  The integration of individual microgrids (MGs) into Microgrid Clusters (MGCs)
significantly improves the reliability and flexibility of energy supply,
through resource sharing and ensuring backup during outages. The dispatch of
MGCs is the key challenge to be tackled to ensure their secure and economic
operation. Currently, there is a lack of optimization method that can achieve a
trade-off among top-priority requirements of MGCs' dispatch, including fast
computation speed, optimality, multiple objectives, and risk mitigation against
uncertainty. In this paper, a novel Multi-Objective, Risk-Sensitive, and Online
Trust Region Policy Optimization (RS-TRPO) Algorithm is proposed to tackle this
problem. First, a dispatch paradigm for autonomous MGs in the MGC is proposed,
enabling them sequentially implement their self-dispatch to mitigate potential
conflicts. This dispatch paradigm is then formulated as a Markov Game model,
which is finally solved by the RS-TRPO algorithm. This online algorithm enables
MGs to spontaneously search for the Pareto Frontier considering multiple
objectives and risk mitigation. The outstanding computational performance of
this algorithm is demonstrated in comparison with mathematical programming
methods and heuristic algorithms in a modified IEEE 30-Bus Test System
integrated with four autonomous MGs.
