Optimal Unified Power Flow Controller Planning in Transmission Grids with Uncertainty Consideration

The increasing penetration of uncertain and intermittent renewables in transmission networks has now posed considerable impacts on system normal operation. As a promising technical solution, unified power flow controllers (UPFCs) can be duly placed to enhance the branch loadability, decrease voltage deviation and reduce power loss by independently managing active and reactive power flow. To deal with the uncertainties involved in renewable generations (i.e. wind and solar PV) and loads, stochastic programming is employed to formulate the UPFC planning problem. This model is aimed to minimize the expected power loss cost, penalty cost for voltage deviation, investment and operational cost of UPFCs under representative operation scenarios, which are extracted by real-world historical data. Mathematically, the proposed model is formulated as a mixed-integer nonlinear programming (MINLP) problem, then we introduce a linearization approach and an approximation method to linearize the model. Further, this two-stage problem can be solved by the newly proposed Benders decomposition-based solution method. The case studies on the modified IEEE 57-bus demonstrate the effectiveness and efficiency of the proposed model and solution method from several aspects, such as performance analysis of the UPFC placement, comparisons with the deterministic model and sensitivity analysis.