Power Network Reconfiguration For Congestion Management And Loss Minimization Using Genetic Algorithm

Pal, Sananda; Sen, Sourav; Sengupta, Samarjit

doi:10.1049/cp.2015.1646

Cited by 18 publications

(11 citation statements)

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“…According to [3], approaches for finding the optimal configuration of a distribution system fall into the following four categories: heuristic methods [4] [5], rule-based approaches [6] [7], genetic algorithms [8], and mathematical programming. After finding the optimal configuration, power flow considerations should be made to ensure that the new state of the system does not overload any of the circuit elements, cause misoperations of protection equipment, or violate any voltage constraints.…”

Section: Introductionmentioning

confidence: 99%

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

Kimble¹,

Vedullapalli²,

Makram³

2017

JPEE

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A great concern for the modern distribution grid is how well it can withstand and respond to adverse conditions. One way that utilities are addressing this issue is by adding redundancy to their systems. Likewise, distributed generation (DG) is becoming an increasingly popular asset at the distribution level and the idea of micro-grids operating as standalone systems apart from the bulk electric grid is quickly becoming a reality. This allows for greater flexibility as systems can now take on exponentially more configurations than the radial, one-way distribution systems of the past. These added capabilities, however, make the system reconfiguration with a much more complex problem causing utilities to question if they are operating their distribution systems optimally. In addition, tools like Supervisory Control and Data Acquisition (SCADA) and Distribution Automation (DA) allow for systems to be reconfigured faster than humans can make decisions on how to reconfigure them. As a result, this paper seeks to develop an automated partitioning scheme for distribution systems that can respond to varying system conditions while ensuring a variety of operational constraints on the final configuration. It uses linear programming and graph theory. Power flow is calculated externally to the LP and a feedback loop is used to recalculate the solution if a violation is found. Application to test systems shows that it can reconfigure systems containing any number of loops resulting in a radial configuration. It can connect multiple sources to a single micro-grid if more capacity is needed to supply the microgrid's load.

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Section: Introductionmentioning

confidence: 99%

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

Kimble¹,

Vedullapalli²,

Makram³

2017

JPEE

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“…From reference, [11] discussed about the generator rescheduling method as a ineffective and slow. Use of artificial intelligence techniques with generator rescheduling was described such as genetic algorithm [12,13] and by using particle swarm optimization with generator rescheduling [14].…”

Section: Congestion Management Methodsmentioning

confidence: 99%

Congestion Management in Power System—A Review

Riyaz

Upputuri

Kumar

2020

Lecture Notes in Electrical Engineering

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“…Reschedulling of active power Vinod Kumar Yadav et al [60] Flower Pollination Algorithm (FPA) Optimum capacity of DG units added to minimize the congestion in the transmission lines. SanandanPal et al [61] Genetic Algorithm (GA) To reduce the actual power loss of the power distribution network by appropriate reconfiguration and congestion reduction.…”

Section: Distributed Generationmentioning

confidence: 99%

A survey on recent advances in transmission congestion management

Gajjala

Ahmad

2021

IRASE

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For the last few decades, the power sector has been restructuring throughout the world, and because of this, congestion is bound to take place in the network. Congestion can lead to market failure, violate transmission capability limits and high electricity prices, and end up threatening the power systems’ reliability and security. Increased congestion may also lead to unexpected price differences in power markets leading to market power. In a deregulated power market (DPM), the independent system operator (ISO)’s fundamental challenge is to preserve the power market’s reliability and safety by improving market efficiency when the network is congested. Therefore, congestion management (CM) is essential in DPM and is the key to the power system. This paper carries out a congestion management methods survey to bring together all recent publications in the DPM. It aims to help readers summarize progressive CM methods, along with traditional CM methods that have been discussed so far. In this paper, we have carried out a comparative survey of the various well-known CM methods.

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Power Network Reconfiguration For Congestion Management And Loss Minimization Using Genetic Algorithm

Cited by 18 publications

References 0 publications

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

Congestion Management in Power System—A Review

A survey on recent advances in transmission congestion management

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