A fuzzy logic controller to increase fault ride-through capability of variable speed wind turbines

A fuzzy controller for improving Fault Ride-Through (FRT) capability of Variable Speed Wind Turbines (WTs) equipped with Doubly Fed Induction Generator (DFIG) is presented. The controller is designed in order to compensate the voltage at the Point of Common Coupling (PCC) by regulating the reactive and active power generated by WTs. The performances of the controller are evaluated in some case studies considering a different number of wind farms in different locations. Simulations, carried out on a real 37-bus Italian weak distribution system, confirmed that the proposed controller can enhance the FRT capability in many cases

A fuzzy controller for maximum energy extraction from variable speed wind power generation systems

The wind power production spreading, also aided by the transition from constant to variable speed operation, involves the development of efficient control systems to improve the effectiveness of wind systems. This paper presents a data-driven design methodology able to generate a Takagi–Sugeno–Kang (TSK) fuzzy model for maximum energy extraction from variable speed wind turbines. In order to obtain the TSK model, fuzzy clustering methods for partitioning the input–output space, combined with genetic algorithms (GA), and recursive least-squares (LS) optimization methods for model parameter adaptation are used. The implemented TSK fuzzy model, as confirmed by some simulation results on a doubly fed induction generator connected to a power system, exhibits high speed of computation, low memory occupancy, fault tolerance and learning capability

Massive data analysis to assess PV/ESS integration in residential unbalanced LV networks to support voltage profiles

The integration of energy storage systems (ESSs), co-located with distributed photovoltaic (PV) units in low voltage (LV) networks, offers new opportunities to support distribution system operator (DSO) in distribution network operations and management. The deepening penetration of renewable resources exacerbates the challenge to maintain demand–supply equilibrium. ESSs can tackle this challenge making PV resources dispatchable. Here, we apply a Monte Carlo analysis considering different residential load profiles and PV/ESS characteristics (e.g., penetration levels, locations, and capabilities) to assess the impact that two different control strategies have in supporting the DSO in improving the power quality of the distribution network