Complete Observability Of Power System Research Articles

Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network

Modern power systems require advanced monitoring and control, a capability made possible by Phasor Measurement Units (PMUs) aided by synchrophasor technology. Because PMUs have significant costs, it is necessary to optimally place them in an electrical power network. This paper proposes the Optimal PMU Placement (OPP) on the Kenya Power Transmission Network (Nairobi Region 30-bus system) using the existing methods; The Depth-First method, the Mixed Integer Linear Programming (MILP) using intlinprog solver, and the Artificial Bee Colony (ABC) algorithm. The algorithms are first implemented on the IEEE-14 and 30 bus test systems for verification before implementing the Kenya Power Transmission Network (Nairobi Region 30-bus system). Finally, the results for the three methods are compared. A key consideration is the System Observability Redundancy Index (SORI) under normal baseload conditions, with and without the inclusion of Zero Injection Buses (ZIBs). A higher value of SORI increases the measurement redundancy of the PMUs installed at a given bus. This paper further proposes the modelling of ZIB with adjacent buses by considering their Observability Index (OI). The case studies are modelled in Power System Analysis Toolbox (PSAT), and the simulations are carried out in MATLAB. From the simulation results, the ABC algorithm gives the optimal solution with the highest SORI compared to the Depth-First method and MILP, with the exclusion of the ZIB. The Nairobi region 30-bus system require 12 PMUs located at buses; 2, 5, 8, 9, 11, 13, 14, 16, 21, 24, 27 and 29 for complete power system observability with a SORI of 43.

Wide area monitoring and measurements using mixed integer linear programming in deregulated power system for smart grid

This paper deals with different methods involved in the determination of complete observability of power system under wide area monitoring using Phasor Measurement Unit (PMU). There are numerous methods available in literature for the determination of optimal locations of PMU for complete system observability, but out of all those methods, fast selection of best suitable with minimum number of PMUs at optimal location for complete observability, is still a challenge to power engineers for applying online in Smart Grid under deregulation environment. After detail analysis with various methods, this paper proposes an algorithm for selecting best possible method for determining optimal locations of PMUs. The analysis compares performance of the available methods, e.g., Binary Integer Linear Programming, Admittance Bus Matrix Method and Mixed Integer Linear Programing using General Algebraic Modelling System. To investigate the effectiveness of the proposed method for complete observability using system observability redundancy index (SORI), Indian Northern Regional Power Grid (NRPG-246 bus system) has also been considered here.

Modeling of Zero Injection Buses Based to Optimal Placement of PMUs for Full Observability of Power Systems

In this research, Zero Injection Buses (ZIBs) were modeled to minimize the number of Phasor Measurements Units (PMUs) and ensure the full observability of power systems. To determine the operation of the proposed method, all ZIBs that are connected to each other and other buses were presented in models H, M, and D, each of which featured new observability constraints. The H set, is defined as the set of buses that are connected to a ZIB. Also, the $$M$$ set is defined as the $$H$$ set that is connected through ZIBs. The $$D$$ set is defined as the $$M$$ set that is connected through ZIBs to a common bus. To increase the assurance of complete power system observability in the method put forward in this work, conditions such as line outage, single PMU loss, and line or PMU exit were examined. To demonstrate the efficiency of the approach, it was applied to 14, 30, 39, 57 and 118 IEEE test systems. The simulation results showed that the developed topologies enhanced network observability under a minimum number of PMUs.

Redundant Location of PMU for Complete Observability and Wide Area Monitoring of Power System using Real Coded Genetic Algorithm

This paper presents an optimal placement of Phasor Measurement Unit model considering measurement redundancy using real coded genetic algorithm(RCGA) for state estimation. This model ensures complete observability of power system for normal conditions as well as contingencies considering Zero injection measurements. Single PMU outages and single branch outages are the contingencies considered in this paper. The optimum solution is obtained by considering objectives such as minimum number of PMU and maximum redundancy. The New England 39, IEEE 57, IEEE118 and practical networks of Indian Grid such as Western regional Indian Power Grid and Northern regional Indian Power Grid are considered for the optimal placement of PMU and it provides verification of globally optimum solution of the proposed model.

Optimal phasor measurement unit placement for numerical observability in the presence of conventional measurements using semi‐definite programming

This study presents a new approach for optimal placement of synchronised phasor measurement units (PMUs) to ensure complete power system observability in the presence of non-synchronous conventional measurements and zero injections. Currently, financial or technical restrictions prohibit the deployment of PMUs on every bus, which in turn motivates their strategic placement across the power system. PMU allocation is optimised here based on measurement observability criteria for achieving solvability of the power system state estimation. Most of the previous work has proposed topological observability based methods for optimal PMU placement (OPP), which may not always ensure numerical observability required for successful execution of state estimation. The proposed OPP method finds out the minimum number and the optimal locations of PMUs required to make the power system numerically observable. The problem is formulated as a binary semi-definite programming (BSDP) model, with binary decision variables, minimising a linear objective function subject to linear matrix inequality observability constraints. The BSDP problem is solved using an outer approximation scheme based on binary integer linear programming. The developed method is conducted on IEEE standard test systems. A large-scale system with 3120 buses is also analysed to exhibit the applicability of proposed model to practical power system cases.

Optimal placement of PMUs with limited number of channels for complete topological observability of power systems under various contingencies

Abstract In optimal PMU placement problem, a common assumption is that each PMU installed at a bus can measure the voltage phasor of the installed bus and the current phasors of all lines incident to the bus. However, available PMUs have limited number of channels and cannot measure the current phasors of all their incident lines. The aim of this paper is to recognize the effect of channel capacity of PMUs on their optimal placement for complete power system observability. Initially, the conventional full observability of power networks is formulated. Next, a modified algorithm based on integer linear programming model for the optimal placement of these types of PMUs is presented. The proposed formulation is also extended for assuring complete observability under different contingencies such as single PMU loss and single line outage. Moreover, the problem of combination of PMUs with different number of channels and varying costs in optimal PMU placement is investigated. Since the proposed optimization formulation is regarded to be a multiple-solution one, total measurement redundancy index is evaluated and the solution with the highest redundancy index is selected as the optimal solution. The proposed formulation is applied to several IEEE standard test systems and compared with the existing techniques.

Optimal PMU placement method for complete topological observability of power system under various contingencies

In optimal phasor measurement units (PMUs) placement problem, it is assumed that each PMU can measure unlimited number of voltages and currents. However, available PMUs have limited number of channels and cannot measure the current phasors of all their incident lines. This paper investigates the effect of channel capacity of PMUs on their optimal placement for complete power system observability. At first, the conventional complete observability of power networks is formulated. Then, a revised formulation for the optimal placement problem of these types of PMUs is presented. Proposed method is further extended for assuring complete observability under single PMU loss or single line outage cases. The proposed method is demonstrated on several IEEE standard test systems and compared with the existing techniques. Results show that the proposed method is simple to implement and accurate compared to other existing methods.

A Weighted Least Squares Algorithm for Optimal PMU Placement

This letter presents a new method for optimal placement of phasor measurement units (PMU) for complete power system observability. The optimal PMU placement (OPP) problem is formulated as a quadratic minimization problem with continuous decision variables subject to nonlinear observability constraints. The optimal solution is obtained by an unconstrained nonlinear weighted least squares (WLS) approach. Simulations are conducted on different IEEE systems (14-bus, 30-bus, 57-bus, and 118-bus) to prove the validity of the proposed algorithm.

Multi-criteria decision-making approach for multi-stage optimal placement of phasor measurement units

An important step in the development of synchrophasor-based wide area monitoring and control system is to optimally place the phasor measurement units (PMUs) in the network. Optimal number of PMUs, to fully observe the power system network, may be large. Owing to their relatively high cost, utilities may like to install these devices in stages. A technique is proposed here for placing the PMUs in multiple stages over a given time period that ensures complete power system observability even under a branch outage or a PMU failure. The proposed scheme is based on integer linear programming (ILP) and a multi-criteria decision-making (MCDM) approach. The ILP is used to obtain the optimal PMU locations in the system to completely observe the system and, subsequently, the MCDM model is developed to prioritise these PMU locations. Three indices are proposed to develop the MCDM model, viz. bus observability index, voltage control area observability index and tie-line oscillation observability index. Finally, the PMU placement is carried out in stages based on the ranking of these optimal locations. The proposed method is applied on three test systems – IEEE 14-bus system, New England 39-bus system and Northern Regional Power Grid 246-bus Indian system.

Optimal PMU placement method for complete topological and numerical observability of power system

This paper presents a new method of optimal PMU placement (OPP) for complete power system observability. A two-stage PMU placement method is proposed, where stage-1 finds out the minimum number of PMUs required to make the power system topologically observable and stage-2 is proposed to check if the resulted PMU placement (from stage-1) leads to a full ranked measurement Jacobian. In case the PMUs placed, ensuring topological observability in stage-1, do not lead to the Jacobian of full rank, a sequential elimination algorithm (SEA) is proposed in stage-2 to find the optimal locations of additional PMUs, required to be placed to make the system numerically observable as well. The proposed method is tested on three systems and the results are compared with three other topological observability based PMU placement methods. The simulation results ensure the complete system observability and also demonstrate the need of using stage-2 analysis along with the topological observability based PMU placement methods.