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Inverse optimization and robust aggregation based bidding strategy for distributed energy resource aggregators using multi-agent reinforcement learning
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DOI：10.1016/j.ijepes.2025.111468.png)
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Abstract
En 中文
• A novel inverse optimization model surrogates the economic parameters of heterogeneous loads. • A two-stage adaptive robust optimization model to evaluate the flexibility of aggregator. • Hybrid framework embeds both physical models in a multi-agent bidding method for aggregators.
Keywords:
Inverse optimization
Economic parameter surrogation Adaptive robust optimization
Flexibility aggregation
Bidding strategy
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