•Discrepancy fluctuation is considered besides synchronous and reverse fluctuations.•Degrees of synchronous, reverse, and discrepancy fluctuation states are considered.•The proposed index is superior ...to the correlation-based complementarity index.•The proposed index can optimize the wind-solar power installed capacity ratio.
Assessing complementarity is a foundational work to combine wind and solar power to mitigate their fluctuations. Correlation coefficient is the most commonly used index to assess complementarity. But correlation coefficient mainly quantifies the synchronous and reverse correlations between wind and solar power. Moreover, it ignores the fluctuation amplitudes of wind and solar power, which would misestimate the complementarity. To address the issue, a novel complementarity index is proposed considering both the fluctuation states and corresponding fluctuation amplitudes. The present study firstly divides the fluctuations of wind and solar power into synchronous, reverse, and discrepancy fluctuation states. Then the degrees of the three different fluctuation states are obtained according to the score rules considering the fluctuation amplitudes. Finally, the novel complementarity index is jointly determined by these fluctuation degrees. Validation results show that the proposed index successfully avoids the misestimation scenarios caused by using correlation coefficient to assess complementarity. Then the proposed index is applied to analyze the complementarity of wind and solar power in China on hourly, daily, and monthly time scales. The complementarity index is generally −0.11–0 on the hourly time scale in most regions of Jilin, Heilongjiang, Liaoning, Inner Mongolia, northern Gansu, southern Xinjiang, and the North China Plain, showing greater complementarity than other onshore regions. But the complementarity index is generally 0–0.3 in most of the aforementioned regions on the monthly time scale, implying that the complementarity on the monthly time scale is smaller than that on the hourly time scale. The complementarity indices in most offshore regions are −0.1–0, −0.12–0 and −0.2–0, respectively, on the hourly, daily, and monthly time scales. Further analysis reveals that the complementarity between wind and solar power would be overestimated once the fluctuation amplitude is ignored. Additionally, the proposed complementarity index can be used to optimize the installed capacity ratio of wind and solar power in a hybrid system. The proposed complementarity metric contributes to a better and more accurate understanding of the complementarity between wind and solar power. Furthermore, the proposed metric can be readily applied to assess the complementarity of other renewable power generations.
One of the short-coming challenges of power systems operation and planning is the difficulty to quantify the variability of power systems Kinetic Energy (KE) to unveil online additional information ...for the system operators' decisions support. KE monitoring requires innovative methods to analyse the continuous fluctuations in the KE power's systems. In this paper, we propose the use of information theory, specifically the concept of Information Length (IL), as a way to provide useful insights into the power system KE variability and to demonstrate its utility as a starting point in decision making for power systems management. The proposed IL metric is applied to monthly collected data from the Nordic Power System during three consecutive years in order to investigate the KE evolution. Our results reveal that the proposed method provides an effective description of the seasonal statistical variability enabling the identification of the particular month and day that have the least and the most KE variability. Additionally, by applying a Long Short-Term Memory (LSTM) neural network model to estimate the value of the IL on-line, we also show the possibility of using the metric as data-driven support.
We quantify investors' preferences over the dynamics of shocks by deriving frequency-specific risk prices that capture the price of risk of consumption fluctuations at each frequency. The ...frequency-specific risk prices are derived analytically for leading models. The decomposition helps measure the importance of economic fluctuations at different frequencies. We precisely quantify the meaning of "long-run" in the context of Epstein-Zin preferences -centuries -and measure the exact relevance of business-cycle fluctuations. Finally, we estimate frequency-specific risk prices and show that cycles longer than the business cycle -long-run risks -are significantly priced in the equity market.
This study has investigated a technique that replicates waveform fluctuations of speech signals by combining partials of limited Q, a parameter defined as the ratio dividing a center frequency of a ...resonance by its bandwidth. This paper shows that the proposed technique may potentially generate amplitude and period fluctuations of 1/f-like frequency characteristics, which are considered to be one of the indices reflecting the naturalness of human speech.
Due to the uncertain effects on economic growth and economic fluctuations caused by environmental policies, the best means of choosing the most appropriate environmental policy remains controversial. ...In the face of various uncertain economic factors, economic fluctuation is an important criterion for evaluating different environmental policies. Thus, we established an environmental dynamic stochastic general equilibrium model under New Keynesian framework embodying nominal price rigidities, environmental policies, pollutant emissions and real uncertainties with the aim of comparing the impacts of different environmental policies on the macroeconomic fluctuations. The results are as follows. First, the responses indicate that all kinds of environmental policies are counter-cyclical. Emissions intensity policy has the strongest effect on curbing fluctuations. Second, a positive energy efficiency shock will lead to a corresponding increase in energy inputs, which is referred to as the energy rebound effect, as well as a rise in pollutant emissions. Third, an emissions intensity shock will exert greater impacts than environmental tax rate shock and emissions cap shock. Fourth, the lower is the price dispersion the less intermediate goods are needed, and, consequently, the lower are the pollutant emissions. Taken together, the results highlight the policy implications associated with choosing an environmental policy.
•We set up a scenario-based dynamic stochastic general equilibrium (DSGE) model.•We explored the impacts of environmental policies on economic fluctuations.•We simulated the effects of tax rate, emissions cap and emissions intensity shocks.•Environmental policies are counter-cyclical in terms of smoothing fluctuations.
Advanced field-effect transistors (FETs), such as gate-all-around (GAA) nanowire (NW) and nanosheet (NS) devices, have been highly scaled; therefore, they are critically affected even by a ...microscopic fluctuation. As the GAA NS device is considered a promising candidate beyond 5-nm technology, it is essential to analyze the effects of these fluctuations on dc and analog/radio frequency (RF) characteristics for future applications. In this article, we for the first time demonstrate that the machine learning (ML)-aided numerical device simulation approach can be used to model the effects of various fluctuations on the characteristics of GAA NS FETs (NSFETs). Among various fluctuations, we mainly focus on work function fluctuation (WKF), random dopant fluctuation (RDF), and interface trap fluctuation (ITF). The independent and combined effects of these fluctuations on the characteristics of NSFETs are studied. Except for transfer and output characteristics, analog and RF parameters, such as gate capacitance, transconductance, cutoff frequency, 3-dB frequency, and transconductance efficiency, are analyzed in detail. The main aim of this work is to show the capability and generality of ML in modeling various electrical characteristics of the explored NSFETs. The results show that the ML-based technique is fast and efficient, which accelerates the overall process and gives engineering acceptable accurate results.
Gross Worker Flows over the Business Cycle Krusell, Per; Mukoyama, Toshihiko; Rogerson, Richard ...
The American economic review,
11/2017, Volume:
107, Issue:
11
Journal Article
Peer reviewed
Open access
We build a hybrid model of the aggregate labor market that features both standard labor supply forces and frictions in order to study the cyclical properties of gross worker flows across the three ...labor market states: employment, unemployment, and nonparticipation. Our parsimonious model is able to capture the hey features of the cyclical movements in gross worker flows. Despite the fact that the wage per efficiency unit is constant over time, intertemporal substitution plays an important role in shaping fluctuations in the participation rate.
Macroscopic fluctuation theory Bertini, Lorenzo; De Sole, Alberto; Gabrielli, Davide ...
Reviews of modern physics,
06/2015, Volume:
87, Issue:
2
Journal Article
Peer reviewed
Open access
The statistical mechanics of systems out of equilibrium provides a formidable challenge. This review describes an approach to a subset of such problems, viz., stationary nonequilibrium states. The ...review includes what is known as the macroscopic fluctuation theory, which allows for the definition of nonequilibrium analogs of thermodynamics potentials, and is applied to various illustrative models. Stationary nonequilibrium states describe steady flows through macroscopic systems. Although they represent the simplest generalization of equilibrium states, they exhibit a variety of new phenomena. Within a statistical mechanics approach, these states have been the subject of several theoretical investigations, both analytic and numerical. The macroscopic fluctuation theory, based on a formula for the probability of joint space-time fluctuations of thermodynamic variables and currents, provides a unified macroscopic treatment of such states for driven diffusive systems. A detailed review of this theory including its main predictions and most relevant applications is given.
It is high time we rediscovered the role of the financial cycle in macroeconomics. In the environment that has prevailed for at least three decades now, it is not possible to understand business ...fluctuations and the corresponding analytical and policy challenges without understanding the financial cycle. This calls for a rethink of modelling strategies and for significant adjustments to macroeconomic policies. This essay highlights the stylised empirical features of the financial cycle, conjectures as to what it may take to model it satisfactorily, and considers its policy implications. In the discussion of policy, the essay pays special attention to the bust phase, which is less well explored and raises much more controversial issues.
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