A Second-Order Cone Optimization Method for Distribution Networks Containing Renewable Energy Sources

Vigorous development of renewable energy sources is an important way to achieve the dual-carbon goal. The large amount of distributed renewable energy sources introduces significant uncertainty and challenges the economic operation of the system. This paper proposes a second-order cone optimization method for a power distribution network with a high proportion of renewable energy to improve system operation economy. First, the wind power generation model is introduced to obtain the relationship between wind speed and wind power. Next, the photovoltaic power generation model is provided to derive the relationship between light intensity and photovoltaic output. Then, the power system optimization model containing renewable energy sources is constructed and transformed into a second order cone convex optimization problem through conditional relaxation, which is effectively solved via “Gurobi”. Finally, simulations are conducted on the IEEE 33-bus distribution system to verify that the proposed method could rapidly achieve the system solution while improving the system operation economy.