Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches

Integration of renewable energy based distributed generation (DG) units provides potential benefits to conventional distribution systems. The power injections from renewable DG units located close to the load centers provide an opportunity for system voltage support, reduction in energy losses, and reliability improvement. Therefore, the location of DG units should be carefully determined with the consideration of different planning incentives. This paper presents a comparison of novel, combined loss sensitivity, index vector, and voltage sensitivity index methods for optimal location and sizing of distributed generation (DG) in a distribution network. The main contribution of the paper is: (i) location of DGs based on existing sensitivity methods, (ii) proposing combined power loss sensitivity based method for DG location, (iii) modified Novel method for DG location, (iv) comparison of sensitivity methods for DG location and their size calculations, and (v) cost of losses and determining cost of power obtained from DGs and the comparison of methods at unity and lagging power factors. 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 33-bus and 69-bus systems.     

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.     

分布式电源接入配电网的经济效益及电压稳定性

借助于回归分析方法将配电网和主网联系起来,基于实时电价理论构建了DG接入配电网的经济效益及配电网电压稳定性分析模型。以IEEE30系统节点8下属配电网接入4个DG为例,定量分析了6个典型日内DG接入前后主配网经济效益及配电网电压稳定性。结果表明：DG合理接入后,终端电力用户的支付电价下降,能够有效消除可能出现的输电阻塞;主配网网损率明显下降,提高了电力输送效率;主配网购电成本显著下降,提高了市场运行效率;高峰时段DG因相对低成本而全额发电,能获得较高的利润;配电网电压稳定性明显增强。随着分布式发电技术的成熟,其成本将会不断下降,DG会因具有成本优势和地理位置优势而成为传统电网的有效补充。     

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.     

Distributed generation placement for congestion management considering economic and financial issues

Congestion management is one of the most important functions of independent system operator (ISO) in the restructured power system. This paper presents two new methodologies for optimal sitting and sizing of distributed generations (DGs) in the restructured power systems for congestion management. The proposed methodologies are based upon locational marginal price (LMP) and congestion rent that forms a priority list of candidate buses to reduce the solution space. The proposed priority list facilitates the optimal placement as well as the level of output power of DGs. The proposed methods are implemented on the IEEE 14-bus and IEEE 57-bus test systems to illustrate their effectiveness. An economic consideration of DG placement and its operation is also studied. Simulation studies and results analysis show that the proposed methodologies are capable of finding the best location and optimal size for DGs, which can alleviate congestion in transmission systems.     

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.     

Novel sensitivity factors for DG placement based on loss reduction and voltage improvement

This paper presents a method to select the load buses for the placement of Distributed generation (DG) based on loss reduction and voltage improvement sensitivity of the system. The strategic placement of DGs can help in reducing power losses and improving voltage profile. The proposed work discusses some new sensitivity factors that can be useful for selecting the locations. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on IEEE 24-bus Reliability Test System (RTS).     

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.     

Optimal DG placement in deregulated electricity market

This paper presents two new methodologies for optimal placement of distributed generation (DG) in an optimal power flow (OPF) based wholesale electricity market. DG is assumed to participate in real time wholesale electricity market. The problem of optimal placement, including size, is formulated for two different objectives, namely, social welfare maximization and profit maximization. The candidate locations for DG placement are identified on the basis of locational marginal price (LMP). Obtained as lagrangian multiplier associated with active power flow equation for each node, LMP gives the short run marginal cost (SRMC) of electricity. Consumer payment, evaluated as a product of LMP and load at each load bus, is proposed as another ranking to identify candidate nodes for DG placement. The proposed rankings bridges engineering aspects of system operation and economic aspects of market operation and act as good indicators for the placement of DG, especially in a market environment. In order to provide a scenario of variety of DGs available in the market, several cost characteristics are assumed. For each DG cost characteristic, an optimal placement and size is identified for each of the objectives. The proposed methodology is tested in a modified IEEE 14 bus test system.     

考虑电能质量的分布式电源优化配置

针对大量电力电子设备投入电网造成严重电能质量问题的现状,提出考虑谐波畸变和电压暂降损失的分布式电源(Distributed Generator,DG)优化配置方法。该方法以DG配置成本、有功损耗、电压暂降损失最小为目标函数,并在满足配网潮流等式和不等式约束的基础上增加谐波畸变限值的约束条件,建立多目标优化模型,最后采用非劣排序遗传算法(Nondominated Sorting Genetic Algorithm-II,NSGA-II)求得最优配置方案。通过IEEE 33节点配电网络对此配置算法进行仿真验证,结果证明该方法得到的DG配置方案可有效降低谐波畸变率、暂降损失及网络损耗。     

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.     

不同类型分布式电源在配电网中的优化布置

分布式电源接入配电网后对电网节点电压、网络潮流、网损等方面带来的影响与分布式电源的种类、接入容量及接入位置密切相关。本文基于静态负荷模型,对小水电、光伏发电两种典型分布式电源与储能设备进行了研究。通过分析不同分布式电源的稳态输出特性,将不同分布式电源的出力特征与电力系统中潮流、电压不越限等约束条件相结合,以网损最小为目标函数提出了小水电、光伏发电与储能设备的优化布置函数。结论表明考虑出力差异性后,不同分布式电源的最优布置计算结果具有明显区别,相比将分布式电源当作常规电源出力将更加精确。     

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 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 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 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.     

分布式电源对配电网电压的影响分析及其优化控制策略

针对配电网中分布式电源(DG)接入渗透率不断提高带来的电压波动、电压越限等电能质量问题,首先从理论上较全面地推导分析分布式电源接入对配电网电压的影响,包括对接入点电压和对电压分布的影响,并通过仿真对比分析了不同DG渗透率和不同DG功率因数下的电压变化情况,指出了全局电压控制的必要性。在此基础上,综合考虑配电网中分布式电源和储能的有功、无功电压调节能力,提出一种基于模型预测控制(MPC)的电压优化控制方案,通过计算各节点电压灵敏度,建立各节点电压预测模型,提前感知各节点电压变化趋势,以各节点预测电压与额定电压之间偏差最小为控制目标,实现了控制成本最低的协调电压控制策略。通过IEEE33节点配电网系统仿真算例分析,结果表明:本文提出的方法能更大限度地消除配电网中分布式可再生能源随机波动带来的影响,具有较好的电压控制灵活性和鲁棒性。     

Quasi-Oppositional Swine Influenza Model Based Optimization with Quarantine for optimal allocation of DG in radial distribution network

Optimal allocation of Distributed Generations (DGs) is one of the major problems of distribution utilities. Optimum locations and sizes of DG sources have profoundly created impact on system losses, voltage profile, and voltage stability of a distribution network. In this paper Quasi-Oppositional Swine Influenza Model Based Optimization with Quarantine (QOSIMBO-Q) has been applied to solve a multi-objective function for optimal allocation and sizing of DGs in distribution systems. The objective is to minimize network power losses, achieve better voltage regulation and improve the voltage stability within the frame-work of the system operation and security constraints in radial distribution systems. The limitation of SIMBO-Q algorithm is that it takes large number of iterations to obtain optimum solution in large scale real systems. To overcome this limitation and to improve computational efficiency, quasi-opposition based learning (QOBL) concept is introduced in basic SIMBO-Q algorithm. The proposed QOSIMBO-Q algorithm has been applied to 33-bus and 69-bus radial distribution systems and results are compared with other evolutionary techniques like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), combined GA/PSO, Teaching Learning Based Optimization (TLBO) and Quasi-Oppositional Teaching Learning Based Optimization (QOTLBO). Numerical studies represent the effectiveness and out-performance of the proposed QOSIMBO-Q algorithm.     

逆变器参数不匹配微电网改进下垂策略

针对逆变器线路阻抗和逆变器参数不匹配以及本地负载不均衡的微电网系统,提出一种改进的P-V控制策略,该策略计算各个分布式发电单元输出有功功率的平均值,然后将平均值与本地有功功率测量值作差,利用该差值的积分项对输出电压幅值进行补偿,从而实现高精度的功率均分。该方法使系统具有很好的稳定性和动态性能,在复杂的微电网结构中也能得到很好的功率均分效果,能够实现不同功率等级逆变器间功率的精确分配。仿真和实验结果证明了方案的正确性。     

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.