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Data centers are the basis of the formation of Cloud computing systems. As is widely known, their overall operational costs directly link the resource management algorithms implemented used to assign virtual machines (VMs) to actual hardware servers and degrees of flexibility to relocate them elsewhere in case of emergencies usually associated with power losses of excessive heating of system elements. In this paper, we propose and analyze a hierarchical SLA-based distributed hierarchical resource allocation and optimization scheme, that considers constraints such as energy consumption and cooling-related energy consumption in addition to the scalability issue. We also incorporate a load balancing algorithm to minimize the operational costs of the proposed distributed data center cloud system. Simulation results show that the scheme together with load balancing significantly reduces the operational cost of the overall cloud system when taking into account the dynamic energy tariffs as a result of incorporating renewable power sources to provide power to the servers.