Sampled-data based discrete and fast load frequency control for power systems with wind power

Information and communication technology tremendously facilitates the operation efficiency and economy of modern power systems in recent years. However, risks such as bandwidth constraints and malicious attacks threaten the secure load frequency control (LFC) of power systems. To mitigate such risks, this paper proposes distributed observer-based event-triggered LFC schemes for multi-area power systems under cyber attacks. Considering the practical situation that only local system output information may be available, distributed observer-based LFC schemes are designed. Meanwhile, to reduce the communication burden, an event-triggered mechanism is adopted to design control laws, where both static and dynamic event-triggered approaches are taken and the dynamic one is proved to be more economical in terms of control cost. Verifiable sufficient conditions are established to guarantee the stability of the closed-loop system in the presence of cyber attacks and the controller gains are explicitly derived. Finally, validation studies on a three-area interconnected power system are carried out to demonstrate the proposed control schemes. Note to Practitioners—Load frequency is a crucial index for evaluating the quality of electric energy and thus LFC has brought considerable attention in the area of power systems control. Although many achievements have been made on the LFC of multi-area power systems, the risks such as bandwidth constraints and malicious attacks affect the normal operation of LFC due to the interconnection between different power systems. To deal with these risks, this paper focuses on designing event-triggered LFC to guarantee the stability of the frequency deviation while reducing the communication burden and mitigating cyber attacks. More importantly, the proposed event-triggered LFC is designed based on an observer and can be implemented in a distributed manner, which is relatively practical in real applications. The results presented in this paper aim to provide a helpful reference for stable and secure LFC design of multi-area power systems, such that the corresponding application research can be promoted.

This paper presents the Ramp Rate (RR) control of a wind power system and the Load Frequency Control (LFC) of a multi-machine power system taking the Virtual Inertia (VI) advantage of Battery Energy Storage Systems (BESS). Power producers, who agreed to meet the standards set by the national grid operators, are obliged to look for the time to time generation variation especially from the Intermittent Power Sources (IPS). The determination and sizing of BESS for RR control is a one-time decision process that needs consideration of many cost components. Dynamic Exponential Smoothing (DES) techniques coupled with large scale data clustering and PSO based optimization algorithms are employed for sizing BESS for Zhangjiakou wind power plant in China. The LFC response improvement of the 3-machine power system by the VI capability of the BESS is studied. Results indicate that the RR characteristic of the wind farm is improved; the VI capability of the BESS improved the transient frequency response and steady state frequency response of the test power system.

Load frequency control (LFC) requires transmission of remote measurements to the control center and of control signals from the control center to the plant. Constant delays exist in the dedicated communication channel and an open communication network introduces time-varying delays. Those delays would degrade the dynamic performance of LFC and even cause instability. This paper investigates the delay-dependent stability of the LFC scheme by adopting a delay-dependent criterion and linear matrix inequalities (LMIs). The maximal delay time which allows a power system with a LFC scheme embedded to retain stable is defined as the delay margin for stability analysis. A proportional-integral (PI) controller using the area control error (ACE) as input signal is employed in the LFC scheme. Special attention is paid to the relationship between the gains of PI controller and the delay margin. Case studies are carried out based on one-area and two-area LFC schemes to demonstrate the effectiveness of the criterion. Both constant and time-varying delays are considered. Moreover, the accuracy of the criterion used is also verified by simulation studies.

Dynamic load frequency control for high-penetration wind power considering wind turbine fatigue load

Frequency response is a key concern for power system security. Usually, it is estimated in a deterministic approach. But in most cases, power systems behave stochastically. Moreover, presence of wind power imposes further variability on generation profile of a power system. Hence, it appears more pragmatic to address these uncertainties during an evaluation of frequency response. This paper develops an index to assess frequency response of a power system with high wind power penetration. A probabilistic method is used for this purpose. K-means algorithm, a well-known data mining technique is employed. The developed index is called a ‘probabilistic frequency response index’. A realistic interconnected power system is investigated for a case study. Impact of increased wind power penetration on probabilistic frequency response index is analysed.

To mitigate the frequency stability challenges induced by random power fluctuations and alterations in Load Frequency Control (LFC) parameters during large-scale wind power integration, an optimal PID controller design method based on an intelligent optimization algorithm is presented in this paper. Firstly, a PID-controlled closed-loop LFC model for interconnected power systems incorporating wind generation is established by using static output feedback control method. Secondly, the minimum value of the integral of time multiplied absolute error (ITAE) index of the time - domain output response is selected as the optimization target function, and the optimal PID controller settings are obtained by using the sine cosine algorithm (SCA) with excellent performance. Finally, simulation results confirm that the suggested LFC method has remarkable robustness, even under condions of step load and random load disturbances, wind power deviation effects, and system parameter variations. Additionally, it facilitates greater wind power penetration into the grid.

Participation of wind energy along with conventional fuel sources in power generation is progressively rising in many countries. Due to continuous development of large-scale wind farms, some synchronous generators are being economically displaced from generation schedule. Modern wind turbine generators do not generally provide frequency control support after a disturbance, while during a fault they usually generate a current, which is close to their rated current value. Thus, presence of substantial wind generation in a system may impose a challenge in maintaining adequate frequency response. Moreover, it may result in low short-circuit ratio at the grid connection point of wind farms. Inadequate frequency response and low short-circuit ratio may create a concern for secured operation of a power system. Both frequency response and short-circuit level primarily depend on the number of committed synchronous generators. Hence, there may be a certain relation between these two system performance indicators. This paper investigates a correlation between frequency response and short-circuit performance due to high penetration of wind power. A case study of an Australian power system is presented.

Adaptive event-triggered PID load frequency control for multi-area interconnected wind power systems under aperiodic DoS attacks

AIn this paper, impact of communication delay on distributed load frequency control (dis-LFC) of multi-area interconnected power system (MAIPS) is investigated. Load frequency control (LFC), as one of ancillary services, is aimed at maintaining system frequency and inter-area tie-line power close to the scheduled values, by load reference set-point manipulation and consideration of the system constraints. Centralized LFC (cen-LFC) requires inherent communication bandwidth limitations, stability and computational complexity, as such, it is not a good technique for the control of large-scale and geographically wide power systems. To decrease the system dimensionality and increase performance efficiency, distributed and decentralized control techniques are adopted. In distributed LFC (dis-LFC) of MAIPS, each control area (CA) is equipped with a local controller and are made to exchange their control actions by communication with controllers in the neighboring areas. The delay in this communication can affect the performance of the LFC scheme and in a worst case deteriorates power system stability. To investigate the impact of this delay, model predictive controller (MPC) is employed in the presence of constraints and external disturbances to serve as LFC tracking control. The scheme discretizes the system and solves an on-line optimization at each time sample. The system is subjected to communication delay between the CAs, and the response to the step load perturbation with and without the delay. Time-based simulations were used on a three-area MAIPS in MATLAB/SIMULINK environment to verify the investigations. The overshoot and settling time in the results reveals deterioration of the control performance with delay. Also, the dis-LFC led to zero steady states errors for frequency deviations and enhanced the MAIPS’ performance. With this achievement, MPC proved its constraints handling capability, online rolling optimization and ability to predict future behavior of systems.

In this article, the H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> dynamic triggering control design problem is concerned for a discrete-time switched control system with aperiodic and parameter uncertainty denial-of-service (DoS) attacks. First, by introducing dynamic trigger scheme, a switched delay system model under discrete-time can be established. Then, by integrating discrete piecewise Lyapunov-Krasovskii functional method with switch system method based on average dwell time (ADT), we obtain a criterion of preserving weighted H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> performance of the switched delay system. Derived from the criterion, since the DoS duration and frequency are constrained by upper/lower bounds, the dynamic output feedback control gain can be designed by solving a set of LMIs. Finally, by investigating a resilient H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> load frequency control (LFC) for a three-area power system, we verify the effectiveness of the method through numerical simulations.

Extended Partial States Observer Based Load Frequency Control Scheme Design For Multi-area Power System Considering Wind Energy Integration

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller.

In this paper, a new method is put forward for the closed-loop stability analysis of PI-type load frequency control (LFC) scheme with interval time-varying delay. Improved delay-dependent conditions in terms of linear matrix inequalities for single-area and multi-area LFC systems are deduced by the proposed augmented Lyapunov–Krasovski (L-K) functional. Less conservativeness of our main results is due to an integral inequality called truncated second-order Bessel–Legendre (B-L) inequality, which can produce tighter bounds than Wirtinger-based inequality that encompasses Jensen inequality. Finally, the two-area interconnected power system based on Matlab/Simulink is provided to show the effectiveness and superiority of the obtained results.

This paper investigates the distributed load frequency control (LFC) for multi-area power systems with communication switching topologies and data transmission time-delays. For stabilizing the power flow frequency while encompassing situations of seldom subsystem disconnections, a decentralized Markov switching control scheme is proposed. To further reduce conservative of the controller, a time-delay equipartition technique is developed. In addition, the distributed cooperative control (DCC) scheme is also discussed and proved to be unsuitable as a LFC strategy. Finally, illustrative examples are provided to validate effectiveness of the proposed methods.

At present, simple and classical tuned controllers are widely used in the power system load frequency control (LFC) application. Existing LFC system parameters are usually tuned based on experiences, classical methods, and trial and error approaches, and they are incapable of providing good dynamic performance over a wide range of operating conditions and various load scenarios. Therefore, the novel modeling and control approaches are strongly required, to obtain a new trade-off between efficiency and robustness. Thus, the proposed techniques in this chapter are referred to be an adaptive control technique based on new optimization methods such as Jaya, Practical Swarm Optimization Algorithm, etc., which are used to make an on-line tuning of the LFC parameters in order to face the previous challenges in LFC. The system under study is a small microgrid with a renewable energy source and variable demand load. Digital simulation results are discussed.