A novel distributed reinforcement learning(DRL)strategy is proposed in this study to coordinate current sharing and voltage restoration in an islanded DC microgrid.Firstly, a reward function considering both equal pro...A novel distributed reinforcement learning(DRL)strategy is proposed in this study to coordinate current sharing and voltage restoration in an islanded DC microgrid.Firstly, a reward function considering both equal proportional current sharing and cooperative voltage restoration is defined for each local agent. The global reward of the whole DC microgrid which is the sum of the local rewards is regarged as the optimization objective for DRL. Secondly,by using the distributed consensus method, the predefined pinning consensus value that will maximize the global reward is obtained. An adaptive updating method is proposed to ensure stability of the above pinning consensus method under uncertain communication. Finally, the proposed DRL is implemented along with the synchronization seeking process of the pinning reward, to maximize the global reward and achieve an optimal solution for a DC microgrid. Simulation studies with a typical DC microgrid demonstrate that the proposed DRL is computationally efficient and able toprovide an optimal solution even when the communication topology changes.展开更多
The issue of "missing baryons” is always an unsolved mystery in galaxy cosmology, and an important reason for the great uncertainty of the galaxies' formation and evolution. To find the "missing" b...The issue of "missing baryons” is always an unsolved mystery in galaxy cosmology, and an important reason for the great uncertainty of the galaxies' formation and evolution. To find the "missing" baryons, extra high-resolution spectral observation and imaging of the soft X-ray band (<1 kev) is required. However, the existing observation methods cannot meet this requirement. Therefore, Tsinghua University leads and proposes the Chinese "Hot Universe Baryon Surveyor (HUBS)" satellite program.展开更多
基金supported by National Key Research and Development Program of China(No.2016YFB0900105)
文摘A novel distributed reinforcement learning(DRL)strategy is proposed in this study to coordinate current sharing and voltage restoration in an islanded DC microgrid.Firstly, a reward function considering both equal proportional current sharing and cooperative voltage restoration is defined for each local agent. The global reward of the whole DC microgrid which is the sum of the local rewards is regarged as the optimization objective for DRL. Secondly,by using the distributed consensus method, the predefined pinning consensus value that will maximize the global reward is obtained. An adaptive updating method is proposed to ensure stability of the above pinning consensus method under uncertain communication. Finally, the proposed DRL is implemented along with the synchronization seeking process of the pinning reward, to maximize the global reward and achieve an optimal solution for a DC microgrid. Simulation studies with a typical DC microgrid demonstrate that the proposed DRL is computationally efficient and able toprovide an optimal solution even when the communication topology changes.
基金supported by the National Natural Science Foundation of China (51706233, U1831203, 51427806)Strategic Pilot Projects in Space Science of China (XDA15010400)Key Research Program of Frontier Sciences, CAS (QYZDYSSW-JSC028)
文摘The issue of "missing baryons” is always an unsolved mystery in galaxy cosmology, and an important reason for the great uncertainty of the galaxies' formation and evolution. To find the "missing" baryons, extra high-resolution spectral observation and imaging of the soft X-ray band (<1 kev) is required. However, the existing observation methods cannot meet this requirement. Therefore, Tsinghua University leads and proposes the Chinese "Hot Universe Baryon Surveyor (HUBS)" satellite program.
