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The Minimization
of Electricity Consumption in Solar Hot Water System by the Use of
Fuzzy Logic Control The excessive use of electrical energy as the secondary energy source in domestic solar hot water systems is common. Available solar energy is not utilised to the full, particularly during the winter months. This research aimed to study the potential economic benefits of applying an intelligent controller to the decision making task of when to apply electric heating given historical and temporal information. It was envisaged that the appropriate control paradigm would be fuzzy logic and the fuzzy rules would be accessible via the training of a neural network. The method adopted for building the controller was through the application of a fuzzy logic controller (FLC). The FLC built consisted of two Fuzzy Inference Systems (FIS). FIS Unit no. 1 was constructed using the Adaptive Neuro-Fuzzy Inference System (ANFIS) based on measurement data taken from the typical operation of a Solar Hot Water System (SHWS). In this case, the ANFIS function was used to construct a Sugeno-type FIS which functioned as the provider of the average monthly tank temperature without draw down. The inputs used for the FIS no. 1 in achieving its function were the actual air temperature and the time-of-the-day. FIS Unit no. 2 (fuzzy switcher) was constructed based on the understanding of the typical operation of the SHWS in relation to minimizing the use of the electric booster. The fuzzy switcher was constructed as a Mamdani-type FIS in which it used a set of fuzzy rules which were formulated to minimize the electricity consumption of the SHWS. In the operation of the controller, the fuzzy switcher functioned to produce a range of numeric outputs which were later interpreted as whether to switch the electric booster ON or OFF. To perform this function the fuzzy switcher used the temperature-difference between the actual tank temperature and the average monthly tank temperature without draw down and time-of-the-day as the inputs. Next, a binary logic script was used to interpret the output of the fuzzy switcher into a Low or High decision that activated an external switching board via the serial port of the PC to control the electric booster ON or OFF. The PC based fuzzy logic controller was tested on a 150 Litre domestic solar hot water system. The test process was carried out by operating the SHWS with the FLC and without the FLC (thermostatic operation). Both operation modes of the SHWS were subject to a constant draw down in the evening period. The parameters recorded during these two test process were daily electricity consumption (kWh per day), maximum air temperature (°C) and maximum actual tank temperature (°C). For the purpose of comparing the electricity consumption, the data of the parameters recorded during the FLC operation and the thermostatic operation were used to build two FIS which served as the comparator for each operation mode of the SHWS. The test result showed that the FLC did not reduce the electricity consumption since the comparison between the FLC operation and the thermostatic operation showed that the FLC operation used higher electricity consumption which was caused by the overheating of the hot water prior to the anticipated draw down time. However, the controller operation showed that it was able to delay the electric booster usage in the morning period and keep the hot water temperature at a lower level compared to the morning period temperature achieved during the thermostatic operation. |
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