Energy management of controllable loads in multi-area power systems with wind power penetration based on new supervisor fuzzy nonlinear sliding mode control

The distributed controllable loads (DCLs) are employed to achieve energy management for hybrid renewable energy-based multi-area power systems (HREPSs). The DCLs are suggested as a cheaper solution instead of the expensive energy storage systems. Due to the nonlinearity, high variability and uncertain nature of HREPSs based on DCLs, the need for an artificial intelligence-based nonlinear energy management system becomes mandatory. This paper suggests a hybrid control methodology based on fuzzy logic and nonlinear sliding mode control (FL-NLSM) to manage the energy of DCLs in a smart grid. The proposed hybrid control strategy merges the unique properties of both FL and NLSM to handle the system nonlinearities and to improve the damping characteristics of the system response against the uncertainties of the parameters; as well as the high variability of renewable energy resources such as wind power and the load demand fluctuations. Moreover, the gains of the proposed FL-NLSM controller are optimized by the imperialist competitive algorithm that is considered a powerful artificial intelligent technique. The modified benchmark IEEE-39 bus test system is utilized to accomplish this study. The output results confirm that the proposed FL-NLSM can diminish the deviations of the system frequency and tie-line power between different areas effectively.