Abstract
The power system’s principal goal is to deliver adequate power to the consumers in reliable form with quality. Due to fluctuating loading circumstances, the load on a power system changes on a regular basis. Maintaining the frequency and voltage within the permitted limits on a continuous basis is difficult. Automatic Generation Control (AGC) system is used to maintain stable output. Under dynamic load disturbances, maintaining the frequency and voltage within the permitted limits on a continuous basis is difficult. In addition to load disturbance, renewable energy penetration may lead to additional unbalance in the system, which creates more unbalance in the system. The conventional controller could not be able to mitigate frequency deviation as fast as needed. So, newly emerged controllers needed to integrate with the system to optimize the working of AGC. FO-PID controllers are used as the secondary controller to analyze the performance over conventional controllers. PV system is considered with one of the areas in the power system, and intermittent characteristics of PV generation are also analyzed. To tune FO-PID parameters using evolutionary algorithm, approaches like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) with objective functions of Integral Time Absolute Error (ITAE) to enhance the efficient optimal solutions to the two-area system are used. From this work, it is found that GA- and PSO-optimized FO-PID controller gives better performance over the optimized conventional controller.
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Vishnu, C.V., Ismayil, C., Sankar, S. (2023). Fractional Order PID Controller for AGC in Multi-area Power Systems Along with Renewable Energy. In: Siano, P., Williamson, S., Beevi, S. (eds) Intelligent Solutions for Smart Grids and Smart Cities. IPECS 2022. Lecture Notes in Electrical Engineering, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-99-0915-5_15
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DOI: https://doi.org/10.1007/978-981-99-0915-5_15
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