The volatility of renewable energy leads to numerous voltage changes in a short period, thus
affecting the quality of the power supply. A real-time smart voltage control framework of …

In recent years, the rapid development of artificial intelligence, especially deep learning
technology, makes machine learning have application scenarios in the fields of power …

This paper designs a reactive power optimization strategy based on multi-agent deep
reinforcement learning soft actor-critic (MASAC) algorithm. Compared with the traditional …

To learn human intelligence, the social system/human system is added to a cyber–physical
energy system in this paper. To accelerate the configuration process of the parameters of the …

With the integration of renewable energy, pumped storage, and new energy storage into
multi-area integrated energy systems, the generation control of multi-area integrated energy …

The increasing penetration of distributed renewable energy resources causes voltage
fluctuations in distribution networks. The controllable active and reactive power resources …

This study proposes a novel control strategy based on deep Q learning (DQL) for smart
generation control of large-scale interconnected power systems. In this novel DQL algorithm …

Because of the high penetration of renewable energies and the installation of new control
devices, modern distribution networks are faced with voltage regulation challenges …

The integrated energy system based on ubiquitous power Internet of Things (IoT) has the
characteristics of ubiquitous connection of everything, complex energy conversion mode …

Recently, a modularized smart grid (SG) architecture, entitled the Internet of Things (IoT)
grid, is developed that accommodates the IoT technology into the dc–dc converters to build …