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Abstract
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networks, while district heating networks have emerged as effective solutions to enhance efficiency and flexibility
in integrated energy systems. Microgrids, as local control units, can improve resilience and stability;
however, uncertainties in demand and renewable generation, along with privacy concerns, pose challenges to
optimal operation. The purpose of this study is to present a distributed optimal scheduling for the operation of an
integrated energy system that consists of numerous microgrids interacting through a transactive energy market.
The objective is to optimize microgrids and distribution system operator cost while satisfying technical constraints,
agent privacy, and accounting for uncertainties. To achieve this, the alternating direction method of
multipliers and adaptive robust optimization are used in the decision-making processes of the distribution system
operator and each microgrid. The resulting three-level problem is efficiently solved using column and constraint
generation and nested column and constraint generation. Numerical studies under various scenarios demonstrate
the effectiveness of the proposed approach in dynamic electricity and heat pricing, leveraging building thermal
inertia to enhance flexibility, and achieving economical and reliable operation of the integrated active distribution
network and district heating network.
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