Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs

Hamida, Imen Ben; Salah, Saoussen Brini; M’Śahli, Faouzi; Mimouni, Mohamed Faouzi

doi:10.1016/j.renene.2017.12.106

Cited by 124 publications

(96 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For that reason, research on the incorporation of DG into the distribution system has turned out to be very popular. The incorporation of DG is anticipated to play an important part in the electric power system [1,2]. DG is one of the small-scale power generations that is frequently associated with distribution system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation and Sizing of Multiple DG in Radial Distribution System Using Binary Particle Swarm Optimization

Rani¹,

Reddy²

2019

IJIES

View full text Add to dashboard Cite

In modern days, utility grids are facing major issues in the power system due to an uninterrupted load development and shortage of capital investment in transmission systems. Due to this, network is not capable to meet the estimated demand and transfer the produced power from the integrated power generation into the distribution network. This may generate high power losses in the distribution side that also disturbs the overall efficiency of the network. By employing an optimal placement of Distributed Generation (DG) in power systems is the only way to minimize this kind of problems in economical and practical way. DG has several benefits over centralized power generations that comprising system steadiness, improvement and dismissing transmission/distribution system bottleneck to meet the power demand. So in this paper, Binary Particle Swarm Optimization (BPSO) is used for optimal DG reconfiguration. BPSO iteratively moves the DG in each load bus of the test system that provides the smallest value of the objective function, which is considered as the finest candidate for DG connection. This method is simulated on IEEE 69-bus system that showed enhancement in voltage profile and decrease in power loss compared to other optimization methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimal Allocation and Sizing of Multiple DG in Radial Distribution System Using Binary Particle Swarm Optimization

Rani¹,

Reddy²

2019

IJIES

View full text Add to dashboard Cite

show abstract

“…Reconfiguration of the network with distributed generations and remote voltage controlled busses has been studied in Das et al For the same situation, a load flow free method has been suggested . A multi‐objective network reconfiguration in parallel with renewable DGs sitting and sizing for minimizing active power loss and annual operation costs has been conducted in Hamidal et al Another similar multi‐objective method for optimal network reconfiguration as well as reactive power dispatches of distributed generations has been proposed to improve the network performances by using nondominated sorting particle swarm optimization . The methods, which have been utilized to reconfigure the network for enhancing reliability and reducing losses, have been compared in Sultana et al Distribution network reconfiguration based on maximizing reliability by using the binary particle swarm optimization (BPSO) search algorithm in Amanulla et al and mixed‐integer second‐order conic programming (MISOCP) in López et al have been accomplished.…”

Section: Introductionmentioning

confidence: 99%

Modified branch exchange reconfiguration of active distributed network for simultaneous loss reduction and power quality improvement

Dejamkhooy

Khaneghah

Shayeghi

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Traditionally active power loss and power quality issues are major concerns in distribution network management. Nowadays, these concerns become more important by integrating distributed energy resources (DERs) in the networks. Network reconfiguration has been adopted as an effective remedy. In this paper, loss reduction and improvement of power quality indices such as total harmonic distortion (THD) and voltage sag are modeled as a multi‐objective problem. The function is weighted sum of terms, which are dealt with each objective. To solve the problem, branch exchange method for the network reconfiguration is modified. In the proposed algorithm, branch exchange operation iterates sequentially. Then, the yielded solution is compared with the best one that has been saved in the memory unit. Because memory is utilized in the method, it is called retentive branch exchange. Application of the proposed method is validated by planning and simulating six scenarios for an unbalanced radial 25‐bus network. For different operation conditions and power quality disturbances, simulation results show high ability and effectiveness of the proposed method.

show abstract

“…[2]. Thus, switching processes are mutual in a distribution system to pass on load from one line to another line even though maintain functioning arrangement as radial [3]. This kind of processes are referred as reconfiguration process that can be accomplished by sectionalizing the tie line switches.…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of Distributed Generation Units in Radial Distribution System using Hybrid Techniques

Rani,

Reddy

2019

IJEAT

View full text Add to dashboard Cite

Reconfiguration is a process that supports to eliminate the power loss from a distribution network and this process have the capability to reduce the losses up to a specific point. Additionally, loss minimization may be calculated through the presentation of Distributed Generation (DG) units. Conversely, the incorporation of DG into the distribution network at an improper position may cause higher in losses and fluctuations in voltage. In the meantime, the uncertainty in voltage may produce partial power failure in the system. For that reason, it is essential to deliberate the stability boundaries in DGs position and sizing in the Radial Distribution System (RDS). In this research paper, hybrid Binary Particle Swarm Optimization (BPSO) with Flower Pollination Algorithm (FPA) is proposed for the ideal reconfiguration process and placing the DG in the 69-bus RDS. BPSO is applied to identify the best DG reconfiguration and FPA is proposed to determine the optimal DG size. This technique narrowly changes the DG location in every load bus of the network that delivers the minimum value of the objective function, which is considered as the finest candidate for DG connection. The simulation outcomes indicate the proposed method is more effective in reducing the power loss from 224.9804 to 27.2183 KW with the reduction of 88.8972% when compared to existing algorithm

show abstract

Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs

Cited by 124 publications

References 37 publications

Optimal Allocation and Sizing of Multiple DG in Radial Distribution System Using Binary Particle Swarm Optimization

Optimal Allocation and Sizing of Multiple DG in Radial Distribution System Using Binary Particle Swarm Optimization

Modified branch exchange reconfiguration of active distributed network for simultaneous loss reduction and power quality improvement

Optimal Placement of Distributed Generation Units in Radial Distribution System using Hybrid Techniques

Contact Info

Product

Resources

About