Optimal PMUs placement considering ZIBs and single line and PMUs outages

• Main Authors: Abdelazeem A. Abdelsalam, Karim M. Hassanin, Almoataz Y. Abdelaziz, Hassan Haes Alhelou
• Format: Article
• Language: English
• Published: AIMS Press 2020-05-01
• Series: AIMS Energy
• Subjects: phasor measurement units; observability; zero-injection bus; flower pollination algorithm; measurement redundancy
• Online Access: https://www.aimspress.com/article/10.3934/energy.2020.1.122/fulltext.html
• ISSN: 2333-8326; 2333-8334

Phasor measurement unit (PMU) is among the most important measurement devices in modern power systems. It measures the voltage and current phasors which have both magnitude and phase angle using a common timing reference. These measurements are utilized in real time applications of electrical power systems. The main drawback of PMUs is its high cost so if PMUs are used to collect or send online real data from a system to a data centre or a decision maker, the used number of PMUs should be minimum with full observability of system measurements. This paper proposes a flower pollination algorithm (FPA) to find the optimal number and locations of PMUs in power systems. The optimization objectives of the work are the minimization of PMUs number, the achievement of complete observability of power system states, and the maximization of measurement redundancy. Existence of zero-injection buses in the system decreases the number of PMUs that is required to fulfil the complete observability of system states. Furthermore, additional constraints for remaining system full observable following failure of single PMU and single line outage are also included to increase the system reliability. The performance and efficiency of the proposed FPA is tested on IEEE standard networks such as 14-bus, 30-bus, 57-bus and 118-bus and new England 39-bus network. The obtained simulation results approve the ability of the proposed optimization method to find the optimal allocation of PMUs in different cases with fulfilling complete observability and reliability of electric power systems. The superiority of FPA is also verified by comparing its results of other optimization algorithms.