A multi-constrained binary ILP method for optimal allocation of PMUs in network
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A multi‑constrained binary ILP method for optimal allocation of PMUs in network P. Lakshminarayana1 · M. Venkatesan2 Received: 6 December 2019 / Accepted: 7 February 2020 © Springer Nature Switzerland AG 2020
Abstract This paper proposes multi-constrained binary integer linear programming (MBILP) method for optimal installation of phasor measurement units in IEEE networks considering Fast Load Voltage Stability Index (FLVSI), branch weight and redundancy constraints to minimize the cost of installation and to accomplish complete network observability. The weak buses of IEEE network are sorted based on their severity through the proposed strategy. A new FLVSI is programmed along with branch weight and redundancy constraints in MBILP to place PMUs in network. As installation cost of PMU for different buses varies with the number of branches or number of channels connected, PMUs should be allotted at bus with minimum cost. Redundancy of bus is computed to measure redundancy of bus network. Priority of PMU placement is considered at weak bus with proposed FLVSI in such a way that the cost is minimized and redundancy is adequate considering both branch weight and redundancy constraints. Ranking is proposed for PMU placement to find weak load bus in network along with the consideration of branch weight and redundancy. Zero injection (ZI) constraint modeling is recommended to minimize allocations further in system without losing observability. Contingency constraints for single-line or PMU loss are considered for allocation of PMUs. The proposed method is compared with ZI and without ZI modeling under general and line-outage or PMU loss cases to show efficacy of method. To estimate observability performance of complete network, a Complete Network Bus Observability Index is suggested. IEEE 14-, 24-, 30- and 57-bus networks are programmed with MATLAB software and compared with standard approaches to validate their efficacy. Keywords Binary integer linear programming (BILP) · Observability · Phasor measurement units · Redundancy · Weak buses · Zero injection bus
1 Introduction With the increase in blackouts in power network, due to sudden generation failure or heavy load changes, protection and control of power system became difficult. Advanced technology in measuring devices, such as implementation of synchrophasor technology for measurement of phasors with respect to time between two buses in network, made tremendous changes in area of state estimation (SE) of power system. Measuring devices
such as PMU located at different places in network commonly connected to Global Positioning System (GPS) provide dynamic date of the network [1, 2]. With proper processing of data with SE method, the state of the system can be found accurately. In the power system, deployment of PMUs at all buses of network leads to high cost which is uneconomical; this problem led to introduction of optimization strategies for PMU allocation to obtain complete observability. PMU devices at different locations without observability
* P. Lakshmi
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