Based on the large amount and variations of the power grid task as well as its requirement of real- time performance and economic benefit, we make a further improvement and expansion of IHA (Improved Heuristic Algorithm) on the combination of bionics in genetic engineering and evolution to solve the decomposing and scheduling problems. Firstly, we transform those complex decomposing problems into the operational optimal solution problem by IHA to decrease the rate of running into the local optimal solution [1]. In task scheduling, we classify the sub-tasks by the emergency degree for resource allocation, which not only largely reduces the calculation and resource cost but also improves working efficiency and the speed of execution [2]. Finally, we select optimal scheduling scheme by the Fitness function defined about time and cost.