Smoothing of renewable energy generation using Gaussian-based method with power constraints

Addisu, Alemayehu; George, Laurent; Courbin, Pierre; Sciandra, Vincent

doi:10.1016/j.egypro.2017.09.555

Cited by 33 publications

(17 citation statements)

References 21 publications

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“…Gaussian smoothing has been widely used with image processing and computer applications. Authors in [34] use the gaussian smoothing to smooth the renewable energy generation and to highlight its capability of reducing the pitfalls of moving average filter. The performance of GF smoothing is like the moving average filter.…”

Section: Saviztky-golay Filtermentioning

confidence: 99%

Saviztky–Golay Filtering for Solar Power Smoothing and Ramp Rate Reduction Based on Controlled Battery Energy Storage

Atif

Khalid

2020

IEEE Access

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Energy is present in every touch we make in our modern life. However, with the increase of energy-consuming devices, there is a burden to meet this demand with a clean power generation. Although solar and wind are considered as clean and renewable energy resources, many issues engender with their higher penetration into electricity grids. However, when renewable energy resources are integrated with battery energy storage systems (BESS), more smoothed and easily dispatchable power can be obtained. This paper investigates the smoothing quality of the solar photovoltaic power output with the help of BESS using a couple of approaches such as low pass filtering (LPF), moving average (MA) filtering, Gaussian filter (GF) and Saviztky-Golay (S-G) filter. Obviously, the smoothed dispatchable power has been achieved with all mentioned methods, however, the performance of moving average and low pass filters is not acceptable comparatively especially when longer window size and time constant are used, which consequently deteriorates the performance of storage system. In contrast, the paper introduces using the Savitsky-Golay filter to reduce battery ramp rate and battery charging and discharging power while smoothing the solar power fluctuations. The simulation results depict the performance of the proposed smoothing filter and compare its performance against MA, LPF and GF.

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Section: Saviztky-golay Filtermentioning

confidence: 99%

Saviztky–Golay Filtering for Solar Power Smoothing and Ramp Rate Reduction Based on Controlled Battery Energy Storage

Atif

Khalid

2020

IEEE Access

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“…The objective function considers the minimization of cost, Equation (14), which includes the fuel cost, Equation (2), and start-up cost, Equation (3). The UC model considers several constraints such as spinning reserve constraint, Equation (4); OFF and ON time constraints, Equation (5)-(8); initial status of unit, Equation (9); load demand constraint, Equation (10); TG unit's power output constraint, Equation (11); generator ramp up and down constraint, as shown in Equations (12) and (13).…”

Section: Ess With Uc Programmentioning

confidence: 99%

“…Sometimes due to these reasons, within short bursts of several seconds, there may be too much power, too little power, or total blackout within the grid. The power output of WTG and PV depends on weather conditions, and power smoothing of WTG and PV outputs remains a technically challenging task [13,14]. WTG has huge ramp up and down requirements, and PV generates power only during the day, besides, they have the uncertainty of power output [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Energy Storage System Analysis Review for Optimal Unit Commitment

et al. 2019

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Energy storage systems (ESSs) are essential to ensure continuity of energy supply and maintain the reliability of modern power systems. Intermittency and uncertainty of renewable generations due to fluctuating weather conditions as well as uncertain behavior of load demand make ESSs an integral part of power system flexibility management. Typically, the load demand profile can be categorized into peak and off-peak periods, and adding power from renewable generations makes the load-generation dynamics more complicated. Therefore, the thermal generation (TG) units need to be turned on and off more frequently to meet the system load demand. In view of this, several research efforts have been directed towards analyzing the benefits of ESSs in solving optimal unit commitment (UC) problems, minimizing operating costs, and maximizing profits while ensuring supply reliability. In this paper, some recent research works and relevant UC models incorporating ESSs towards solving the abovementioned power system operational issues are reviewed and summarized to give prospective researchers a clear concept and tip-off on finding efficient solutions for future power system flexibility management. Conclusively, an example problem is simulated for the visualization of the formulation of UC problems with ESSs and solutions.

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“…A MM filter has been proposed and compared against the LPF and MA filters in [53], simulation results concluded that the MM filter with window sizes equal to that of a MA filter results in better power tracking but at the cost of poorer degree of solar power smoothing. Literature [58] proposes the use of a GF filter to smooth the power from different renewable energy sources. Nonetheless, it has been concluded in [59] that a Gaussian filter tends to over smooth the power which results in the loss of the power signal characteristics, this in turn causes more energy to be drawn from the battery thereby decreasing its lifetime.…”

Section: Introductionmentioning

confidence: 99%

Moving Regression Filtering With Battery State of Charge Feedback Control for Solar PV Firming and Ramp Rate Curtailment

Syed

Khalid

2021

IEEE Access

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The surge in energy demand needs to be met with environmentally pleasant resources to reduce the production of greenhouse gases. Solar Photovoltaic (PV) power is a widespread choice as it is accessible in plenty and is comparatively inexpensive. However, the large-scale penetration of intermittent PV power causes multiple variabilities in the grid such as frequency issues and voltage deviations. To counteract these instabilities, Battery Energy Storage System (BESS) is integrated into the grid as it reduces the PV fluctuations and promotes optimal operation. Nevertheless, storage systems are expensive, and thus smoothing filters are coupled with the BESS for cost reduction and power smoothing. Formerly, traditional filters such as Low Pass Filters (LPF), Moving Average (MA), and Moving Median (MM) filters have been proposed for power smoothing. However, these filters have inadequate power tracking capabilities particularly with longer window sizes (W.S) and time constants, which subsequently depreciates the storage system performance. To compensate for the delayed power tracking, larger energy storage systems are required which in turn adds to the overall operational costs. This paper proposes the Moving Regression (MR) filter combined with state of charge (SoC) feedback control for solar PV variability reduction, reduced time delay, decreased battery charging/discharging power, and ramp rate. Simulation results attest that the MR filter achieves better solar power smoothing without increasing the BESS capacity. Also, the performance of the MR filter is less affected with the increase in window sizes. Additionally, the execution of the introduced smoothing filter was found to be superior when assessed against the LPF, MA, MM, Savitsky-Golay (SG), and the Gaussian filter. In comparison to the SG (W.S = 53), the MR (W.S = 45) filter reduces the battery charging/discharging power by approximately 30.48% and as opposed to the LPF (T.C = 48), the peak SoC is reduced by 19.1%.INDEX TERMS Battery energy storage system, low pass filter, machine learning, moving average filter, moving regression filter, renewable energy, solar power smoothing.

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Smoothing of renewable energy generation using Gaussian-based method with power constraints

Cited by 33 publications

References 21 publications

Saviztky–Golay Filtering for Solar Power Smoothing and Ramp Rate Reduction Based on Controlled Battery Energy Storage

Saviztky–Golay Filtering for Solar Power Smoothing and Ramp Rate Reduction Based on Controlled Battery Energy Storage

Energy Storage System Analysis Review for Optimal Unit Commitment

Moving Regression Filtering With Battery State of Charge Feedback Control for Solar PV Firming and Ramp Rate Curtailment

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