Aiming at the problem of energy conservation and optimal deployment of WSN, this paper establishes an optimal coverage model. Meanwhile, an energy saving deployment algorithm is proposed based on the particle swarm theory and quantum behaved particle swarm optimization. The quasi physical strategy, namely the quasi-gravitation and quasi-coulomb force, are introduced in the position evolution equation of quantum particle swarm optimization algorithm, which can regulate the distance between the sensor nodes reasonably. Also, the algorithm can obtain the fast optimization with low regional repetition rate. In addition, the sensing radius of WSN nodes is adjusted dynamically in order to minimize the node energy consumption. The simulation results show that the proposed algorithm has better performances in terms of network coverage rate and convergence speed, compared to the traditional particle swarm and quantum behaved particle swarm optimization schemes. At the same time, the algorithm has certain advantage in reducing the node energy consumption in WSN.