Reducing the power consumption and operational cost of IT servers is of great concern today. With the growth of the Internet and online services, the number of data centers is increasing day by day. Servers for many cloud applica- tions and other large providers are spread globally. Energy costs across the globe vary dynamically. Servers operate at varied energy costs based on their location and time of use. The load of a server varies based on its geographical location and the time of operation. This paper focuses on exploiting the dynamic nature of electrical power pricing, so that a cost saving is obtained by geo-location of requests to servers operating at lower costs at particular times. There exist patterns of load that are similar for different types of servers. Scheduling decisions are made considering both loads and operating costs of the servers into account, i.e., requests are scheduled to run on servers operating at low cost that also have low expected load. In order to meet the business requirements of an application, scheduling decisions for requests that have stringent SLA considerations or high server affinity, are made by assigning high priority for these requests. Geo-location of requests is done for low priority requests.