RESUMO
As the penetration of renewable energy increases to a large scale and power electronic devices become widespread, power systems are becoming prone to synchronous oscillations (SO). This event has a major impact on the stability of the power grid. The recent research has been mainly concentrated on identifying the parameters of sub-synchronous oscillation. Sub/Super synchronous oscillations (Sub/Sup-SO) simultaneously occur, increasing the difficulty in accurately identify the parameters of SO. This work presents a novel method for parameter identification that effectively handles the Sub/Sup-SO components by utilizing the Rife-Vincent window and discrete Fourier transform (DFT) simultaneously. To mitigate the impact of spectral leakage and the fence effect of DFT, we integrate the tri-spectral interpolation algorithm with the Rife-Vincent window. We use the instantaneous data of the phasor measurement unit (PMU) to identify Sub/Sup-SO-related parameters (Sub/Sup-SO damping ratio, frequency, amplitude and phase). First, the spectrum of the Sub/Sup-SO signals is analyzed after incorporating the Rife-Vincent window, and the characteristics of the Sub/Sup-SO signal are determined. Then, the signal spectrum is identified using a three-point interpolation algorithm, and the damping ratio, amplitude, frequency, and phase of the Sub/Sup-SO signals are obtained. In addition, we consider the identification accuracy of the algorithm under various complex conditions, such as the effect of Sub/Sup-SO parameter variations on parameter identification in the presence of a non-nominal frequency and noise. The proposed algorithm accurately identifies the parameters of multiple Sub/Sup-SO components and two Sub-SO components that are in close proximity. Testing with synthetic and real data demonstrates that the proposed algorithm outperforms existing methods in terms of identification accuracy, identification bandwidth, and adaptability.
RESUMO
The outbreak of the COVID-19 pandemic has brought significant changes to the power sector. This study proposes general and coherent methodological steps to explore the future impact of lockdown measures on the power sector. In a case study from the Netherlands, two lockdown levels were defined and simulated to identify the influence of the pandemic upon the sector. Moreover, four renewable scenarios were developed to represent the green transition of the Netherlands' power sector up to 2035. For this future power sector, the results show that the green transition can achieve a reduction of 65% in CO2 emissions and 20% in power sector cost. Under the implementation of a simulated lockdown level, electricity demand decreased by 6.3% under Level 1 and 11.9% under Level 2 in 2035. The influences of lockdowns on future power sectors differ with respect to scenario. In addition, Lockdown Level 1 leads to a reduction of 8-12% in emissions and a reduction of 6-8% in cost, and Lockdown Level 2 expands this reduction to 15-21% in emissions and 11-13% in cost. The findings of this exploratory study can elucidate what may happen in the future green power sector if such event arises.
RESUMO
The COVID-19 pandemic affects all the aspects of modern society worldwide, especially in the power sector. Measures of flexibility enhancement are regarded as solutions to guarantee reliable and flexible electricity supply in such an emergency. This study aims at investigating the impact of flexibility enhancement measures (electricity storage and flexible demand) in different situations of the preliminary COVID-19 pandemic. Case studies in different regions (Denmark, the Netherlands, and the Sichuan province of China) are conducted and assessed using the hourly simulation tool EnergyPLAN. These regions own different electricity supply mix and level of renewable electricity. It is found that the flexible demand measure within one day or one week can hardly eliminate the electricity imbalance caused by either the pandemic or the increasing renewable electricity. The monthly flexible demand is effective for balancing, but its potential in these regions is not enough. However, electricity storage measure enhances the electricity balance even during the most extreme situation of the pandemic. From the economic perspective, electricity storage measure leads to an increase of up to 15% in total system costs, while flexible demand measure has a negligible effect on costs. This study serves as the first step to understand the performance of flexibility enhancement measures in the power sector under the shock of a pandemic.
RESUMO
Nickel cobalt manganese ternary cathode materials are some of the most promising cathode materials in lithium-ion batteries, due to their high specific capacity, low cost, etc. However, they do have a few disadvantages, such as an unstable cycle performance and a poor rate performance. In this work, polyethylene oxide (PEO) with high ionic conductance and flexibility was utilized as a multifunctional binder to improve the electrochemical performance of LiNi0.6Co0.2Mn0.2O2 cathode materials. Scanning electron microscopy showed that the addition of PEO can greatly improve the adhesion of the electrode components and simultaneously enhance the integrity of the electrode. Thus, the PEO-based electrode (20 wt% PEO in PEO/PVDF) shows a high electronic conductivity of 19.8 S/cm, which is around 15,000 times that of the pristine PVDF-based electrode. Moreover, the PEO-based electrode exhibits better cycling stability and rate performance, i.e., the capacity increases from 131.1 mAh/g to 147.3 mAh/g at 2 C with 20 wt% PEO addition. Electrochemical impedance measurements further indicate that the addition of the PEO binder can reduce the electrode resistance and protect the LiNi0.6Co0.2Mn0.2O2 cathode materials from the liquid electrolyte attack. This work offers a simple yet effective method to improve the cycling performance of the ternary cathode materials by adding an appropriate amount of PEO as a binder in the electrode fabrication process.
