scholarly journals A Novel Analytical Approach for Optimal Placement and Sizing of Distributed Generations in Radial Electrical Energy Distribution Systems

2021 ◽  
Vol 13 (18) ◽  
pp. 10224
Author(s):  
Sasan Azad ◽  
Mohammad Mehdi Amiri ◽  
Morteza Nazari Heris ◽  
Ali Mosallanejad ◽  
Mohammad Taghi Ameli

Considering the strong influence of distributed generation (DG) in electric distribution systems and its impact on network voltage losses and stability, a new challenge has appeared for such systems. In this study, a novel analytical algorithm is proposed to distinguish the optimal location and size of DGs in radial distribution networks based on a new combined index (CI) to reduce active power losses and improve system voltage profiles. To obtain the CI, active power losses and voltage stability indexes were used in the proposed approach. The CI index with sensitivity analysis was effective in decreasing power losses and improving voltage stability. Optimal DG size was determined based on a search algorithm to reduce active power losses. The considered scheme was examined through IEEE 12-bus and 33-bus radial distribution test systems (RDTS), and the obtained results were compared and validated in comparison with other available methods. The results and analysis verified the effectiveness of the proposed algorithm in reducing power losses and improving the distribution system voltage profiles by determining the appropriate location and optimal DG size. In IEEE 12 and 33 bus networks, the minimum voltage increased from 0.9434 p.u and 0.9039 p.u to 0.9907 p.u and 0.9402 p.u, respectively. Additionally, the annual cost of energy losses decreased by 78.23% and 64.37%, respectively.

Author(s):  
Mahesh Kumar ◽  
Perumal Nallagownden ◽  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Luqman Hakim Rahman

In the distribution system, distributed generation (DG) are getting more important because of the electricity demands, fossil fuel depletion and environment concerns. The placement and sizing of DGs have greatly impact on the voltage stability and losses in the distribution network. In this chapter, a particle swarm optimization (PSO) algorithm has been proposed for optimal placement and sizing of DG to improve voltage stability index in the radial distribution system. The two i.e. active power and combination of active and reactive power types of DGs are proposed to realize the effect of DG integration. A specific analysis has been applied on IEEE 33 bus system radial distribution networks using MATLAB 2015a software.


2011 ◽  
Vol 62 (3) ◽  
pp. 163-167 ◽  
Author(s):  
Ali Elmaouhab ◽  
Mohamed Boudour ◽  
Rabah Gueddouche

New Evolutionary Technique for Optimization Shunt Capacitors in Distribution NetworksThe paper presents a new evolutionary technique for optimizing on one part the numbers, the sizes and locations of shunt capacitors in radial distribution network in away to minimize the annual cost of active power losses with the improvement of voltage profiles of different buses. The technique is applied on 10 buses network and on IEEE 34 buses network test. The results are compared with ones of previous studies using heuristiques methods and the same network tests.


Author(s):  
Diego Issicaba ◽  
Jorge Coelho

This paper introduces a modified edition of classical Cespedes' load flow method to radial distribution system analysis. In the developed approach, a distribution network is modeled in different complex reference systems and reduced to a set of connected equivalent subnetworks, each without resistance, while graph topology and node voltage solution are preserved. Active power losses are then not dissipated in the modeled subnetworks and active power flows can be obtained as a consequence of radiality. Thus, the proposed method preprocesses a series of variable transformations concomitant to an iterative algorithm using a forward-backward sweep to arrive at the load flow solution. The proposed approach has been tested using literature and actual distribution networks, and efficiency improvements are verified in comparison to Cespedes' load flow method.


Author(s):  
Diego Issicaba ◽  
Jorge Coelho

This paper introduces a modified edition of classical Cespedes' load flow method to radial distribution system analysis. In the developed approach, a distribution network is modeled in different complex reference systems and reduced to a set of connected equivalent subnetworks, each without resistance, while graph topology and node voltage solution are preserved. Active power losses are then not dissipated in the modeled subnetworks and active power flows can be obtained as a consequence of radiality. Thus, the proposed method preprocesses a series of variable transformations concomitant to an iterative algorithm using a forward-backward sweep to arrive at the load flow solution. The proposed approach has been tested using literature and actual distribution networks, and efficiency improvements are verified in comparison to Cespedes' load flow method.


2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Khalid Mohammed Saffer Alzaidi ◽  
Oguz Bayat ◽  
Osman N. Uçan

Distributed generators (DGs) are currently extensively used to reduce power losses and voltage deviations in distribution networks. The optimal location and size of DGs achieve the best results. This study presents a novel hybridization of new metaheuristic optimizations in the last two years, namely, salp swarm algorithm (SSA) and whale optimization algorithm (WOA), for optimal placement and size of multi-DG units in radial distribution systems to minimize total real power losses (kW) and solve voltage deviation. This hybrid algorithm is implemented on IEEE 13- and 123-node radial distribution test systems. The OpenDSS engine is used to solve the power flow to find the power system parameters, such power losses, and the voltage profile through the MATLAB coding interface. Results describe the effectiveness of the proposed hybrid WOA-SSA algorithm compared with those of the IEEE standard case (without DG), repeated load flow method, and WOA and SSA algorithms applied independently. The analysis results via the proposed algorithm are more effective for reducing total active power losses and enhancing the voltage profile for various distribution networks and multi-DG units.


2017 ◽  
Vol 2 (1) ◽  
pp. 6
Author(s):  
Souhaib Remha

In this paper, a novel optimization algorithm is presented for optimal location and sizing of Distributed Generation (DG) units on distribution systems. For this purpose, a recently based meta-heuristic called Firefly Algorithm (FA) has been employed to minimize the total active power losses. The results show a considerable improved in voltage profiles of all the buses and enhance the voltage stability index. The investigations were tested on IEEE 33 bus radial distribution system. Simulation results demonstrate the effectiveness of firefly algorithm. Comparison with another method is also given.


Author(s):  
Hazim Sadeq Mohsin Al-Wazni ◽  
Shatha Suhbat Abdulla Al-Kubragyi

This paper presents a hybrid algorithm by applying a hybrid firefly and particle swarm optimization algorithm (HFPSO) to determine the optimal sizing of distributed generation (DG) and distribution static compensator (D-STATCOM) device. A multi-objective function is employed to enhance the voltage stability, voltage profile, and minimize the total power loss of the radial distribution system (RDS). Firstly, the voltage stability index (VSI) is applied to locate the optimal location of DG and D-STATCOM respectively. Secondly, to overcome the sup-optimal operation of existing algorithms, the HFPSO algorithm is utilized to determine the optimal size of both DG and D-STATCOM. Verification of the proposed algorithm has achieved on the standard IEEE 33-bus and Iraqi 65-bus radial distribution systems through simulation using MATLAB. Comprehensive simulation results of four different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms in supporting voltage stability and loss reduction in distribution networks. Furthermore, comparisons have achieved to demonstrate the superiority of HFPSO algorithms over other techniques due to its ability to determine the global optimum solution by easy way and speed converge feature.


Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.


DYNA ◽  
2015 ◽  
Vol 82 (192) ◽  
pp. 60-67 ◽  
Author(s):  
John Edwin Candelo-Becerra ◽  
Helman Hernández-Riaño

<p>Distributed generation (DG) is an important issue for distribution networks due to the improvement in power losses, but the location and size of generators could be a difficult task for exact techniques. The metaheuristic techniques have become a better option to determine good solutions and in this paper the application of a bat-inspired algorithm (BA) to a problem of location and size of distributed generation in radial distribution systems is presented. A comparison between particle swarm optimization (PSO) and BA was made in the 33-node and 69-node test feeders, using as scenarios the change in active and reactive power, and the number of generators. PSO and BA found good results for small number and capacities of generators, but BA obtained better results for difficult problems and converged faster for all scenarios. The maximum active power injections to reduce power losses in the distribution networks were found for the five scenarios.</p>


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