Sizing Of Distributed Generation Units Research Articles

Optimal Sizing and Location of DG Units for Enhancing Voltage Profile and Minimizing Real Power Losses in the Radial Power Systems Based on PSO Technique

Distributed generation (DG) units have an important number of economic, environmental and technical features, which can contribute to the improvement of the reliability and security of the electric grid. However, all benefits that mentioned before cannot be maximised and enhanced unless the best sizing and position of distributed generation units are accurately determined. The arbitrary placement of DG units can lead to negative influences on the electrical networks. A noteworthy number of methods have been suggested to compute the optimal sizing and position of Distributed generation (DG) units in distribution networks. However, some of them focused on an analytical approach to estimate the optimum allocation of DG units in the radial distribution networks. Indeed, although this method was considered both constant and variable loads, as well as this method, overcome the problem of convergence, but the optimal sizing of DG units was not considered. The main intention of this study is to improve a technique that based on an intelligent algorithm for optimal planning and operation of DG technologies to minimise the real power losses, boost the voltage profile and enhance the overall reliability. IEEE Node-15 system has been taken to perform this study based on a MATLAB environment.in a single paragraph.

Optimum placement and sizing of DG units based on improving voltage stability using multi-objective evolutionary algorithm

This paper presents a method for locating and sizing Distributed Generation (DG) units based on the enhancement of voltage stability and network total loss reduction in radial distribution systems. In this method, a voltage stability index is used to determine the weakest buses from the voltage stability point of view as the best candidates for installing DGs. Also, an evolutionary algorithm based on Pareto Strength is used for solving the DG sizing problem. This problem is configured as a multi-objective optimization problem. The objective functions are defined as minimizing total power loss, enhancement of voltage stability and voltage profile improvement. Also, the effects of DG operating power factor and DG penetration level on total network loss and voltage stability are investigated and the DGs with the ability of generating reactive power are used. The selected DG penetration level is considered as a constraint in the evolutionary algorithm for determining the optimal size of DGs. It is shown that the selection of optimum DG penetration level can optimize the objective functions simultaneously. The proposed method is tested on a standard IEEE 69-bus radial distribution network. The obtained results are compared with similar previous methods and the appropriate performance of the proposed method is verified.

Improved stochastic fractal search algorithm with chaos for optimal determination of location, size, and quantity of distributed generators in distribution systems

In the power system operation, the reduction of the power loss in distribution systems has significance in the reduction of operating cost. In this paper, a novel chaotic stochastic fractal search (CSFS) method is implemented for determining the optimal siting, sizing, and number of distributed generation (DG) units in distribution systems. The objective of the optimal DG placement problem is to minimize the power loss in distribution systems subject to the constraints such as power balance, bus voltage limits, DG capacity limits, current limits, and DG penetration limit. The proposed CSFS method improves the performance of the original SFS by integrating chaotic maps into it. On the other hand, ten chaotic maps are utilized to replace the random scheme of the original SFS to enhance its performance in terms of accuracy of solution and convergence speed, corresponding to ten chaotic variants of the SFS where variant being chosen is the best chaotic variant regarding search performance. For solving the problem, the CSFS is implemented to simultaneously find the optimal siting and sizing of DG units and the optimal number of DG units will be obtained via comparing optimal results from different numbers of DG in the problem. The proposed method is tested on the IEEE 33-bus, 69-bus, and 118-bus radial distribution systems. The obtained results from the CSFS are verified by comparing to those from the original SFS and other methods in the literature. The result comparisons indicate that the proposed CSFS method can obtain higher quality solutions than the original SFS version and many other methods in the literature for the considered cases of the test systems. Moreover, the incorporation of chaos theory allows performing the search process at higher speeds. Therefore, the proposed CSFS method can be a very promising method for solving the problem of optimal placement of DG units in distribution systems.

Power loss minimisation of rural feeder of Jaipur city by renewable-based DG technologies

ABSTRACTPower systems are becoming more complex day by day due to stressed situation in a distribution system, augmented growth in population and high demands of electrical power. In India, the distribution losses are around 20–25%. Distributed Generation (DG) units are broadly used to reduce the power losses in distribution system. To optimise the benefits of DGs, it is essential to determine its appropriate size and location. A new mathematical expression, power voltage sensitivity constant, has been formulated to determine its size and location. In this paper, two types of DG units (PV module and shunt capacitor) are employed for power loss reduction. The size of DG units (PV module) has been restricted to 50% of total system load in the paper. The proposed approach is tested on standard IEEE 69 bus distribution system and 130 bus real distribution system of Jamwa Ramgarh village, Jaipur, India. The results obtained from standard systems are compared with latest optimisation techniques to show the effectiveness and robustness of the proposed approach. The results of real systems are also encouraging.

Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems

This paper mainly focused on the impact of distributed generation (DG) placement on distribution system. The integration of DG is transforming the traditional radial distribution system into a multi-source system. Distributed generation is a term that refers to the production of electricity near the consumption place. The effects of distributed generation are short circuit levels are increased, load losses change, reliability change and voltage profiles change along the network. The above advantages can be accomplished by ideal position and sizing of DG units. The ideal positions are obtained from index vector method. Ant Lion Optimization (ALO), a novel meta heuristic algorithm is used to determine the optimal DG size. ALO is modeled based on the unique hunting behavior of ant lions. The ALO algorithm is evaluated on IEEE 15, 33, 69 and 85-bus test systems. ALO algorithm was compared with different types of DG units and other evolutionary algorithms. When compared with other algorithms the ALO algorithm gives better results. From the analysis best results have been achieved from type III DG operating at 0.9pf.

Impact of Distributed Generation on the Reliability of Local Distribution System

With the growth of distributed generation (DG) and renewable energy resources the power sector is becoming more sophisticated, distributed generation technologies with its diverse impacts on power system is becoming attractive area for researchers. Reliability is one of the vital area in electric power system which defines continuous supply of power and customer satisfaction. Around the world many power generation and distribution companies conduct reliability tests to ensure continues supply of power to its customers. Uttermost reliability problems in power system are due to distribution network. In this research reliability analysis of distribution system is done. The interruption frequency and interruption duration increases as the distance of load points increase from feeder. Injection of single DG unit into distribution system increase reliability of distribution system, injecting multiple DG at different locations and near to load points in distribution network further increases reliability of distribution system, while introducing multiple DG at single location improves reliability of distribution system. The reliability of distribution system remains unchanged while varying the size of DG unit. Different reliability tests were done to find the optimum location to plant DG in distribution system. For these analyses distribution feeder bus 2 of RBTS is selected as case study. The distribution feeder is modeled in ETAP, ETAP is software tool used for electrical power system modeling, analysis, design, optimization, operation, control, and automation. These results can be helpful for power utilities and power producer companies to conduct reliability tests and to properly utilize the distributed generation sources for future expansion of power systems.

Distribution Network Power Loss Minimization by Optimal DG Allocation

This paper presents a methodology based on analytical approach to optimally allocate (site and size) the Distributed Generation (DG) units(s) in radial power distribution networks for minimizing the real power losses. The proposed method requires only the results of base case load flow to determine the optimal size of DG unit(s) required at each bus. For this, suitable analytical expressions have been proposed to determine the optimal size of DG unit(s) to cause total minimum real power loss in a given distribution network with their corresponding optimal location(s). Two cases with two scenarios comprising of DG type and number of DG units (single and multiple), respectively, are considered. The proposed method is applied to an IEEE 33-bus radial distribution test system. Results obtained by this proposed method validate the suitability and importance of appropriate DG allocation and also the number of DG units in power distribution networks.

Feeder Reconfiguration for Unbalanced Distribution Systems With Distributed Generation: A Hierarchical Decentralized Approach

Most existing approaches for distribution network reconfiguration assume that the distribution system is (three-phase) balanced and a single-phase equivalent is used. However, distribution feeders are usually unbalanced due to a large number of single-phase loads, nonsymmetrical conductor spacing, and three-phase line topology. This paper builds on our previous work and studies feeder reconfiguration for unbalanced distribution systems with distributed generation (DG). The three-phase bus locations and sizes of DG units are determined using sensitivity analysis and nonlinear programming, respectively, and distribution feeders are reconfigured every hour based on the status of time-varying loads, output power from DG units and faults on the network while minimizing the energy loss costs and DG operating costs. Simulation results show the effectiveness and computational efficiency of the proposed approach.

A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network

Abstract This paper proposes a new methodology to optimize network topology and placement of distributed generation (DG) in distribution network with an objective of reduction real power loss and voltage stability enhancement. A meta-heuristic cuckoo search algorithm (CSA) inspired from the obligate brood parasitism of some cuckoo species which lay their eggs in the nests of other birds of other species for solving optimization problems is adapted to simultaneously reconfigure and identify the optimal location and size of DG units in a distribution network. The graph theory is used to determine the search space which reduces infeasible network configurations of reconfiguration process and check the radial constraint of each configuration of distribution network. The effectiveness of the proposed method has been validated on three different distribution network systems at seven different scenarios. The obtained results show well the effectiveness and performance of the proposed method in distribution network reconfiguration with optimal location and size of DG problems.

Network Reconfiguration with Optimal DG Integration into Distribution Network for Power Loss Minimization via AGPSO

Enhancement of Voltage profile and suppression of real power loss are the two major tasks for the Distribution system engineers. Network Reconfiguration (NR) is one of the traditional techniques used to address the above issue. During the last decade, optimal allocation and sizing of DG units had played a significant role in minimizing the power loss as well as bus voltage improvement. In the recent days power scenario, combination of Distributed Generation (DG) and Network Reconfiguration (NR) were extensively applied to mitigate the above problems in an effective and efficient manner in comparison study of their individual counterparts. This paper proposes an application of Autonomous Group Particle Swarm Optimization (AGPSO) to solve the NR problem with optimal allocation and sizing of DG units under three different cases. Further, a comprehensive study has been conducted to ascertain the impact of power loss in increasing the number of DG units with NR considering single and two DG units. This developed technique is demonstrated using two test systems (IEEE 33 and 69) and the results are compared with other methods. Simulation results reveal that the developed technique effectively improved in power loss suppression and bus voltage improvement.

Optimal dispatchable DG allocation in a distribution network considering load growth with a mixed-PSO algorithm

In recent years, one of the major issues faced by distribution utilities is integrating distributed generation (DG) units in distribution networks. This paper proposes a population-based method called particle swarm optimization (PSO) for optimal planning of the location and sizing of different types of DG units in the distribution network, considering different loading conditions. The objective of this application is power loss minimization. In order tond the optimal location and size of DG units, continuous and discrete forms of PSO are deployed, respectively (mixed PSO). In addition, the optimal locations and sizes of the DG units are determined in the areas of signicant feeder load growth. This meta- heuristic approach makes little or no assumption about the issue being optimized and can search large spaces of possible solutions. The presented method is tested on the standard IEEE 33-bus and IEEE 69-bus test systems. In order to show the effectiveness of the proposed methodology, the results are compared with another method of DG allocation and another loss minimization technique.

Distributed Generation Placement in Distribution Network Based on Power-Flow Relations

Installing Distributed Generation (DG) influences distribution network stability and losses. The aim of the Distributed Generation placement (DGP) is to provide the best locations and sizes of DG units to optimize electrical distribution network operation and planning taking into account DG capacity constraints. In this paper a really formula based on Power flow for obtaining DGP and sizing to improve the performance of the distribution network is offered. The aim of this really formula is to eliminate complex and time-consuming algorithms in solving DGP problems. Using the proposed method, one can easily and without complex calculations obtains the size and location of DG units on the network. The proposed method has been tested on several networks and the test results show its effectiveness. The benefit of the proposed method is its low computational burden as well as its simplicity of implementation.

Novel analytical method for the placement and sizing of distributed generation unit on distribution networks with and without considering P and PQV buses

Abstract This paper proposes a new analytical method for placement and sizing of distributed generation (DG) units for loss reduction. This analytical method for DG placement in the distribution network is developed based on a new mathematical formulation which does not require bus impedance matrix. This is the main advantage of the proposed method. This paper also proposes the placement and sizing of DG unit considering two novel bus types, i.e., P and PQV buses. The ‘ P ’ bus is represented by real power specification only whereas the ‘ PQV ’ bus is one whose voltage magnitude is remotely controlled by the ‘ P ’ bus. A simple method is suggested to select ‘ P ’ bus in a distribution network to control the voltage magnitude of ‘ PQV ’ bus. The effectiveness of the proposed method is demonstrated through examples of 33 bus and 69 bus distribution networks.

AN MINLP APPROACH FOR OPTIMAL DG UNIT'S ALLOCATION IN RADIAL/MESH DISTRIBUTION SYSTEMS TAKE INTO ACCOUNT VOLTAGE STABILITY INDEX

Application of distributed generation (DG) units in distribution networks has increased in recent years. Sizing and sitting of DG units are two important factors which should be considered, especially for reduction of power losses in distribution system. This paper presents a new approach for DG placement in distribution systems using the mixed integer nonlinear programming (MINLP). This approach determines the optimal number, sitting and sizing of DG units in both radial and meshed distribution networks with the objectives of reducing the power losses, as well as minimizing the investment and operation costs of DG units, and the monetary value of voltage stability index improvement. The performance of the proposed method is compared with the genetic algorithm (GA), particle swarm optimization (PSO), combined GA and PSO, and combined loss sensitivity factor and simulated annealing (LSFSA). Compared with the conventional methods, the proposed scheme can be applied in the meshed distribution networks as well. A 33-bus radial network and CIVANLAR meshed distribution system have been used for simulation studies. The obtained results approve the efficiency of proposed method for sitting and sizing of DG units in distribution networks.

Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation

Different types of distributed generation (DG) are broadly used and optimally placed in a distribution system to improve its performance. Since the network configuration affects the system operational conditions, the network reconfiguration and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent from achieving the optimal solution. This paper presents a novel hybrid method of metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs. The developed backward/forward power flow is adopted to consider the PV(Q) model of DG. Moreover, different patterns of load types are taken into consideration to perform a practical study. To assess the capabilities of the proposed method, simulations are carried out on IEEE 33-bus and 83-bus practical distribution network of Taiwan Power Company. Furthermore, the proposed method is applied to a 33-bus unbalanced distribution network to verify its applicability in unbalanced distribution systems. The obtained results demonstrate the effectiveness of the proposed method to find optimal status of switches, as well as locations and sizes of DG units, in a rather shorter time than other approaches in the literature.

Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks

This study presents an analytical approach for optimal siting and sizing of distributed generation (DG) in radial power distribution networks to minimise real and reactive power losses. For this purpose, suitable analytical expressions have been derived which are based on change in active and reactive components of branch currents cause by the DG placement. This method first determines the DG capacity causing maximum benefit at different buses, and then selects the bus as the best location for DG placement which corresponds to highest benefit. The proposed method is applicable for sizing and siting of single as well as multiple DG units. Moreover, the proposed method requires only the results of base case load flow to determine the optimal size of DG unit(s). The proposed method is tested on 33-bus and 69-bus radial distribution test systems. The results obtained by this proposed method validate the suitability and importance of proposed analytical method to determine the size and site of DG unit(s).

An elegant emergence of optimal siting and sizing of multiple distributed generators used for transmission congestion relief

After the implementation of deregulation in a power system, an appreciable volume of renewable energy sources is used to generate electric power. Even though they are intended to improve the reliability of the power system, the unpredictable outages of generators or transmission lines, an impulsive increase in demand, and failures of other equipment lead to congestion in one or more transmission lines. There are several ways to alleviate this transmission congestion, such as the installation of new generation facilities in the place where the demand is high, the addition of a new transmission facility, generation rescheduling, and curtailment of load demand processes. Among the above methods generation rescheduling and load shedding are normally preferred, since the other methods require additional investments. However, some critical cases require improved methods to alleviate congestion. With the extensive application of distributed generation (DG), congestion management is also accomplished by the optimal placement of multiple DG units. It is well known that incorrect sizes and improper locations of DG undoubtedly create higher power losses and an undesirable voltage profile. Hence, this research effort employs the line flow sensitivity index to establish the optimal location of DG units and genetic algorithm-based optimization for determining the optimal sizes of DG units. The objective of this research is to minimize the total losses and real power flow performance index and to improve the voltage shape of the modified IEEE 30-bus test system. The results of this proposed approach are encouraging and help in anticipating higher efficiency by satisfying all the objectives.

An analytical approach for sizing and siting of DGs in balanced radial distribution networks for loss minimization

This paper presents a novel analytical approach to determine the optimal siting and sizing of distributed generation (DG) units in balanced radial distribution network to minimize the power loss of the system. The proposed analytical expressions are based on a minimizing the loss associated with the active and reactive component of branch currents by placing the DG at various locations. This method first identifies a sequence of nodes where DG units are to be placed. The optimal sizes of DG units at the identified nodes are then evaluated by optimizing the loss saving equations and need only the results of base case load flow. To find out the best location for DG placement, a computational method is also developed. The proposed method has been tested and validated on two IEEE test distribution systems (DSs) consisting of 15 and 33-buses and it has been found that a significant loss saving can be obtained by placing DG units in the system using proposed analytical method.

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

Abstract 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

Abstract 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.