In renewable microgrid systems, energy storage system (ESS) plays an important role, as an energy buffer, to stabilize the system by compensating the demand-generation mismatch. Battery energy storage system serves as a decisive and critical component. However, due to low power density and consequently slow dynamic response the lifetime of BESS is observably reduced due to high current stress, specifically experienced during abrupt/transient power variations. Hence, hybridization with supercapacitor storage system is conferred. Additionally, the controllers designed for energy storage systems should substantially respond for compensating the transient requirement of the system. In this article, we propose a decoupled control strategy for batteries and supercapacitors based on k -Type compensators and a nonlinear PI controller (NPIC) respectively. The formulated control design is tested for voltage regulation in a standalone microgrid. Furthermore, a comparative analysis is presented with benchmark low-pass-filter (LPF) based controller. The results obtained shows the proposed control technique possess a faster response with improved voltage regulation capabilities. For the test system regulated at 48 V for various abrupt load-generation various case studies presented, the proposed methodology maintains a significantly reduced voltage deviation between 47 V -51 V in contrast to 45 V -56 V observed in the LPF methodology. Furthermore, the complexity is simpler in comparison to LPF based control strategy and a comparative obviation of additional sensing devices is achieved, that inherently reduces the detrimental effect on ESS response during transient condition.

Nonlinear equations governing the dynamics of low-frequency (in comparison with electron gyro-frequency) electrostatic disturbances in a nonuniform resistive dust-contaminated electron-positron magnetoplasma with equilibrium sheard flow are derived. In the linear limit, a local dispersion relation has been derived and analyzed. On the other hand, in the nonlinear case, the temporal behavior of the nonlinear system can be represented in the form of a 5 × 5 matrix, which is a generalization of Lorenz-Stenflo equations admitting chaotic trajectories. We have also presented a linear stability analysis of a generalized Lorenz-Stenflo system of equations under different approximations. It is also shown that for small magnetic shear and for a nondissipative plasma, a quasi-stationary solution of the mode coupling equations can be represented in the form of counter-rotating vortices. These results would be helpful to understand plasma turbulence and wave phenomena which have frequently been observed in several laboratory and astrophysical plasma systems.

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Integration of renewable energy sources (RES) in a distribution network facilities the establishment of sustainable power systems. Concurrently, the incorporation of energy storage system (ESS) plays a pivotal role to maintain the economical significance as well as mitigates the technical liabilities associated with uncontrollable and fluctuating renewable output power. Nevertheless, ESS technologies require additional investments that imposes a techno-economic challenge of selection, allocation and sizing to ensure a reliable power system that is operationally optimized with reduced cost. In this paper, a deterministic cost-optimization framework is presented based on a multi-input nonlinear programming to optimally solve the sizing and allocation problem. The optimization is performed to obviate the demand-generation mismatch, that is violated with the introduction of variable renewable energy sources. The proposed optimization method is tested and validated on an IEEE 24-bus network integrated with solar and wind energy sources. The deterministic approach is solved using GAMS optimization software considering the system data of one year. Based on the optimization framework, the study also presents various different scenarios of renewable energy mix in combination with advanced ESS technologies to outline an technical as well as economical framework for ESS sizing, allocation, and selection. Based on the optimal results obtained, the optimal sizing and allocation were obtained for lead-acid, lithium-ion, nickel-cadmium and sodium-sulfur (NaS) battery energy storage system. While all these storage technologies mitigated the demand-generation mismatch with optimal size and location. However, the NaS storage technology was found to be the best among the given storage technologies for the given system minimum possible cost. Furthermore, it was observed that the cost of hybrid wind-solar mix system results in the lowest overall cost.

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