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This research proposes the application of fractional‐order sliding mode control (FOSMC) at the primary controller level to improve the stability of an islanded microgrid by adjusting its voltage and frequency. The control strategies used in the microgrid are performed in two levels (primary and secondary) in the islanded mode. Practically, most previous studies have worked to improve the primary controller. Droop control is one of the most commonly used methods at the primary level and is adopted in this study as well. The sliding mode control (SMC) strategy is normally used to control linear equations. Thus, the non‐linear microgrid equations were transformed into some linear ones using the input‐output feedback linearization technique. Further, a fractional sliding surface was acquainted. The sliding surface and FOSMC were designed to reject system uncertainties and organize the voltage and frequency. Design parameters were chosen using the Lyapunov stability theorem. The validation of the proposed method using Simulink‐MATLAB confirms its effectiveness in enhancing level power sharing, regulating frequency, and maintaining voltage stability across the system. [ABSTRACT FROM AUTHOR]

Today, with growing expansion of renewable energy resources, electricity production is accompanied by uncertainties. The usage and optimal management of energy storage is one of the effective ways to compensate for these uncertainties. Compressed air energy storage (CAES) is one of the two bulk electricity storage methods for power systems, burning natural gas (NG) to extract the stored energy. Therefore, the NG price uncertainty and gas availability along with carbon emission resulting from burning NG can affect optimal bidding result of this unit. Hence, this study addresses the optimal bidding problem of CAES and wind units, considering the aforementioned issues, while taking into account uncertainties of day‐ahead (DA) and balancing market prices, wind speeds, and NG prices and availability. Furthermore, the dynamics of natural gas flow in the pipeline is modelled. The stochastic programming (SP) method is proposed for solving this problem while taking risk into consideration. The scheduling has been presented for participation of generating company in DA and carbon emission markets. Simulation results indicate the capability of the proposed method in optimal bidding of CAES units while taking gas‐burning related constraints into consideration. [ABSTRACT FROM AUTHOR]

This study presents a new control scheme to provide both voltage regulation and power sharing within a DC microgrid. It includes both primary and secondary levels as well as the proposed auxiliary feedback. The secondary control distributes and uses the consensus algorithm to share power. First, the auxiliary feedback is formulated. Then the features of the feedback are analytically extracted to provide both voltage regulation and power sharing. Next, the particle swarm optimisation algorithm determines the parameters of the controller optimally. Following that, a series of simulations is carried out to show the performance of the proposed scheme in comparison with the conventional methods. Hence, to validate the advantages of the proposed scheme, a four distributed energy resource (DER) DC microgrid is considered, and the proposed approach is applied. Afterwards, the eigenvalue and sensitivity analysis show the effect of the parameters variation on microgrid stability. The results show that the applied method can regulate the voltage well and shares the power in the presence of the load demand as a disturbance besides the long‐time delay associated with the secondary control as an uncertainty. [ABSTRACT FROM AUTHOR]