Search

Self-healing smart grids are characterized by fast-acting, intelligent control mechanisms that minimize power disruptions during outages. The corrective actions adopted during outages in power distribution networks include reconfiguration through switching control and emergency load shedding. The conventional decision-making models for outage mitigation are, however, not suitable for smart grids due to their slow response and computational inefficiency. Here, we present a graph reinforcement learning model for outage management in the distribution network to enhance its resilience. The distinctive characteristic of our approach is that it explicitly accounts for the underlying network topology and its variations with switching control, while also capturing the complex interdependencies between state variables (along nodes and edges) by modeling the task as a graph learning problem. Our model learns the optimal control policy for power restoration using a Capsule-based graph neural network. We validate our model on three test networks, namely the 13, 34, and 123-bus modified IEEE networks where it is shown to achieve near-optimal, real-time performance. The resilience improvement of our model in terms of loss of energy is 607.45 kWs and 596.52 kWs for 13 and 34 buses, respectively. Our model also demonstrates generalizability across a broad range of outage scenarios., (© 2024. The Author(s).)

Retinoic acid-inducible gene (RIG)-I is an essential innate immune sensor that recognises pathogen RNAs and induces interferon (IFN) production. However, little is known about how host proteins regulate RIG-I activation. Here, we show that leukocyte cell-derived chemotaxin 2 (LECT2), a hepatokine and ligand of the MET receptor tyrosine kinase is an antiviral regulator that promotes the RIG-I-mediated innate immune response. Upon binding to MET, LECT2 induces the recruitment of the phosphatase PTP4A1 to MET and facilitates the dissociation and dephosphorylation of phosphorylated SHP2 from MET, thereby protecting RIG-I from SHP2/c-Cbl-mediated degradation. In vivo, LECT2 overexpression enhances RIG-I-dependent IFN production and inhibits lymphocytic choriomeningitis virus (LCMV) replication in the liver, whereas these changes are reversed in LECT2 knockout mice. Forced suppression of MET abolishes IFN production and antiviral activity in vitro and in vivo. Interestingly, hepatocyte growth factor (HGF), an original MET ligand, inhibits LECT2-mediated anti-viral signalling; conversely, LECT2-MET signalling competes with HGF-MET signalling. Our findings reveal previously unrecognized crosstalk between MET-mediated proliferation and innate immunity and suggest that targeting LECT2 may have therapeutic value in infectious diseases and cancer., (© 2022. The Author(s).)