Dispatch optimization of multi-station integrated system in 220 kV substations using the primal-dual interior-point method

The multi-station integrated system (MSIS) integrates traditional substations with renewable sources such as photovoltaics, wind power, energy storage, and electric vehicle (EV) charging to enhance energy efficiency and economics. However, the challenge remains on how to efficiently integrate and utilize these resources while ensuring a stable and reliable power supply. This paper proposes a primal-dual interior-point-based scheduling method for a small-scale multi-energy system in a 220 kV substation integrating electricity, solar, wind, and geothermal energy. The MSIS within this substation solely supplies power to the EV charging station, hydrogen production station, ground source heat pump system, and internal lighting loads. Mathematical models are established in this paper for various energy sources and loads to describe their characteristics. An optimization scheduling model for the MSIS within the substation is constructed, aiming to maximize system profits. Constraint conditions include energy balance, charging and discharging power, water storage volume, gas tank capacity, and energy storage battery capacity. This model employs a combination of the primal-dual interior-point method and rolling optimization to seek the globally optimal energy scheduling strategy. Simulation results based on a system configuration reflective of real-world deployment in Wuhan demonstrate that, compared with the grid-only baseline, the proposed strategy reduces electricity purchase cost by 20.4%, achieving the lowest net energy cost of 970.05 Chinese Yuan and the highest carbon reduction benefit of 1993.80 kg. Moreover, the optimization helps reduce peak demand, fill valleys, and improve the load-balancing capability of the power grid.