scholarly journals Symbiotic Organism Search Algorithm for Power Loss Minimization in Radial Distribution Systems by Network Reconfiguration and Distributed Generation Placement

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Tung Tran The ◽  
Sy Nguyen Quoc ◽  
Dieu Vo Ngoc
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Power Loss ◽  
Distribution Systems ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Symbiotic Organism Search

This paper proposes the Symbiotic Organism Search (SOS) algorithm to find the optimal network configuration and the placement of distributed generation (DG) units that minimize the real power loss in radial distribution networks. The proposed algorithm simulates symbiotic relationships such as mutualism, commensalism, and parasitism for solving the optimization problems. In the optimization process, the reconfiguration problem produces a large number of infeasible network configurations. To reduce these infeasible individuals and ensure the radial topology of the network, the graph theory was applied during the power flow. The implementation of the proposed SOS algorithm was carried out on 33-bus, 69-bus, 84-bus, and 119-bus distribution networks considering seven different scenarios. Simulation results and performance comparison with other optimization methods showed that the SOS-based approach was very effective in solving the network reconfiguration and DG placement problems, especially for complex and large-scale distribution networks.

scholarly journals Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4172 ◽  
Author(s):  
Ibrahim Diaaeldin ◽  
Shady Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Abdelaziz ◽  
Ahmed F. Zobaa
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Network Reconfiguration ◽  
Efficient Manner ◽  
Optimal Network ◽  
Network Losses

In this study, we allocated soft open points (SOPs) and distributed generation (DG) units simultaneously with and without network reconfiguration (NR), and investigate the contribution of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to distribution systems under different loading conditions. A recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of SOPs and DGs allocation, along with new NR methodology to obtain radial configurations in an efficient manner without the possibility of getting trapped in local minima. Further, multi-scenario studies are conducted on an IEEE 33-node balanced benchmark distribution system and an 83-node balanced distribution system from a power company in Taiwan. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. It was clear from the results obtained that simultaneous NR, SOP, and DG allocation into a distribution system creates a hybrid configuration that merges the benefits offered by radial distribution systems and mitigates drawbacks related to losses, power quality, and voltage violations, while offering a far more efficient and optimal network operation. Also, it was found that the contribution of the internal loss of SOPs to the total loss for different numbers of installed SOPs is not dependent on the number of SOPs and that loss minimization is not always guaranteed by installing more SOPs or DGs along with NR. One of the findings of the paper demonstrates that NR with optimizing tie-lines could reduce active losses considerably. The results obtained also validate, with proper justifications, that SOPs installed for the management of constraints in LV feeders could further reduce losses and efficiently address issues related to voltage violations and network losses.

scholarly journals Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm

DYNA ◽  
2015 ◽  
Vol 82 (192) ◽  
pp. 60-67 ◽  
Author(s):  
John Edwin Candelo-Becerra ◽  
Helman Hernández-Riaño
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Distribution Networks ◽  
Power Losses ◽  
Number Of Generators ◽  
Metaheuristic Techniques ◽  
Distributed Generation Placement ◽  
Made In

<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>

Distributed Generation Placement for Power Distribution Networks

2014 ◽  
Vol 24 (01) ◽  
pp. 1550009 ◽  
Author(s):  
Xiaodao Chen ◽  
Shiyan Hu
Keyword(s):  
Smart Grid ◽  
Distributed Generation ◽  
Power Distribution ◽  
Power Loss ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Electrical Power ◽  
Distribution Networks ◽  
Ocean Energy ◽  
Electrical Power System

Growing concerns on the energy crisis impose great challenges in development and deployment of the smart grid technologies into the existing electrical power system. A key enabling technology in smart grid is distributed generation, which refers to the technology that power generating sources are located in a highly distributed fashion and each customer is both a consumer and a producer for energy. An important optimization problem in distributed generation design is the insertion of distributed generators (DGs), which are often renewable resources exploiting e.g., photovoltaic, hydro, wind, ocean energy. In this paper, a new power loss filtering based sensitivity guided cross entropy (CE) algorithm is proposed for the distributed generator insertion problem. This algorithm is based on the advanced CE optimization technique which exploits the idea of importance sampling in performing optimization. Our experimental results demonstrate that on large distribution networks, our algorithm can largely reduce (up to 179.3%) power loss comparing to a state-of-the-art sensitivity guided greedy algorithm with small runtime overhead. In addition, our algorithm runs about 5× faster than the classical CE algorithm due to the integration of power loss filtering and sensitivity optimization. Moreover, all existing techniques only test on very small distribution systems (usually with < 50 nodes) while our experiments are performed on the distribution networks with up to 5000 nodes, which matches the realistic setup. These demonstrate the practicality of the proposed algorithm.

ON OPTIMAL DESIGN AND EXPANSION OF ELECTRICAL POWER DISTRIBUTION SYSTEMS

2010 ◽  
Vol 19 (01) ◽  
pp. 45-58 ◽  
Author(s):  
SAJAD NAJAFI RAVADANEGH ◽  
ARASH VAHIDNIA ◽  
HOJAT HATAMI
Keyword(s):  
Optimal Design ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Optimization Problems ◽  
Distribution Networks ◽  
Coding Method ◽  
Real Size

Optimal planning of large-scale distribution networks is a multiobjective combinatorial optimization problem with many complexities. This paper proposes the application of improved genetic algorithm (GA) for the optimal design of large-scale distribution systems in order to provide optimal sizing and locating of the high voltage (HV) substations and medium voltage (MV) feeders routing, using their corresponding fixed and variable costs associated with operational and optimization constraints. The novel approach presented in the paper, solves hard satisfactory optimization problems with different constraints in large-scale distribution networks. This paper presents a new concept based on MST in graph theory and GA for optimal locating of the HV substations and MV feeders routing in a real-size distribution network. Minimum spanning tree solved with Prim's algorithm is employed to generate a set of feasible population. In the present article, to reduce computational burden and avoid huge search space leading to infeasible solutions, special coding method is generated for GA operators to solve optimal feeders routing. The proposed coding method guarantees the validity of the solution during the progress of the GA toward the global optimal solution. The developed GA-based software is tested in a real-size large-scale distribution system and the well-satisfactory results are presented.

scholarly journals Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping Algorithm

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 553 ◽  
Author(s):  
Arun Onlam ◽  
Daranpob Yodphet ◽  
Rongrit Chatthaworn ◽  
Chayada Surawanitkun ◽  
Apirat Siritaratiwat ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Network Reconfiguration ◽  
Loss Minimization ◽  
Power Loss Minimization ◽  
Electrical Distribution ◽  
Power Loss Reduction

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.

scholarly journals Placement of Distributed Generation and Shunt Capacitor in Distribution Network using Cuckoo Search Algorithm

2020 ◽  
Vol 17 (2) ◽  
pp. 79-87
Author(s):  
Moses Uchendu
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Voltage Stability ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Distribution Networks ◽  
Cuckoo Search Algorithm ◽  
Capacitor Placement ◽  
Shunt Capacitor ◽  
Bus System

This work aims at reduction in active and reactive power loss reduction in distribution networks as well as to improve the voltage stability of the networks. Optimum Distributed Generation (DG) placement and sizing is carried out in conjunction with shunt capacitor placement and sizing to determine the appropriate sizes of DG units and Capacitor banks to be placed in the networks so as not to violate certain constraints. The optimal sizes of the DG units and capacitor banks were obtained on application of a Cuckoo Search Optimization Algorithm while computations for Voltage stability was performed using the Voltage Stability Index (VSI). The obtained optimal sizes of DG units and Capacitors were individually and simultaneously placed on the distribution networks to ascertain the behaviour of the networks prior to and after their placements. The performance factors considered are power loss and voltage stability. A comparison of these performance factors under separate and simultaneous placement method was demonstrated using IEEE 33 and 69 test buses. Result show that power loss (active and reactive) reduced by 63.29% and 59.38% respectively for 33 bus system, with a 74.29% and 79.19% reduction on 69 bus system. Voltage stability also increased by 7.89% and 3.79% respectively for 33 and 69 bus system relative to values obtained for base case and separate DG and shunt capacitor placement. Keywords: Distributed generation, shunt capacitor, Cuckoo Search Algorithm (CSA), power loss and voltage stability.

scholarly journals Power Loss Reduction using Instantaneous Network Reconfiguration and DG Placement with Cuckoo Search Algorithm in Distribution System

2020 ◽  
Vol 8 (6) ◽  
pp. 2393-2398
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Network Reconfiguration ◽  
Radial Distribution System ◽  
Distributed Generator ◽  
Power Loss Reduction

The aim of reducing power loss, enhancing profile of voltage in a radial distribution system at which consumers are connected and also determining the ratings of power, optimal placement of Distributed generator. In this paper to resolve the drop in voltage profile by using network reconfiguration that gives possible switching possibilities with an efficient Cuckoo Search Algorithm (CSA) is discussed and Sensitivity analysis are carried out simultaneously for finding sizing and possible location of distributed generation. To confirm the usefulness of the discussed method it was conducted on radial distribution system of 33 bus connected by various load levels, the result shows that the discussed method is fast and efficient. However to meet power requirement and lack of transmission capabilities importance for DG is rapidly evolving in electrical systems. For reliability and stability for the power system best possible location of Distributed Generator is needed in distribution system. To overcome the shortcomings of mathematical optimization practices, soft computing algorithms have been actively introduced during the last decade.

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