Stability optimization for distributed generation of load-following energy

Increasing integration of distributed energy resources is severely impacting the operation of the power grid, modifying its topology and making it necessary to revise different technical issues that follow the massive implementation of these resources. One interesting point being currently discussed is the use of distributed energy resources for the provision of ancillary services such as load-following. However, in a grid with variable and widespread renewable generation, meteorologic and economic factors impact directly the flow of energy, which correspondingly alter the dynamic interactions between power inverters. In order to ensure stable operation, we derive a system model considering both grid and inverter parameters, while the amount of operating reserve and therefore the droop gains of the inverters are given by a higher-level clustering algorithm which considers weather forecasts and market constraints among others. System stability is examined and a decentralized improved controller is introduced. The controller parameters are derived solving an optimization problem, stabilizing the system without altering the droops. The proposed controller is simulated with real-world grid and inverter parameters, showing its stabilizing capabilities for a set of n inverters injecting power into a low-voltage grid.