Reconfiguration of Active Distribution Networks Equipped with Soft Open Points Considering Protection Constraints

Azizi, Ali; Vahidi, Behrooz; Nematollahi, Amin Foroughi

doi:10.35833/mpce.2022.000425

Cited by 20 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, extensive studies have been conducted on NR, and their objectives mainly focus on power loss deduction, voltage deviation reduction, and load balance function in the DN (Li et al, 2023). Azizi et al (2023) proposed a DN reconfiguration approach that considers renewable DG, soft open points (SOPs), and protection devices, aiming to minimize the power loss while ensuring the correct operation of protection devices under normal and fault conditions. Meanwhile, the loop-closing situation during the NR process was considered by Jun et al (2016) to obtain the optimum NR scheme without power interruption.…”

Section: Introductionmentioning

confidence: 99%

Multi-time-scale voltage control of the distribution network with energy storage equipped soft open points

Ding,

Chen,

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

The integration of distributed generation (DG) units into distribution networks (DNs) has brought about several operational challenges, including voltage issues and increased power loss. Energy storage equipped soft open points (E-SOPs) can accurately and flexibly control active and reactive power flows to address these problems. Additionally, the photovoltaic (PV) inverter and the network reconfiguration (NR) play a significant role in voltage control by adjusting the reactive power and the topology of the DN, respectively. However, due to differences in response times, there is a lack of systematic coordination between NR and the inverters of the E-SOP and PV. This paper proposes a multi-time-scale voltage control model that includes day-ahead NR scheduling, inter-day droop control optimization of the PV and E-SOP, and real-time local droop control. Considering the uncertainties of renewable DG outputs and loads, a robust optimization method is used in the day-ahead stage to obtain a reliable network structure. Then, with more accurate intra-day predictions, a stochastic optimization method is used to obtain the optimal state-of-charge interval, aiming to provide a flexible regulation range for battery energy storage to cope with the power fluctuations during the real-time stage. In addition, to address the intra-day voltage control model with bilinear constraints of the droop control function, a particle swarm optimization method is used. The results are verified on a 33-bus DN system through comparative analyses, showing effective performance.

show abstract

Section: Introductionmentioning

confidence: 99%

Multi-time-scale voltage control of the distribution network with energy storage equipped soft open points

Ding,

Chen,

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

show abstract

“…Distributed generations (DGs) have significantly changed many features of power systems, such as reducing network losses, voltage profiles, and serving as back-ups, etc. [1][2][3]. Although DGs can improve some electrical parameters, they may cause several types of problems in power systems [4].…”

Section: Introductionmentioning

confidence: 99%

A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Çelik,

Farkhani,

Lashab

et al. 2023

Energies

View full text Add to dashboard Cite

The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To verify the improvements, a test system based on a real distribution network that includes three generators with a capacity of 6 MW is utilized. The extensive simulations of the power network are performed using DIgSILENT Power Factory and MATLAB software. The obtained results reveal that a mean absolute percentage error (MAPE) of 3.51% for the GMDH-network-based protection system is accomplished thanks to formulation via optimized algorithms, without requiring the utilization of any feature selection techniques. The proposed method has a high-speed operation of around 20 ms for the detection of faults, while the conventional OC relay performance is in the blinding mode in the worst situations for faults with HIFs.

show abstract

“…To propose the optimal protective coordination (OPC) in the single-phase without DG connection, there has to be considered the time operation period. Afterward, the Coordinate Protection Index (PCI) by considering the power flows and downtime for operation [34].…”

Section: Introductionmentioning

confidence: 99%

Impact on Protective Device Sequence of Operation in Case Distributed Generation Integrated to Distribution System

et al. 2023

View full text Add to dashboard Cite

This study aims to evaluate the impact of the distributed generator (DG) connection to the grid. The simulated results present the parameters of the system required to install DG on the end of the main distribution feeder. Various parameters, such as voltage, current, and protective relay coordination are modelled after the actual provincial electricity authority (PEA) distribution system. Various case studies compared the coordination without and with DG connections to the grid by finding the difference of protective devices. The results indicate that the malfunction can be fixed in order of priority protective devices, which operate according to the parameter setting. Additionally, the coordinate functions between the recloser and fuse devices in both phase and ground configurations in the operating zone prevented the drop-out fuse melting or burning out. Based on the result, this problem is fixed by providing a directional recloser device and increasing the fuse-link rated with 40k installation for replacing the conventional sizing, which can improve the performance in case of fault occurrence to investigate the reliability and stability of the distribution system.

show abstract

Reconfiguration of Active Distribution Networks Equipped with Soft Open Points Considering Protection Constraints

Cited by 20 publications

References 26 publications

Multi-time-scale voltage control of the distribution network with energy storage equipped soft open points

Multi-time-scale voltage control of the distribution network with energy storage equipped soft open points

A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Impact on Protective Device Sequence of Operation in Case Distributed Generation Integrated to Distribution System

Contact Info

Product

Resources

About