The increasing amount of photovoltaic (PV) systems leads to a voltage rise in the distribution grid. By providing reactive power, PV and battery inverters can reduce the voltage. For this purpose, most inverters have implemented a voltage-dependent reactive power curve, which is often parameterised once during the installation of the system. In most cases, the parameterisation does not take into account the position of the system in the grid. As a result, inverters closer to the distribution transformer provide less or no reactive power as the voltage at the beginning of a feeder is much smaller. This study presents a regulation tool, which parameterises the reactive power curve in dependence on the position in the grid. This leads to a coordinated behaviour of all inverters in a distribution grid and ensures that all inverters provide a similar amount of reactive power. Moreover, the regulation tool notices if the grid topology has changed and adapts the reactive power control to this change.

In future power systems with little system inertia, grid operators will require the provision of synthetic inertia (SI) from renewable energy sources. Unlike today, grid operators may require continuous provision of SI. This can lead to an unwanted disconnection of wind turbine generators (WTGs) from the grid, and has the potential to cause a significant decrease of the energy yield and financial losses for the turbine operator. In order to avoid such situations a controller is proposed, which interprets the grid codes to the benefit of all parties involved. This can be achieved by a variable inertia constant, which changes with the operating point of the WTG. In this study, the behaviour of the variable inertia constant controller is described, assessed and verified with time domain simulations.

This study presents and assesses the outcomes of inertial response tests performed on a transmission system-connected wind power plant in the Canadian province of Quebec. Frequency signals representing a response to a typical loss of generation event were injected into the wind turbines’ control systems to artificially trigger an active power increase. The measurement campaign aimed to fulfil two main objectives. First, to validate the performance of a wind turbine control algorithm designed to optimise the active power behaviour after inertial response activation. Second, to study the correlation between individual wind turbine and wind power plant behaviours during, and immediately after, an inertial response event. This publication offers an update on the capabilities and limitations of type 4 wind turbines for providing inertial response functionalities. Furthermore, it underlines the importance of understanding the various parameters that have an impact on the aggregate inertial response of a wind power plant in reality as well as in dynamic simulations. This publication also addresses how simulations can be used to predict the behaviour of inertial response from wind power plants. Final results suggest that current approaches for integrating and evaluating inertial response from wind power plants in system planning studies should be revisited.

The recent development of a number of advanced wind farm (WF) operation strategies, using designed verification studies, has resulted in various operational and economic improvements. These applications focused on stabilised conditions to confirm the improved effect derived from a maximum power extraction condition. In the case of large-scale WFs, however, a physical area with realistic environmental variations should be considered in order to conduct applicable case studies. In this study, the authors propose a modified reactive power allocation strategy, based on proportional techniques, with the system components of a WF structure for utilisation under a variety of practical situations. The proposed method introduces a modified loss prediction model, which takes the resistive components of the wind turbine into consideration. Each analysis is conducted to confirm the feasibility of active reference assignment in terms of loss reduction and flexibility. The simulations are based on electromagnetic transients using DC software tools to perform electrical loss estimation, in order to verify the effectiveness of this strategy.