Abstract
Under open access of transmission grid and unbundling of generation in the deregulated electricity market, frequency regulation is considered as ancillary service to balance minute to minute generation and demand. To ensure the reliability and quality of regulation are well maintained, a fair evaluation of load frequency control (LFC) performance and responsibilities between providers and customers has become a major concern. This paper demonstrates the features of Artificial-Neural-Network based System Control Error (ANN-SCE) model in tracking a single area's AGC dynamics, in gauging various impacts on the performance of AGC, and in identifying system dynamics that may be further used as a control reference in supplementing AGC logic.
| Original language | English |
|---|---|
| Article number | 465-135 |
| Pages (from-to) | 121-126 |
| Number of pages | 6 |
| Journal | Series on Energy and Power Systems |
| Publication status | Published - 2005 Dec 1 |
| Event | IASTED International Conference on Energy and Power Systems, EPS 2005 - Krabi, Thailand Duration: 2005 Apr 18 → 2005 Apr 20 |
All Science Journal Classification (ASJC) codes
- Engineering(all)