• Energy Research

The distributed frequency control system of microgrids, which relies on classical communication networks between distributed generations (DGs) for frequency regulation and restoration, is vulnerable to cyber-attacks. Quantum distributed controllers offer a secure quantum communication scheme but are less efficient because of continuous communication in quantum systems. This paper proposes a quantum distributed event-triggered secondary frequency control strategy for the islanded AC microgrid. The suggested event-triggered control significantly lessens the communication load and is Zeno-free. Furthermore, a novel false data injection attack (FDIA) scenario is introduced for the quantum-microgrid system. The non-periodic nature of communication can be exploited to directly identify and isolate compromised communication links, thereby enhancing the resilience of the quantum-microgrid system. Finally, simulation results on an AC microgrid with four DGs validate the effectiveness of the suggested control scheme.

In the power demand side, responsive loads can provide fast regulation and ancillary services as reserve capacities in interconnected power systems. This paper presents a distributed pinning demand side control (DSC) strategy for coordinating multiple load aggregators, i.e., aggregated responsive loads, to provide frequency regulation services. Specifically, a leader-following communication protocol is considered for the load aggregators in which there is a centralized pinner (leader) and multiple load aggregators (followers). The regulation objective is generated from the pinner and only shared with a small fraction of load aggregators. Moreover, a multi-step algorithm is proposed to determine the control gains in the DSC, which not only guarantees the stability of the close-loop system, but also restrains the plant disturbance. Furthermore, the distributed pinning DSC algorithm is integrated into the traditional centralized proportional-integral-based automatic generation control (AGC) framework, which has formed the coupled secondary frequency control structure. It has been shown that the total power mismatch in each control area is shared with both AGC units and load aggregators, and the system frequency can be improved by considering the distributed pinning DSC for load aggregators. Finally, simulation results are provided to demonstrate the effectiveness of the proposed coupled frequency control strategy.

This article addresses the characteristics of convective heat transfer and radially imposed magnetic field on peristaltic flow of an incompressible Carreau fluid in a curved channel. Joule heating is also present. Mathematical analysis has been carried out under long wavelength and low Reynolds number considerations. Solutions of the resulting non-linear system for small values of Weissenberg number are constructed. The salient features of flow quantities are pointed out with particular focus to pumping, velocity, temperature and trapping. It is observed pressure gradient enhances for larger values of power law index parameter. The velocity and temperature are decreasing functions of radial magnetic field parameter. Further the impact of Weissenberg and Biot numbers on the temperature are opposite.

The present analysis concentrates on the boundary layer flow of Maxwell fluid over a stretching sheet with variable thickness. Cattaneo-Christov heat flux model is used instead of classical Fourier’s law to explore the heat transfer characteristics with variable thermal conductivity. Suitable transformations are employed to achieve the nonlinear ordinary differential equations. Convergent series solutions of the momentum and energy equations are obtained. Behavior of various pertinent parameters on the velocity and temperature distributions are analyzed and discussed.

The machine vision based methods for micro-cracks detection of solar cells surface have become one of the main research directions with its efficiency and convenience. The existed methods are roughly classified into two categories: current viewing information based methods, prior knowledge based methods, however, the former usually adopt hand-designed features with poor generality and lacks the guidance of prior knowledge, the latter are usually implemented through the machine learning, and the generalization ability is also limited since the large-scale annotation dataset is scarce. To resolve above problems, a novel micro-cracks detection method via combining short-term and long-term deep features is proposed in this paper. The short-term deep features which represent the current viewing information are learned from the input image itself through stacked denoising auto encoder (SDAE), the long-term deep features which represent the prior knowledge are learned from a large number of natural scene images that people often see through convolutional neural networks (CNNs). The subjective and objective evaluations demonstrate that: 1) the performance of combining the short-term and long-term deep features is better than any of them alone, 2) the performance of proposed method is superior to the shallow learning based methods, 3) the proposed method can effectively detect various kinds of micro-cracks.

Demand response flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a joint optimization dispatch control strategy for source-load system with stochastic renewable power injection and flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs). Specifically, the optimization model is characterized by a chance constraint look-ahead programming to maximal the social welfare of both units and load agents. By solving the chance constraint optimization with sample average approximation (SAA) method, the optimal power scheduling for units and TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed respectively based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. The effectiveness of the proposed dispatch and control algorithm has been demonstrated by the simulation studies on a modified IEEE 39 bus system with a wind farm, a photovoltaic power station, two TCL agents and two PEV agents.