Synchrophasor-based predictive control considering optimal phasor measurement unit placements methods

A blackout is the total collapse of an electric power grid, due to the inability to balance load demand and power generation. Blackouts generally develop from a series of unattended voltage stability problems, stemming from a combination of human and operational errors, and may have fatal consequences. The report on the blackout incident of August 14 2003, which affected parts of the United States and Canada, particularly emphasised the need for improved wide area monitoring of the grid. In the United Kingdom, the recent blackout of August 9 2019 has reinforced the need for increased grid visibility and data recording. These have led to an ever-increasing interest in a family of measurement devices known as Wide Area Monitoring Systems (WAMS). The most popular device in this family is the Phasor Measurement Unit (PMU), which report voltage and current phasors at rates up to 60 samples/second. PMUs may be used to monitor all or part of the grid to prevent future blackouts with timely control actions. The goal is to ’See it fast: Keep it calm’. Wide-area monitoring enhances the possibility of visualizing the electric grid as a single system. This has led to the extension of the application of WAMS from mainly monitoring to wide-area control in relatively recent research efforts. This work explores how predictive control technique may be used to automate the control of power systems voltages at secondary level using an array of synchrophasors. The intuition is to develop a model-free (or synchrophasor-based) control algorithm, which reduces, as much as possible, the need for human interventions in the mitigation of voltage problems, and is fast enough to be applied online in real-time. Although model-based techniques can be applied online, they may not be fast enough for real-time applications. In addition, this method may depend on components’ parameters, which may not be available in practice. The work is split into two parts. First, novel WAMS deployment algorithms —using multi-variable, multi-objective optimization set-ups, which return optimal placement solutions —are presented. Formulations are described for multi-stage deployments given a limited budget and for application-focused cases. Practical issues which may develop are anticipated and addressed. The formulations were shown to return optimal solutions with qualitative placement specifications. In the second part, methods of realizing models from input-output relationships are developed and described. The first involved a method numerical derivatives based on data that are sampled at PMU rates. This may be seen as a viable alternative to the use of trajectory sensitivity, especially for real-time control design. In the second, subspace algorithm are used to realise models. The process is comprehensively described for secondary voltage regulation in normal and emergency situations. The approach is demonstrated on a number of IEEE test cases and the controller’s performance were found to be satisfactory for non-viable voltage regulations. This research work is particularly relevant in a number of ways. Chief among these is that voltage control problems may be handled in real-time without a knowledge of the model parameters. The model-free approach particularly desired since increasing integration of renewable energy sources means that the electric grid is becoming increasingly complex. Another is that the placement algorithms describe all various practical issues around the measurement-based design, which utilities may found useful, especially when they wish to address budget limitation and device compatibility issues

A Decision Modeling For Phasor Measurement Unit Location Selection In Smart Grid Systems

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed

Optimal placement of phasor measurement units using the Advanced Matrix Manipulation algorithm

Includes abstract.Includes bibliographical references.This thesis investigates the problem of the Optimal Placement scheme of Phasor Measurement Units in electrical power systems for State Estimation to facilitate improved monitoring and control of the system parameters. The research work done for this thesis begins with review of Supervisory Control and Data Acquisition systems (SCADA). SCADA-based systems are currently employed for condition monitoring and control of industrial and utility electrical power systems. For utility power networks, the main problem with voltage and current phasor data captured by SCADA systems is that they are not synchronised with respect to each other in a present-time or Real-time framework. This implies that both magnitude and phase angle of the measured phasors tend to get affected by slow data flow provided by SCADA to the points of utilization and also by differences in time instants of data capture. These factors inhibit theefficiency and quality of the power system monitoring and control. “Phasor Measurement Unit” (PMU) is a relatively new technology that, when employed in power networks, offers real-time synchronised measurements of the voltages at buses and currents along the lines that connect them. This is accomplished by using a GPS based monitoring system which facilitates time synchronisation of measurements and unlike SCADA, makes the measured data available in Real-Time format. SCADA is not able to provide Real-time data due to the low speeds at which RTUs (Remote Terminal Units) provide data. Availability of time-stamped phasor measurements makes PMUs preferable for power system monitoring and control applications such as State Estimation, Instability Prediction Analysis, Real-time Monitoring of the system conditions, Islanding Detection, System Restoration and Bad Data Detection

Phasor measurement unit (PMU) placement optimisation in power transmission network based on hybrid approach

The Phasor Measurement Unit (PMU) is a device that is employed to detect the voltage and current waveform that is synchronised with a clocking signal obtained continuously from the global positioning system (GPS). Integrating with the GPS receiver, the base station is able to receive the synchronous data from each PMU in real time. This thesis presents novel optimal placement approaches of PMU for applications such as state estimation and fault detection. In this thesis, the PMU placement is realised based on two hybrid algorithms namely Approximation Algorithm and Global Optimization Algorithm. The proposed algorithms will ensure optimum PMU placement with full network observability under different contingency conditions. The IEEE 14, 24, 30, 57 and the New England 39 standard test systems will be used to exam the proposed algorithm adequately and the result will be compared to existing methods. In this thesis, we demonstrated that the proposed methods are very effective in determining the minimum number of PMU and the results are comparable to the best methods presented in the past literature. In addition, the comparison between the proposed methods to the existing methods show that the proposed hybrid approaches achieve higher System Observability Redundancy Index (SORI) which will in turn improve the reliability and stability of power transmission

Optimal allocation of phasor measurement units using practical constraints in power systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The purpose of the research is to find a strategic placement of phasor measurement units (PMUs) that can maintain the observability of the power system using a binary variant of particle swarm optimisation method (BPSO). In recent years, integer linear programming (ILP) is the common optimisation method used to solve this problem. However, recent studies have shown that deterministic methods such as ILP are still unable to find the most optimal placement of PMUs. Therefore, there is still room for further investigation using heuristic algorithm due to its search-based nature. It is important to determine the most strategic placement of PMUs to ensure that the PMUs are fully utilised due to their expensive price tag. The challenge in using heuristic algorithm lies in its weakness when involving large-sized problem since it is prone to stuck in local optima as shown in earlier studies where most of them applied their proposed approach to small bus systems. To prevent the BPSO method from being stuck in local optima, a mutation strategy is proposed in addition to the V-shaped sigmoid function replacing the S-shaped sigmoid function. The proposed method is designed to intensify the local search of the algorithm around the current best solution to help instigate the particles from being stuck in local optima and consequently finding a better solution. This is shown to be a crucial factor based on the numerical results obtained where it outperforms all methods for all bus systems tested including the IEEE 300-bus system in terms of measurement redundancy and the number of PMUs. This study also considers other problem constraints such as zero-injection bus, single PMU loss and also PMU’s channels limit. Most of the existing studies considered PMU to have an unlimited number of channels whereas in practical, PMU does have a finite number of channels that it can use.Majlis Amanah Rakyat (MARA) and University Kuala Lumpur (UniKL

Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

Electromechanical Dynamics of High Photovoltaic Power Grids

This dissertation study focuses on the impact of high PV penetration on power grid electromechanical dynamics. Several major aspects of power grid electromechanical dynamics are studied under high PV penetration, including frequency response and control, inter-area oscillations, transient rotor angle stability and electromechanical wave propagation.To obtain dynamic models that can reasonably represent future power systems, Chapter One studies the co-optimization of generation and transmission with large-scale wind and solar. The stochastic nature of renewables is considered in the formulation of mixed-integer programming model. Chapter Two presents the development procedures of high PV model and investigates the impact of high PV penetration on frequency responses. Chapter Three studies the impact of PV penetration on inter-area oscillations of the U.S. Eastern Interconnection system. Chapter Four presents the impacts of high PV on other electromechanical dynamic issues, including transient rotor angle stability and electromechanical wave propagation. Chapter Five investigates the frequency response enhancement by conventional resources. Chapter Six explores system frequency response improvement through real power control of wind and PV. For improving situation awareness and frequency control, Chapter Seven studies disturbance location determination based on electromechanical wave propagation. In addition, a new method is developed to generate the electromechanical wave propagation speed map, which is useful to detect system inertia distribution change. Chapter Eight provides a review on power grid data architectures for monitoring and controlling power grids. Challenges and essential elements of data architecture are analyzed to identify various requirements for operating high-renewable power grids and a conceptual data architecture is proposed. Conclusions of this dissertation study are given in Chapter Nine