Title
An Optimal Power-Flow Approach to Improve Power System Voltage Stability Using Demand Response
Abstract
The increasing penetration of renewables has driven power systems to operate closer to their stability boundaries, increasing the risk of instability. We propose a multiperiod optimal power-flow approach that uses demand responsive loads to improve the steady-state voltage stability, which is measured by the smallest singular value (SSV) of the power-flow Jacobian matrix. In contrast to past work that employs load shedding to improve the stability, our approach improves the SSV by decreasing and increasing individual loads while keeping the total loading constant to avoid the fluctuation of the system frequency. Additionally, an energy payback period maintains the total energy consumption of each load at its nominal value. The objective function balances SSV improvements against generation costs in the energy payback period. We develop an iterative linear programming algorithm using singular value sensitivities to obtain an ac-feasible solution. We demonstrate its performance on two IEEE test systems. The results show that demand response actions can improve the static voltage stability, in some cases, more cost effectively than generation actions. We also compare our algorithm's performance to that of an iterative nonlinear programming algorithm from the literature. We find that our approach is approximately six times faster when applied to the IEEE 9-bus system, allowing us to demonstrate its performance on the IEEE 118-bus system.
Year
DOI
Venue
2019
10.1109/TCNS.2019.2910455
IEEE Transactions on Control of Network Systems
Keywords
Field
DocType
Demand response,iterative linearization,optimal power flow,singular value,voltage stability
Approximation algorithm,Payback period,Mathematical optimization,Control theory,Nonlinear programming,Demand response,Electric power system,Energy consumption,Numerical stability,Mathematics,Real versus nominal value
Journal
Volume
Issue
ISSN
6
3
2325-5870
Citations 
PageRank 
References 
1
0.38
0
Authors
3
Name
Order
Citations
PageRank
Mengqi Yao111.06
Daniel K. Molzahn210015.94
Johanna L. Mathieu312021.94