Optimisation of wind farm reactive power for congestion management

Abstract

Variable speed wind turbines are fast becoming the most adopted form of turbine in the harvesting of wind energy. Global awareness of a carbon free mode of electricity generation is driving the interest in the installation of this technology. With increasing wind farm connections on power systems, effective congestion management is vital for maintaining a secure and stable system. Power electronics enable the control of reactive power from modern wind turbines. In this paper the control of this resource has been incorporated into an AC Optimal Power Flow (OPF) tool. This work investigates the ability of wind farms in altering system flows with the aim of easing congestion. This paper shows that minimising the power flow through a selection of congested lines is possible with the coordinated response of reactive power dispatch from wind farms.

Information Gap Decision Theory based congestion and voltage management in the presence of uncertain wind power

“…The analysis is undertaken on the transmission system where it can be assumed that only active power injections affect voltage angle and reactive power injections will only contribute to a change in voltage magnitude. The coordinated dispatch of reactive power on a distribution system, as in [14], affects both the magnitude and phase of the voltages on a network; informing the solution to optimally allocate reactive power from DG to manage congestion.…”

“…The objective function (14) aims to minimize the sum of power flow in all lines of the network, across multiple periods, t. min :…”

“…The reactive power from DG is the sole control variable used by the AC OPF tool, through (14) to achieve the objective. With the objective of minimizing the complex power flow the intention is to ease congestion and better manage the thermal limits of the network.…”

“…The method of allocating the nodes which are most influential to the objective of this work (14), is formulated in Appendix B. The DR allocation method returns, in ranked order, the most influential nodes in the system where providing flexibility of the demand would have most impact on the objective function (14).…”

“…The DR allocation method returns, in ranked order, the most influential nodes in the system where providing flexibility of the demand would have most impact on the objective function (14). The CONOPT solver of GAMS [25] is used to solve the non-linear power flow problem and IGDT modeling.…”