Load frequency control of power systems with electric vehicles and diverse transmission links using distributed functional observers

This paper presents a load frequency control scheme using electric vehicles (EVs) to help thermal turbine units to provide the stability fluctuated by load demands. First, a general framework for deriving a state-space model for general power system topologies is given. Then, a detailed model of a four-area power system incorporating a smart and renewable discharged EVs system is presented. The areas within the system are interconnected via a combination of alternating current/high voltage direct current links and thyristor controlled phase shifters. Based on some recent development on functional observers, novel distributed functional observers are designed, one at each local area, to implement any given global state feedback controller. The designed observers are of reduced order and dynamically decoupled from others in contrast to conventional centralized observer (CO)-based controllers. The proposed scheme can cope better against accidental failures than those CO-based controllers. Extensive simulations and comparisons are given to show the effectiveness of the proposed control scheme.

Improved GART neural network model for pattern classification and rule extraction with application to power systems

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

H∞ dynamic output feedback control of power systems with electric vehicles

This paper presents a H∞ dynamic output feedback control scheme for load frequency control (LFC) of interconnected power systems with multiple input timedelays. In this study, electric vehicles (EVs) are participated in the LFC to support reheated thermal power units to rapidly suppress load and frequency fluctuations. A mathematical model of an interconnected power system is first introduced. This model takes into consideration of the different time delays in control inputs; specifically the communication/information delays between the control center and the fleet of EVs. We then derive stabilization conditions in terms of feasible linear matrix inequalities (LMIs) for the proposed system and develop an effective algorithm to parameterize H∞ controllers ensuring stability of the closed-loop system with H∞ performance. Extensive simulations are given to show the effectiveness of the proposed control method.

Static output feedback frequency stabilization of time-delay power systems with coordinated electric vehicles state of charge control

In this paper, for the first time, electric vehicles are used for both the primary and secondary frequency controls to support power plants to rapidly suppress fluctuations in the system frequency due to load disturbances. Via networked control and wide-area communication infrastructures, multiple interval time-varying delays exist in the communication channels between the control center, power plant, and an aggregation of electric vehicles. By coordinating batteries’ state of charge control, the behaviors of the vehicle owners and the uncertainties imposed by the changes of the batteries’ state of charge are taken intoconsideration. A power system model incorporating multiple time-varying delays and uncertainties is first proposed. Then, a robust static output feedback frequency controller is designed to guarantee the resulting closed-loop system stable with an H∞ attenuation level. By utilizing a novel integral inequality, namely refined-Jensen inequality, and an improved reciprocally convex combination, the design conditions are formulated in terms of tractable linear matrix inequalities which can be efficiently solved by various computational tools. The effectiveness of the proposed control scheme is verified by extensive simulations.

The 6 by the power of 3 model for enhancing academic teachers' capacities for effective online teaching and learning: benefits, initiatives and future directions

To gain the full educational benefits of the major new investments in corporate technologies supporting online teaching and learning it is argued that a strategic, systems based approach of academic professional development (APD) is required. Such an approach requires a clear view of the key areas of potential and enduring teaching and learning benefit which can be realised from online developments, including an understanding of the changing role of the academic teacher in higher education, the identification of the desired professional capacities to educate online and the implementation of a number of coordinated initiatives to develop these professional capacities in order to engage constructively with the learning and technology opportunities. Based on previous work, we propose a '6' by the power of '3' model of Academic Professional Capacities Development for effective APD of online teaching and learning. The model can help inform the actions of policy makers, executives and practitioners in ways that promote an authentic learning organisation.

Quasi-decentralized functional observers for the LFC of interconnected power systems

This letter presents a novel approach to the load-frequency control (LFC) of interconnected power systems. Based on functional observers theory, quasi-decentralized functional observers (QDFOs) are designed to implement any given global PI state feedback controller. The designed functional observers are decoupled from each other and also of low-order; thus, they are cost effective and easy to implement. Although the proposed approach is applicable to N- area power systems, an example of a two-area interconnected power system with reheat thermal turbines is considered for simplicity.

Robust nonlinear adaptive backstepping excitation controller design for rejecting external disturbances in multimachine power systems

This paper proposes a new approach to design a robust adaptive backstepping excitation controller for multimachine power systems in order to reject external disturbances. The parameters which significantly affect the stability of power systems (also called stability sensitive parameters) are considered as unknown and the external disturbances are incorporated into the power system model. The proposed excitation controller is designed in such a way that it is adaptive to the unknown parameters and robust to external disturbances. The stability sensitive parameters are estimated through the adaptation laws and the convergences of these adaptation laws are obtained through the negative semi-definiteness of control Lyapunov functions (CLFs). The proposed controller not only provides robustness property against external disturbances but also overcomes the over-parameterization problem of stability sensitive parameters which usually appears in some conventional adaptive methods. Finally, the performance of the proposed controller is tested on a two-area four machine 11-bus power system by considering external disturbances under different scenarios and is compared to that of an existing nonlinear adaptive backstepping controller. Simulation results illustrate the robustness of the proposed controller over an existing one in terms of rejecting external disturbances.

An alternative LQR-based excitation controller design for power systems to enhance small-signal stability

This paper presents a new approach to design excitation controller for power systems to enhance small-signal stability. Partial feedback linearization scheme is used to design the controller for a linearized power system model which transforms a part of this model into a new system through linear coordinate transformation. In this paper, the excitation control law as a function of state variables is determined from the dynamics of the partly transformed new system provided that the controller stabilizes the remaining dynamics of the system which are not transformed through feedback linearization. The stability of the remaining dynamics is also discussed in this paper. Since the proposed control scheme uses state variables as feedback, it is analogous to a linear quadratic regulator (LQR) based excitation controller. Therefore, the performance of the proposed scheme is evaluated on a single machine infinite bus (SMIB) system and compared to that of an LQR controller.

An improved stability criterion for time-delay power systems with electric vehicles and high voltage direct current power links

This paper presents an improved stability criterion for load frequency control (LFC) of time-delay power systems including AC/HVDC transmission links and EVs. By employing a novel refined Jensen-based inequality, an improved stability condition is derived in terms of feasible linear matrix inequalities (LMIs) which allow us to compute the maximal upper bounds of time-delay ensuring stability of the LFC scheme equipped with an embedded controller. Cases studies here are implemented for LFC scheme of a two-area power system, which is interconnected by parallel (AC/HVDC) links, with embedded proportional integral (PI) controller for discharged EVs. The relationships between the parameters of PI controller, supplementary control of HVDC links and delay margins of the LFC scheme are also discussed. As a consequence of facts, the results of delay margins can be used as a guideline to tune PI controller and set-up parameters for HVDC control.

Robust partial feedback linearizing excitation controller design for multimachine power systems

This paper presents a new robust nonlinear excitationcontroller design for synchronous generators in multimachine powersystems to enhance the transient stability. The mismatches betweenthe original power system model and formulated mathematical modelare considered as uncertainties which are modeled through thesatisfaction of matching conditions. The exogenous noises appearingfrom measurements are incorporated with the power system modelincluding the two-axis model of synchronous generators. The partialfeedback linearization technique is used to design the controller whichtransforms the original nonlinear multimachine power system modelinto several reduced-order linear and autonomous subsystems. Thedesired control law is obtained for each subsystem and implemented ina decentralized manner provided that the dynamics of the autonomoussubsystems have no effects on the overall stability of the system. Theanalysis related to the dynamics of noisy autonomous subsystems isalso included and the proposed controller has the excellent capabilityto decouple these noises. Finally, the performance of the proposedcontrol scheme is evaluated on an IEEE 39-bus benchmark powersystem following different types of large disturbances. The performanceof the proposed controller is compared to that of a partialfeedback linearizing controller, which is designed without robustnessproperties, to verify the effectiveness of the proposed control scheme.

Transient stability enhancement of multimachine power systems using nonlinear observer-based excitation controller

This paper presents an approach to design a nonlinear observer-based excitation controller for multimachine power systems to enhance the transient stability. The controller is designed based on the partial feedback linearization of a nonlinear power system model which transforms the model into a reducedorder linear one with an autonomous dynamical part. Then a linear state feedback stabilizing controller is designed for the reduced-order linear power system model using optimal control theory which enhances the stability of the entire system. The states of the feedback stabilizing controller are obtained from the nonlinear observer and the performance of this observer-based controller is independent of the operating points of power systems. The performance of the proposed observer-based controller is compared to that of an exact feedback linearizing observer-based controller and a partial feedback linearizing controller without observer under different operating conditions.

Multi-temporal land use mapping using remotely sensed techniques and the integration of a pollutant load model in a GIS

Estimation of nutrient load production based on multi-temporal remotely sensed land-use data for the Glenelg-Hopkins region in southwest Victoria, Australia, is discussed. Changes in land use were mapped using archived Landsat data and computerized classification techniques. Land-use
change is unparalleled in recent history, with 13% of the region transformed in the last decade. Total nitrogen and phosphorus loading were estimated using an export coefficient model. The analysis demonstrated a disturbing increase in nitrogen and phosphorus loadings from 1995 to 2002. Whilst such increases were suspected from past anecdotal and ad-hoc evidence, our modelling quantitatively estimated such increases and thus demonstrated the enormous potential of using remote sensing and GIS for monitoring land-use change and hence improve land-use management.

Design of minimal-order stabilisers for multi-machine unstable power systems

A reduced dynamics stabiliser for multi-machine power systems is presented in this paper. The design of the stabiliser is based on the theory of linear functional observers and the solution of a simple parameter optimisation problem. The order of the stabiliser could be as low as the number of machines in the system. The design is applied to an open-loop unstable multi-machine power system.

Development and delivery of the appropriate assessments items for power systems related PBL subjects

Problem Based Learning (PBL) as a teaching method has been around for many years. It is one of the most effective ways of learning and teaching. It uses real world problems as a learning method and encourages learners to learn independently while a mentoring support is provided by the academic. However, various academic institutions develop the assessments items in many ways; the implementation and delivery become a challenge in ensuring the right assessment and implementation. This paper discusses some of the practical experiences of the development and delivery of the appropriate assessment items for power systems related PBL subjects.