Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model

Nhung Nguyen-Hong, Yosuke Nakanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, renewable energy has become a very viable alternative solution to provide electricity. However, the uncertainty of renewable energy changes traditional issues in operation and control of power system. This paper proposes a Stochastic Dynamic Power Flow Analysis to evaluate state variables' probability distribution at any time t. Stochastic process of renewable energy is modeled and simulated by ARMA-GARCH model. The Stochastic Response Surface Method is also applied to increase computational efficiency with the same accuracy as Monte Carlo simulation. Stochastic Dynamic Power Flow Analysis is applied to IEEE 30-bus system and time dependent probability distribution of voltage, frequency and network loss will be analyzed.

Original languageEnglish
Title of host publication2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538628904
DOIs
Publication statusPublished - 2017 Oct 26
Event2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 - Washington, United States
Duration: 2017 Apr 232017 Apr 26

Other

Other2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
CountryUnited States
CityWashington
Period17/4/2317/4/26

Fingerprint

ARMA Model
GARCH Model
Power Flow
Renewable Energy
Stochastic Dynamics
Probability distributions
Probability Distribution
Computational efficiency
Random processes
Loss Networks
Response Surface Method
Electricity
Stochastic Methods
Power System
Computational Efficiency
Stochastic Processes
Electric potential
Monte Carlo Simulation
Voltage
Uncertainty

Keywords

  • ARMA-GARCH
  • Dynamic power flow
  • Renewable energy
  • Stochastic power flow
  • Wind power

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

Cite this

Nguyen-Hong, N., & Nakanishi, Y. (2017). Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model. In 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 [8086059] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT.2017.8086059

Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model. / Nguyen-Hong, Nhung; Nakanishi, Yosuke.

2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8086059.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nguyen-Hong, N & Nakanishi, Y 2017, Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model. in 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017., 8086059, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017, Washington, United States, 17/4/23. https://doi.org/10.1109/ISGT.2017.8086059
Nguyen-Hong N, Nakanishi Y. Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model. In 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8086059 https://doi.org/10.1109/ISGT.2017.8086059
Nguyen-Hong, Nhung ; Nakanishi, Yosuke. / Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model. 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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