Back to Search
Start Over
Frequency Stability Using MPC-Based Inverter Power Control in Low-Inertia Power Systems
- Source :
- IEEE Transactions on Power Systems. 36:1628-1637
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- The electrical grid is evolving from a network consisting of mostly synchronous machines to a mixture of synchronous machines and inverter-based resources such as wind, solar, and energy storage. This transformation has led to a decrease in mechanical inertia, which necessitate a need for the new resources to provide frequency responses through their inverter interfaces. In this paper we proposed a new strategy based on model predictive control to determine the optimal active-power set-point for inverters in the event of a disturbance in the system. Our framework explicitly takes the hard constraints in power and energy into account, and we show that it is robust to measurement noise, limited communications and delay by using an observer to estimate the model mismatches in real-time. We demonstrate the proposed controller significantly outperforms an optimally tuned virtual synchronous machine on a standard 39-bus system under a number of scenarios. In turn, this implies optimized inverter-based resources can provide better frequency responses compared to conventional synchronous machines.<br />Submitted to IEEE Transactions on Power Systems
- Subjects :
- Computer science
020209 energy
Energy Engineering and Power Technology
Systems and Control (eess.SY)
02 engineering and technology
Electrical Engineering and Systems Science - Systems and Control
Electrical grid
Power (physics)
Electric power system
Model predictive control
Optimization and Control (math.OC)
Control theory
FOS: Electrical engineering, electronic engineering, information engineering
FOS: Mathematics
0202 electrical engineering, electronic engineering, information engineering
Inverter
Electrical and Electronic Engineering
Synchronous motor
Mathematics - Optimization and Control
Power control
Subjects
Details
- ISSN :
- 15580679 and 08858950
- Volume :
- 36
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Power Systems
- Accession number :
- edsair.doi.dedup.....bdb5315e54d650229dd9435b479759a2