A Simple and Fast Heuristic Approach for the Reconfiguration of Radial Distribution Networks

Harsh, Pratik; Das, Debapriya

doi:10.1109/tpwrs.2023.3256136

Cited by 11 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Cases 1 and 2, the amount of active and reactive power of the network is affected by the load. Since the power factor of loads is around 0.85 according to [80], the power factor of the distribution substations for Cases 1 and 2 is around 0.85. However, in Case 3, distributed generations can change the amount of active and reactive power requested from the distribution substation, therefore the power factor in this case can change between 0.9 and 0.98.…”

Section: Evaluation Of Network Indicesmentioning

confidence: 99%

“…Figure 1 depicts the standard IEEE 69-bus radial distribution system adopted in this article [80]. The base voltage and power of the system are 12.66 kV and 1 MW, and its minimum and maximum permissible voltage limit is [0.9, 1.05] p.u.…”

Section: Problem Datamentioning

confidence: 99%

“…In addition, the tie lines are located between the buses (11,43), (13,21), (15,46), (27,65), and (50,59), and the breakers on these lines are identified by numbers 69, 70, 71, 72, and 73. The data of distribution lines and distribution substations and peak data of P 0 and Q 0 are extracted from [80]. The hourly amount of P 0 and Q 0 can be found by multiplying the daily curve of the load factor and peak values of P 0 and Q 0 .…”

Section: Problem Datamentioning

confidence: 99%

“…from [80]. The hourly amount of P 0 and Q 0 can be found by multiplying the daily curve of the load factor and peak values of P 0 and Q 0 .…”

Section: Problem Datamentioning

confidence: 99%

See 3 more Smart Citations

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

Jiang

Zhang

2023

Applied Sciences

View full text Add to dashboard Cite

One of the approaches to improve operation indices, such as power loss and reliability, is to smoothen voltage profiles. Energy management of generation units and network reconfiguration are two methods to achieve this. Hence, the latter is presented in this paper in a distribution with distributed generation units. To this end, an objective function is formulated aiming to minimize power loss and enhance the operating situation of the network. This problem is subject to various constraints and limits such as AC power flow equations, operation limits, planning model, and operation model of distributed generations. It is an integer nonlinear optimization problem and is solved using the crow search algorithm and the optimal solution is obtained. Two major innovations of the study include modeling generation units’ operation and network configuration mathematical expression of operation indicators. The method is applied to a test system and results demonstrate the high performance of this approach in improving the operation of the network. Finding the solution in less time with a satisfying standard deviation are two advantages of the proposed algorithm. Adopting this method, the network operator can reduce power loss through proper management of distributed generation power and optimal scheduling of switches. Moreover, the obtained voltage profile is more desirable in comparison to that of power flow studies.

show abstract

Section: Evaluation Of Network Indicesmentioning

confidence: 99%

Section: Problem Datamentioning

confidence: 99%

Section: Problem Datamentioning

confidence: 99%

“…from [80]. The hourly amount of P 0 and Q 0 can be found by multiplying the daily curve of the load factor and peak values of P 0 and Q 0 .…”

Section: Problem Datamentioning

confidence: 99%

See 2 more Smart Citations

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

Jiang

Zhang

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The heuristic algorithms can solve the DNR problem with high speed. In the study by Harsh and Das (2023), a two-stage heuristic algorithm based on the power flow analysis is used for DNR. Zhan et al (2020) proposed the switch opening and exchange method for DNR.…”

Section: Introduction 1literature Reviewmentioning

confidence: 99%

Dynamic reconfiguration of distribution network considering the uncertainty of distributed generation and loads

Liu,

Zhang,

et al. 2023

Front. Energy Res.

View full text Add to dashboard Cite

This study presents a new methodology to perform the distribution network dynamic reconfiguration (DNDR), taking into consideration the stochastic variations of loads and distributed generation (DG) of power. To solve the heavy computational burden that exists in traditional algorithms of the DNDR, this study first establishes the nodal sensitivity models to calculate the nodal variations caused by nodal power variations. Then, the DNDR is executed utilizing a co-evolutionary algorithm with the goal of loss minimization. The stochastic power flow calculations (PFCs) based on the nodal sensitivity are performed in the DNDR to handle the power fluctuations of the DGs and loads. Finally, the modified IEEE 33-bus test system and a practical distribution system are used for simulations. The simulation results validate the quickness and effectiveness of the proposed DNDR method.

show abstract

A multi-objective energy scheduling of the reconfigurable off-grid microgrid with electric vehicles using demand response program

Harsh,

Das

2024

Computers and Electrical Engineering

View full text Add to dashboard Cite

A Simple and Fast Heuristic Approach for the Reconfiguration of Radial Distribution Networks

Cited by 11 publications

References 7 publications

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

Dynamic reconfiguration of distribution network considering the uncertainty of distributed generation and loads

A multi-objective energy scheduling of the reconfigurable off-grid microgrid with electric vehicles using demand response program

Contact Info

Product

Resources

About