Effective Method for Load Restoration

Gnanambigai, S.; Anisha, K.; Rathnakumar, M.

doi:10.2139/ssrn.2240276

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…However, solving a load restoration problem by using mix integer programming is complicated as the power flow problem is a non-convex problem which also involve non-linear objective functions and constraints. Tabu Search [7], Genetic Programming [8], and Particle Swarm Optimization techniques [9] [10] are the example of meta heuristics methods employed to solve the load restoration problem. The disadvantage of meta heuristics method is that there is no guarantee for optimality and different searching algorithm may result in different solution for the identical problem.…”

Section: Introductionmentioning

confidence: 99%

Load Restoration in Distribution System using Minimum Spanning Tree - Prim's Algorithm

Mohamad*¹,

Razali²,

Salim³

et al. 2019

IJRTE

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Power outage is detrimental to the grid system therefore solving the issue within a short amount of time is indeed compulsory. Load restoration is one the solution required in ensuring the load can be connected within short amount of time. This study proposes a methodology to solve the load restoration problem using minimum spanning tree by determining the switching sequence according to the Prim’s algorithm. By using this algorithm, the switching is done based on the most minimum path which refer to the flow of power through the minimal value of weighted impedances. This method ensures that the losses is minimized and the voltage limit is not violated. The load restoration in this study focuses on reconfiguring the tie-lines in the 33-bus radial distribution network. Results obtained shows that Prim’s algorithm is effective in restoring the loads by reconfiguring the network in a way that total active power losses are minimized. This algorithm is also compared with the Binary Particle Swarm Optimization (BPSO) to prove the effectiveness of this method thus enhancing the power system reliability.

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Section: Introductionmentioning

confidence: 99%