Abstract
Energy storage system (ESS) possesses tremendous potential to counter both the rapid growth of intermittent renewable energy resources (RESs) and provide frequency support to the microgrid (MG). Since the deployment of ESS has overcome the imbalance between generation and consumption, however, their massive cost, as well as degradation tendency, are the restricting considerations that demand alternative solutions to provide stable microgrid operation. To assist ESS, the electric vehicles (EVs) are incorporated into the system. EVs have been gradually commercially viable and considerable focus has been paid to vehicle-to-grid technologies. Appropriate collaboration between ESS and EVs has good capability to manage the frequency irregularities to ensure the efficient operation of the MG. This article presents a novel combination of two control techniques i.e., model predictive control (MPC) and adaptive droop control (ADC), to tackle the frequency regulation issue in the isolated MG, by effectively controlling the ESS and EVs during the large-scale integration of RESs or huge change in load demand. Firstly, the MPC regulates the ESS according to the system frequency deviation, and secondly, the ADC manages the power of EVs according to system specifications by retaining the least possible power for potential usage of EVs. Moreover, an advanced genetic algorithm is applied to tune the MPC and ADC parameters in order to achieve optimized performance. An isolated MG is modeled and verified in MATLAB/Simulink using the above-mentioned control techniques. Further, different case studies are taken into account to validate the combination of ADC and MPC for frequency regulation of an isolated MG. Additionally, the proposed MPC controller is compared with fuzzy logic proportional-integral (FPI) controller and proportional-integral (PI) controller, the MPC provides better performance results as compared with FPI and PI controllers.
Highlights
In an electrical power grid, one of the biggest challenges is preserving the power balance between power supply and consumption
This article presented the control techniques that regulate the frequency of isolated MG in an effective manner
The adopted control technique is comprised of proportional integral controller (PI), adaptive droop control (ADC), fuzzy logic proportional integral controller (FPI) and model predictive controller (MPC) controller
Summary
In an electrical power grid, one of the biggest challenges is preserving the power balance between power supply and consumption. As stated earlier the operational band of frequency in China is small, the inclusion of RES in the electric network needs additional fortification for smooth operation especially in islanded MG For this purpose, the energy storage system (ESS) is emerged as a vital entity to be deployed in the power network to support the grid and to make possible the realization of microgrid and smart grid. The combination of the ESS and large EVs fleets can be utilized in regulating the frequency of the system rather than using huge synchronous generators through a proper control strategy for battery charge and discharge [11]. The ESS provides partial power support due to its limited capacity, a cooperative control schemes between the generating units and ESS is essential for smooth operation [14], [22]. This article is divided into five sections, the microgrid model is presented in section II, the proposed control system design in section III, the results and simulations are presented in section IV, and lastly, the conclusion is drawn
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