Bi-level coordinated operation optimization of multi-park integrated energy systems considering categorized demand response and uncertainty: A unified adaptive robust optimization approach

This study tackles the multi-objective robust coordinated operation optimization of multi-park integrated energy systems (MPIESs) with categorized demand response (DR), accounting for diverse load characteristics across different parks, energy interdependence, uncertainties in wind and solar energy, and the flexibility of demand-side management. First, categorized DR models are developed for industrial, residential, and commercial parks to reduce system operating costs and carbon emissions. A coordinated operation optimization model incorporating categorized DR into MPIESs is then proposed. Second, a bi-level operation framework for MPIESs is introduced to address uncertainties in wind and solar energy. The first level manages day-ahead operations based on complete wind and solar forecasts for a 24-h cycle, utilizing a unified adaptive robust optimization (UARO) method to derive DR plans across parks. The second level addresses intra-day operations, leveraging the GUROBI solver to dynamically adjust electricity transactions between parks and optimize the operation of energy conversion devices in response to hourly fluctuations in wind and solar energy. Finally, a case study demonstrates the feasibility and effectiveness of the proposed categorized DR models and bi-level operation framework, benchmarking their performance against alternative operational approaches.