Details

Autor(en) / Beteiligte

• Ming Zhou
• Centeno, V.A.
• Phadke, A.G.
• Yi Hu
• Novosel, D.
• Volskis, H.A.R.

Titel

A preprocessing method for effective PMU placement studies

Ist Teil von

• 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 2008, p.2862-2867

Ort / Verlag

IEEE

Erscheinungsjahr

2008

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• The invention of the phaser measurement unit (PMU) in mid 1980's enabled the synchronized measurements of voltages and currents in real time that has become the foundation of today's wide-area measurement, protection, and control (WAMP AC) systems. The trend in recent years is the steady increase of PMU installations worldwide for various applications, such as those targeted for State Estimation enhancement. Several algorithms/methods for optimal PMU placement have been introduced to minimize the system cost while still achieving the full observability of a power system with a minimum number of phasor measurements. These algorithms perform an optimization process by considering all system buses. In real systems, for practical reasons, some buses may be selected for mandatory PMU installations and some others can be selected as not desirable for PMU installations. In other words, a group of buses may be identified for the optimal placement. In this paper, a virtual data elimination preprocessing method and a matrix reduction algorithm are introduced for reducing the scale of a placement study. By identifying those buses with "known status", the method could significantly reduce the computation efforts. The methodology has been applied to four IEEE systems and the Brazilian National Interconnected Power System. The sizes of these systems before and after the reduction are tabulated to show the effectiveness of this method in reducing the computational effort. To prove the performance guarantee for the proposed algorithm, Lagrangian Relaxation has been applied to calculate the low bound of the minimum number of PMUs necessary for full observability. The results are shown in the simulation section.