In a performance-based frequency regulation market, increasing number of controllable
renewable energy will actively participate in automatic generation control (AGC) of …

In many countries, wind power is being developed as a primary source of renewable energy.
However, it is difficult to describe and forecast wind speed features, which are stochastic and …

Neuroevolution is a machine learning method for evolving neural networks parameters and
topology with a high degree of flexibility that makes them applicable to a wide range of …

In response to the automatic generation control (AGC) signals, the direct power control of a
large-scale PV power plant easily encounters the communication bottlenecks, the high …

This paper proposes a novel equilibrium-inspired multiagent optimizer (EMO) with extreme
transfer learning for decentralized optimal carbon-energy combined-flow (OCECF) of large …

Crow search algorithm (CSA) is a novel meta-heuristic optimization algorithm based on the
intelligent behavior of the crow population. Although the algorithm has the characteristics of …

The topology of the electrical distribution systems is somehow similar to the topology of
leaves as a natural optimal system. The leaves having internal loops (ILs) are more reliable …

Sport is one of the activities of human being where cooperative, competitive, self-learning
and interactive environment helps in the overall improvement of the performance. These …

This paper proposes a novel multi-agent bargaining learning (MABL) for the distributed
energy hub economic dispatch (EHED) of multiple energy carrier systems (MECS) …

This paper proposes a novel adaptive consensus algorithm (ACA) for distributed heat-
electricity energy management (HEEM) of an islanded microgrid. In order to simultaneously …