A scalable three-stage model for local energy community management and pricing

This study introduces and evaluates advanced optimization models for local energy community management, focusing on pricing and energy scheduling. We propose a novel three-stage approach to address the complexities of local energy community price determination and enhance model efficiency. The research builds upon previous works, analyzing a basic local energy community optimization model, modifying the formulation to a bi-level optimization model, and finally proposing an efficient three-stage model offering significant improvements in computational scalability and economic performance. Our results demonstrate that all models perform better than traditional business-as-usual scenarios without local transactions. Specifically, the three-stage approach balances economic benefits and computational efficiency. It achieves low net costs and optimal computational times, handling the problem with up to a thousand households in less than 2 seconds, making it particularly effective for large-scale applications. In contrast, when 1000 households are considered, the basic local energy community model cannot provide feasible solutions within acceptable times, and the bilevel model takes up to 700 seconds to provide feasible solutions. Overall, the proposed three-stage model significantly enhances model performance, providing a scalable and efficient framework for local energy community management.