Techno-economic Analysis of Optimal Distributed Generators Placement for Distribution Network Performance Enhancement

This paper proposes a novel adaptive optimization algorithm to solve the network reconfiguration and distributed generation (DG) placement problems with objective functions including power loss minimization and voltage stability index (VSI) improvement. The proposed technique called Adaptive Shuffled Frogs Leaping Algorithm (ASFLA) was performed for solving network reconfiguration and DG installation in IEEE 33- and 69-bus distribution systems with seven different scenarios. The performance of ASFLA was compared to that of other algorithms such as Fireworks Algorithm (FWA), Adaptive Cuckoo Search Algorithm (ACSA) and Shuffled Frogs Leaping Algorithm (SFLA). It was found that the power loss and VSI provided by ASFLA were better than those given by FWA, ACSA and SFLA in both 33- and 69-bus systems. The best solution of power loss reduction and VSI improvement of both 33- and 69-bus systems was achieved when the network reconfiguration with optimal sizing and the location DG were simultaneously implemented. From our analysis, it was indicated that the ASFLA could provide better solutions than other methods since the generating process, local and global searching of this algorithm were significantly improved from a conventional method. Hence, the ASFLA becomes another effective algorithm for solving network reconfiguration and DG placement problems in electrical distribution systems.

The recent trends in electrical power distribution system operation and management are aimed at improving system conditions in order to render good service to the customer. Reforms in the distribution sector have given major scope for employment of distributed generation (DG) resources which will boost system performance. This article proposes a heuristic technique for allocation of multiple distribution generation sources in a distribution system. The allocation is determined based on overall improvement in network performance parameters like reduction in system losses, improvement in voltage stability, improvement in voltage profile. The hybrid of Genetic Algorithm with the proposed Network Performance Enhancement Index (NPEI) along with the heuristic rules facilitates determination of feasible location for insertion of DG sources. A priority list is prepared with decreasing values of NPEI so that the designer can select most feasible locations. The developed approach is tested with different t...

Voltage stability is an important issue in power system operation. Flexible AC transmission systems, so-called FACTS devices, help to improve voltage stability and minimize real power losses. The effectiveness of FACTS devices depend on their proper location and rating. This paper presents a method, based on line flow sensitivity factors such as bus voltage stability index and line voltage stability index, to find suitable locations of multi-type FACTS devices. Also this paper proposes an application of particle swarm optimization (PSO) and harmony search algorithm (HSA) in optimizing the rating of FACTS devices. The proposed approaches are evaluated with three different objective functions namely, minimization of real power loss, improvement of voltage profile and enhancement of voltage stability. The performance of proposed methods is analyzed on IEEE 14 bus system by implementing FACTS devices such as static var compensator (SVC), thyristor controlled series capacitor (TCSC) and unified power flow controller (UPFC).The analysis shows that there is a reduction in real power loss and improvement in voltage stability and voltage profile of the system after employing FACTS devices. It also shows that both real power loss and bus voltage stability index (BVSI) have been reduced more with FACTS ratings obtained from PSO than with that from HSA.

Objectives: The main objective of the proposed investigation is to enhance the voltage stability of Radial Distribution System (RDS). It is achieved by proper allocation between combined Electric Vehicle Charging Stations (EVCSs) and Distributed Generators (DGs) in RDS. Here, three objective functions such as Real Power loss, Average Voltage Devotion Index (AVDI) and Voltage Stability Index (VSI) are considered. Methods: The multi-objective optimization problem is implemented using a novel and an effective Pelican Optimization Algorithm (POA) to attain the best compromised solutions. POA is a nature inspired parameter less optimization tool and it is well suited for solution of complex, non-linear voltage stability problem. It determines the most excellent site and size of the EVCSs and DG units. The control parameter of POA considered are population size as 40, the number of variables as 8 and the maximum number of iterations as 100. MATLAB 14.0 platform is utilized for the projected problem. Findings: The bench mark test system of IEEE-33 node system is considered to authenticate the presentation of planned POA methodology. The outcomes such as minimized power loss and AVDI, improved voltage at each bus and VSI are presented. The percentage of loss reduction 39.30% is enhanced, when compared with the base case approach and 5.42 % more improved than the other existing methods like TLBO and HHO approaches. Similarly, the VSI 24.96 % is improved, when compared with the base case method and 1.58 % better than the other obtainable methods. Novelty: The POA is a newly urbanized and well-designed optimization algorithm. It efficiently reaches the global optimal solutions with less time duration. The comparative study with the existing algorithm of TLBO and HHO is considered to prove the performance of Projected POA approach. Keywords: Radial distribution system, Distributed Generators, Electric Vehicles, Charging Stations, Voltage stability, Network loss reduction, Pelican Optimization Algorithm

A novel method to solve the problem of reconfiguration and distributed generation (DG) planning in distribution systems is proposed in this paper. By a multistage hieratical optimization problem, this problem has been modeled as a nonlinear and multi-objective optimization problem based on to improve power system voltage stability margin, investment cost, and reduce losses. As the first stage, the ability of developed harmony search is used to reach the best network configuration and DGs location under variable load patterns. This reconfiguration algorithm starts with a radial topology by a theoretical approach based on the Graph concept and Matroid theory. The presented approach is useful to avoid tedious mesh checks for the topology constraint validation. In the second stage of proposed approach, the voltage stability index is calculated to evaluate static voltage stability security margin. This calculation is done for each time variable reconfiguration pattern with defined DGs planning based on a developed toolbox which evaluate the loadability limit and other terms of task function. Finally, the simulations are carried out on 69 and 119 bus IEEE distribution systems and have been compared with particle swarm optimization. The results show good enhancement to reach the optimum solution with respect to the other studies.

The identification of voltage collapse (VC) is crucial to prevent a possible collapse of the preventive control actions and voltage security evaluation. Selecting the critical buses in the network can assist in determining the locations where voltage collapses may occur. VC initially manifests at the weakest bus in a serious emergency case. So, for operational and planning purposes, it is essential to detect critical buses in an electric power system. The analysis of the power system in view of voltage stability (VS) was performed under different loading conditions using voltage stability indices (VSIs). The line voltage stability indices in terms of the fast voltage stability index (FVSI) and line stability index (LMN) are utilized in this paper to identify the weakest bus in the network. The suggested procedure is tested on a standard network (IEEE 14-bus system) at different overloading conditions (25 – 100 % overload) utilizing power system analysis toolbox (PSAT) software. The results proved that this index has a higher standard for predicting the point of voltage collapse and identification the weakest bus in the network, so consider more reliable and accurate relative to other indices.

The necessity of Distributed Generation (DG) in the modern power system has increased greatly. Optimal placement and sizing of DGs have a significant impact on the objectives of voltage stability enhancement, real and reactive power loss minimization and power system security and reliability. Different types of DGs such as Type I, Type II, Type III and Type IVare placed. The optimal placement of these DGs is found using Voltage Stability Index (VSI). The optimal sizing of these DGs is done using Differential Evolution (DE) algorithm. MATLAB simulation is carried out in standard IEEE 33-bus test system. The test is performed for various combinations of different types of DG. The results show that the voltage stability index along with Differential Evolution algorithm provides better voltage profile and power loss minimization as compared to the system without DG.

Proliferation of electric demand and congestion in the existing network intensify challenges and problems for researchers and power system planners. Currently, these problems are mostly solved by Distributed Generation (DG). DG is placed near the customer end to meet the load demand economically, hence reducing the existing network burden. This paper attempts to present an overview of technological development carried out in the DG field. Numerous technical constraints must be considered while integrating DG in the system. The improvement in voltage stability, voltage profile, and reduction in power losses are the main benefits posed by DG integration. This paper also highlights the key issues associated with the DG allocation problem, types of DG, and methodologies for optimal DG units allocation.

In present days, power systems are more complex and highly stressed due to rise in population, and it requires more electrical demands. Presently, the distribution losses in India are approximately 25–30%. In recent days, distributed generation (DG) units are attracting the utility and consumers to use it largely in distribution system, to get more benefit from this like reduced power losses, increased reliability and maintain voltage stability. To get more benefits from DGs, it is necessary to find out its proper size and position. In this paper, a new analytical method is used to calculate the loss sensitivity factor at the buses, which is used to find best size and location of DG to increase the performance of distribution system. The mainly used DG units are PV unit and shunt capacitor for analysis of proposed method in one of the practical feeders with 41-bus emanating from 110/11 kV Alkola substation in Shivamogga, Karnataka, India. The loss sensitivity factor method is used to find optimal position and size of DG in the practical system. Power World Simulator (PWS) software is used to model the practical feeder, and simulated results are analysed for voltage magnitude and system losses. The result indicates that optimal position and size of DG will recover the voltage profile in the system within the suitable limits, and system losses are reduced.

Optimal Allocation of Combined DG and Capacitor Units for Voltage Stability Enhancement

From few decades, the growth in electricity demand and increase in nonlinear loads increase the requirement of high Voltage stability for electrical power system. The voltage of the power system can be monitored and controlled continuously using voltage stability indices. In this paper firstly contingencies are ranked based on their voltage stability margin, then line stability index (Lmn), fast voltage stability index (FVSI) as well as line stability factor (Lqp) methods are employed to find the most critical line of the IEEE 14-bus system. These three voltage stability indices have been analyzed under top five different contingencies to detect the most critical bus of the system. Static Synchronous Series compensator (SSSC) has placed in top five critical lines and voltage stability indices are observed for optimal location of SSSC.

The issues regarding generation uncertainties associated with wind energy and solar photovoltaic (PV) systems along with load demand uncertainties are considered in this paper to evaluate the maximum penetration of renewable energy resources. The nodes which are less voltage stable are considered as the most suitable locations for distributed generations (DGs) placement. For identification of these critical nodes, a voltage stability index (VSI) has been utilized. To analyze the voltage profile, power losses and system voltage stability with large penetration of the wind energy and solar PV into the distribution networks, a probabilistic-based approach has been adopted. The penetration limit depends upon the type of DG that is connected to the distribution network. Usually, the integration of DGs reduces the power losses in the network, however as penetration level increases, the power losses begins to increase. The detailed mathematical models of wind and solar PV-based renewable resources are used. The Hong’s $$2m+1$$ point estimation method combined with Cornish–Fisher expansion is adopted in this paper to conduct the probabilistic studies. The effectiveness of the method is validated through IEEE 33-node radial distribution test network for four different scenarios. The results obtained have been verified and compared with Monte Carlo simulation technique.

Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. FACTS have made the power systems operation more flexible and secure. Amongst the several FACTS controllers, the Unified Power Flow Controller (UPFC) is most effective to improve the enhancement of voltage stability and reduces the power loss. This study investigates the application of Particle Swarm Optimization (PSO) to find sizing of Unified Power Flow Controller (UPFC) device to minimize the voltage stability index, total power loss, load voltage deviation, and cost of FACTS devices to improve voltage stability in the power system. A new model is proposed in this thesis to improve existing power-based model by using the Norton Equivalent Theorem. The proposed model can be integrated with the Equivalent Current Injection (ECI) power flow model easily. By ECI algorithm, it is much quickly and precisely to implement power flow calculations. Finally It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased and real power losses also reduced by optimally sizing UPFC device in the power system. Index Terms: Voltage stability, Unified Power Flow Controller (UPFC), Equivalent -Current Injection (ECI), Modified particle swarm optimization (MPSO)

This study presents the optimal allocation of distributed generators (DGs) in distribution network based on an adaptive multi-objective particle swarm optimization (AMPSO). In order to enable the DGs to make the best contribution to the distribution network, a multi-objective optimization model addressing power loss and a voltage stability index (VSI) is constructed, in which the capacity factor of DGs is taken into consideration. In the AMPSO, some adaptive techniques including the use of dynamically changing inertia weight, time-varying acceleration coefficients, mutation operation and circular crowding sorting have been integrated to improve the convergence and the diversity performance of the algorithm. The proposed algorithm has been used to determine the optimal allocation of DGs in a IEEE 33-bus distribution network. Simulation results show that the proposed method can identify the optimal solutions with a good tradeoff between the power loss and the VSI.

With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique.