Active and Reactive Power Collaborative Optimization by Considering the Deep Peak Regulation of Thermal Power Units

In view of a series of challenges brought by large-scale wind power integration, an active and reactive power collaborative optimization model in which the deep peak shaving of thermal power units is proposed in this paper to enhance the stability and flexibility of the power grid. On the basis of AC power flow model, the collaborative optimal scheduling model which aims at minimizing unit operating cost, wind curtailment penalty cost and active network loss is proposed to improve the operating status of power system and deal with uncertainty of wind power output from both active and reactive perspectives. Then, partial constraints and objective functions are processed by second-order cone relaxation and linearization technology, and the model is simulated and verified by improved IEEE30 case in different scenarios. The optimization model established in this paper can actually reduce operating cost of the units and network active loss of system, stabilize voltage of each node during load peak periods, and promote the absorption of wind power output.