| Abstract |
Modern power systems are experiencing a rapid movement from fossil-based generations to renewable energy resources (RERs) due to concerns about the environment and the dependence on fossil fuel sources. However, the replacement of conventional generation with intermittent and low inertia RERs in the power grid can negatively affect system regulation capability. Also, the increasing integration of electric vehicles (EVs) presents concerns over power system stability and reliability. To maintain the frequency of the system within stable limits, load frequency control (LFC) regulates the power output of the generating units in response to the changes in load demand. Therefore, appropriate control strategies and optimization algorithms are required for effective LFC while RER/EV penetration increases. In this paper, an advanced LFC model of a multi-area interconnected system with EV and RER integration is developed which considers the change in system inertia that arises from generator outages or the replacement of conventional units with RERs. A non-sequential Monte Carlo simulation (MCS) is implemented to calculate the system inertia and regulation capacity of each area considering the generator failure rates and load changes. The contribution of inertial response and primary frequency regulation from EVs to the system is assessed using a simulation-based approach. A particle swarm optimization (PSO) algorithm is used to tune the parameters of the PID controllers. The efficacy of the developed algorithm is demonstrated on a two-area model of the IEEE RTS-96 system with varying RER penetration levels. |
| Authors |
Deepak Pandit  , R. K. Saket  , Niannian Cai , Nga Nguyen
|
| Journal Info |
Not listed | 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET)
|
| Publication Date |
5/19/2023 |
| ISSN |
Not listed |
Type |
article |
| Open Access |
closed
|
| DOI |
https://doi.org/10.1109/globconet56651.2023.10150172 |
| Keywords |
Load Frequency Control (Score: 0.661457) , Voltage and Frequency Control (Score: 0.556713) , Intelligent Control (Score: 0.552068) , Automatic Generation Control (Score: 0.53789) , Voltage Control (Score: 0.531491)
|
