Load flow study is done to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state working condition of a power system. It is important and most frequently carried out study performed by power utilities for power system planning, optimization, operation and control. In this paper a Particle Swarm Optimization Neural Network (PSO-ANN) is proposed to solve load flow problem under different loading/ contingency conditions for computing bus voltage magnitudes and angles of the power system. A multilayered feed-forward neural network is trained by using PSO technique. The results show the effectiveness of the proposed PSO-ANN based approach for solving power flow problem having differ...
AbstractThe load forecast level in power system is a important symbol to measure operations and mana...
Power flow (PF) study, which is performed to determine the power system static states (voltage magni...
Different optimization techniques are used for the training and fine-tuning of feed forward neural n...
Load flow study is done to determine the power system static states (voltage magnitudes and voltage ...
This paper proposes an under-frequency load shedding (UFLS) method by using the optimization techniq...
The present paper shows an application of Particle Swarm Optimization (P.S.O.) to load flow optimiza...
Voltage instability is considered as a major problem that faces the power systems during its operati...
Power systems operation is widely monitored through load flow analyses. The three main methods used ...
Electrical load forecasting plays a key role in power system planning and operation procedures. So f...
ABSTRACT- This paper narrates an application of Particle Swarm Optimization (PSO) for economic load ...
In this work, PSO is applied to solve power flow problem. For efficient search, some parameters in P...
In this work, the indicators of electrical power network stability and voltage stability (VS) are di...
In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the b...
A load frequency controller (LFC) is a crucial part in the distribution of a power system network (P...
The quality of short term load forecasting can improve the efficiency of planning and operation of e...
AbstractThe load forecast level in power system is a important symbol to measure operations and mana...
Power flow (PF) study, which is performed to determine the power system static states (voltage magni...
Different optimization techniques are used for the training and fine-tuning of feed forward neural n...
Load flow study is done to determine the power system static states (voltage magnitudes and voltage ...
This paper proposes an under-frequency load shedding (UFLS) method by using the optimization techniq...
The present paper shows an application of Particle Swarm Optimization (P.S.O.) to load flow optimiza...
Voltage instability is considered as a major problem that faces the power systems during its operati...
Power systems operation is widely monitored through load flow analyses. The three main methods used ...
Electrical load forecasting plays a key role in power system planning and operation procedures. So f...
ABSTRACT- This paper narrates an application of Particle Swarm Optimization (PSO) for economic load ...
In this work, PSO is applied to solve power flow problem. For efficient search, some parameters in P...
In this work, the indicators of electrical power network stability and voltage stability (VS) are di...
In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the b...
A load frequency controller (LFC) is a crucial part in the distribution of a power system network (P...
The quality of short term load forecasting can improve the efficiency of planning and operation of e...
AbstractThe load forecast level in power system is a important symbol to measure operations and mana...
Power flow (PF) study, which is performed to determine the power system static states (voltage magni...
Different optimization techniques are used for the training and fine-tuning of feed forward neural n...