Optimal recloser and autosectionalizer allocation in distribution networks using IPSO–Monte Carlo approach

Abdi, Sh.; Afshar, K.; Ahmadi, S.; Bigdeli, Nooshin; Abdi, M.

doi:10.1016/j.ijepes.2013.10.012

Cited by 38 publications

(24 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, by installing switches, SAIDI and SAIFI can be minimized respectively and at minimal cost [15]. The paper [16] tackles the subject of reclosers and switches location based on a cost/benefit analysis methodology in order to minimize the cost of reliability. The optimization method is based on a hybrid solution using the IPSO method (Improved Particle Swarm Optimization) and Monte Carlo simulation.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective optimization-based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

Lekbich

Belfqih

Ouaderhman³

et al. 2020

IJEECS

View full text Add to dashboard Cite

Since they are fast, remote-controlled, automated and intelligent, reclosers and switches are an inevitable solution for improving the reliability of intelligent electrical distribution networks at optimal cost. However, their location and coordination have great effects on the protection and automation strategies of complex electrical distribution networks against multiple unpredictable faults. Which requires a flexible and multi-criteria optimization method. In this article, we propose a multi-objective method based on an analytical model by considering the fault rate, restoration times, outage cost and coordination between devices. The non-dominated genetic sorting algorithm II was proposed to obtain the optimal Pareto solutions, and a technique of performance control by similarity with the ideal solution was used to classify them. The objective criteria weights are based on the entropy method which allows solutions to be obtained and better classified with the minimum of subjectivity. The IEEE33 and IEEE13 bus test networks were used to verify the method. The results obtained are compared to a binary multi-objective particle swarm optimization method and the results show that the proposed method reduces the overall costs, reduces the undelivered energy of the system and improves the reliability of the service.

show abstract

Section: Introductionmentioning

confidence: 99%

A multi-objective optimization-based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

Lekbich

Belfqih

Ouaderhman³

et al. 2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…Abdi et al. developed an efficient maximum power point tracking algorithm based on sliding mode controller used to control the power converter duty cycle. The developed MPPT controller has been evaluated and compared to P&O MPPT using different scenarios including temperature and membrane water content variations showing low tracking error, fast response time, simple control law and low implementation cost and complexity.…”

Section: Introductionmentioning

confidence: 99%

A Novel Single Sensor Variable Step Size Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell Power System

Harrag

Bahri

2019

Fuel Cells

View full text Add to dashboard Cite

This paper proposes a novel single sensor variable step size maximum power point tracking (MPPT) method for proton exchange membrane (PEM) fuel cell. This paper is a first, if modest, attempt to develop a single sensor MPPT for fuel cell systems. The proposed MPPT algorithm uses only one sensor to track the maximum power of PEM fuel system composed of 7 kW proton exchange membrane fuel cell (PEMFC) powering 50 Ω resistive load via a DC–DC boost converter driven using the proposed MPPT. The performances of the proposed controller have been evaluated using the implemented PEM fuel cell power system Matlab/Simulink model using two test scenarios considering temperature and hydrogen pressure variation. Simulation results show that the proposed controller can effectively track the maximum power point using only one sensor which reduces the cost as well as the complexity of the PEM fuel cell power system. Comparative results with the two sensors MPPT show that the two sensors MPPT outperforms the single sensor MPPT regarding the dynamic performances. However, the proposed single sensor MPPT performs better considering the static performances. In addition, the proposed controller reduces drastically the current ripple increasing by the way the fuel cell efficiency and lifetime by reducing the frequent trip due to over‐current and even harmonics.

show abstract

“…The improvement of the efficiency of the tracking of the MPPT using new control strategies is the easiest and not expensive compared to the effort due for the improvement of the conversion ratio of fuel cells or the efficiency of the converter. This push to a massive development of MPPT algorithms over the last decade: perturbation and observation (P&O) , incremental conductance (IC) , , extremum seeking control (ESC) , hysteresis controller (HC) , fractional order filter (FO) , sliding mode controller (SMC) , , neural network (NN) , fuzzy logic controller (FLC) , , particle swarm optimization (PSO) , eagle strategy (ES) , water cycle algorithm (WCA) , etc.…”

Section: Introductionmentioning

confidence: 99%

Variable Step Size IC MPPT Controller for PEMFC Power System Improving Static and Dynamic Performances

Harrag

Messalti

2017

Fuel Cells

View full text Add to dashboard Cite

In this paper, a variable step size IC MPPT controller for the proton exchange membrane fuel cell (PEMFC) power system is proposed. The efficiency of the proposed algorithm has been studied successfully using a 7 kW PEMFC fed by DC‐DC boost converter derived using the proposed MPPT controller implemented under Matlab/Simulink environment. Comparison results obtained using both implemented fixed and variable step size IC MPPTs on two scenarios test considering temperature and hydrogen pressure variation show that the proposed variable step size IC MPPT outperforms the conventional fixed step size in static and dynamic performances.

show abstract

Optimal recloser and autosectionalizer allocation in distribution networks using IPSO–Monte Carlo approach

Cited by 38 publications

References 26 publications

A multi-objective optimization-based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

A multi-objective optimization-based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

A Novel Single Sensor Variable Step Size Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell Power System

Variable Step Size IC MPPT Controller for PEMFC Power System Improving Static and Dynamic Performances

Contact Info

Product

Resources

About