In recent years, Wireless Sensor Networks (WSN) gained popularity in sensing information from an interesting area. Day by day new technologies are emerging with innovative features, which make this field active for development and research oriented work. Since the available energy of sensor nodes are limited and hard to renew, energy supervision is critical for nodes and network lifetime in wireless sensor networks. In this paper, clustering algorithms like LEACH, K-means, Fuzzy c means are applied in WSN scenario for sensing applications to reduce energy consumption. We propose modifications on the above-mentioned algorithms by selecting cluster heads (CH) based on the residual energy of the sensor nodes. Simulation results show that the proposed approach produces better cluster head energy efficiency.