Asymmetric GARCH type models for asymmetric volatility characteristics analysis and wind power forecasting

Chen, Hao; Zhang, Jianzhong; Tao, Yubo; Tan, Fenglei

doi:10.1186/s41601-019-0146-0

Cited by 24 publications

(15 citation statements)

References 17 publications

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“…Table 6 above shows the estimation results of GJR-GARCH model for determining the Contagion effect of stock market volatility in the SAARC region. Chen et al [ 68 ] the presence of asymmetric conditional volatility in GARCH models is verified by the asymmetric parameters. Results indicate that the coefficient of ARCH (α) and GARCH (β) for all the indices were positive and statistically significant with P -values < 0.05, indicating existence of ARCH effect and presence of volatility clustering among the indices studied.…”

Section: Results and Interpretationmentioning

confidence: 99%

Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region

Saleem

2021

Ann. Data. Sci.

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The Southern Region has reported a large number of contagious pandemic outbreaks. These epidemics brought threats to human health and resulted in serious economic losses. The COVID-19 is a global virus and has weakened the global financial markets with significant effect on stock returns and market volatilities. The study obtained a dataset about the financial market structure of South Asian Association for Regional Cooperation (SAARC) Countries. The purpose of the study is to determine the effect of 2019-nCov on stock market performance of SAARC member states. The study considered indexes of the National Stock Exchanges of each country and applied an event study approach for estimating the impact of Mad COVID-19 on the stock returns and market volatilities with an event window of 25 days of severe pandemic hits. The CAR approach proved the declining effect of Mad COVID-19 on the stock returns of SAARC countries. Asymmetric GJR-GARCH Model estimated the changeable volatility and proved the increase in volatility with COVID-19 as a negative shock. SAARC Region significantly reacts to Mad COVID-19 with falling markets and rising volatility.

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Section: Results and Interpretationmentioning

confidence: 99%

Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region

Saleem

2021

Ann. Data. Sci.

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“…A limitation is that the forecasting error is high. Hao Chen et al [24], performed wind power forecasting based on GARCH type models, and the limitation accuracy was improved.…”

Section: )mentioning

confidence: 99%

Accurate prediction of different forecast horizons wind speed using a recursive radial basis function neural network

Madhiarasan¹

2020

Prot Control Mod Power Syst

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Environmental considerations have prompted the use of renewable energy resources worldwide for reduction of greenhouse gas emissions. An accurate prediction of wind speed plays a major role in environmental planning, energy system balancing, wind farm operation and control, power system planning, scheduling, storage capacity optimization, and enhancing system reliability. This paper proposes an accurate prediction of wind speed based ona Recursive Radial Basis Function Neural Network (RRBFNN) possessing the three inputs of wind direction, temperature and wind speed to improve modern power system protection, control and management. Simulation results confirm that the proposed model improves the wind speed prediction accuracy with least error when compared with other existing prediction models.

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“…For example, the installed capacity of renewable energy with wind and hydropower as the main installed capacity reached 7.94 million kilowatts by the end of 2019 in China, and their installed capacity increased by 9% year on year, which accounted for 39.5% of the total installed capacity [6]. However, in the context of the increasing installed capacity of renewable energy such as wind and hydropower, the operation security problem of power systems is more prominent [7]. Especially in extreme weather environments such as typhoons, wind farms and hydropower stations are affected to various degrees.…”

Section: Introduction 1impact Of Natural Disasters On the Power Grid And The Increase In Installed Capacity Of Renewable Energy Power Genmentioning

confidence: 99%

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

Qian¹,

Chen²,

Chen

et al. 2021

Energies

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Typhoons and other natural disasters affect the normal operation of power systems thus it is an important goal for strong and intelligent power grid construction to improve the ability of power systems to resist typhoons and other natural disasters. Especially, an effective coordinated and optimized dispatching strategy for a multi-source power system is greatly helpful to cope with the impact of typhoons and other natural disasters on power system operation. Given this background, a typhoon wind circle model considering the temporal and spatial distribution of typhoons is established to obtain the input wind speed of the wind farm at first. Second, based on the initial input wind speed of wind farms, a typical scenario set of wind power output is constructed to reflect its fluctuation and uncertainty. Next, an optimal coordinated dispatching model of a multi-source power system with wind, hydro and thermal power based on the conditional value at risk (CVaR) is established with the target of minimizing the total cost of system dispatching, in which a 72 h pre-dispatching mode is studied to optimize the system operation for 72 h on the day before, on and after the typhoon. Finally, a revised 24-node transmission network system in a coastal area with typhoon is served as a case for demonstrating the effectiveness of the proposed model, and the simulation result shows that the proposed model could take the advantages of the coordination and complementarity of multi-sources power system and decrease the total cost of system dispatching and improve the renewable energy consumption level.

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Asymmetric GARCH type models for asymmetric volatility characteristics analysis and wind power forecasting

Cited by 24 publications

References 17 publications

Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region

Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region

Accurate prediction of different forecast horizons wind speed using a recursive radial basis function neural network

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

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