Day-ahead optimal scheduling method for incremental distribution network with high penetration of distributed photovoltaic

Aimed at the day-ahead scheduling problem for incremental distribution network with high penetration of distributed photovoltaic and energy storage system at user side, an optimal scheduling model is established based on branch flow model. The model minimizes the total operating cost of the incremental distribution network operator and takes into account the adjustment of on load tap changer, static var compensator, reactive power control of the PV converter and charge and discharge of the energy storage system. The original model is a Quadratically Constrained Quadratic Programming (QCQP) due to voltage square and current square in the power flow constraints and current square in the loss part of the objective function. By linearization and second order cone relaxation, the original NP hard problem is transformed into a Mixed Integer Second Order Cone Programming (MISOCP). In order to ensure the precision of cone relaxation, a multi-period cutting plane constraint is proposed to calculate the optimal power flow in the distribution network, and it is added to each iterative optimization until cone relaxation error is reduced to a predetermined range. Finally, the effectiveness of the proposed scheduling method is verified by a simulation example in a practical project. © 2019, Power System Protection and Control Press. All right reserved.