Large-scale Interconnected Systems Research Articles

Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller.

Frequency-limited pseudo-optimal rational Krylov algorithm for power system reduction

In this paper, a computationally efficient frequency-limited model reduction algorithm is presented for large-scale interconnected power systems. The algorithm generates a reduced order model which not only preserves the electromechanical modes of the original power system but also satisfies a subset of the first-order optimality conditions for H2,ω model reduction problem within the desired frequency interval. The reduced order model accurately captures the oscillatory behavior of the original power system and provides a good time- and frequency-domain accuracy. The proposed algorithm enables fast simulation, analysis, and damping controller design for the original large-scale power system. The efficacy of the proposed algorithm is validated on benchmark power system examples.

Coordinated design of PSS and unified power flow controller using the combination of CWT and Prony methods with the help of SPEA II multi‐objective optimisation algorithm

Since the initial objective of power system stabiliser (PSS) units and flexible AC transmission system (FACTS) devices is the damping of inter-area and local oscillations, it is very substantial that the network electromechanical oscillatory modes are identified for tuning the controller of large-scale interconnected power systems. In this research, a method based on the combination of continuous wavelet transform and Prony algorithm is presented to study low-frequency electromechanical oscillations of the power system. The coordinated design of PSS and FACTS parameters become a multi-objective optimisation problem that will be solved using the SPEA II. The residue method is used to improve damping and satisfy the controller constraints of the suggested power systems. Finally, the proposed method of mode estimation and controller design is simulated on the two well-known test case systems, namely IEEE 2-area 4-generator and New England- New York 68-bus 16-generator systems using MATLAB software. The results represent accurate performance and validity of the proposed method to improve oscillation damping, dynamic stability of the power systems.

Observer-based adaptive fuzzy output constrained FTC for nonlinear interconnected large-scale systems

Observer-based adaptive fuzzy output constrained FTC for nonlinear interconnected large-scale systems

Decentralized Fault-tolerant Resilient Control for Fractional-order Interconnected Systems with Input Saturation

This paper investigates the problem of robust decentralized fault-tolerant resilient control for fractional-order large-scale interconnected uncertain system, and the problem considered here is subject to mixed H∞ and passivity performance constraint, external disturbances, controller perturbations and control input saturation. Based on the Lyapunov approach, the sufficient conditions are derived in terms of linear matrix inequalities to ensure the asymptotic stabilization of the fractional-order large-scale system with a prespecified mixed H∞ and passivity performance index. The main objective of this work is to design a robust decentralized fault-tolerant resilient controller which compensates both actuator fault and input saturation in its design for obtaining the required result. Finally, a numerical example is included to illustrate the effectiveness of the designed control law. The simulation results reveal that our proposed controller not only can effectively deal with actuator faults, but also has very good robustness for input saturation and external disturbances.

Power Flow in a Multi-Frequency HVac and HVdc System: Formulation, Solution, and Validation

This paper proposes a novel power flow formulation and solution algorithm for a generalized large-scale interconnected transmission system encompassing multi-frequency HVac and HVdc grids having arbitrary numbers of buses, topologies, and operating frequencies. Back-to-back and ac/dc voltage-source converters are employed to interconnect and control the voltage and power interchange between two power grids operating at different frequencies. The power Flow formulation is based on a steady-state model of back-to-back and ac/dc converters operated in centralized and distributed droop control strategies. Each power grid is represented by a set of nonlinear power balance equations. These equations are solved simultaneously using a unified power flow algorithm, taking into account generator and converter limits. It is shown that the solution convergence is achieved rapidly despite the system size, topology, and converter control strategies. The efficacy and accuracy of the proposed steady-state solution algorithm are demonstrated by comparing the numerical solution to the one obtained by time-domain electromagnetic models of multi-frequency HVac and HVdc transmission systems with fully controllable back-to-back and ac/dc converters. The results obtained by using the proposed algorithm and the time-domain simulation are practically identical.

Control of large scale interconnected systems with input and state delays using decentralized adaptive state observers

AbstractThis paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of large scale interconnected systems with both state and input delays. The upper bounds of the interconnection terms are considered to be unknown. Time varying delays in the nonlinear interconnection terms are bounded and nonnegative continuous functions and their derivatives are not necessarily less than one. For exact prediction, a decentralized adaptive state observer is designed and a nested predictor based approach is established to predict the future states of the input delay compensation. It is shown that the solutions of uncertain large‐scale time‐delay interconnected systems converge uniformly exponentially to a desired small ball. The effectiveness of the proposed approaches is illustrated by two examples.

Implementing triple helix through Listrik Kerakyatan initiative: community-based energy from waste

As depicted by its three components, A (academic), B (business), and G (government), the Triple Helix principle aims at narrowing the gap between the competencies of university graduates and those required by businesses or industries in the real world, under the corridor of government rules and regulations. The main issues that will be addressed by the triple helix concept is the national policy to attain 23% of renewable energy portion by the year 2025. However, the conventional electricity construction, which usually prefer a large-scale interconnected system, is currently facing serious delay due to difficulties in acquiring land and permit. Moreover, such large-scale power plants are not sufficient to serve consumers that are scattered in more than three thousand islands in Indonesia archipelago. In addition, such big projects are mostly owned by giant investors that depend on foreign fund and technology, leaving no opportunity for local people to contribute and have ownership over their energy needs. STT PLN proposes a simple small-scale distributed generation that can be owned and managed by local people by using renewable energy sources that are available around the communities. Waste is the most attractive resources because by converting waste to energy, the problem of waste can be solved at the same time. Based on the research and pilot project that had been conducted in three locations, Listrik Kerakyatan (Community-based Electricity) is technically simple so it can be applied and managed by local people. It is also economically viable as the required capital is relatively small and affordable by small enterprises. The commutative law of math also says that 1x1000 = 1000 x1. Therefore, going by that law, the total capacity generated by 1000 units of small LKs can be similar to one large unit of conventional model.

Event-triggered distributed dynamic output-feedback dissipative control of multi-weighted and multi-delayed large-scale systems

This paper considers multi-weighted and multi-delayed large-scale interconnected systems, which have multiple coupling links between neighboring subsystems and all links have different coupling weights and delays. It describes an event-triggered distributed dynamic output-feedback control approach for dissipative stabilization of the concerned systems under quantization, packet dropouts and stochastic deception attacks. An event-triggered distributed dynamic output feedback controller (DOFC) is constructed and sufficient conditions are calculated for the exponential mean square stability along with a strict ( Q, S, R)-dissipative performance of the considered large-scale systems. The control gains for the subsystem controllers are determined by solving a nonlinear minimization problem using the cone complementarity linearization (CCL) algorithm. Finally, the obtained results are verified through a numerical example consisting of a continuous stirred tank reactor (CSTR) system.

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

In this paper, we propose a novel distributed fault detection method to monitor the state of a—possibly large scale—linear system, partitioned into interconnected subsystems. The approach hinges on the definition of a partition-based distributed Luenberger-like estimator, based on the local model of the subsystems and that takes into account their dynamic coupling. The proposed methodology computes— in a distributed way —a bound on the variance of a properly defined residual signal. This bound depends on the uncertainty affecting the state estimates computed by the neighboring subsystems and it allows the computation of local fault detection thresholds, as well as the maximum false-alarm rate. The implementation of the proposed estimation and fault detection method is scalable , allowing Plug & Play operations, and the possibility to disconnect the faulty subsystem after fault detection. Theoretical conditions on the convergence properties of the estimates and of the estimation error bounds are provided. Simulation results on a power network benchmark show the effectiveness of the proposed method.

Decentralized adaptive tracking control for high-order interconnected stochastic nonlinear time-varying delay systems with stochastic input-to-state stable inverse dynamics by neural networks

The paper solves the problem of a decentralized adaptive state-feedback neural tracking control for a class of stochastic nonlinear high-order interconnected systems. Under the assumptions that the inverse dynamics of the subsystems are stochastic input-to-state stable (SISS) and for the controller design, Radial basis function (RBF) neural networks (NN) are used to cope with the packaged unknown system dynamics and stochastic uncertainties. Besides, the appropriate Lyapunov-Krosovskii functions and parameters are constructed for a class of large-scale high-order stochastic nonlinear strong interconnected systems with inverse dynamics. It has been proved that the actual controller can be designed so as to guarantee that all the signals in the closed-loop systems remain semi-globally uniformly ultimately bounded, and the tracking errors eventually converge in the small neighborhood of origin. Simulation example has been proposed to show the effectiveness of our results.

Decentralized event-triggered output feedback control for a class of interconnected large-scale systems

This paper is concerned with the problem of decentralized event-triggered dynamic output feedback control for large-scale systems with unknown interconnections. By using a modified cyclic-small-gain condition and introducing a free-matrix-based integral inequality, a novel sufficient condition is derived to ensure that the overall closed-loop system is asymptotically stable with a prescribed H∞ performance. Based on this condition, a convex condition is presented to design the controller gains and the event-triggered parameters simultaneously. In contrast with the existing event-triggered results, the derived stability criterion can be applied to the large-scale systems with unmatched unknown interconnections. The effectiveness of the proposed control strategy is demonstrated by a double-inverted pendulum model.

Wide-area damping state feedback and output feedback controller design strategy considering time delays and actuator saturation based on parametric Lyapunov theory

Remote signal transmission time delays are the major factors to affect the performance of wide-area damping controller (WADC) and even deteriorate stability of large-scale power system. If the physical structure and the mathematical model of the system are different, the method of mathematically dealing with time delay is not the same. From the perspective of mathematical application engineering, there are two main ways to deal with the communication time delay: linear matrix inequalities (LMI) theory and conventional time-delay predictive compensation theory. Traditional time delay damping controller based on linear matrix inequalities (LMI) suffers relatively large conservatism and complexity. Traditional time delay damping controller based on time delay compensation has no clear relation between the control parameter and the time delay. On the other hand, the saturation of actuator leads to the deterioration of control performance and even threat system stability. The existing methods for saturation are negative feedback anti-saturation after the actuator is saturated, which is an afterwards control and it is difficult to well eliminate the influence of saturation. In this paper, a novel design strategy for wide-area time-delay damping controller based on parametric Lyapunov theory is derived. The explicit expression of the controller parameter value associated with the time delay is determined. This strategy can deal with arbitrary large time-vary delay theoretically and have extremely low controller dimension, which makes it have potential capability to be applied in large-scale inter-connected power systems. The control strategy is determined according to the system stability original definition (The system energy function is finite and positive and its first derivative is negative), which avoids complex matrix inequalities cyclic solution and reduces the conservatism of the controller. Moreover, it can directly give simple and explicit control law and specific control parameters, which enable this method to adjust its parameters online according to the exact time delay obtained by GPS. In the design process, the saturation characteristics of the actuator are taken into account in the linearization model of the closed-loop system. This makes it very adaptable to actuator saturation, so that the proposed design strategy can ensure the small signal stability of the closed-loop system considering time delays and actuator saturation. Case study is undertaken based on a New England ten-machine 39-bus power system, which stands for a large scale power system to verify the feasibility and effectiveness of the proposed design strategy. Compared with the free weight matrix damping controller (FWMC), which is a kind of LMI-based design strategy with excellent performance, the advantages and superiority of the proposed control strategy are verified. The proposed design strategy based on state feedback and output feedback has better control performance than FWMC.

An IOS Small-Gain Theorem for Large-Scale Hybrid Systems

This paper presents a small-gain result for large-scale interconnected systems composed of hybrid subsystems. It is assumed that the subsystems are input-to-output practically stable (IOpS) with offset and unboundedness observability (UO), and the interconnected system can be proved to be IOpS with offset and UO as long as the proposed small-gain condition is satisfied. If, moreover, the assumption of IOpS on the subsystems is reduced to input-to-output stability (IOS), then the interconnected system is IOS.

Design and real-time implementation of data-driven adaptive wide-area damping controller for back-to-back VSC-HVDC

This paper proposes a data-driven adaptive wide-area damping controller (D-WADC) for back-to-back VSC-HVDC to suppress the low frequency oscillation in a large-scale interconnected power system. The proposed D-WADC adopts a dual-loop control structure to make full use of the active and reactive power control of VSC-HVDC to improve the damping of the power system. A data-driven algorithm named the goal representation heuristic dynamic programming is employed to design the proposed D-WADC, which means the design procedure only requires the input and output data rather than the mathematic model of the concerned power system. Thus, the D-WADC can adapt to the change of operating condition through online weight modification. Besides, the adaptive delay compensator (ADC) is added to effectively compensate the stochastic delay involved in the wide-area feedback signal. Case studies are conducted based on the simplified model of a practical power system and the 16-machine system with a back-to-back VSC-HVDC. Both the simulation and hardware-in-loop experiment results verify that the proposed D-WADC can effectively suppress the low-frequency oscillation under a wide range of operating conditions, disturbances, and stochastic communication delays.

Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems With Stochastic Uncertainties

This paper proposes a novel scalable model-based fault detection and isolation approach for the monitoring of nonlinear large-scale systems, consisting of a network of interconnected subsystems. The fault diagnosis architecture is designed to automatically manage the possible plug-in of novel subsystems and unplugging of existing ones. The reconfiguration procedure involves only local operations and communication with neighboring subsystems, thus, yielding a distributed and scalable architecture. In particular, the proposed fault diagnosis methodology allows the unplugging of faulty subsystems in order to possibly avoid the propagation of faults in the interconnected large-scale system. Measurement and process uncertainties are characterized in a probabilistic way leading to the computation, at each time-step, of stochastic time-varying detection thresholds with guaranteed false-alarms probability levels. To achieve this goal, we develop a distributed state estimation scheme, using a consensus-like approach for the estimation of variables shared among more than one subsystem; the time-varying consensus weights are designed to allow plug-in and unplugging operations and to minimize the variance of the uncertainty of the fault diagnosis thresholds. Convergence results of the distributed estimation scheme are provided. A novel fault isolation method is then proposed, based on a generalized observer scheme and providing guaranteed error probabilities of the fault exclusion task. Detectability and isolability conditions are provided. Simulation results on a power network model comprising 15 generation areas show the effectiveness of the proposed methodology.

Adaptive Distributed Consensus Protocol for Automatic Generation Control of Large-Scale Interconnected Power Systems

An adaptive distributed consensus protocol (ADCP) for the automatic generation control of large-scale interconnected power systems is proposed in this paper. An updated strategy of the parameters of the ADCP is designed. Furthermore, the stability of the proposed ADCP is analyzed. A four-area power system that all the areas are connected in the large-scale interconnected power system is simulated in this paper. Comparing with the simulation results obtained by three control protocols, i.e., none protocol, distributed consensus protocol, and the proposed ADCP, the ADCP can obtain higher control performance. The feasibility and effectiveness of the ADCP are verified through the simulation results.

Notice of Violation of IEEE Publication Principles: Multi-Area Distributed State Estimation Strategy for Large-Scale Power Grids

Distributed state estimation system is beneficial in power grids with complex structures and large quantities of measurements because of its advantages, such as high computational efficiency and enhanced reliability. This study investigates a novel multi-area distributed state estimation algorithm for large-scale interconnected power systems. The state estimation model of the entire power grid is effectively decomposed into a group of estimation models that can be locally solved using an area estimator. The global information required by an estimator in solving its estimation model is effectively synthesized as two average values, and an average consensus-based algorithm is developed for an area estimator to access the required global information in a distributed fashion. Bad data are identified and eliminated after the convergence of the iterative estimation process. Simulation results of the IEEE 14-bus test system are provided to show the correctness and effectiveness of the proposed algorithm. Solution accuracy, computational efficiency and state estimation speed are compared with those of existing centralized, hierarchical and distributed methods by the numerical example in the IEEE 300-bus test system.

Decentralized networked stabilization of a nonlinear large system under quantization

Stabilization of a nonlinear large scale interconnected system is investigated. The system is linearized by the exact feedback linearization, then a procedure to reduce the complexity of the system is applied. This allows to find a controller for the linearized problem as a solution of an optimization problem whose dimension is equal to the dimension of one subsystem. The quantization of the control signal brings some uncertainty hence the controller design is proposed with the necessary degree of robustness. The inverse transformation yields than a controller for the original nonlinear system. The design method is illustrated by an example.

Decentralized Variable Gain Robust Controllers Based on Piecewise Lyapunov Functions for a Class of Uncertain Large-Scale Interconnected Systems

This paper deals with a design problem of a decentralized variable gain robust controller via piecewise Lyapunov functions for a class of uncertain large-scale interconnected systems. The decentralized variable gain robust controller developed in this paper consists of fixed gains and compensation inputs tuned by parameter adjustment laws. In this paper, we show LMI-based sufficient conditions for the existence of the decentralized variable gain robust controller. Finally, the effectiveness of the proposed decentralized variable gain robust control system is presented through a simple numerical example.