customers’ bills.     

Development of Three-Phase Unbalanced Power Flow Using PV and PQ Models for Distributed Generation and Study of the Impact of DG Models

With the increased installations of distributed generators (DGs) within power systems, load flow analysis of distribution systems needs special models and algorithms to handle multiple sources. In this paper, the development of an unbalanced three-phase load flow algorithm that can handle multiple sources is described. This software is capable of switching the DG mode of operation from constant voltage to constant power factor. The algorithm to achieve this in the presence of multiple DGs is proposed. Shipboard power systems (SPS) have other special characteristics apart from multiple sources, which make the load flow difficult to converge. The developed software is verified for a distribution system without DG using the Radial Distribution Analysis Package (RDAP). The developed software analyzes an IEEE test case and an icebreaker ship system. System studies for the IEEE 37-node feeder without the regulator show the effect of different models and varying DG penetration related to the increase in loading. System losses and voltage deviations are compared.     

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.     

分布式电源模型和负荷模型对配电系统的影响

针对配电系统中分布式电源的配置问题,考虑负荷模型下的不同电压来分析DG模型对DG的选址和容量大小的影响。通过结合不同性能指标为优化子目标的多目标函数,并利用遗传算法对适当的配置地点及DG的容量进行评估,从而根据多目标函数解决接入配电网的DG的配置问题。在IEEE 25节点系统中进行的仿真结果表明,负荷模型对DG在配电网中的配置影响很小,而DG模型对其在配电系统中的配置地点、单机容量和渗透率有明显的影响。     

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.     

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.     

考虑环境因素的分布式发电多目标优化配置

分布式发电优化布置与定容问题是智能电网发展中所面对的一个重要课题。该文在节点有功、无功网损微增率基础上,通过负荷功率法将两者结合,提出等效网损微增率的概念。通过计算该微增率并对其进行排序,可确定分布式发电(distributed generation,DG)的最优安装位置,并且最小化输电线路网损。对于DG定容问题,该文同时考虑了有功网损、电压改善程度和环境改善程度这3个重要指标,将DG优化容量确定问题转化为一个多目标非线性规划问题。采用目标逼近和二次序列规划方法对提出的算法进行求解。算例结果表明,采用该方法确定DG在系统中的布置位置和容量可有效提高系统运行电压,降低有功网损,减少电厂排放的污染气体。该方法对DG在规划阶段的选址和定容问题有着一定的实用价值。     

Optimal placement and sizing of distributed generators based on a novel MPSI index

The Objective: This paper presents a method to identify the optimal location and size of DGs based on the power stability index and particle swarm optimization (PSO) algorithm.Materials and methods: First, a novel maximum power stability index (MPSI) is derived from the well-established theorem of maximum power transfer. The MPSI is utilized as an objective function to determine the optimal DG locations. Next, a PSO-based model with randomized load is developed to optimize DG sizing in view of the system’s real power losses.Results and Conclusion: Lastly, a IEEE 30-bus test system is employed in the simulation. The performance of proposed MPSI index are comparable with other voltage stability indices. The DG optimization model considering voltage stability and loss minimization provides better results compared to that obtained using only loss minimization approach.