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This paper describes a permissive load frequency control (LFC) real life model for long-term time domain simulations. The model represents a supplementary control system to governor control systems based on area control error (ACE) calculation. Each forth second, ACE will be checked. If ACE is outside of its dead-band, one signal will be generated and broadcasted to all power plants involved in secondary control. Considering the received signal (positive or negative) and power plant participation factors, each power plant will react in order to reduce ACE. This LFC type is around 20 years in service in the Serbian power system with minimum maintenance. The advantage of this LFC is that it is simple, reliable, it can follow strict ENTSO- E rules, and it could be implemented to all generation types including renewable sources. The paper does not bring a new LFC methodology. However, it provides a contribution to modelling existing LFCs.

Load flow is the most used calculations in power system operation planning. Renewable resources have caused that system operator has to do power flow analysis and/or contingency analysis as fast as possible in order to predict next step in power system control. LU Decomposition of Jacobian matrix remains the most computationally expensive task during Newton–Raphson iterative method. Computational time appears to be critical issue when load flow calculation is performed on large power system load flow models. In this case, Jacobian matrix LU decomposition should not be performed in iterations in which convergence rate is not violated but performed in iterations in which convergence rate drop below specified level. In other words, modified Newton–Raphson Method which eliminates the repeated Jacobian matrix LU decomposition and generic Newton–Raphson method are combined depending on convergence rate. The paper presents application of proposed combined Newton–Raphson method which is based on convergence rate control. Comparison of combined, Shamanskii, generic, and modified Newton–Raphson methods is carried out taking into consideration computational time and number of iterations required to achieve convergence of load flow models of various dimensions.