PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach

Md Shafiul Alam, Fahad Saleh Al-Ismail and Mohammad Ali Abido
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Md Shafiul Alam: K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
Fahad Saleh Al-Ismail: K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia
Mohammad Ali Abido: K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia

Sustainability, 2021, vol. 13, issue 14, 1-21

Abstract: A paradigm shift in power engineering transforms conventional fossil fuel-based power systems gradually into more sustainable and environmentally friendly systems due to more renewable energy source (RES) integration. However, the control structure of high-level RES integrated system becomes complex, and the total system inertia is reduced due to the removal of conventional synchronous generators. Thus, such a system poses serious frequency instabilities due to the high rate of change of frequency (RoCoF). To handle this frequency instability issue, this work proposes an optimized fractional-order proportional integral (FOPI) controller-based superconducting magnetic energy storage (SMES) approach. The proposed FOPI-based SMES technique to support virtual inertia is superior to and more robust than the conventional technique. The FOPI parameters are optimized using the particle swarm optimization (PSO) technique. The SMES is modeled and integrated into the optimally designed FOPI to support the virtual inertia of the system. Fluctuating RESs are considered to show the effectiveness of the proposed approach. Extensive time-domain simulations were carried out in MATLAB Simulink with different load and generation mismatch levels. Systems with different inertia levels were simulated to guarantee the frequency stability of the system with the proposed FOPI-based SMES control technique. Several performance indices, such as overshoot, undershoot, and settling time, were considered in the analysis.

Keywords: virtual inertia control; renewable energy resources; solar and wind energy; superconducting magnetic energy storage (SMES); fractional-order proportional integral (FOPI); frequency response (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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