TY - GEN
T1 - A convex relaxation approach to optimal placement of phasor measurement units
AU - Kekatos, Vassilis
AU - Giannakis, Georgios B.
PY - 2011
Y1 - 2011
N2 - Instrumenting power networks with phasor measurement units (PMUs) facilitates several tasks including optimum power flow, system control, contingency analysis, visualization, and integration of renewable resources, thus enabling situational awareness - one of the key steps toward realizing the smart grid vision. The installation cost of PMUs currently prohibits their deployment on every bus, which in turn motivates their strategic placement across the power grid. As state estimation is at the core of grid monitoring, PMU deployment is optimized here based on estimation-theoretic criteria. Considering both voltage and current PMU readings and incorporating conventionally derived state estimates under the Bayesian framework, PMU placement is formulated as an optimal experimental design task. To obviate the combinatorial search involved, a convex relaxation is also developed to obtain solutions with numerical optimality guarantees. In the tests performed on standard IEEE 14- and 118-bus benchmarks, the proposed relaxation is very close to and oftentimes attains the optimum.
AB - Instrumenting power networks with phasor measurement units (PMUs) facilitates several tasks including optimum power flow, system control, contingency analysis, visualization, and integration of renewable resources, thus enabling situational awareness - one of the key steps toward realizing the smart grid vision. The installation cost of PMUs currently prohibits their deployment on every bus, which in turn motivates their strategic placement across the power grid. As state estimation is at the core of grid monitoring, PMU deployment is optimized here based on estimation-theoretic criteria. Considering both voltage and current PMU readings and incorporating conventionally derived state estimates under the Bayesian framework, PMU placement is formulated as an optimal experimental design task. To obviate the combinatorial search involved, a convex relaxation is also developed to obtain solutions with numerical optimality guarantees. In the tests performed on standard IEEE 14- and 118-bus benchmarks, the proposed relaxation is very close to and oftentimes attains the optimum.
UR - http://www.scopus.com/inward/record.url?scp=84857151603&partnerID=8YFLogxK
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U2 - 10.1109/CAMSAP.2011.6135909
DO - 10.1109/CAMSAP.2011.6135909
M3 - Conference contribution
AN - SCOPUS:84857151603
SN - 9781457721052
T3 - 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011
SP - 145
EP - 148
BT - 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011
T2 - 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011
Y2 - 13 December 2011 through 16 December 2011
ER -