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 language | English |
|---|---|
| Title of host publication | 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538628904 |
| DOIs | |
| Publication status | Published - 2017 Oct 26 |
| Event | 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 - Washington, United States Duration: 2017 Apr 23 → 2017 Apr 26 |
Other
| Other | 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 |
|---|---|
| Country/Territory | United States |
| City | Washington |
| Period | 17/4/23 → 17/4/26 |
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
