Multiple base stations (BSs) cooperation can effectively reduce the inter-cell interference and especially improve the performance of the cell-edge users, which has been regarded as an important technology in future wireless communication system. All BSs full cooperation is unaffordable for system overhead, so how to partition the BSs in the system into different clusters to cooperate with a low complexity is a challenging issue. In this paper, a novel dynamic clustering algorithm for multiple BSs cooperation in downlink is proposed, and system energy efficiency (EE) is investigated. Firstly, with equal power allocation per symbol and per antenna equal power constraint, the formulas of spectral efficiency (SE) and EE for the case of ideal transmit and the case of actual transmit are derived, respectively. In addition, a novel dynamic clustering algorithm based on channel norm is presented. By calculating the mutual interference matrix according to channel norm, for each clustering judgment, the BS which has the biggest element in the present interference matrix is selected as the leader BS. Then the rest BSs which have the larger interference coefficient with the leader BS are chosen to joint the cluster until the cluster is formed. The computational complexity of the proposed algorithm is analyzed. Simulation results show that EE of the proposed algorithm is better than that of the static clustering one and slightly worse than that of the decentralized algorithm but with a lower complexity.