Sizing and Operation of a Hybrid Energy Storage System to Compensate Forecast Errors of Wind Farms - An Approach

Soliman, Ramy; Bierhoff, Michael

doi:10.1109/isie51582.2022.9831749

Cited by 1 publication

(1 citation statement)

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“…The grid-level MPC at the top layer scheduled energy between microgrid subarrays based on the power demand of the whole system and the discharge state of each subarray. The converter-level MPC at the bottom layer was used for power management within the microgrid subarrays to ensure the SOC balance of the battery in each subarray [28]. The upper grid-level MPC provided the reference power, P ref , for each distributed microgrid subarray.…”

Section: Soc-based Model Predictive Controlmentioning

confidence: 99%

Energy Balance in a Standalone PV Battery Hybrid Generation System on Solar-Powered Aircraft Using the Model Predictive Control Method

Xu,

Lei,

Liu

et al. 2023

Energies

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This paper proposes a battery state of charge (SOC)-based energy management strategy using hierarchical distributed model predictive control (HDMPC) for a standalone microgrid on solar-powered long-endurance aircraft. The microgrid was innovatively designed as a two-layer structure in which the first layer consists of a photovoltaic generation and battery storage system named the PV battery module (PBM). The second layer, named the microgrid subsystem (MGSS), consists of several PBMs, each of which supplies power to a specific DC load on the aircraft. The control system is divided into two levels: the grid-level model predictive control (MPC) and the converter-level MPC. The grid-level MPC adopts a distributed model predictive control strategy to obtain the reference power of each module. The converter-level MPC calculates the control variables of converters using a supervisory model predictive control (SMPC) strategy. The new microgrid structure and the proposed control strategy have improved the reliability of the energy system and increased its energy utilization rate.

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Section: Soc-based Model Predictive Controlmentioning

confidence: 99%