Research On Using Energy Optimization Of Air-Conditioning System In Office Buildings

The air conditioning user and electric energy provider are challenged continuously by the sustainable growth of the buiding's energy consumption and power demand. The low energy efficiency and serious energy waste is a universal phenomenon for the air conditioning system of office buildings, therefore, the main research purpose of this thesis is to realize the win-win results for the air conditioning user and electric energy provider by optimizing the energy consumption of air conditioning system under different price mechanism. The energy utilization efficiency is obtained by the multiplication of conversion efficiency, transmission efficiency and use efficiency of terminal energy. The improvement for the use efficiency of terminal energy can decrease greatly energy consumption in energy conversion and transmission chain. However, the actual energy analysis of air conditioning system is often focused on transimission chain.Therefore, it is essential to find a correct analysis approach which can begin from the analysis of terminal demand for air conditionding, then backward analysis for the transmission chain. To studing the cool load demand under different price mechanism is an effective method for improving use efficiency of air conditioningsystem. Based on system enegy input ratio, optimizing the transmission chain of fan coil and VAV system is an important means for improving the transmission efficiency of air conditioning system.The main research of this theis is that the air conditioning syetem of office buildings is optimized under different price mechanism. The corresponding details are shown as follows:1. Basing on the fact that the baseline cool load for air conditioning system is hard to predict effectively under different price mechanism, a kind of BP neural networks forecasting model based on FCM optimization preprocesses is proposed. The hourly outdoor meteorological data of daily demand response predicting is clustered by adopting the FCM method. The hourly load forecasting model is obstained by training network for a large of training samples based on BP neural network. The prediction results show that the prediction precision of the model is higher than that of linearity model, especially at the great variation moment of hour load.2. A dynamic method based on optimal indoor temperature set point is proposed to solve problem of fixed indoor temperature set point under fixed power price. The minimal cool load demand is obtained by optimizing indoor temperature set point. Firstly, taking a simplified office as an example, an office building model with thermal mass is constructed. According to this model, the heat balance equation about cool load with indoor temperature set point and outdoor hourly tempareture is built. Then, the relation model about PMV with indoor temperature and thermal mass inner surface temperature is built by simplified PMV. Finally, taking the least cool load demand as an objective function, PMV as constraint, the optimal model on indoor temperature set point is built. The experimental results indicate that the thermal mass can delay the creation time of cool load peak value and have the effect of peak load shifting. Compared with the26℃temperature set point, the dynamic temperature can reduce the cool load demand by7percents as well as improve the PMV index. Compared with the baseline cool load, the cool load reduces by11.2percents under fixed price.3. An optimal control method for indoor temperature set point based on minimal electricity charge is proposed to solve the problem of being hard to forecast cool load when precooling control strategy is used under TOU price. The terminal energy of the air conditioning system is obtained by optimizing indoor temperature set point. Taking a simplified office as an example, an office building model with thermal mass is constructed. Basing on this model, the heat balance equation about indoor temperature set point and cool load is built during work and precooling. It is analyzed that the parameters of thermal mass influence on cool load. Taking the least electricity charge as an objective function, PMV as constraint, and indoor temperature set point and precooling time as decision variable, the optimal model is built. Comparing with no adoption of precooling stratege, the experimental results indicate that using the precooling control strategy ahead of two hours based on two-stage TOU power price can reduce the electricity charge by9percents, as well as ensure the unchanged PMV index. Compared with the baseline cool load, the cool load reduces by by25.5percents under TOU price. Therefore, it can realize peak load shifting for adoping the TOU price.4. An optimal method of dynamic position and changed pressure difference for the fan coil pump is proposed to solve problem of fixing most disadvantaged position and pressure difference.Firstly, starting from the difinition of the water maladjustment degree, a new judgment method was obtained to ensure the most disadvantaged branch position with the water maladjustment degree. Then, according to the judgment method, the system flow is regulated for the water system based on the cool load demand under fixed power price. Finally, taking the least energy input ratio of pump as an objective function, the resistance characteristic coefficient and pump lift is optimized under fixed power price. The experimental results indicate that compared with end pressure control method, the optimal method can reduce the pump consumption by20percents as well as improve the hydraulic aberration of the coupling pipe network.5. Thinking of transmission chain of VAV of office buildings the air conditioning optimal model based on system energy input ratio is proposed to meet cool load demand under different price mechanism. Firstly, according to each equipment characteristic, the performance curve model of each equipment power is built. Based on these models, the performance curve model of system energy consumption is built too.Then, basing on energy conservation constraint, each equipment performance constraint and coupling constraint, the constraint equation is built. Finally, simplifying the model parameter, taking the least energy input ratio as an objective function, the optimal set point model of various equipments is built. The experimental results indicate that compared with the least energy consumption optimal method, the ststem power is improved by6.89percents under fixed power price, by7.28percents under TOU power price. Therefore, this method has better energy saving effect.Finally, we point out a few existing problems to be solved after summarizing the works done in this dissertation.