The methodology of ADRC and the progress of its theoretical analysis are reviewed in the paper. Several breakthroughs for control of nonlinear uncertain systems, made possible by ADRC, are discussed. The key in employing ADRC, which is to accurately determine the “total disturbance” that affects the output of the system, is illuminated. The latest results in theoretical analysis of the ADRC-based control systems are introduced.

Active disturbance rejection control: Methodology and theoretical analysis

In optimization studies including multi-objective optimization, the main focus is placed on finding the global optimum or global Pareto-optimal solutions, representing the best possible objective values. However, in practice, users may not always be interested in finding the so-called global best solutions, particularly when these solutions are quite sensitive to the variable perturbations which cannot be avoided in practice. In such cases, practitioners are interested in finding the robust solutions which are less sensitive to small perturbations in variables. Although robust optimization is dealt with in detail in single-objective evolutionary optimization studies, in this paper, we present two different robust multi-objective optimization procedures, where the emphasis is to find a robust frontier, instead of the global Pareto-optimal frontier in a problem. The first procedure is a straightforward extension of a technique used for single-objective optimization and the second procedure is a more practical approach enabling a user to set the extent of robustness desired in a problem. To demonstrate the differences between global and robust multi-objective optimization principles and the differences between the two robust optimization procedures suggested here, we develop a number of constrained and unconstrained test problems having two and three objectives and show simulation results using an evolutionary multi-objective optimization (EM0) algorithm. Finally, we also apply both robust optimization methodologies to an engineering design problem.

Introducing robustness in multi-objective optimization

Energy storages introduce many advantages such as balancing generation and demand, power quality improvement, smoothing the renewable resource’s intermittency, and enabling ancillary services like frequency and voltage regulation in microgrid (MG) operation. Hybrid energy storage systems (HESSs) characterized by coupling of two or more energy storage technologies are emerged as a solution to achieve the desired performance by combining the appropriate features of different technologies. A single ESS technology cannot fulfill the desired operation due to its limited capability and potency in terms of lifespan, cost, energy and power density, and dynamic response. Hence, different configurations of HESSs considering storage type, interface, control method, and the provided service have been proposed in the literature. This paper comprehensively reviews the state of the art of HESSs system for MG applications and presents a general outlook of developing HESS industry. Important aspects of HESS utilization in MGs including capacity sizing methods, power converter topologies for HESS interface, architecture, controlling, and energy management of HESS in MGs are reviewed and classified. An economic analysis along with design methodology is also included to point out the HESS from investor and distribution systems engineers view. Regarding literature review and available shortcomings, future trends of HESS in MGs are proposed.

Hybrid energy storage system for microgrids applications: A review

This paper proposes the adaptive extended state observer (AESO)-based active disturbance rejection control (ADRC) to deal with the uncertainties, both in the plant and in the sensors. The gain of ESO is automatically timely tuned to reduce the estimation errors of both states and “total disturbance” against the measurement noise. Furthermore, the satisfactory performance of the closed-loop system is achieved by compensation for uncertainties. This novel controller is applied to the air–fuel ratio (AFR) control of gasoline engine, which has large nonlinear uncertainties due to the unknown speed change, fuel film dynamics, etc. In addition, the measurement of AFR is polluted by sensor noise. The experimental results demonstrate that the proposed controller can ensure high deviation precision of AFR despite both uncertain dynamics and measurement noise. Moreover, the experimental comparison validates the effectiveness of the AESO's gain by which the performance of ADRC on mitigating uncertainties can be improved.

ADRC With Adaptive Extended State Observer and its Application to Air–Fuel Ratio Control in Gasoline Engines

Forecasting municipal solid waste generation using artificial intelligence modelling approaches

Solid-oxide fuel cell (SOFC) power plant plays a vital role in a hybrid alternative energy based microgrid due to its reliability and flexibility in power supply However, the control of SOFC is challenging in terms of providing a fast load tracking while maintaining the fuel utilization rate within a safe range To this end, this paper builds two basic coordinated control strategies (CCS) for power management of SOFC-based microgrid The first is “Fuel Cell follows Inverter” scheme, where fast tracking is preferred while SOFC may operate on the edge of the safety range The second is “Inverter follows Fuel Cell” scheme, where high security is guaranteed by sacrificing performance in load tracking To obtain a robust and simple scheme, energy balance principle is used in CCS such that PI controller is sufficient to fulfill the basic duties Moreover, a simple supervisory control strategy is proposed for microgrid to provide a reasonable power reference for SOFC The control system is designed and tuned based on an SOFC plant with inverter's average model The efficiency of the proposed strategies is validated via a grid-connected SOFC/photovoltaic microgrid

Coordinated Control Strategies for Fuel Cell Power Plant in a Microgrid

Multi-objective optimization for advanced superheater steam temperature control in a 300 MW power plant

Active disturbance rejection control for the ALSTOM gasifier benchmark problem

Superheated steam temperature control based on modified active disturbance rejection control

The conventional direct energy balance (DEB) based PI control can fulfill the fundamental tracking requirements of the coal-fired power plant. However, it is challenging to deal with the cases when the coal quality variation is present. To this end, this paper introduces the active disturbance rejection control (ADRC) to the DEB structure, where the coal quality variation is deemed as a kind of unknown disturbance that can be estimated and mitigated promptly. Firstly, the nonlinearity of a recent power plant model is analyzed based on the gap metric, which provides guidance on how to set the pressure set-point in line with the power demand. Secondly, the approximate decoupling effect of the DEB structure is analyzed based on the relative gain analysis in frequency domain. Finally, the synthesis of the DEB based ADRC control system is carried out based on multi-objective optimization. The optimized ADRC results show that the integrated absolute error (IAE) indices of the tracking performances in both loops can be simultaneously improved, in comparison with the DEB based PI control and H∞ control system. The regulation performance in the presence of the coal quality variation is significantly improved under the ADRC control scheme. Moreover, the robustness of the proposed strategy is shown comparable with the H∞ control.

Yali Xue

Papers

Coordinated Control Strategies for Fuel Cell Power Plant in a Microgrid

Multi-objective optimization for advanced superheater steam temperature control in a 300 MW power plant

Active disturbance rejection control for the ALSTOM gasifier benchmark problem

Superheated steam temperature control based on modified active disturbance rejection control

Direct energy balance based active disturbance rejection control for coal-fired power plant.