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With the increasing proportion of renewable energy in microgrids (MGs), its stochastic fluctuation of output power has posed challenges to system safety and operation, especially frequency stability. Virtual synchronous generator (VSG) technology, as one effective method, was used to smoothen frequency fluctuation and improve the system's dynamic performance, which can simulate the inertia and damping of the traditional synchronous generator. This study outlines the integration of VSG-controlled energy storage systems (ESSs) and traditional synchronous generators so they jointly participate in secondary frequency regulation in an independent MG. Firstly, a new uncertain state-space model for secondary frequency control is established, considering the measurement noises and modelling error. Then, an improved linear quadratic Gaussian (LQG) controller is designed based on stochastic optimal control theory, in which the dynamic performance index weighting matrices are optimized by combining loop transfer recovery (LTR) technology and the distribution estimation algorithm. On the issue of secondary frequency devices' output power allocation, the dynamic participation factors based on the ESS's current state of charge (SOC) are proposed to prevent the batteries' overcharging and overdischarging problems. The energy storage devices' service life can be prolonged and OPEX (operational expenditure) decreased. Multiple experimental scenarios with real parameters of MGs are employed to evaluate the performance of the proposed algorithm. The results show that, compared with the lead-compensated-proportional-integral-derivative (LC-PID) control and robust µ-control algorithms, the proposed stochastic optimal control method has a faster dynamic response and is more robust, and the fluctuations from renewable energy and power loads can be smoothened more effectively.

IoT is the technical basis to realize the CPS (Cyber Physical System) for distribution networks, with which the complex system becomes more intelligent and controllable. Because of the multihop and self-organization characteristics, the large-scale heterogeneous CPS network becomes more difficult to plan. Using topological potential theory, one of typical big data analysis technologies, this paper proposed a novel optimal CPS planning model. Topological potential equalization is considered as the optimization objective function in heterogeneous CPS network with the constraints of communication requirements, physical infrastructures, and network reliability. An improved binary particle swarm optimization algorithm is proposed to solve this complex optimal problem. Two IEEE classic examples are adopted in the simulation, and the results show that, compared with benchmark algorithms, our proposed method can provide an effective topology optimization scheme to improve the network reliability and transmitting performance.

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The state parameters of electrical equipment and power system control parameters are the key data to realize the precise control and cooperative autonomy of a cyber physical power system. The trustworthiness of the data is the primary condition to guarantee the electric power system’s safe and reliable operation. In the traditional centralized data acquisition and management architecture, the security and trustworthiness completely depend on the central main server. A small mistake in the main server will result in data loss, which is irreversible and fatal. Blockchain technique combines the dispersed data with mutual backup and retrieval mechanism, which guarantees that the data cannot be tampered with and forged privately. Based on the blockchain technology, this article proposes a novel data trustworthy acquisition model with high credibility, applied to a self-organized cyber physical power system. In order to overcome the long time-consuming process of building traditional blockchains, a new on-demand data transmission routing algorithm with M/M/1/k queuing model is proposed in this article. Different scales of IEEE standard bus systems are employed as experimental examples to evaluate the algorithm’s performance. The results show that the proposed algorithm can effectively shorten the time consumption of blockchain construction and realize the data trustworthiness of cyber physical power system.

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With the significant increase in the use of image information, image restoration has been gaining much attention by researchers. Restoring the structural information as well as the textural information of a damaged image to produce visually plausible restorations is a challenging task. Genetic algorithm (GA) and its variants have been applied in many fields due to their global optimization capabilities. However, the applications of GA to the image restoration domain still remain an emerging discipline. It is still challenging and difficult to restore a damaged image by leveraging GA optimization. To address this problem, this paper proposes a novel GA-based image restoration method that can successfully restore a damaged image. We name it structure-priority image restoration through GA optimization. The main idea is to convert an image restoration task into an optimization problem, and to develop a GA optimization algorithm to solve it. In this study, the structural information of a damaged image, which is represented by curves or lines (COLs), is prioritized to be repaired first. The structural information is classified into relevant and irrelevant information according to the information of their locations. The relevant information is analyzed through the proposed GA optimization algorithm to find the matched COLs. The matched COLs are used to restore the structural information of the damaged area. The textural information will then be restored according to the different partitions separated by the restored structural information. Lastly, through case studies, we evaluate the proposed method by using four typical indices to measure the differences between the original and restored image. The results of case studies demonstrate the applicability and feasibility of the proposed method. INDEX TERMS Genetic algorithm, image processing, image restoration, relevant information, structurepriority, textural information, curves or lines (COLs). I. INTRODUCTION With the advent of social networking platforms, more and more people are sharing their thoughts about products or services by posting text messages, images, audio or video files [1]. Vision is the most advanced human sense [2], as a result, as social media data accumulates, it is not surprising that images play an important role and have become a more and more popular form of data on the Internet. With the significant increase in the use of images over the Internet, image processing and analysis have been gaining much research attention in the transportation, medical, aerospace, energy and other fields [3]-[6]. The associate editor coordinating the review of this manuscript and approving it for publication was Kathiravan Srinivasan .