flow solution
Recently Published Documents


TOTAL DOCUMENTS

425
(FIVE YEARS 74)

H-INDEX

38
(FIVE YEARS 6)

2022 ◽  
Vol 8 ◽  
pp. 1438-1447
Author(s):  
Hao Bai ◽  
Xueyong Tang ◽  
Zhiyong Yuan ◽  
Qingsheng Li ◽  
Shuhui Pan ◽  
...  

Author(s):  
Robson Pires ◽  
G. Chagas ◽  
Lamine Mili

2021 ◽  
Vol 13 (23) ◽  
pp. 13382
Author(s):  
Muhammad Riaz ◽  
Aamir Hanif ◽  
Haris Masood ◽  
Muhammad Attique Khan ◽  
Kamran Afaq ◽  
...  

A solution to reduce the emission and generation cost of conventional fossil-fuel-based power generators is to integrate renewable energy sources into the electrical power system. This paper outlines an efficient hybrid particle swarm gray wolf optimizer (HPS-GWO)-based optimal power flow solution for a system combining solar photovoltaic (SPV) and wind energy (WE) sources with conventional fuel-based thermal generators (TGs). The output power of SPV and WE sources was forecasted using lognormal and Weibull probability density functions (PDFs), respectively. The two conventional fossil-fuel-based TGs are replaced with WE and SPV sources in the existing IEEE-30 bus system, and total generation cost, emission and power losses are considered the three main objective functions for optimization of the optimal power flow problem in each scenario. A carbon tax is imposed on the emission from fossil-fuel-based TGs, which results in a reduction in the emission from TGs. The results were verified on the modified test system that consists of SPV and WE sources. The simulation results confirm the validity and effectiveness of the suggested model and proposed hybrid optimizer. The results confirm the exploitation and exploration capability of the HPS-GWO algorithm. The results achieved from the modified system demonstrate that the use of SPV and WE sources in combination with fossil-fuel-based TGs reduces the total system generation cost and greenhouse emissions of the entire power system.


2021 ◽  
Author(s):  
Hongyue Zhen ◽  
Hefeng Zhai ◽  
Weizhe Ma ◽  
Ligang Zhao ◽  
Yixuan Weng ◽  
...  

2021 ◽  
pp. 127239
Author(s):  
Jinlan Guo ◽  
Weiquan Jiang ◽  
Guoqian Chen ◽  
Zhi Li ◽  
Njud S. Alharbi ◽  
...  

2021 ◽  
Vol 302 ◽  
pp. 117524
Author(s):  
Veerapandiyan Veerasamy ◽  
Noor Izzri Abdul Wahab ◽  
Rajeswari Ramachandran ◽  
Mohammad Lutfi Othman ◽  
Hashim Hizam ◽  
...  

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2663
Author(s):  
Raavi Satish ◽  
Kanchapogu Vaisakh ◽  
Almoataz Y. Abdelaziz ◽  
Adel El-Shahat

Due to the rapid advancement in power electronic devices in recent years, there is a fast growth of non-linear loads in distribution networks (DNs). These non-linear loads can cause harmonic pollution in the networks. The harmonic pollution is low, and the resonance problem is absent in distribution static synchronous compensators (D-STATCOM), which is the not case in traditional compensating devices such as capacitors. The power quality issue can be enhanced in DNs with the interfacing of D-STATCOM devices. A novel three-phase harmonic power flow algorithm (HPFA) for unbalanced radial distribution networks (URDN) with the existence of linear and non-linear loads and the integration of a D-STATCOM device is presented in this paper. The bus number matrix (BNM) and branch number matrix (BRNM) are developed in this paper by exploiting the radial topology in DNs. These matrices make the development of HPFA simple. Without D-STATCOM integration, the accuracy of the fundamental power flow solution and harmonic power flow solution are tested on IEEE−13 bus URDN, and the results are found to be precise with the existing work. Test studies are conducted on the IEEE−13 bus and the IEEE−34 bus URDN with interfacing D-STATCOM devices, and the results show that the fundamental r.m.s voltage profile is improved and the fundamental harmonic power loss and total harmonic distortion (THD) are reduced.


2021 ◽  
Author(s):  
Roberto Benato ◽  
Giovanni Gardan ◽  
Luca Rusalen ◽  
Giorgio Maria Giannuzzi ◽  
Cosimo Pisani ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document