1580 Words7 Pages

Abstract— The foremost vital aspects in power systems is that the voltage stability analysis. One among the strategies used to investigate the voltage stability is that determination of maximum loadability limit (MLL) of power systems. Most of the ways utilized in determining the voltage stability or the maximum loading point of the system depend upon the answer of the power flow. MLL problem is developed as maximization problem. So this paper proposes an Artificial Bee Colony (ABC) algorithmic rule to solve the maximum loadability limit (MLL) problem. The proposed methodology has been tested on IEEE 30-bus system. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem. Therefore, the*…show more content…*

The power systems are heavily stressed due to the increased loading and this results in voltage stability problem. The other factors, that cause voltage stability, are outage of equipment (generator, line, electrical device and bus bar), decrement of production and/or weakening of voltage management. Voltage Stability is also referred to as the “load stability”. The main issue causing voltage instability is inability of the power system to fulfill the reactive power demands. In order to stop the incidence of voltage instability, it's essential to investigate voltage stability of power systems. Maximum loadability limit (MLL) is an economical thanks to evaluate the steady state voltage stability The maximum loadability limit is that the margin between the operating point of the system and therefore the maximum loading point. General the maximum loading point is additional interesting from the practical point of view than true voltage collapse point, as a result of the maximum of grid loading is achieved at now. The load increase beyond the voltage collapse point ends up in loss of equilibrium and grid will not operate. The power system becomes voltage unstable at the voltage collapse*…show more content…*

PSO may be machine intelligence-based technique that’s not mostly affected by the size and nonlinearity of the matter, and may converge to the optimum answer in several issues [].This Hybrid PSO has been used to solve the maximum loadability problem [8]. This paper doesn't contemplate the voltage limit and this rule isn't appropriate for large scale system (limited to fourteen bus system). Multi agent hybrid PSO (MAHPSO) have been developed and applied to work out the maximum loadability limit in []. This MAHPSO has benefits of each HPSO and MAPSO. The optimum allocation of generators at this maximum loading purpose is set in []. During this rule, the load is uniformly redoubled in all the load buses till the voltage limits square measure violated. Maximum loadability limit is identified using genetic rule in [] and using CAPSO in []. Here maximum limit is that the voltage stability limit wherever the voltage magnitude is way less than the lower limit. Hybrid differential evolution with particle swarm optimization has been developed and implemented to see maximum loadability limit. During this approach the powerful DE algorithm is combined with PSO to get the benefits of each. The main operator is DE and its search capability is improved by PSO. Even though time per iteration for the proposed DEPSO algorithm is greater

The power systems are heavily stressed due to the increased loading and this results in voltage stability problem. The other factors, that cause voltage stability, are outage of equipment (generator, line, electrical device and bus bar), decrement of production and/or weakening of voltage management. Voltage Stability is also referred to as the “load stability”. The main issue causing voltage instability is inability of the power system to fulfill the reactive power demands. In order to stop the incidence of voltage instability, it's essential to investigate voltage stability of power systems. Maximum loadability limit (MLL) is an economical thanks to evaluate the steady state voltage stability The maximum loadability limit is that the margin between the operating point of the system and therefore the maximum loading point. General the maximum loading point is additional interesting from the practical point of view than true voltage collapse point, as a result of the maximum of grid loading is achieved at now. The load increase beyond the voltage collapse point ends up in loss of equilibrium and grid will not operate. The power system becomes voltage unstable at the voltage collapse

PSO may be machine intelligence-based technique that’s not mostly affected by the size and nonlinearity of the matter, and may converge to the optimum answer in several issues [].This Hybrid PSO has been used to solve the maximum loadability problem [8]. This paper doesn't contemplate the voltage limit and this rule isn't appropriate for large scale system (limited to fourteen bus system). Multi agent hybrid PSO (MAHPSO) have been developed and applied to work out the maximum loadability limit in []. This MAHPSO has benefits of each HPSO and MAPSO. The optimum allocation of generators at this maximum loading purpose is set in []. During this rule, the load is uniformly redoubled in all the load buses till the voltage limits square measure violated. Maximum loadability limit is identified using genetic rule in [] and using CAPSO in []. Here maximum limit is that the voltage stability limit wherever the voltage magnitude is way less than the lower limit. Hybrid differential evolution with particle swarm optimization has been developed and implemented to see maximum loadability limit. During this approach the powerful DE algorithm is combined with PSO to get the benefits of each. The main operator is DE and its search capability is improved by PSO. Even though time per iteration for the proposed DEPSO algorithm is greater

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