Congestion Management in Power Systems Via Intelligent Method
In the deregulated power systems, transmission congestion is one of the significant and main problems of the electrical networks which can cause incremental cost in the energy. This problem has resulted to new challenging issues in different parts of power systems which there was not in the traditional systems or at least had very little importance. Transmission congestion happens when the maximum available power transmission capacity is lower than the consumption side. As congestion happens, the system power losses are increased which can cause problem in the voltage constraints. Therefore, this paper proposes a new method to handle the optimal management and control of congestion problem by the use of distributed generations (DGs). In this regard, the optimal size and location of DGs are investigated using the powerful bacteria foraging algorithm (BFA) as a new intelligence-based optimization technique to solve the congestion problem on the three IEEE 14-bus, 30-bus and 57-bus test systems. The simulation results show the high speed, fast convergence and accurate performance of the proposed algorithm to solve the congestion problem in the system
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Analysis and Simulation of Dynamic Behavior of Load Frequency Control for a Thermal–Hydro Power System with Photovoltaic System
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