Donglan Liu

Operating modern power grids requires coordinated solutions for optimal dispatch, state estimation, price prediction, and contingency analysis, yet these tasks are usually modeled separately. We present PhysBridge, a response-oriented pretraining framework in which historical windows provide context while solver-generated perturbation responses, active constraints, and local sensitivities define the pretraining targets. PhysBridge combines a temporal-graph encoder with a Primal-Dual Response Bridge (PDR-Bridge) that performs safeguarded local refinement and outputs transferable primal, projection-dual, sensitivity, and health tokens. Across IEEE 14-, 30-, 57-, 118-, and 300-bus systems, the benchmark contains 26.3 million solver-generated perturbation-response pairs; in the 300-bus transfer setting, pretraining uses only the 21.04 million nominal pairs from the 14-, 30-, 57-, and 118-bus source topologies. Across three runs on unseen IEEE 300-bus transfer with 10% labels, PhysBridge obtains a 2.21 ± 0.05 % OPF cost gap, 96.3 ± 0.2 % feasibility, 1.84 ± 0.05 $/MWh LMP MAE, and 91.6 ± 0.3 % contingency/fault event macro F1. Relative to a matched rollout-only model trained on the same source corpus without response targets or bridge refinement, these values correspond to a 50.8% lower OPF gap and a 7.4 percentage-point higher event F1. The bridge requires 12.4 ms per 300-bus forward pass and activates fallback on 4.6% of stressed windows. Comparisons with supervised-only OPF specialists that do not receive matched solver-generated pretraining are interpreted as task-relevant performance under the proposed pretraining regime, not as architecture-only superiority.

Low power consumption is critical for wireless communication, particularly for the Internet of Things (IoT) applications. Addressing these energy conservation requirements, 5G-Advanced (5G-A) introduces the Reduced Capability (RedCap) concept, incorporating techniques such as Discontinuous Reception (DRX), Extended DRX (eDRX), Wake-up Signal (WUS), and Wake-up Receiver (WUR). Nevertheless, scope for further optimization remains. Focusing on improving energy efficiency for 5G-A and 6G, in this study we propose a simultaneous wireless information and power transfer (SWIPT) cooperative communication scheme leveraging environment backscattering and wake-up receiver technology, specifically designed to enhance the energy conservation performance of internet of things (IoT) devices and the energy efficiency of communication links, while extending the application scenarios for WUS. By establishing a backscattering system comprising a base station, a sensor equipped with a WUR module, and a receiving terminal, the system harvests both energy and information from ambient sources utilizing SWIPT technology. This approach reduces the sensor's communication power consumption and formulates an energy efficiency optimization problem for the communication link, subject to constraints on base station transmit power and the power splitting ratio. This research ultimately maximizes communication link energy efficiency with WUS participation, satisfying current IoT energy conservation requirements and contributing significantly to the sustainable development of batteryless IoT and future communication networks.

Quantitative assessment of data risks is a focal point in the field of data security. In this paper, we establish a multi-level power data security risk indicator system based on Data Security Capability Maturity Mode (DSMM) to delineate risk indicators covering the entire data lifecycle. We propose a method for representing expert evaluation information based on probabilistic hesitant fuzzy sets to mitigate issues arising from individual expert biases and the number of experts. By transforming the quantification of power data risks into a multi-attribute decision-making problem, we present a method for power data risk assessment based on probabilistic hesitant fuzzy multi-attribute group decision-making. Experimental results demonstrate that the proposed approach can effectively calculate power data risk levels, providing theoretical support for power data security protection.

The expansion of the scale of the Power Internet of Things stimulated by the development of the Energy Internet makes the growth in demand for the effective authentication and access control technologies in the cross-domain data exchange. Based on the cross-chain technology of the blockchain and the cuckoo filter, this paper proposes a cross-domain authentication scheme for Power Internet of Things. Firstly, a cross-chain authentication architecture is established. Combined with the existing authentication technologies used in intra-domain authentication, a cross-domain authentication process based on the cross-chain technology is proposed to realize the automatic transmission of the authentication credentials from application domain to authentication domain. The cuckoo filter is deployed on the blockchain as smart contracts, and the user certificate fingerprint is inserted into the filter to realize user registration, query, and revocation, which reduces the cost of the user certificate management. Experimental results show the effectiveness and feasibility of our scheme. Based on the proposed authentication scheme, a cross-domain access control scheme based on roles and object classes is presented, by treating the object classes as controlled objects and then applying the role-based access control to the object classes, on the condition that the heterogeneous domains in the Energy Internet have the same kinds of resources.

With the increase in global geopolitical risks and the frequent occurrence of extreme climate in recent years, the electricity prices in Europe have shown large fluctuations. Electricity price has an important impact on the cost of production and living, while electricity demand will also affect other energy markets. A double-layer system based on the spillover effects from a systematic perspective is constructed in this paper to explore the connectedness between different electricity markets and other related energy markets in Europe, considering the impact of climate risks. The results show that there are certain spillover effects among electricity markets in different countries, with a temporary upward trend in the beginning of the Russia–Ukraine conflict, and the electricity markets in the UK and Germany have a more important role in Europe. There are two-way spillover effects between the electricity market and fossil fuel markets, carbon market and carbon emission. Since 2022, the electricity market is affected by gas prices, while it has a certain impact on carbon emissions. The heating degree day (HDD) has significant spillover effects on the electricity market and other energy markets, while the spillover effects of the cooling degree day (CDD) are relatively small.

In software‐defined wireless sensor networks (SDWSNs), topology control is a fundamental procedure to maintain the global network topology. However, the open wireless channels of SDWSNs make it possible for an attacker to eavesdrop, replay, or modify the topology messages, thus posing a great threat to the network operations. The security of SDWSN topology control has not received enough attention yet. Identity‐based cryptography (IBC) may be fitter for SDWSNs due to its capability of generating the public key from the node identity directly, compared with traditional cryptography. In particular, identity‐based combined encryption and signature cryptography (IBCES) could encrypt and sign the messages using the same identity. As such, to secure the confidentiality, integrity, and authentication of topology information, we put forward a secure topology control mechanism based on IBCES. First, we use an identity‐based encryption authenticated key agreement scheme to implement the authentication of neighbor nodes and hop‐to‐hop verification via secure neighbor discovery and topology discovery processes. Then through the node admission and key establishment process, the end‐to‐end secure channels are established between the nodes, sinks, and Controller. Finally, secure topology collection and management processes supporting flat and hierarchical network structures are designed to guarantee the security of topology information. Theoretical analysis shows that our methods could satisfy the security needs of SDWSN topology control and resist several security attacks. The experimental results indicate that our mechanisms are suitable for SDWSNs.