The field of energy management and power systems is moving towards more efficient and intelligent mechanisms for balancing the energy market and managing distribution networks. This is driven by the integration of renewable sources and the need to address the challenges of power outages, financial losses, and grid instability. Researchers are exploring innovative approaches, including the use of microgrids, distributed generation, and advanced control architectures. Notable papers in this area include:

• A method for identifying optimal microgrids coalitions that can address the dynamics of the energy market, using a combination of cooperative game theory and memetic algorithms.
• A distributed component-level modeling and control approach for energy dynamics in electric power systems, which has been validated on two systems and shown to improve transient response and reduce control effort.
• A quantitative indices approach for improving metro load curves using distributed generation, which has been shown to significantly improve load curve parameters.
• A general reference frame identification and transformation method for unbalanced power systems, which provides a direct transformation valid for any degree of unbalance and has been demonstrated through numerical simulations and experimental validation.