By locally solving an optimization problem and broadcasting an update message over the underlying communication infrastructure, demand response program based on the distributed optimization model encourage all users to participate in the program. However, some challenging issues present themselves, such as the existence of an ideal communication network, especially when utilizing wireless communication, and the effects of communication channel properties, like the bit error rate, on the overall performance of the demand response program. To address the issues, this paper first defines a Cloud-based Demand Response (CDR) model, which is implemented as a two-tier cloud computing platform. Then a communication model is proposed to evaluate the communication performance of both the CDR and DDR (Distributed Demand Response) models. The present study shows that when users are finely clustered, the channel bit error rate is high and the User Datagram Protocol (UDP) is leveraged to broadcast the update messages, making the optimal solution unachievable. Contradictory to UDP, the Transmission Control Protocol (TCP) will be caught up with a higher bandwidth and increase the delay in the convergence time. Finally, the current work presents a cost-effectiveness analysis which confirms that achieving higher demand response performance incurs a higher communication cost.

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