Shenwan Hongyuan Group: Flexible upgrade of distribution networks is timely, a 100 GWh-level blue ocean market is launching.

date
10:44 14/09/2026
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GMT Eight
Recommended focus: first, energy storage system integrators with grid customer resources; second, equipment companies with distribution network adaptability and cluster scheduling capabilities; third, virtual power plant and integrated energy service providers with distributed resource aggregation, power trading, and cross-regional operation capabilities.
Shenwan Hongyuan Group released a research report stating that in the short term, focus on the ramp-up of grid bidding and procurement, and in the medium to long term, focus on the establishment of market-based revenue mechanisms. The bank believes that distribution area energy storage is at a critical stage transitioning from demonstration and validation to batch replication, and recommends focusing on: first, energy storage system integrators with grid customer resources; second, equipment enterprises with distribution network adaptation and cluster scheduling capabilities; third, virtual power plant and integrated energy service providers with distributed resource aggregation, power trading, and cross-regional operation capabilities. The main views of Shenwan Hongyuan Group are as follows: Distributed new energy growth combined with distribution network carrying capacity constraints is pushing distribution area energy storage from an "optional configuration" toward a "rigid-demand distribution network regulation resource" The large-scale integration of distributed photovoltaics, charging piles, and other resources is driving the distribution network to shift from one-way power supply to bidirectional power flow. Some distribution areas face issues such as photovoltaic reverse power flow, voltage violations, and heavy or overloaded distribution transformers. Distribution area energy storage achieves local power flow regulation through on-site charging and discharging, and can simultaneously undertake functions such as new energy consumption, peak shaving and valley filling, dynamic capacity expansion, and emergency supply assurance, becoming an important lever for enhancing distribution network flexibility. The core of competition is shifting from single equipment supply to comprehensive capabilities in "distribution network adaptation, system integration, and aggregated operation" In terms of business models, in the short term, unified grid construction and operation and equipment procurement remain the main pathways for project implementation; third-party investment and grid leasing are suitable for seasonal overload and temporary supply assurance scenarios; in the long term, participation in spot markets, ancillary services, and demand response through virtual power plant aggregation is expected to drive the industry to transform from one-time equipment sales to "equipment + operation and maintenance + operations." "Storage instead of construction" broadens the boundaries of distribution area governance, and the long-term market space is expected to reach the 100 GWh level With advantages such as short construction cycles, low retrofit costs, and diversified revenue sources, energy storage has outstanding flexible substitution value. Based on a national base of 5 million distribution areas, assuming 40% are overloaded distribution areas, and assuming that 20%-30% of distribution area energy storage retrofits are planned to be completed during the 15th Five-Year Plan period, with a calculation of 600-800 kWh per unit (considering the scaling up of energy storage), the potential market space for distribution area energy storage is approximately 240-480 GWh. Distribution network-side energy storage is expected to become a new growth pole for the energy storage industry. Risk warnings: 1) Distributed new energy and distribution area governance demand fall short of expectations; 2) Grid investment and project construction progress fall short of expectations; 3) The development of distribution area energy storage business models falls short of expectations.