• Energy Research

This paper presents a new method to design a current controller for grid-tied inverters under both balanced and unbalanced grid voltage conditions. The proposed controller consists of combining a feedback-output controller with a disturbance observer (DO). The control design is carried out in the $\alpha \beta$ reference frame. Thus, the objective of the composite controller is to ensure that the output of the system tracks a sinusoidal reference signal with zero steady-state error. A feedback controller only cannot achieve a good tracking performance because of the presence of model uncertainties and unknown disturbances. To account for the natural mismatch between the actual system and the mathematical model, the system dynamics are first augmented with an additional state-variable, representing the disturbance, and the feedback controller is designed based on the assumption that the disturbance input is available for feedback. Then, an observer is constructed to estimate the disturbance, which is assumed to be a sine wave oscillating at the grid frequency. Another feature of the DO is its ability to compensate for the effect of the saturation blocks required to limit the control input during transients, leading to improved dynamic performance. Several experimental tests were conducted to verify the effectiveness of the proposed controller, and the results demonstrated its capability to achieve accurate fast stable responses.

Monitoring and control of electrical power grids are highly reliant on the accuracy of the digital measurements. These digital measurements reflect the precision of the installed sensors, which are vulnerable to the injection of unknown parameters in the form of device malfunction and cyberattacks. This may question the operational security and reliability of many cyberphysical infrastructure such as smart grid. To resolve this issue, a multisensor temporal prediction based wide-area control scheme is proposed in this paper. The feasibility of the designed scheme is verified in an advanced synchrophasor measurements based wide-area monitoring and control system (WAMCS). This WAMCS adopts a flexible ac transmission system device (the primary controller) for controlling the smart grid's voltage profile. The algorithm is validated in a real-time environment with an innovative software-in-the-loop testing setup. The performance of the proposed technique in the presence of false-data-injection attacks shows promising results.

Data-driven methods have been widely applied to fault diagnosis and aging predictions to assist fuel cell Prognostic and Health Management (PHM) system, in order to achieve early maintenance management and corrective measures for fuel cell systems. This paper proposes a novel fuel cell aging prediction method considering the applicability of data and algorithm. This method first adopts empirical mode decomposition (EMD) to split the aging data into several intrinsic mode functions (IMFs), and each IMF represents a different characteristic. Then the sample entropy (SE) is used as the quantitative criterion for complexity threshold. Furthermore, the nonlinear autoregressive neural network (NARNN) and the Long Short-Term Memory (LSTM) recurrent neural network are combined to ensure the applicability of data and algorithm. The results show that EMD can split the various data types of the aging data and weaken or even eliminate the excessive mutation phenomenon that occurs at the beginning of each experimental fuel cell. In addition, the targeted selection of data-driven methods can ensure the applicability of the data and algorithm. Finally, by comparing different prediction methods, the proposed method shows higher accuracy in the prediction of each experimental dataset, and good generality for different fuel cell types. This work was funded by the: National Natural Science Foundation of China , Grant numbers: 51977177 ; Shaanxi Province Key Research and Development Projects , Grant numbers: 2022QCY-LL-11 , 2021ZDLGY11-04 ; Fundamental Research Funds for the Central Universities , Grant numbers: D5000230128 ; Natural Science Basic Research Program of Shaanxi Province , Grant numbers: 2020JQ-152 .

Abstract Energy storage systems provide a promising solution for the renewable energy sector to facilitate large-scale grid integration. It is thus very important to explore means to validate their control scheme and their behaviour in the intended application before actual commissioning. This paper presents a reduced-scale hardware-in-the-loop simulation for initial testing of the performance of energy storage systems in renewable energy applications. This relieves the need of selecting and tuning a detailed model of the energy storage element. A low-power test rig emulating the storage element and the power converter is interfaced with a real time digital simulator to allow dynamic experimental tests under realistic conditions. Battery energy storage for smoothing the output power of a variable speed wind turbine is considered in this paper; however the proposed test methodology can be easily adapted for other storage elements in renewable energy, distributed generation and smart grid applications. The proposed HIL simulation is detailed and the experimental performance is shown.

Electrification of the transportation sector is a crucial step toward achieving a sustainable society. It will lead to several advantages, such as: reduce consumption of oil, reduce emissions and integrate renewable energy resources into the grid. Deployment of electric vehicle charging stations (EVCS) is essential to encourage large adoption of Electric Vehicle (EV) as it will reduce ‘range anxiety’ concern regarding the distance the EV could travel before the battery runs out. In this work, an optimal design of an electric vehicle charging station that integrates renewable distributed generation (DG) will be designed for cost and emission reduction. Both an isolated microgrid EVCS and an EVCS connected to the grid were studied in different cases, where energy sources such as PV, wind, and diesel generator are considered to supply the EVCS demand. The model was designed using HOMER software and designed based on realistic input data in terms of physical, operational and economic characteristics.

AbstractThis paper proposes a robust continuous nonlinear control method for grid‐tied photovoltaic (PV) inverters by combining model predictive control and integral sliding mode control (ISMC). The robustness of the proposed augmented controller is demonstrated mathematically by showing that the equivalent control signal of the ISMC system cancels disturbances to the system. Further, the proposed controller can compensate for system perturbations without knowing their characteristics, thereby simplifying controller design for the PV systems. The robustness of the proposed controller against parameter uncertainties and external disturbances was demonstrated via experimental and simulation verification.

Cooperative control of power converters in a microgrid offers power quality enhancement at sensitive load buses. Such cooperation is particularly important in the presence of reactive, nonlinear and unbalanced loads. In this paper, a multi-master-slave-based control of Distributed Generators (DGs) interface converters in a three-phase four-wire islanded microgrid using the Conservative Power Theory (CPT) is proposed. Inverters located in close proximity operate as a group in master-salve mode. Slaves inject the available energy and compensate selectively unwanted current components of local loads with the secondary effect of having enhanced voltage waveforms while masters share the remaining load power autonomously with distant groups using frequency droop. The close proximity makes it practical for control signals to be communicated between inverters in one group with the potential to provide rapid load sharing response for mitigation of undesirable current components. Since each primary source has its own constraints, a supervisory control is considered for each group to determine convenient sharing factors. The CPT decompositions provide decoupled current and power references in abc-frame, resulting in a selective control strategy able to share each current component with desired percentage among the microgrid inverters. Simulation results are presented to demonstrate the effectiveness of the proposed method.