Distributed wind power faces significant operational challenges due to its inherent variability and the risk of energy curtailment when output exceeds grid demand. A new planning methodology addresses these issues by coupling wind installations with hydrogen production and battery storage systems, creating a more flexible and economically viable energy ecosystem.
Researchers have developed a hybrid stochastic-robust optimization (HSRO) framework that determines optimal equipment capacities in an initial planning stage, then evaluates operational performance across multiple realistic scenarios. The approach uses an improved K-means clustering algorithm to identify representative wind power scenarios, reducing computational complexity while maintaining accuracy.
The joint planning model maximizes annualized profit while accounting for grid-connection penalties that discourage excessive power fluctuations. Rather than treating hydrogen production and storage as competing technologies, the framework intelligently allocates investment between water electrolyzers and battery systems based on typical wind patterns and market conditions.
Case studies demonstrate significant advantages over conventional approaches. Compared to traditional stochastic planning and pure robust optimization methods, the HSRO model achieved optimal profits of approximately 145 million Chinese Yuan by strategically reallocating capital from over-sized battery storage toward electrolyzer capacity. This rebalancing reflects the reality that hydrogen production offers longer-duration energy shifting and industrial applications, while batteries serve shorter-duration smoothing needs.
The predictive analysis extending to 2050 reveals how optimal capacity configurations evolve over time, providing valuable strategic guidance for utilities planning large-scale wind integration. By smoothing wind output variations and converting excess power into storable hydrogen, the system reduces curtailment, improves grid stability, and creates additional revenue streams through hydrogen sales.
This methodology provides power system planners with a practical tool for evaluating multi-technology portfolios around variable renewable resources, balancing technical performance with financial returns in an increasingly decentralized energy landscape.
