Large frequency oscillations happen when the unbalanced power is not compensated by Load Frequency Controller (LFC) system. In recent years, the using of electric vehicles (EVs) has increased with renewable generation sources such as solar cells, wind turbines, fuel cells, and so on. The large-scale integration of these new types of generation sources and demand in power grids will have significant impact on operations, planning and stability control. This work sets out to design an effective PID controller for LFC in an island Micro-grid (MG) and also proposes a model for EVs to contribute to LFC system. To this end, particle swarm optimization (PSO) based artificial neural network (ANN) technique is considered to tune the parameters of PID controller in MG structure. Simulation results demonstrate that with PSO-based ANN, the system is becoming stable in shortest time. In addition, frequency oscillation magnitude, overshoot and settling time are reduced.

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.

Today, time-varying delays may result from a communication network’s engagement in frequency control services. These delays have an impact on the effectiveness of the load frequency control (LFC) system, which can occasionally lead to power system instability. The electric vehicle (EV) can be used as a beneficial source for the LFC system with the development of demand-side response due to its vehicle-to-grid capacity. Although demand response control has certain advantages for the power system, communication networks used in LFC systems result in time delays that reduce the stability of the LFC schemes. A stability study of an LFC system, comprising an EV aggregator with two additive time-varying delays, is demonstrated in this work. An enhanced Lyapunov–Krasovskii functional (LKF), which incorporates time-varying delays using the linear matrix inequality approach, is used to perform a delay-dependent stability analysis of the LFC to determine the stability zone and criterion. In conclusion, the efficiency of the proposed stability criterion is validated by making use of the thorough simulation findings.