| The buildings sector account for more than 27.5% of the overall energy consumption in China, the ratio will be increased to more than 30% with the improvement of people's living standards. The Public buildings have the highest energy consumption intensity among all kinds of the buildings. In particular, within the public buildings sector, heating and cooling energy consumption account for 40%-50%. Design standards for energy efficiency of public buildings, which carried out on 1st Oct, 2015, required that energy consumed by heating, ventilation air-conditioning and lighting applications should be decreased 20%-30% than the previous edition in 2005.Heating and cooling system should undertake 7%-10% decrease, which depend on reasonable operation strategy except cold or heat source scheme, enhancement of equipment and design energy efficiency.However, operation strategy is overlooked during air-conditioning management in the exiting heating ventilation and air-conditioning(HVAC) systems. On the premise of a certain thermal comfort, it is essential to cost down HVAC system's operation fee with the constant growth of the exiting building.Based on the retrofit of a small constant flow distribution with primary pump chilled water system, different operation strategy test work was undertake during similar typical consecutive summer days, thus to evaluate component's operation condition, electricity consumption, indoor temperature and relative humidity, affection of thermal comfort. It is concluded that there is an optimum operation strategy with a certain load, which could save electricity consumption. A component-based model of the entire building- HVAC simulation system was built up in TRNSYS and calibrated by testing data based on test platform. In addition, a correlation analysis between load and six meteorological factors was carried out by stepwise multiple regression method with employing SPSS software, to provide the operator a reference between load and meteorological factor. The results shows that three factors i.e. dry bulb temperature, wet bulb temperature and rainfall have obvious significance to the load among the six meteorological factors, which explains 34.8% amount of variability.For a HVAC system, three single optimum variables, combined variables by two and three optimum factors, were chosen to minimize the objective optimum equation. There are five kinds of conditions: I.Temperature of chilled water supply(CHW) II. Flow rate of cooling water(CLR) III. Temperature of chilled water supply and return(CHW\CRW) IV.Temperature of chilled water supply and flow rate of cooling water(CHW\CLR).Temperature of chilled water supply and return, flow rate of cooling water(CHW\CRW\CLR). With regard to thermal comfort constraint, which is defined as DPPD(sum of PPD during the working day), total HVAC system electricity consumption problem was optimized by Hooke-Jeeves algorithm, Particle Swarm Optimization with inertia weight, and the above solution's hybrid optimization algorithm. For the optimum results, Kaldor Hicks improvement is adopted to explain the phenomenon of the system electricity saving.The optimum results demonstrate that significant electricity saving in total by variables optimization. For the total cost, comparing with base case settings, optimized settings for temperature of chilled water supply and flow rate of cooling water saved 14% of the total energy consumption, which is the best solution among five optimization scenarios. It is also can be found that optimization results of combined three factors i.e. the temperature of chilled water supply and return, flow rate of cooling water(CHW\CRW\CLR) could save 13.9% of the total electricity cost. Using flow rate of the cooling water(CLR) optimization showed a total energy conservation of 9.4% compared with base case model. Optimization results for temperature of chilled water supply and return indicated that 8.8% energy could be reduced by a hybrid optimization algorithm, which is lower than that of a single optimum algorithm. What is more, 5.3% energy conservation can be obtained by optimized temperature of chilled water supply, which is the lowest energy saving strategy among five methods, it is still an improvement in operation energy conservation.For optimizing settings, the results indicated that temperature of chilled water supply and return is 10?,12?,respectively, while cooling water flow rate is 100m3/h. It could be concluded that combined variables optimizing is better than a single variable optimization. With regard to optimizing algorithm, because HJ algorithm is good at local optimization while PSO algorithm is strong at global optimization, When there is an obvious difference between HJ algorithm and PSO algorithm' results, the result by hybrid optimization algorithm(PSOIW-HJ) is lower than the single algorithm used in the paper, which has a specific refinement.The paper presents a flow chart optimal strategy according to energy efficiency of five strategies and adjustability of variables during operation. It could provide analysis method and basis for similar engineering operation strategy selection by low cost or without cost.The proposed optimization method to water system of the HVAC system was verified that it could efficiently save more operation energy cost. It is a useful method by optimizing variables of the components in the HVAC system at a low cost or zero cost.Regarding to the fresh air load account for a great part of heating or cooling loads, Energy Recovery Ventilator(ERV) is proposed as an effective solution to reduce fresh air load. ERV's net recovered quantity depends on the following factors, such as indoor and outdoor environment state, the volume of fresh air and exhaust air, electricity consumption by ERV itself, which results in the total quantity of recovered energy in dynamic state. The situation that pre-cooled fresh air in winter and pre-heated in summer might be happen. In addition, energy recovered by ERV should compensate ERV fan power consumption. The aim of this study is to find optimal operating conditions for the existing office building with ERV system. An economic quantitative analysis is implemented with the full operating condition and optimal operation.This study employed TRNSYS to construct model, taking an existing office building in Chongqing as an example, outdoor air parameters state points were divided into four condition zones on ID chart by analyze of the results. The optimal operation condition was analyzed according to profit and loss analysis. The results shows that, Results indicated that if ERV only operating in zone III and IV, which ensured electricity saving could trade off fan power consumption, 65.23% electricity and 31.18% operating running time could be saved than operating throughout the heating and cooling seasons.The optimal operation conditions presented in this paper although limited to a specific case demonstrate improvement of the operation performance of the ERV. Based on the specific air-conditioning system operation period, the energy recovery equipment parameters and local climate, optimal operating conditions strategy would save more energy. |
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