Model Of Solar Heating System Research Articles

Smart Evaluation Index of Roof SHS Suitability

The instability of solar energy and its resource distribution characteristics make it difficult to judge its suitability in practical engineering applications, which hinders its promotion and application. In order to better promote the effective use of solar energy and promote the solar heating system, it is necessary to put forward a simple method of judging the suitability of the solar heating system for engineering application. This study puts forward “F, Q” as the basis for judging the suitability of solar heating systems built on the roof. Two types of public buildings, office buildings and three-star hotels, are taken as the research objects. DeST software is used to change the heating area of the building by superimposing floors to simulate the heat load of the building when the heating area changes. A dynamic simulation coupling model of solar heating system is established in the TRNSYS software to analyze the operating status of the system under all working conditions. The functional relationship between “F, Q” and solar energy guarantee rate is established, and the solar energy contribution rate is divided into three regions of F < 30%, 30% ≤ F ≤ 50%, and F > 50%. The evaluation standard of the building suitability of the solar energy heating system is established according to the scope of “F, Q” in different regions (An office building for, e.g., if the contribution rate of solar heating system is required to be greater than 50%, the “F” of these four areas should be greater than 0.11388, 0.15543, 0.10572, and 0.04511.), and the effectiveness of “F” is verified through actual cases verified by other scholars in the research. The method proposed in this paper is helpful to judge the suitability of solar heating systems in different regions and different types of conventional buildings, so as to better promote solar heating systems.

Mathematical Modeling of Solar Heating System for an Aluminum Factory

Mathematical Modeling of Solar Heating System for an Aluminum Factory

Maximum-power-point tracking control of solar heating system

The present study developed a maximum-power point tracking control (MPPT) technology for solar heating system to minimize the pumping power consumption at an optimal heat collection. The net solar energy gain Qnet (=Qs−Wp/ηe) was experimentally found to be the cost function for MPPT with maximum point. The feedback tracking control system was developed to track the optimal Qnet (denoted Qmax). A tracking filter which was derived from the thermal analytical model of the solar heating system was used to determine the instantaneous tracking target Qmax(t). The system transfer-function model of solar heating system was also derived experimentally using a step response test and used in the design of tracking feedback control system. The PI controller was designed for a tracking target Qmax(t) with a quadratic time function. The MPPT control system was implemented using a microprocessor-based controller and the test results show good tracking performance with small tracking errors. It is seen that the average mass flow rate for the specific test periods in five different days is between 18.1 and 22.9kg/min with average pumping power between 77 and 140W, which is greatly reduced as compared to the standard flow rate at 31kg/min and pumping power 450W which is based on the flow rate 0.02kg/sm2 defined in the ANSI/ASHRAE 93-1986 Standard and the total collector area 25.9m2. The average net solar heat collected Qnet is between 8.62 and 14.1kW depending on weather condition. The MPPT control of solar heating system has been verified to be able to minimize the pumping energy consumption with optimal solar heat collection.

A finite element model of solar heating system with underground storage

In this study, the performance of a solar heating system with seasonal storage is evaluated using finite element method. The time-dependent heat transfer problem between storage and the surrounding ground is solved by using a computer program in MATLAB and the transient temperature distribution in ground and transient temperature of water in the storage are calculated. The effects of storage volume and solar collector area on annual average temperature distribution in the ground surrounding storage are investigated. It is observed that the temperature of water in the storage increases with increase of the solar collector area. It was found that the water temperature for storage surrounded with sand ground was higher than the other ground types.