Study On Key Technologies In Wireless Sensor Networks For Intelligent Power Utilization

Intelligent Power Utilization (IPU) is an important part of smart grid, while Wireless Sensor Network (WSN) plays a significant role in the local network communication to support IPU’s system. Given the fact that IPU related services are of distinct characterisitics, the releated WSN research faces a new challenge. By analyzing the operational characteristics of IPU’s services, this dissertation intends to study the key technologies of WSN to support IPU, which will build the theoretical base for the constraction of smart grid in China and the industry-oriented application of WSN technology.Firstly, the dissertation studies the compressive sensing modeling of low power-expenditure imformation to decrease data’s content in WSN and statistics actual samples of electricity consumption, which focuses on analyzing the characteristics of the electricity information. The calculation of normalized correlation-coefficients demonstrates that the electricity in adjacent time of residents implies the charactersisticsof high correlation, redundancy, which can be sparse. On the basis of the conclusion above, biorthogonal wavelet matrix and gaussian random matrix are implemented as the sparse measurement system. Furthermore, two-step iterative shrinkage algorithm is proposed to reconstruct target signals.Simulation results illustrate that the proposed model and related algorithnm can maitain the good structure of original data and decrease the network data effectively.Secondly, a congestion control algorithm based on Compressed Sensing is proposed to the congestion control issue of WSN in IPU inspired by the mechanism of data aggregation, which implements source-data compression to reduce network traffic via data compression. Furthermore, a congestion control algorithm based on flow prediction is proposed inspired by the mechanism of rate control, which implements both local and global’s rate control for WSN congestion control.Simulation results illustrate that both algorithms can improve network’s QoS (Quality of Service) performance in the state of network congestion.Thirdly, an adaptive service-classified power control algrithm is proposed to power control issue of WSN in IPU, which is based on analysing the impact of power control on QoS of electricity information and the impact of interference between WSN nodes. The proposed algorithm implements service-classification mechanism to ensure QoS requirements of different services, and reduce node-interference by means of adaptive power mechanism. Simulation results illustrate the effectiveness of the algorithm.Finally, a region-energy routing algorithm based on mixed virtual potential field is proposed to the routing optimization issue of WSN in IPU, which constructs a mixed virtual potential field based on the hop count of nodes to sink, reserving energy of single node and region-energy to avoid relatively lower reserving energy regions. The proposed algorithm selects node’s force of the mixed virtual potential field as metric to choose the next hop of routing operation, which may balance the consumption of nodes’ energy. Simuation results illustrate that the proposed algorithm has superior performance over similar algorithms because it is capable of balancing energy consumption and extending the network life time.