Research On Communication Network And Control Strategies Of Large-scale Energy-efficient Monitoring System

In the process of urbanized construction and development, the proportion of building energy consumption is increasing. In our country, the total building energy consumption occupies27.5%of the total social energy consumption. The building energy consumption has imposed the large energy burden on the state and our society, and restricted sustainable economic development to some extent. According to the research and practice from the field of energy, how to save energy efficiently from building energy consumption is currently considered as the most direct and effective way. The study of how to save building energy has become an important research issue, and it is main way that building of the Energy-efficient Monitor to save energy. This paper focuses on the design of energy monitoring network of the large-scale public buildings energy-saving and control strategies, fault detection diagnosis and recovery of heating ventilating and air conditioning (shorted as HVAC) system. Our main contributions are:(1) We have studied the large-scale energy monitoring network in depth. For consumed energy short range transmission, aiming at some special characteristics including the strong noise interference of low voltage distribution network, the frequency selectivity of the noise distribution and the complex access load leading hard to realize effective estimation and forecast for communication channel, we design a frequecy hopping OFDM-based power line carrier communication scheme for the short range transmission of consumed energy data. Especilly, we emphasize the transmission performance of frequency hopping OFDM power line carrier communication network and optimization strategies. By deducing the transmission interrupt probability function of the frequency hopping OFDM power line communication network for BPP model,and analyzing the influence of different network communication parameters on the network transmission performance,. We propose an optimal parameter group searching algorithm to optimize the transmission performance of frequency hopping OFDM power line communication network.(2) We use the group-orthogonal multi-carrier code-division multiple-access (shorted as GO-MC-CDMA) as the way of remote energy data transmission to effectively improve the system capacity and resist multiple access interference. We emphasize the multi-user detection algorithm and channel estimation algorithm,which take the Carrier-Frequency Offset (CFO) into consideration and give the system bit error rate performance of the GO-MC-CDMA uplink by using the Maximum Likelihood (ML) multi-user detection,and also give the closed-form solution..Numerical simulation results show that the GO-MC-CDMA system using ML detection not only has low complexity, but also has out-standing performance of bit error rate and against carrier frequency offset. Then we present an improved scheme to overcome some defects of LS channel estimation in GO-MC-CDMA system. In addition, we exploit the relationship between the mean-squared error (MSE) and the number of chosen first estimate value in the LS channel estimation algorithms.Based on the above relationship, we propose some rules to estimate the initial value L, and then use fussy algorithm to realize the L self-adaptive modification.The self-adaptive LS channel estimation fuzzy algorithm can automatically choose the optimal L value according to the change of the signal to noise rate,which can guarantee perfect performance of the system error bit rate. The complexity of the fussy algorithm is far below the LMMSE channel estimation algorithm, and more practical.(3) Aiming at the characteristics of the HVAC system, such as time-delay and nonlinear, we design the Smith Predictor for reducing the influence on system stability because of time-delay and also design an adaptive algorithm for improving the adaptive ability of smith predictor. On the basis of analyzing the improved smith predictive scheme, we study the adjusted rules of filtering time constant tf, and propose the self-adaptive Smith predictive compensated controlling scheme. An fuzzy adaptive PID control strategy with fast response and short feedback time based on FPAA is proposed to reduce the time-delay of controller.(4) We optimize the neural network PID control and apply it to the HVAC system to improve control accuracy and to reduce time-vary effect. In allusion to the defects of the slowly converging and easily immerging in partial minimum in the learning process of Back Propagation (BP) Neural Network (NN), a Levenberg-Marquardt (LM) algorithm has been presented. In order to solve the two problems including the choice of learning rate and the inverse matrix solving in LM algorithm, which seriously influence on both training time and converging accuracy, we use the LU decomposition method to improve the LM algorithm, and the effect of which is simulated by MATLAB. In this paper, we apply the LMBP Neural Network PID controller in cooling water cycle of heating ventilating and air conditioning (HVAC) system, also simulate and compare the results of LMBP neural network PID controller, PID controller, and BP neural network PID controller. Because the settings of initial parameter values in fuzzy neural network PID controller have an important influence on the performance of the controller, we propose an improved PSO algorithm to optimize the parameters of fuzzy neural network PID controller.(5) For solving the typical bugs of sensors and actuators in HVAC system, this paper presents a diagnosis method based on HHT-WNN. Simulation results of four typical sensor bugs (i.e. complete failure, bias failure, drift failure and decreased accuracy) show that this method can improve effectly the diagnosis accuracy, compared with BP neural network.