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

2019 ◽  
Author(s):  
Ibrahim M. Diaaeldin ◽  
Shady H. E. Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Y. Abdelaziz ◽  
Ahmed F. Zobaa
Keyword(s):  
Distribution Systems ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Total Power ◽  
Network Reconfiguration ◽  
Distributed Generators ◽  
Optimal Network ◽  
Balanced Distribution ◽  
Network Losses

In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. 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. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.

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 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 Loss allocation in distribution networks with distributed generators undergoing network reconfiguration

2020 ◽  
Vol 10 (4) ◽  
pp. 3375
Author(s):  
Ambika Prasad Hota ◽  
Sivkumar Mishra
Keyword(s):  
Distribution System ◽  
Search Time ◽  
Distribution Networks ◽  
Load Flow ◽  
Network Reconfiguration ◽  
Radial Distribution System ◽  
Loss Allocation ◽  
Distributed Generators ◽  
System A ◽  
Optimal Network

In this paper, a branch exchange based heuristic network reconfiguration method is proposed for obtaining an optimal network in a deregulated power system. A unique bus identification scheme is employed which makes the load flow and loss calculation faster due to its reduced search time under varying network topological environment. The proposed power loss allocation technique eliminates the effect of cross-term analytically from the loss formulation without any assumptions and approximations. The effectiveness of the proposed reconfiguration and loss allocation methods are investigated by comparing the results obtained by the present approach with that of the existing “Quadratic method” using a 33-bus radial distribution system with/without DGs.

scholarly journals A Nondominated Sorting Stochastic Fractal Search Algorithm for Multiobjective Distribution Network Reconfiguration with Distributed Generations

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Tung Tran The ◽  
Bao-Huy Truong ◽  
Khanh Dang Tuan ◽  
Dieu Vo Ngoc
Keyword(s):  
Search Algorithm ◽  
Stability Index ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Solution Quality ◽  
Optimal Network ◽  
Benchmark Test Functions ◽  
Nondominated Sorting ◽  
Stochastic Fractal Search

This paper aims to propose a new multiobjective algorithm for multiobjective distributed network reconfiguration (DNR) with the placements of distributed generation (DG) in radial distribution networks (RDNs). The new proposed algorithm, called the nondominated sorting stochastic fractal search (NSSFS), is a new multiobjective version of the original SFS algorithm. NSSFS incorporated fast nondominated sorting strategies, crowding distance computation, and selection mechanism into SFS to find and maintain the best nondominated solutions. The proposed NSSFS algorithm was tested with eight multiobjective benchmark test functions to validate its performance. The NSSFS was then implemented to define the optimal network configuration, positions, and sizes of DG units in the RDNs, where real power loss, voltage profile, and voltage stability index were optimized simultaneously. The implementation of multiobjective DNR-DG (MODNR-DG) significantly enhanced the performance of the system. Based on the comparison outcomes, the NSSFS algorithm obtained better solution quality than other multiobjective techniques, proving the effectiveness of NSSFS in dealing with the MODNR-DG problem.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

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