Electric vehicles (EVs) battery has the ability to enhance the balance between the load demand and power generation units. Random behaviour of owners and EVs low capacity are some factors that develop the EV aggregator notion to increase the EV participation in the ancillary services market. In the presence of EVs aggregator, the frequency control service is capable of causing time-varying delay in load frequency control (LFC) systems. Owing to the dependency of controller effectiveness on its parameters, these parameters should be designed optimally in order to have a better result in an LFC system in the presence of time-varying delay. Therefore, a salp swarm algorithm (SSA) is utilised to adjust the fractional-order proportional integral derivative (PID) (FOPID) controller coefficients. Also, some evaluations are performed about the proposed LFC performance by an integral absolute error, integral time absolute error and mean absolute error indicators. In this study, both single and two-area LFC systems containing EVs aggregator with time-varying delay are simulated and analysed. The results indicate that the proposed controller has fewer frequency variations in contrast to other controllers presented in the case studies. Moreover, it is concluded that the FOPID controller could significantly decrease the overshoot and settling time of the frequency variation signal.
In this paper, we study the concept and forming manner of Solid Oxide Fuel Cell (SOFC) into the electrical system and then, its effect on small signal stability is investigated. The paper illustrates the essential module, mathematical analysis and small signal modeling of the SOFC joined to single machine system. The aim of this study is to reduce power oscillations in the presence of the SOFC with optimal stabilizer. The multi-objective Particle Swarm Optimization (MOPSO) technique has been used for designing a Power System Stabilizer (PSS) in order to improve the performance of the system. Two objective functions are regarded for the design of PSS parameters in order to maximize the damping factor and the damping ratio of the system. To evaluate the efficiency of the proposed optimal stabilizers, four scenarios are considered and then, its results have been analyzed. The proposed PSS tuning technique can be applied to a multi-machine system connected to the SOFC. The efficiency of MOPSO based proposed PSS on the oscillations the system related to SOFC is illustrated by time-domain simulation and also, the comparison of the MOPSO based proposed PSS with the PSS based-single objective method has been prepared.
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