Modelling a Directly Coupled Photovoltaic Pumping System in a Solar Domestic Hot Water System

2008 ◽  
pp. 1883-1888 ◽  
Author(s):  
Y. Bai ◽  
G. Fraisse
Keyword(s):  
Water System ◽  
Hot Water ◽  
Domestic Hot Water ◽  
Pumping System

DESIGN PROCEDURE FOR SELECTING AN OPTIMUM PHOTOVOLTAIC PUMPING SYSTEM IN A SOLAR DOMESTIC HOT WATER SYSTEM

Solar Energy ◽  
1998 ◽  
Vol 64 (4-6) ◽  
pp. 227-239 ◽  
Author(s):  
A.M. Al-Ibrahim ◽  
W.A. Beckman ◽  
S.A. Klein ◽  
J.W. Mitchell
Keyword(s):  
Water System ◽  
Design Procedure ◽  
Hot Water ◽  
Domestic Hot Water ◽  
Pumping System

scholarly journals Investigation and Modelling of the Centralized Solar Domestic Hot Water System in Residential Buildings

2016 ◽  
Vol 146 ◽  
pp. 424-430 ◽  
Author(s):  
Rui Yu ◽  
Da Yan ◽  
Xiaohang Feng ◽  
Yan Gao
Keyword(s):  
Residential Buildings ◽  
Water System ◽  
Hot Water ◽  
Domestic Hot Water

Simulation of a combined heating, cooling and domestic hot water system based on ground source absorption heat pump

2014 ◽  
Vol 126 ◽  
pp. 113-122 ◽  
Author(s):  
Wei Wu ◽  
Tian You ◽  
Baolong Wang ◽  
Wenxing Shi ◽  
Xianting Li
Keyword(s):  
Heat Pump ◽  
Water System ◽  
Hot Water ◽  
Absorption Heat Pump ◽  
Domestic Hot Water ◽  
Ground Source

scholarly journals Analysis and Adaptation of Q-Learning Algorithm to Expert Controls of a Solar Domestic Hot Water System

2019 ◽  
Vol 2 (2) ◽  
pp. 15 ◽  
Author(s):  
Bettoni ◽  
Soppelsa ◽  
Fedrizzi ◽  
del Toro Matamoros
Keyword(s):  
Control Algorithm ◽  
Fuzzy Controller ◽  
Learning Algorithm ◽  
Water System ◽  
Hot Water ◽  
Reference Case ◽  
Domestic Hot Water ◽  
Q Learning ◽  
Performance Factor ◽  
Seasonal Performance

This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers without the need for devoting time to modelling and simulations to tune its parameters before deployment. The performance of the proposed control algorithm was analysed in detail concerning the input membership function defining the fuzzy controller. The algorithm was compared to four standard reference control cases using three performance figures: the seasonal performance factor of the solar collectors, the seasonal performance factor of the system and the number of on/off cycles of the primary circulator. The work shows that the reinforced learning controller can find the best performing fuzzy controller within a family of controllers. It also shows how to increase the speed of the learning process by loading the controller with partial pre-existing information. The new controller performed significantly better than the best reference case with regard to the collectors’ performance factor (between 15% and 115%), and at the same time, to the number of on/off cycles of the primary circulator (1.2 per day down from 30 per day). Regarding the domestic hot water performance factor, the new controller performed about 11% worse than the best reference controller but greatly improved its on/off cycle figure (425 from 11,046). The decrease in performance was due to the choice of reward function, which was not selected for that purpose and it was blind to some of the factors influencing the system performance factor.

Hybrid Domestic Hot Water System for Efficiency and Performance—Preliminary Design

2007 ◽  
Vol 104 (6) ◽  
pp. 63-75
Author(s):  
Joe Wiehagen ◽  
Tom Kenney
Keyword(s):  
Water System ◽  
Hot Water ◽  
Preliminary Design ◽  
Domestic Hot Water ◽  
And Performance

scholarly journals Glazed Photovoltaic-thermal (PVT) Collectors for Domestic Hot Water Preparation in Multifamily Building

2020 ◽  
Vol 12 (15) ◽  
pp. 6071
Author(s):  
Nikola Pokorny ◽  
Tomáš Matuška
Keyword(s):  
Thermal Energy ◽  
Simulation Study ◽  
Water System ◽  
Hot Water ◽  
Electrical Performance ◽  
Electricity Production ◽  
Thermal System ◽  
Conventional System ◽  
Domestic Hot Water ◽  
Photovoltaic Thermal System

Photovoltaic–thermal collector generates electrical and thermal energy simultaneously from the same area. In this paper performance analysis of a potentially very promising application of a glazed photovoltaic–thermal collector for domestic hot water preparation in multifamily building is presented. Solar system in multifamily building can be installed on the roof or integrated in the façade of the building. The aim of this simulation study is to show difference of thermal and electrical performance between façade and roof installation of a glazed photovoltaic-thermal collectors at three European locations. Subsequently, this study shows benefit of photovoltaic-thermal collector installation in comparison with side-by-side installation of conventional system. For the purpose of simulation study, mathematical model of glazed photovoltaic-thermal collector has been experimentally validated and implemented into TRNSYS. A solar domestic hot water system with photovoltaic–thermal collectors generates more electrical and thermal energy in comparison with a conventional system across the whole of Europe for a particular installation in a multifamily building. The specific thermal yield of the photovoltaic–thermal system ranges between 352 and 582 kWh/m2. The photovoltaic–thermal system electric yield ranges between 63 and 149 kWh/m2. The increase in electricity production by the photovoltaic–thermal system varies from 19% to 32% in comparison with a conventional side-by-side system. The increase in thermal yield differs between the façade and roof alternatives. Photovoltaic-thermal system installation on the roof has higher thermal yield than conventional system and the increase of thermal yield ranges from 37% to 53%. The increase in thermal yield of façade photovoltaic-thermal system is significantly higher in comparison with a conventional system and ranges from 71% to 81%.

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