Wyniki wyszukiwania - Biblioteka Nauki

Ten serwis zostanie wyłączony 2025-02-11.

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Technical-economic indices for optimal integration of photovoltaic distributed generation units using hybrid PSO-WOA technique

100%

Settoul S. , Zellagui M. , Chenni R. , Belbachir N.

Journal of Power Technologies

2022

tom Vol. 102, nr 1

25--36

This paper proposes to hybridize the Whale Optimizer (WOA) and Particle Swarm Optimization (PSO) algorithms to achieve optimal integration of Distributed Generator (DG) based photovoltaic sources in the search for optimal allocation. Optimal integration reduces the Active Power Loss (APL) index and enhances the Total Voltage Variation (TVV) index and the Total Operating Cost (TOC) index. The proposed hybrid PSO-WOA algorithm is validated on standard IEEE 33-bus and 69-bus Electrical Distribution Systems (EDS). Numerical and graphical comparative studies were conducted to benchmark the hybrid approach results against those obtained using other powerful algorithms and techniques existing in the literature. Active and reactive branch currents are calculated and plotted to show how the DG affects current flows in the EDS. To make the results more realistic, linear load level variation is considered, with the loads varying from 60% to 120% of the rated loading level.

Multi-objective optimal allocation and sizing of hybrid photovoltaic distributed generators and distribution static var compensators in radial distribution systems using various optimization algorithms

100%

Zellagui M. , Belbachir N. , El-Bayeh C. Z. , Bekkouche B.

Journal of Power Technologies

2023

tom Vol. 103, nr 2

89--103

In the recent years, a considerable growth was about the integration of renewable sources in the Radial Distribution Systems (RDS), as Photovoltaic Distributed Generators (PVDG) due to their importance in achieving plenty desired technical and economic benefits. Implementation of the Distribution Static Var Compensator (DSVC) in addition to the PVDG would be one of the best choices that may provide the maximum of those benefits. Hence, it is crucial to determine the optimal allocation of the devices (PVDG and DSVC) into RDS to get satisfactory results and solutions. This paper is devoted to solving the allocation problem (location and sizing) of hybrid PVDG and DSVC units into the standards test systems IEEE 33-bus and 69-bus RDSs. Solving the formulated problem of the optimal integration of hybrid PVDG and DSVC units are based on minimizing the proposed Multi-Objective Functions (MOF) which is represented as the sum of the technical-economic parameters of Total Active Power Loss (TAPL), Total Reactive Power Loss (TRPL), Total Voltage Deviation (TVD), Total Operation Time (TOT) of the overcurrent relays (OCRs) installed in the RDS, the Investment Cost of PVDGs (ICPVDG) and the Investment Cost of DSVC (ICDSVC)), by applying various recent metaheuristic optimization algorithms. The simulation results reveal the superiority and the effectiveness of the Slime Mould Algorithm (SMA) in providing the minimum of MOF, including minimization of the powers losses until 16.209 kW and 12.110 kVar for the first RDS, 4.756 kW and 7.003 kVar for the second RDS, enhancing the voltage profiles and the overcurrent protection system. Based on the paper’s results it is recommended to optimally integrate both PVDG and DSVC units into practical distribution networks.

Fault detection in photovoltaic systems using the inverse of the belonging individual Gaussian probability

88%

Sendjasni S. , Yagoubi B. , Daoud M. , Belbachir N. , Ziane A.

2023

tom Vol. 24, No. 1

art. no. 2023112

This article addresses the problem of fault early detection in photovoltaic systems. In the production field, solar power plants consist of many photovoltaic arrays, which may suffer from many different types of malfunctions over time. Hence, fault early detection before it affects PV systems and leads to a full system failure is essential to monitor these systems. The fields of control and monitoring of systems have been extensively approached by many researchers using various fault detection methods. Despite all this research, to early detect and locate faults in a very large photovoltaic power plant, we must, in particular, think of an effective method that allows us to do so at the lowest costs and time. Thus, we propose a new robust technique based on the inverse of the belonging individual Gaussian probability (IBIGP) to early detect and locate faults in the power curve as well as in the Infrared image of the photovoltaic systems. While most fault detection methods are well incorporated in other domains, the IBIGP technique is still in its infancy in the photovoltaic field. We will show, however, in this work that the IBIGP technique is a very promising tool for fault early detection enhancement.