基于气象数据的家用太阳能热水系统利用优化方法研究

Optimization study on domestic solar water heating systems based on meteorological data

中文关键词: 家用太阳能热水器  太阳辐射数据库  天气状况  预测制自动控制系统

英文关键词: Domestic solar water heating system  Solar radiation data  Weather pattern  Hot-water estimation  Automatic control system

中文摘要:

      太阳能热水系统每天的太阳能制热水量及用户在不同季节天气中的热水需求量会不同，但家用太阳能热水系统的水箱容量都普遍偏大，在冬季或阴雨天使用辅助能源加热的整箱热水有剩余，造成辅助能源的浪费。本研究提出依据天气状况利用历年气象数据预测太阳能制热水量的方法，从而自动控制水箱水量来提高家用太阳能热水系统热利用效率。在自动控制器中录入各地区历年太阳辐射量数据库和各种太阳能热水系统的太阳能制热水量计算程序，用户可依据当天天气预报的天气状况使用自动控制器就能预测出当天的太阳辐射量可能加热的热水量，再根据自身的热水需求情况选择是否增加辅助能源热水量。此方法在满足用户使用需求的同时提高太阳能有效利用率，也避免浪费不必要的辅助能源。研究以太阳能资源较贫乏地区（Ⅳ区）的南宁市为例进行实验验证，结果可预测出当天太阳辐射制热水量，并能够控制热水出水温度与目标水温的偏差在5℃以内。

英文摘要:

      Geographical environment, climate, season and weather are the factors that affect daily hot water heated by solar energy in domestic solar water heating systems (DSWH). Because of different climates, season, weather and hot-water using habits, the amount of daily consumed hot-water is different from different users. Hot water consumed in a household is also different in different seasons and weather conditions. In general, all water in the hot-water tank will be heated up to the setpoint temperature by auxiliary energy on winter days or dull rainy days. This would result in consumption of large auxiliary energy due to a larger size of the hot-water tank in DSWH systems. Therefore, this study proposed a method for predicting the solar heated hot-water every day based on meteorological data and intraday weather, and developed an intelligent controlling system to control the water amount in the hot-water tank so as to improve utilization of collected solar heat. Hot-water calculation programs and data base such as local solar radiation were assigned into the developed intelligent controller. According to weather information from weather forecast on a day, the user can use this intelligent controller to predict the amount of hot water that may be produced only by solar radiation on that day, and can also select the amount of hot water according to user"s needs. The increased hot water can be heated by auxiliary energy. The proposed controlling method can optimize utilization of collected solar energy in meeting the user"s needs, and also can reduce auxiliary energy consumption. A case study was conducted in Nanning for verifying the effectiveness and applicability of the proposed controlling system. Nanning is located in the forth zone with poor solar energy resource. Experimental results show that the developed intelligent controller can predict the amount of solar-heated hot water according to the weather, and the differences between predicted and measured temperatures of hot water are within 5℃.