This paper describes a rapid algorithm deployment platform for Smart Grid research. Accounting for the complex interplay of power system dynamics and communication delays in the network by means of rapid code deployment during algorithm design can improve the evaluation of Smart Grid control schemes and their impact on grid power quality. Our novel approach bridges the gap between the implementation of highly realistic multi-timeframe simulations, and expensive hardwired deployment. The architecture and behavior of the platform is presented for one specific Demand Response algorithm namely Dual Decomposition. Large numbers of distributed agents are efficiently managed by employing FIPA compliant Agent Management Specification (AMS) and Directory Facilitator (DF) functionalities, as well as an efficient SQL database monitoring and logging scheme. The architecture is deployed both on an actual laboratory setup and a virtual OPAL-RT environment. Simulations results show that system latency and computational load increase linearly for increasing numbers of distributed agents. This novel approach provides a realistic and pragmatic solution for evaluating distributed applications for grid management, market applications and advanced monitoring of power quality requirements.