Research On Optimal Operation Strategy Of Solar-assisted Air Source Heat Pump Hot Water System

With the increasing energy demand and environmental pollution caused by the burning of a large number of fossil fuels,the problem of energy shortage and environmental pollution has become the focus problem of the world.The heat-pump-assisted solar water heater(HPASWH)has become an excellent choice for alleviating energy shortages in the future due to its low energy cost and environmental protection.The joint hot water project composed of solar energy and air source heat pump can effectively compensate for the sensitivity of climate to solar hot water system and realize continuous heating in all-weather condition.However,the current control strategy of system is simply based on some timing start-stop controls.The lack of efficient control strategy leads to low system COP.Based on a HPASWH system,which is installed in a university in Lishui area,this paper analyzes the whole process of this system,then models the process units.The optimal operation strategy to reduce water production cost is studied.After reading and analyzing domestic and foreign documents,the following research works are carried out:(1)Based on the analysis of the structure and work flow of the HPASWH system in Lishui,the system is divided into three process unit parts:collector unit,heat pump unit,and hot water storage tank unit.The mechanism models of those process units are established,and the model parameters are identified based on the test data.1)The heat loss coefficient of the collector unit is identified by using the historical data as 0.86～0.94W/(m~2·℃);2)For the heat pump unit,the empirical model is used for fitting,and the determination coefficient,R-square,of COP after fitting is 0.9465;and the coefficient,R-square,of power P after fitting is 0.9898,which can better fit the performance of heat pump;3)The water tank is divided into three nodes for its temperature stratification phenomenon,and different injection strategies are adopted according to the entering temperature of the tank to effectively improve the energy efficiency ratio of the system.(2)Taking the operating cost as the objective function,and considering the continuous changes in the water demand in the actual condition,an optimal scheduling model is established by integrating heat pump COP,irradiance changes and time-of-use electricity prices and other factors.An improved genetic algorithm(GA)is proposed to solve this optimal scheduling problem.A normal distribution prediction model is established for four seasonal irradiances in Lishui area,and discretize the irradiance probability density function from 9:00 to 15:00 to obtain the irradiance in each time period and then integrate to obtain the heat collection.The compensation value is introduced for correcting the error of each time period to keep the final model error within 8%.The area water consumption of students is studied to build a prediction model by using the sliding translation method to keep the predicted error of the water consumption peak at night is as low as 5.07%.(3)The improved GA is used to solve this optimal scheduling problem.The results show that the operating costs under four typical working conditions(sunny and rainy days in spring and autumn;sunny and rainy days in summer)are reduced by 12.3%,5.6%,52%,and 3.57%,respectively.Then the operation strategy under severe cold conditions in winter was studied.The results show that early water storage is not conducive to cost saving,and the smart choose is that storing water before the predicted peak of water consumption.Under the optimized operation plan,the operating cost has been reduced by 15.6%,and the COP has increased by 9.35%.