<p>To enhance the local consumption of photovoltaic (PV) energy in distribution substations and increase the revenue of centralized energy storage service providers, this paper proposes a novel business model aimed at maximizing local PV consumption and the profits of centralized energy storage service providers. The study focuses on a 35(110) kV distribution substation area in Baoding City, Hebei Province, based on the actual PV output and load demand conditions. The objectives are to maximize local PV consumption and annual profits for centralized energy storage service providers. A pricing optimization model for charging and discharging centralized energy storage is constructed within this new business model, employing the NSGA-II genetic algorithm to explore optimal pricing strategies for energy storage charging and discharging. Furthermore, electricity users are categorized into four groups, and the cost–benefit models for these four user groups and centralized energy storage service providers are examined. A multi-objective storage capacity allocation planning problem is proposed to promote local PV consumption and maximize the benefits for centralized energy storage service providers. Four scenarios are set up for case analysis. The conclusions indicate that under the novel business model for centralized energy storage presented in this paper, optimized pricing strategies for energy storage charging and discharging can achieve improved local PV consumption and maximize the profits of centralized energy storage service providers.</p>