  Motivated by the benefits of multi-energy integration, this paper establishes
a bi-level two-stage framework based on transactive control, in order to
achieve optimal energy provision among interconnected multi-energy systems
(MESs). At the lower level, each MES autonomously determines the optimal set
points of each controllable assets by solving a cost minimization problem, in
which rolling horizon optimization is adopted to deal with load and renewable
energies' stochastic features. A technique is further implemented for
optimization model convexification by relaxing storages' complementarity
constraints, and its mathematical proof verifies the exactness of the
relaxation. At the upper level, a coordinator is established to minimize total
costs of collaborative interconnected MESs while preventing transformer
overloading. This collaborative problem is further decomposed and solved
iteratively in a two-stage procedure based on market-clearing mechanism. A
distinctive feature of the method is that it is compatible with operational
time requirement, while retaining scalability, information privacy and
operation authority of each MES. Effectiveness of the proposed framework is
verified by simulation cases that conduct detailed analysis of the
autonomous-collaborative optimization mechanism.
