On the Transient Behavior of Large-Scale Distribution Networks During Automatic Feeder Reconfiguration

2012 ◽  
Vol 3 (2) ◽  
pp. 887-896 ◽  
Author(s):  
V. Spitsa ◽  
X. Ran ◽  
R. Salcedo ◽  
J. F. Martinez ◽  
R. E. Uosef ◽  
...  
Keyword(s):  
Large Scale ◽  
Transient Behavior ◽  
Distribution Networks ◽  
Automatic Feeder

Minimizing area of VLSI power distribution networks using river formation dynamics

2018 ◽  
Vol 20 (4) ◽  
pp. 417-429 ◽  
Author(s):  
Satyabrata Dash ◽  
Sukanta Dey ◽  
Deepak Joshi ◽  
Gaurav Trivedi
Keyword(s):  
Power Distribution ◽  
Large Scale ◽  
Distribution Network ◽  
Distribution Networks ◽  
Power Distribution Networks ◽  
Power Distribution Network ◽  
Content Type ◽  
Ir Drop ◽  
Formation Dynamics ◽  
River Formation Dynamics

Purpose The purpose of this paper is to demonstrate the application of river formation dynamics to size the widths of power distribution network for very large-scale integration designs so that the wire area required by power rails is minimized. The area minimization problem is transformed into a single objective optimization problem subject to various design constraints, such as IR drop and electromigration constraints. Design/methodology/approach The minimization process is carried out using river formation dynamics heuristic. The random probabilistic search strategy of river formation dynamics heuristic is used to advance through stringent design requirements to minimize the wire area of an over-designed power distribution network. Findings A number of experiments are performed on several power distribution benchmarks to demonstrate the effectiveness of river formation dynamics heuristic. It is observed that the river formation dynamics heuristic outperforms other standard optimization techniques in most cases, and a power distribution network having 16 million nodes is successfully designed for optimal wire area using river formation dynamics. Originality/value Although many research works are presented in the literature to minimize wire area of power distribution network, these research works convey little idea on optimizing very large-scale power distribution networks (i.e. networks having more than four million nodes) using an automated environment. The originality in this research is the illustration of an automated environment equipped with an efficient optimization technique based on random probabilistic movement of water drops in solving very large-scale power distribution networks without sacrificing accuracy and additional computational cost. Based on the computation of river formation dynamics, the knowledge of minimum area bounded by optimum IR drop value can be of significant advantage in reduction of routable space and in system performance improvement.

scholarly journals Distributed Generation Effects on Large-Scale Distribution Networks

Engineering ◽  
2014 ◽  
Vol 06 (01) ◽  
pp. 34-41
Author(s):  
Anastasia S. Safigianni ◽  
George N. Koutroumpezis ◽  
Anastasios I. Spyridopoulos
Keyword(s):  
Distributed Generation ◽  
Large Scale ◽  
Distribution Networks

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.

Large-scale integration of distributed generation in reconfigured distribution networks considering load uncertainty

2021 ◽  
pp. 441-484
Author(s):  
Ibrahim Mohamed Diaaeldin ◽  
Shady H.E. Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Y. Abdelaziz ◽  
Ahmed F. Zobaa
Keyword(s):  
Distributed Generation ◽  
Large Scale ◽  
Distribution Networks ◽  
Load Uncertainty ◽  
Large Scale Integration ◽  
Scale Integration

scholarly journals On the Sensitivity of Local Flexibility Markets to Forecast Error: A Bi-Level Optimization Approach

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1959
Author(s):  
Delaram Azari ◽  
Shahab Shariat Torbaghan ◽  
Hans Cappon ◽  
Karel J. Keesman ◽  
Madeleine Gibescu ◽  
...  
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Optimization Problem ◽  
Distribution Networks ◽  
Second Order ◽  
Optimization Approach ◽  
Second Order Cone ◽  
Local Flexibility ◽  
Level Problem ◽  
Relaxation Error

The large-scale integration of intermittent distributed energy resources has led to increased uncertainty in the planning and operation of distribution networks. The optimal flexibility dispatch is a recently introduced, power flow-based method that a distribution system operator can use to effectively determine the amount of flexibility it needs to procure from the controllable resources available on the demand side. However, the drawback of this method is that the optimal flexibility dispatch is inexact due to the relaxation error inherent in the second-order cone formulation. In this paper we propose a novel bi-level optimization problem, where the upper level problem seeks to minimize the relaxation error and the lower level solves the earlier introduced convex second-order cone optimal flexibility dispatch (SOC-OFD) problem. To make the problem tractable, we introduce an innovative reformulation to recast the bi-level problem as a non-linear, single level optimization problem which results in no loss of accuracy. We subsequently investigate the sensitivity of the optimal flexibility schedules and the locational flexibility prices with respect to uncertainty in load forecast and flexibility ranges of the demand response providers which are input parameters to the problem. The sensitivity analysis is performed based on the perturbed Karush–Kuhn–Tucker (KKT) conditions. We investigate the feasibility and scalability of the proposed method in three case studies of standardized 9-bus, 30-bus, and 300-bus test systems. Simulation results in terms of local flexibility prices are interpreted in economic terms and show the effectiveness of the proposed approach.

Sign in / Sign up

Export Citation Format

Share Document