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With the rapid growth of thermostatically controlled loads, active power fluctuation and peak demand growth within an autonomous micro-grid become serious problems. This paper tries to suppress power fluctuation and shave peak demand for a micro-grid through optimizing domestic electric water heaters (controllable load). In this paper, domestic electric water heater models are first built to optimize power flow within a single water heater. Subsequently, the Monte Carlo method is proposed to simulate power consumption of a cluster of domestic electric water heaters. After that, the temperature state priority list method is presented to suppress power flow and shave peak demand for a given micro-grid. Optimization results show that the proposed temperature state priority list method can reduce peak demand by 12.5%. However, it has a wider active power fluctuation range and needs a longer reaction time compared with the simplified temperature state priority list method. In addition, the optimization results show that by increasing the number of controllable loads participating in load scheduling, active power fluctuation can be reduced and the maximum active power of the given micro-grid can be cut. However, to achieve this, about 1.2% of extra electrical energy needs to be generated by the external grid.