Fractional Cascade LFC for Distributed Energy Sources via Advanced Optimization Technique Under High Renewable Shares

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Abstract

Unpredictable high renewable shares in a standalone microgrid (MG) system with stochastic load demands introduces an unavoidable mismatch among loads and sources. This mismatch directly impacts the system frequency, which can be mitigated via applying a suitable load frequency control (LFC) scheme. This brief proposes a maiden attempt of marine predator algorithm (MPA) assisted one plus proportional derivative with filter-fractional order proportional-integral ((1+PDF)-FOPI) controller to obtain the proper power flow management among loads and sources. The investigated MG system consists of a photovoltaic (PV) system, a wind turbine (WT) generator (WTG), and a diesel engine generator (DG) as the distributed energy sources, and an ultracapacitor (UC) and a flywheel are chosen as the energy storage elements (ESEs). Various system nonlinearities, such as governor dead-band (GDB) and generation rate constraint (GRC) are also considered to reflect the practical scenario. Five state-of-the-art optimization techniques and three traditional controllers, PID, FOPID, and PI-PD, are vividly compared to assess the proposed scheme's performance. The parametric uncertainties are considered obtaining the robust performance of the proposed control scheme. An eigenvalues-based stability evaluation of the considered plant employing the proposed LFC scheme is also included in this work. In the worst situation, the maximum frequency deviation is obtained as -0.016 Hz, which is entirely satisfactory and under the range of the IEEE standard. Finally, a modified New England IEEE-39 test bus system is chosen to perform the real power system validation via MATLAB/Simulink.

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APA

Pathak, P. K., Yadav, A. K., Padmanaban, S., & Kamwa, I. (2022). Fractional Cascade LFC for Distributed Energy Sources via Advanced Optimization Technique Under High Renewable Shares. IEEE Access, 10, 92828–92842. https://doi.org/10.1109/ACCESS.2022.3202907

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