In the coming renewable energy-dominated power systems, their uncertain nature calls for a controllable load to track the change of renewable energy. To achieve power balance during peak load, a compensation mechanism for the controllable load to reduce power consumption is constructed. First, a multi-round sequential auction method is used to determine the reduced and non-reduced loads. Second, based on the proportional distribution according to the reduction loss, a compensation method for the reduced load by the non-reduced load is proposed. Considering both the reduction of electricity consumption and the carbon emission rate indicator, a compensation method for the reduced load by new energy enterprises is proposed; then, the compensation method and process of the controllable load reduction are formed. Finally, simulations are performed on a practical test case, and the effectiveness of the proposed scheme is verified by the numerical results.

The increasing popularity of crypto assets has resulted in greater cryptocurrency investor interest and more exposure in both industry and academia. Despite the substantial socioeconomic benefits, the anonymous character of cryptocurrency trading makes it prone to abuse and a magnet for illicit purposes, which cause monetary losses for individual traders and erosion in the standing of the tokenomics industry. To regulate the illicit behavior and secure users' privacy for cryptocurrency trading, we present an Anomaly Detection and Privacy-Preserving (ADPP) Framework integrating blockchain and deep learning technologies. Specifically, ADPP leverages blockchain technologies to build a user management platform that ensures anonymity and enhances the privacy-preservation of user information. Atop the user management system, an Anomaly Detection System adapts neural networks and imbalanced learning on topological cryptocurrency flow among users to identify anomalous addresses and maintain a sanction list repository. The experiments on the real-world dataset demonstrate the effectiveness and superior performance of ADPP. The flexible framework can be easily generalized to the crypto assets with public real-time transaction (e.g., Non-fungible Token), which takes up a significant proportion of market capitalization in the domain of tokenomics.

Traffic management systems play a vital role in ensuring safe and efficient transportation on roads. However, the use of advanced technologies in traffic management systems has introduced new safety challenges. Therefore, it is important to ensure the safety of these systems to prevent accidents and minimize their impact on road users. In this survey, we provide a comprehensive review of the literature on safety in traffic management systems. Specifically, we discuss the different safety issues that arise in traffic management systems, the current state of research on safety in these systems, and the techniques and methods proposed to ensure the safety of these systems. We also identify the limitations of the existing research and suggest future research directions.

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