Dynamic optimal power flow in distribution networks with wind/PV/storage based on second-order cone programming

Day-ahead multi-period scheduling can provide reasonable operation plans for various power sources and energy storage systems in distribution networks, so as to reduce costs and improve energy utilization. In this paper, the dynamic power flow optimization model of radial distribution network with wind/PV/energy storage is established firstly. The model takes the output of various power sources and the charge-discharge power of energy storage systems as decision variables, which belongs to nonconvex nonlinear programming problems. Then the second-order cone relaxation is applied to the power flow equation, and the problem is transformed into a second-order cone programming model which can be solved strictly and efficiently. Finally, the extended IEEE 30-node system is simulated, and the software Gurobi is used to obtain the optimal scheduling scheme, which verifies the effectiveness of this method. Test results show that the operating cost is reduced by adding wind/PV/energy storage into networks, and the consumption of renewable energy is increased by considering the punishment for wind and PV abandonment.