Adaptive Price Estimation in Cognitive Radio Enabled Smart Grid Networks

摘要

This paper focuses on the allocation of resources to cognitive users in a two-way cognitive radio facilitated smart grid (SG)network. The resources are essential in controlling the performance of demand response management in the SG, ensuringprofit to the power supplier and simultaneously cost-saving to the consumers. However, cognitive users need more power fortheir data transmission, which compels the utility company to increase its electricity price. Hence, we propose an adaptiveresource allocation algorithm based on normalized least mean squares (NLMS) to estimate the electricity price that benefitsboth the supplier and consumers with optimal allocation of power demands under the constraints of transmission power,system throughput, and the probability of detection. The simulation results validate the performance of our proposed schemeby comparing it with the application of metaheuristic algorithms for maximizing aggregate profit. The impact of the channelparameters on system performance is also studied.