Complete System Observability Research Articles

Steiner Tree-Based Design of Communication Infrastructure With Co-Optimizing the PMU Placement for Economical Design of WAMS

In the smart grid, the monitoring and estimation of the power grid states are essential factors for real-time operation and control. In this regard, wide area measurement system(WAMS) needs to be developed wherein the phasor measurement units (PMUs) and communication infrastructure (CI) are the essential components. To achieve the economical design of WAMS, PMUs need to be placed optimally so that with minimal cost, the complete system observability is ensured. Additionally the cost of CI, to connect all the PMUs, needs to be considered during the economical design of WAMS. Hence in this work, the simultaneous optimization of PMUs and CI cost has been considered as the objective whereas the complete system observability has been considered as the constraint. The consequence of zero injection buses (ZIBs) on the economic design of WAMS has also been considered. Additionally, the effect of N-1 contingency, pre-installed fiber optic and pre-installed PMUs have also been simulated. In this work, a new Steiner tree-based approach has been proposed for securing economical design of CI. The swarm intelligence based binary dragonfly algorithm (BDA) has been adopted for optimization of considered problem. To showcase the effectiveness of the proposed approach, it has been simulated on IEEE 14, 30 and 118 bus standard test systems. The comparative analysis has also been presented and it clearly indicates the effectiveness of the proposed approach compared to other reported methods.

Attack-Resilient Optimal PMU Placement via Reinforcement Learning Guided Tree Search in Smart Grids

The operation of smart grids heavily relies on secure and accurate meter measurements provided by phasor measurement units (PMUs). Therefore, the optimal PMU placement (OPP) aiming to achieve the complete system observability of smart grids with as few PMUs as possible has been extensively investigated. Although many existing studies have focused on the OPP, few of them are concerned with the placement order of PMUs. To protect as many buses as possible in smart grids when installing PMUs in stages owing to high cost, this paper proposes the attack-resilient OPP strategy which places PMUs in order by using reinforcement learning guided tree search, where the sequential decision making of reinforcement learning is utilized to explore placement orders. The least-effort attack model is carried out to screen vulnerable buses such that the buses adjacent to these buses can be placed PMUs in advance to reduce the state space and action space of the large-scale smart grid environment. Based on that, the reinforcement learning guided tree search approach is used to explore the key buses which need placing PMUs, where the repeated exploration of the agent is avoided by tree search. Then, a reasonable placement order of PMUs is obtained according to the action sequence the proposed method provides. Finally, the effectiveness of the proposed method is verified on various IEEE standard test systems and the comparison results with existing methods are provided.

Optimal phasor measurement unit placement for power system observability using teaching–learning based optimization

A Phasor measurement unit (PMU) is a device that gives a fast and accurate measurement of both current and voltage with time synchronization. This PMU data facilitates effective monitoring and control of power systems in a smart grid (SG). PMU collects data from various buses linked with it and led to an increase in the data generation of the particular PMU and it encourages cramming in data transmission. The delay in data reception at the control centre affects the performance of the SG protection. In a wide-area monitoring system (WAMS), the data traffic model is introduced to calculate the data traffic index. The net traffic can be reduced by installing the PMUs at suitable buses such that the number of PMUs must be reduced which, minimizes the system cost. This paper presents the optimal PMU placement technique with complete system observability by considering the WAMS data traffic index and installation cost index. The teaching learning-based optimization (TLBO) technique is used to obtain optimal PMU positions. In addition, the zero injection bus (ZIB) case is considered for further reduction in the PMU count which in turn reduces installation cost. The selection of an appropriate PMU location set is identified based on the installation cost and WAMS data traffic for normal and ZIB cases. The proposed optimum PMU placement (OPP) algorithm is tested on various test systems such as IEEE 14-bus, 24-bus, 30-bus, 57-bus, and 118-bus systems for normal and ZIB cases. The MATLAB-based simulation results are compared with the various optimization techniques existing in the state of art. The results show that the effectiveness of the proposed methodology for determining the best PMU locations.

A multi-objective grey wolf optimizer (GWO)-based multi-layer perceptrons (MLPs) trainer for optimal PMUs placement

PurposeThis paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.Design/methodology/approachAn efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.FindingsFollowing extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.Practical implicationsThe efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.Originality/valueThis paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.

Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

This paper proposes a method for the optimal placement of phasor measurement units (PMUs) for the complete observability of a power system based on the degree of the neighbourhood vertices. A three-stage algorithm is used to determine the minimum number of PMUs needed to make the system observable. The key objective of the proposed methodology is to minimize the total number of PMUs to completely observe a power system network and thereby minimize the installation cost. In addition, the proposed technique also focuses on improving the measurement redundancy. The proposed method is applied on standard IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test systems and a hybrid AC/DC microgrid test system. The results obtained are compared with already existing methods in terms of the Bus Observability Index (BOI) and System Observability Redundancy Index (SORI). The results show that the proposed method is simple to implement and provides better placement locations for effective monitoring compared to other existing methods.

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.

Graph-Theory Based Optimal PMU Allocation Considering ZIB Effects

Continuous monitoring is the prerequisite for secure operation and efficient control of power system. This paper presents a new and straightforward approach to monitor the system efficiently. Optimal PMU placement (OPP) deals with the complete system observability with a minimum number of PMU. The Modified Graph theoretic configuration has been presented here to select some strategic locations for PMU installation. Initially, a new technique has been used here to form spanning tree from its system graph. Some standard bus systems i.e. IEEE 7-bus, IEEE 14-bus, and 30-bus have been used to test the effectiveness of the applied approach. The proposed approach has been carried out for normal operating conditions (NOC) as well as considering Zero Injection Bus (ZIB) effects. The simulation result of this efficient and state forward approach has been compared with some other established approaches.

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.

Research on Optimal D-PMU Placement Technology to Improve the Observability of Smart Distribution Networks

With the continuous development of smart distribution networks, their observable problems have become more serious. Research on the optimal placement of the distribution phasor measurement unit (D-PMU) is an important way to improve the measurability, observability and controllability of a smart distribution network. In this paper, the optimal D-PMU placement methods and implementation technology were studied to determine the optimal D-PMU placement scheme. Considering the bus vulnerability index and the different operating states of the system, the more practical one-time optimal placement methods to ensure complete system observability was proposed. On this basis, the system's measurement redundancy and unobservable depth were considered to realize the multistage optimal D-PMU placement. The corresponding mathematical model and solution flow were given. Then the implementation technology of the methods was studied and the optimal D-PMU placement assistant decision-making software for smart distribution network was developed. Thereby, the structure and requirements of different distribution networks can be satisfied. The application analysis, functional architecture and the overall design process were given. Finally, the methods and software were analyzed by using the IEEE 33 bus system and an actual project, the Guangzhou Nansha Yuan'an Substation. The verification results showed that the method and software mentioned in this paper can provide convenient and quick operation for optimal D-PMU placement, improve the efficiency of smart distribution network planning work, and promote the theoretical application level of smart distribution network planning results.

Optimal PMU Placement using Binary Particle Swarm and Artificial Bee Colony with Channel Limitations and Redundancy.

Phasor Measurement Unit (PMU) being expensive and to be placed optimally, a meta-heuristic approach of Binary particle swarm optimization (BPSO) and Binary artificial bee colony optimization (BABC) is made for the optimal allocation of PMU in a power system. The PMU locations resulted are served by basic system conditions like network configuration, critical generators, and loads. The pattern of locations on including Zero-Injection Buess (ZIB) is also discussed. The redundancy in case of PMU loss is coined so as to obtain a complete observability of the power system. the channel limitations of device is also taken into consideration for better results in real-time systems. Optimal PMU locations for IEEE 30-bus and 14-bus systems with channel limits are compared with all above considerations. The number of PMU locations is reduced as channel limits increases. The simulated PMU locations are decreased with improved observability by Binary Artificial Bee Colony Optimization as compared to Binary Particle Swarm Optimization.

Determining minimum number and optimal placement of PMUs for fault observability in one‐terminal algorithms

One-terminal algorithms utilise only measurements at one end of the transmission lines for fault location, and thus, the required number of phasor measurement units (PMUs) is less compared to two-end algorithms. There have not been major studies in terms of reducing required number of PMUs to implement fault location algorithms based on single terminal data. This study develops a fault observability rule using the basic theories of power system observability. Then, this rule is used in some optimisation problems for determining the minimum number and optimal placement of PMUs to attempt the complete system observability in normal condition and complete or relative fault observability simultaneously. Moreover, here, a novel fault location algorithm is proposed, which uses one-terminal voltage and current data. To enhance the accuracy of fault location, the novel algorithm utilises positive bus impedance matrix of the network along with the voltage and current equations of the faulted line. The performance of the proposed fault location algorithm and optimal placement method of PMUs for power system and fault observability is investigated on 39-bus test system.

Reduction of PMUs via hybrid PMU-RTU communication changeover in the case of cyberattack on vulnerable power transmission lines

A power grid strictly depends on information and communication technology. The key role of real-time measurement and information control for the reliable operation of a power grid is the responsibility of the phase measurement units (PMUs). As smart power grids encounter a variety of unauthorized malicious accesses such as cyberattacks, PMU placement is an important problem. In this study, a new algorithm was proposed to specify the minimum number of PMUs in the case of cyberattacks on their communication lines and equipment. In order to analyze complete observability of the distribution system, a range of probable contingencies for the vulnerable lines of a typical power system was discussed. The proposed algorithm implementation shows that the number of required PMUs can be reduced by removing irrelevant information through cyberattack circumstance intervals by using communication equipment potential.

Bus Allocation for Voltage Stabilization in Multi-Machine Power System Using GWO

Today, power systems are being operated under greatly stressed conditions due to rapidly growing demand for electrical energy, penetration of renewable energy sources, large seasonal load variations, and operation in competitive energy market conditions. The main part of this work involves achieving complete system observability and improving voltage stability level simultaneously by placing a minimal number of PMUs. Initially, weak buses (very sensitive to smaller reactive power variations) are identified by using Fast Voltage Stability Index (FVSI) calculation. In this work, the reliability of observing the weak buses is purposely maximized. Suppose any sudden voltage instability problem occurs on the weak bus. In that case,PMUs can immediately communicate to the operator and prevent the outage of the weak bus, even if one of the PMUs fails. PMUs can maintain the FVSI value of the critical lines, not exceeding their maximum limit, by initiating the remedial actions scheme, such as smart islanding, controlling the transformer tap settings, coordinating between automatic corrective devices, etc. In this system, the positioning of PMUs on poor buses should be favoured over other buses. Improved voltage reliability can be accomplished by effective and accurate control of critical lines and vulnerable buses. This is done by a small rise in the amount of PMUs relative to previous results.

Fault localization for transmission lines with optimal Phasor Measurement Units

This paper discusses a novel fault localization algorithm for multi-terminal transmission lines. The technique is tested for different fault types and fault locations. The exact fault location is determined along with the latitude and longitude by involving geo-referenced data of the power system. In addition, Phasor Measurement Units (PMUs) are effectively used for complete system observability. The number of PMUs is optimised using Genetic Algorithm. Thus, the objective is to find the distance of the fault occurrence and to locate the fault point along with the latitude and longitude, using optimal PMUs. For evaluation purpose, Indian Utility (TamilNadu Electricity Board) 49 bus system is used and validated, using software such as MATLAB, Power World Simulator and Google Earth View. The results show the effectiveness of the proposed technique to spot the exact fault point in the transmission lines with a minimum number of PMUs, to make the concept economical.

Идентификация математической модели режима энергосистемы с помощью синхронизированных векторных измерителей

The article presents a solution to the problem of placement phasor measurement units (PMUs) for the identification of the mathematical model of the energy system in the state space. The basis is the criterion for the complete observability of the dynamic system according to Kalman. As a method of optimization, the canonical genetic algorithm is taken. The complete observability of the power system during the PMUs placement is provided by applying the «observability rule» in the form of an original recursive observability test. As a practical example, the problem of PMUs placement in the power system of the Kaliningrad region was solved.

On the placing of synchronized vector measurements in network 110 - 330 kV for identification of the Kaliningrad region power system regime

A solution is presented for the problem of placing phasor measurement unit to identify the mathematical model of the electric power system in the state space. The criterion for complete observability of the Kalman dynamic system is taken as a basis. As a method of solution, we use the canonical genetic algorithm. The complete observability of the power system is ensured by the application of the observability rule in the form of a recursive test of observability. The proposed approach is demonstrated by the arrangement of synchronized vector meters in the Kaliningrad region power system.

An innovative navigation scheme for Mars entry using dynamic pressure measurement

Complete observability of dynamic system is a major concern of navigation in Mars precision landing exploration missions. It is demonstrated that, however, the current measurements used for navigation during Mars entry cannot guarantee the complete observability of the dynamic system. This paper proposes an integrated navigation scheme for Mars entry phase using the dynamic pressure and accelerations from inertial measurement unit (IMU). The dynamic pressure derived from the Mars Entry Atmospheric Data System (MEADS), and the triaxle accelerations from IMU are integrated in a filter as navigation measurements to increase the dynamic system observability and perform state estimation on-board. Afterward, the perturbation of the dynamic caused by parameter uncertainties is built. In order to address the impact of perturbation on state estimation, an adaptive estimator based on modified mixture-of-expert framework is given. Numerical simulation results demonstrate that the proposed integrated navigation scheme can ensure the complete observability of the dynamic system, and the state estimation are converged with entry time after the dynamic pressure has built up.

Multi-objective artificial bee colony-based optimal PMU placement with considering zero injection bus in power network

A novel multi-objective discrete artificial bee colony-based optimisation algorithm is proposed for the optimal phasor measurement units placement problem. The proposed algorithm is designed to incorporate a binary mutation step for efficient exploration and exploitation of any undiscovered region in the search space. A fuzzy-based mechanism is used to evaluate the best compromised solution from the final Pareto optimal set obtained by non-dominated sorting and crowding distance mechanism. A combination of two diverse objectives, i.e., minimisation of number of phasor measurement units and maximisation of N − 1 measurement reliability are taken into consideration with complete system observability. The simulation results are obtained both with and without inclusion of the zero injection effect in the observability analysis on IEEE standard systems and are compared with the recently published papers to demonstrate the effectiveness of the proposed algorithm. All the programmes are implemented in standard MATLAB environment version R2010a.

Optimal Placement of PMUs Using Adaptive Genetic Algorithm Considering Measurement Redundancy

With the extensive use of PMUs in power system, how to implement the optimal PMU placement for complete system observability is becoming more and more significant. Against simple genetic algorithm, easy to fall into local minima, this paper proposed a simple and effective adaptive genetic algorithm, aimed at determining the optimal placement of PMUs. The proposed algorithm provides adaptive crossover and mutation probability in iterations and has better convergence and global search ability than simple genetic algorithm, confirmed in many practical applications. Generally speaking, minimum PMU placement problem has multiple solutions, and this paper proposed an index of observability redundancy to rank these multiple solutions. Moreover, several observability rules were also put forward and proved with great help in obtaining the optimal solution. Simulations using MATLAB are conducted on IEEE 7 bus, 14 bus, 24 bus, 30 bus, 57 bus, 118 bus and New England 39 bus test systems in order to verify the validity of this adaptive method. Results compared with other existing methods show that the proposed adaptive method is simple to realize and obtains the optimal solution with high redundancy in very few generations, which is much more effective than the results by major existing algorithms and shows a good reference value.