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Energy consumption is an increasingly important consideration in computing. High-performance computing environments consume substantial amounts of energy, at an increasing financial and environmental cost. We explore the possibility of reducing the energy consumption of a grid of heterogeneous computers through appropriate resource allocation strategies. We examine a number of possible grid workload scenarios and analyse the impact of different resource allocation mechanisms on energy consumption. We perform this analysis first on a cluster of heterogeneous nodes, then on a grid of several clusters. Our results show that different resource allocation mechanisms perform better under different scenarios, and that selection of an appropriate resource allocation mechanism can significantly reduce the total grid energy consumption.