With the increase of uncertain and intermittent renewable energy supply on the grid, the power system has become more vulnerable to instability. In this paper, we develop a demand response strategy to improve power system small-signal stability. We pose the problem as an optimization problem wherein the total demand-responsive load is held constant at each time instance but shifted between different buses to improve small-signal stability, which is measured by small-signal stability metrics that are functions of subsets of the system’s eigenvalues, such as the smallest damping ratio. To solve the problem, we use iterative linear programming and generalized eigenvalue sensitivities. We demonstrate the approach via a case study that uses the IEEE 14-bus system. Our results show that shifting the load between buses, can improve a small-signal stability margin. We explore the use of models of different fidelity and find that it is important to include models of the automatic voltage regulators and power system stabilizers. In addition, we show that load shifting can achieve similar improvements to generation shifting and better improvement than simply tuning power system stabilizers.
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Sensitivity of Distributed Optimization Convergence Performance to Reference Bus Location
Distributed optimization is becoming popular to solve a large power system problem with the objective of reducing computational complexity. To this end, the convergence performance of distributed optimization plays an important role to solve an optimal power flow (OPF) problem. One of the critical factors that have a significant impact on the convergence performance is the reference bus location. Since selecting the reference bus location does not affect the result of centralized DC OPF, we can change the location of the reference bus to get more accurate results in distributed optimization. In this paper, our goal is to provide some insights into how to select reference bus location to have a better convergence performance. We modeled the power grid as a graph and based on some graph theory concepts, for each bus in the grid a score is assigned, and then we cluster buses to find out which buses are more suitable to be considered as the reference bus. We implement the analytical target cascading (ATC) on the IEEE 48-bus system to solve a DC OPF problem. The results show that by selecting a proper reference bus, we obtained more accurate results with an excellent convergence rate while improper selection may take much more iterations to converge.
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- Award ID(s):
- 1711850
- NSF-PAR ID:
- 10177046
- Date Published:
- Journal Name:
- 2019 IEEE Power & Energy Society General Meeting (PESGM)
- Page Range / eLocation ID:
- 1 to 5
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/PESGM40551.2019.8973576
