As global energy demand rises and climate change poses an increasing threat, the development of sustainable, low-carbon energy solutions has become imperative. This study focuses on optimizing shared energy storage (SES) and distribution networks (DNs) using deep reinforcement learning (DRL) techniques to enhance operation and decision-making capability. An innovative dynamic carbon intensity calculation method is proposed, which more accurately calculates indirect carbon emissions of the power system through network topology in both spatial and temporal dimensions, thereby refining carbon responsibility allocation on the user side. Additionally, we integrate user-side SES and ladder-type carbon emission pricing into DN to create a low-carbon economic dispatch model. By framing the problem as a Markov decision process (MDP), we employ the DRL, specifically the deep deterministic policy gradient (DDPG) algorithm, enhanced with prioritized experience replay (PER) and orthogonal regularization (OR), to achieve both economic efficiency and environmental sustainability. The simulation results indicate that this method significantly reduces the operating costs and carbon emissions of DN. This study offers an innovative perspective on the synergistic optimization of SES with DN and provides a practical methodology for low-carbon economic dispatch in power systems.

Josephson voltage standards (JVSs), which are based on fundamental physical constants, serve as natural voltage references with exceptional accuracy and long-term stability. They play a foundational role in modern precision metrology and in the development of advanced scientific instruments and measurement technologies. This paper reviews their fundamental principles, historical development, key technologies, and application progress. First, the physical mechanism of voltage reproduction based on the Josephson effect is explained. Building on this basis, the working principles, technical features, and research status of three types of standards, i.e., the conventional Josephson voltage standard (CJVS), the programmable Josephson voltage standard (PJVS), and the Josephson arbitrary waveform synthesizer (JAWS), are described in detail. Second, a series of international key comparisons conducted to validate consistency among different Josephson voltage standards is summarized. Next, novel voltage measurement techniques based on Josephson voltage standards are described, with a focus on their broad applications in establishing quantum-based power standards, enabling precise measurements with Kibble/Joule balances, developing noise thermometers, and calibrating advanced metrology standards. Furthermore, directions for further exploration in quantum measurement techniques based on Josephson quantum voltage standards are discussed, and future prospects are outlined. Finally, conclusions are presented.