Double Moving Average Methodology for Smoothing of Solar Power Fluctuations with Battery Energy Storage

Syed, Miswar Akhtar; Atif, Ammar; Al-Hamdi, A.; Khalid, Muhammad

doi:10.1109/sges51519.2020.00058

Cited by 11 publications

(5 citation statements)

References 29 publications

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“…As indicated in (7), battery SoC control is used to govern the battery storage capacity. Thus, output of the battery is the sum of storage capacity margins, charging/discharging power, and the flattened wind-PV power [34,35].…”

Section: Microgrid With Hydrogen Elctrolyzer Fuel Cell Systemmentioning

confidence: 99%

“…The scheme approach of charging and discharging BESS is another frequently utilized way for power smoothing with BESS [33] that necessitates frequent switching between charging and draining of the BESS. Failure to maintain recurrent shifting between BESS discharging and charging will have an impact on wind fluctuation management and could lead to overcharge and deep discharge of the battery [34,35]. As a response, it is essential to control the battery charging levels and to supply the necessary power to stabilize the fluctuating renewable power production [36].…”

Section: Introductionmentioning

confidence: 99%

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An Intelligent Model Predictive Control Strategy for Stable Solar-Wind Renewable Power Dispatch Coupled with Hydrogen Electrolyzer and Battery Energy Storage

Syed

Khalid

2023

International Journal of Energy Research

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Renewable energy sources such as photovoltaic (PV) and wind power are widely used; however, their intermittent nature impairs power supply quality by creating frequency distortions and irregularities in voltage. Battery energy storage systems (BESS) are utilized to flatten out and relieve fluctuation issues. To prevent the need for larger storage systems and to prolong their operational life through controlled charging and discharging, a method of control for BESS charging level regulation is necessary. This study presents a solar-wind power and battery state of charge (SoC) control technique using a hydrogen electrolyzer (HE) fuel cell unit. An Intelligent Model Predictive Controller (IMPC) has been developed that utilizes a neural network (NN) plant model for predictive minimization instead of using a mathematical plant model for dynamic management of the HE output, which allows for flattened PV-wind power supply with regulated BESS charging and discharging. The IMPC accepts as inputs the intermittent renewable power and different battery attributes and intelligently manages the HE production while staying within the imposed restrictions. The NN, as opposed to a mathematical plant model, captures the dynamics of the plant with exceptionally high accuracy. Moreover, the NN plant model performance increases as the data gathered from the actual system increases. The neural network model resolves concerns with the MPC model’s mathematical intricacy that occurs as the plant becomes more complicated. According to simulation results, the IMPC greatly reduces PV-wind power fluctuations, for solar power, the IMPC reduces the peak battery SoC by 26.7% and compared to FLC, the peak SoC is reduced by 11.2%. Similarly, for wind power, the peak SoC is reduced by 7.3% and is decreased 3.2% more than the FLC. To demonstrate the power smoothing effectiveness of the IMPC, the peak solar power ramp rate is reduced by 30.3% and the peak wind power ramp rate is reduced by 91.3%. The presented method encourages green hydrogen usage in the electrical sector for supplying firmed solar and wind power.

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Section: Microgrid With Hydrogen Elctrolyzer Fuel Cell Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Intelligent Model Predictive Control Strategy for Stable Solar-Wind Renewable Power Dispatch Coupled with Hydrogen Electrolyzer and Battery Energy Storage

Syed

Khalid

2023

International Journal of Energy Research

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“…Energy storage systems (ESS) can effectively improve the inertia of PV systems due to their fast and flexible power regulation capability and achieve power smoothing of PV power generation while ensuring the maximum power output of PV arrays. Therefore, using energy storage to smooth out the power fluctuations of PV power generation is the focus of current research [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Research on PV power fluctuation smoothing control strategy based on ESS

Sun,

Wang,

et al. 2023

3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023)

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Energy storage systems can effectively improve the inertia of PV systems and achieve power smoothing of PV power generation due to their fast and flexible power regulation capability. This study proposes a BESS charging and discharging control method with limited PV fluctuation smoothing for the capacity optimization of energy storage in high permeability PV grids. This method can reduce the number of times the BESS is charged and discharged and improve its service life while smoothing out large fluctuations in PV power output.

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“…The moving average algorithm and the double moving average algorithm are used in (Jiang and Hong, 2012) and (Prasad et al, 2022), respectively. The low-pass filtering algorithm considering the state of charge (SOC) of the energy storage system is designed in (Huixiang et al, 2020) and (Syed et al, 2020). However, the low-pass filtering algorithm has a delay problem that is difficult to overcome.…”

Section: Introductionmentioning

confidence: 99%

Power allocation method of battery energy storage system considering state balance in smoothing photovoltaic power fluctuations

Zhang¹,

Hou²,

Diao³

et al. 2022

Front. Energy Res.

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Aiming at the imbalances of SOC (state of charge, SOC) and SOH (state of health, SOH) for battery energy storage system (BESS) in smoothing photovoltaic power fluctuations, a power allocation method of BESS is proposed. Firstly, the hierarchical structure of the power allocation method is given, including acquisition of the grid-connected photovoltaic power reference and double-layer power allocation strategy for BESS. Secondly, a swing door trend algorithm optimized by the improved Aquila optimizer is devised and used to deal with the raw photovoltaic power to obtain the grid-connected signal. Next, the dynamic grouping principle considering the SOC and SOH of battery units is devised, and the double-layer power allocation method of BESS is designed in terms of the dynamic grouping results of battery units. Finally, the proposed power allocation method is simulated through actual data, and the results compared with other methods show that it can smooth photovoltaic power fluctuations more effectively, and the SOC and SOH can be balanced more quickly and accurately, which verifies its effectiveness.

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Double Moving Average Methodology for Smoothing of Solar Power Fluctuations with Battery Energy Storage

Cited by 11 publications

References 29 publications

An Intelligent Model Predictive Control Strategy for Stable Solar-Wind Renewable Power Dispatch Coupled with Hydrogen Electrolyzer and Battery Energy Storage

An Intelligent Model Predictive Control Strategy for Stable Solar-Wind Renewable Power Dispatch Coupled with Hydrogen Electrolyzer and Battery Energy Storage

Research on PV power fluctuation smoothing control strategy based on ESS

Power allocation method of battery energy storage system considering state balance in smoothing photovoltaic power fluctuations

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