Multi-objective optimization with post-pareto optimality analysis for the integration of storage systems with reactive-power compensation in distribution networks

2019 ◽  
Vol 24 ◽  
pp. 100769 ◽  
Author(s):  
V. Fernão Pires ◽  
A. Vieira Pombo ◽  
João Miguel Lourenço
Keyword(s):  
Pareto Optimality ◽  
Reactive Power ◽  
Storage Systems ◽  
Distribution Networks ◽  
Reactive Power Compensation ◽  
Multi Objective Optimization ◽  
Multi Objective

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

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.

A multi-objective evolutionary algorithm for reactive power compensation in distribution networks

2009 ◽  
Vol 86 (7-8) ◽  
pp. 977-984 ◽  
Author(s):  
Carlos Henggeler Antunes ◽  
Dulce Fernão Pires ◽  
Carlos Barrico ◽  
Álvaro Gomes ◽  
António Gomes Martins
Keyword(s):  
Evolutionary Algorithm ◽  
Reactive Power ◽  
Distribution Networks ◽  
Reactive Power Compensation ◽  
Multi Objective

scholarly journals Cooperative Multi-Objective Optimization of DC Multi-Microgrid Systems in Distribution Networks

2021 ◽  
Vol 11 (19) ◽  
pp. 8916
Author(s):  
Zhiwen Xu ◽  
Changsong Chen ◽  
Mingyang Dong ◽  
Jingyue Zhang ◽  
Dongtong Han ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Operating Cost ◽  
Distribution Networks ◽  
Double Loop ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Ac Converters

By constructing a DC multi-microgrid system (MMGS) including renewable energy sources (RESs) and electric vehicles (EVs) to coordinate with the distribution network, the utilization rate of RESs can be effectively improved and carbon emissions can be reduced. To improve the economy of MMGS and reduce the network loss of the distribution network, a cooperative double-loop optimization strategy is proposed. The inner-loop economic dispatching reduces the daily operating cost of MMGS by optimizing the active power output of RESs, EVs, and DC/AC converters in MMGS. The outer-loop reactive power optimization reduces the network loss of the distribution network by optimizing the reactive power of the bidirectional DC/AC converters. The double-loop, which synergistically optimizes the economic cost and carbon emissions of MMGS, not only improves the economy of MMGS and operational effectiveness of the distribution network but also realizes the low-carbon emissions. The Across-time-and-space energy transmission (ATSET) of the EVs is considered, whose impact on economic dispatching is analyzed. Particle Swarm Optimization (PSO) is applied to iterative solutions. Finally, the rationality and feasibility of the cooperative multi-objective optimization model are proved by a revised IEEE 33-node system.

scholarly journals Efficient Reactive Power Compensation Algorithm for Distribution Network

2017 ◽  
Vol 20 (3&4) ◽  
pp. 373-384
Author(s):  
J. Jerome
Keyword(s):  
Reactive Power ◽  
Supply Voltage ◽  
Distribution Networks ◽  
Reactive Power Compensation ◽  
Load Flow ◽  
Solution Technique ◽  
Distribution Automation ◽  
Automation System ◽  
Voltage Deviation ◽  
Propagation Technique

The use of automation and energy efficient equipment with electronic control would greatly improve industrial production.  These new devices are more sensitive to supply voltage deviation and the characteristics of the power system that was previously ignored are now very important. Hence the benefits of distribution automation have been widely acknowledged in recent years. This paper proposes an efficient load flow solution technique extended to find optimum location for reactive power compensation and network reconfiguration for planning and day-to-day operation of distribution networks.  This is required as a part of the distribution automation system (DAS) for taking various control and operation decisions.  The method exploits the radial nature of the network and uses forward and backward propagation technique to calculate branch currents and node voltages.  The proposed method has been tested to analyze several practical distribution networks of various voltage levels and also having high R/X ratio.

Multi-objective optimization of water distribution networks using particle swarm optimization

2021 ◽  
Vol 218 ◽  
pp. 18-31
Author(s):  
Douglas F. Surco ◽  
Diogo H. Macowski ◽  
Flávia A.R. Cardoso ◽  
Thelma P.B. Vecchi ◽  
Mauro A.S.S. Ravagnani
Keyword(s):  
Particle Swarm Optimization ◽  
Water Distribution ◽  
Particle Swarm ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective
Sign in / Sign up

Export Citation Format

Share Document