Optimal substation capacity planning method in high-density load areas considering renewable energy

Abstract

With the increasing penetration of renewable energy, the adaptability of the existing substation planning model in terms of capacity and quantity of transformer needs to be further studied when preferring large-capacity substations. Considering the variations of renewable energy penetration rate and load, this paper proposes a method to optimize the total capacity of substations in distribution networks. This paper introduces the influence of renewable energy access on power supply reliability and introduces the idea of partitioning for economic analysis of reliability. An economic analysis model for simultaneously optimizing the capacity and quantity of substation transformer in the distribution network is constructed, taking into account the effects of reducing net load and enhancing the reliability of the distribution feeders resulting from renewable energy access to the medium and low voltage side of the substation. Various wiring means of the distribution network are retained and the impact of renewable energy access on the reliability of the network power supply is quantified. The optimization model is solved by the multivariate universe optimizer(MVO) algorithm with stronger optimality finding capability and short solving time. Finally, the case study results of a regional distribution network are employed to demonstrate and verify the validity and rationality of the method.

Keywords

• Large capacity substation
• Renewable energy
• Multivariate universe optimizer
• Reliability
• Economic analysis