Intelligent Algorithms for a Hybrid FuelCell/Photovoltaic Standalone System : Simulation Of Hybrid FuelCell/Photovoltaic Standalone System

The Intelligent Algorithm is designed for theusing a Battery source. The main function is to automate the Hybrid System through anintelligent Algorithm so that it takes the decision according to the environmental conditionsfor utilizing the Photovoltaic/Solar Energy and in the absence of this, Fuel Cell energy isused. To enhance the performance of the Fuel Cell and Photovoltaic Cell we used batterybank which acts like a buffer and supply the current continuous to the load. To develop the main System whlogic based controller was used. Fuzzy Logic based controller used to develop this system,because they are chosen to be feasible for both controlling the decision process and predictingthe availability of the available energy on the basis of current Photovoltaic and Battery conditions. The Intelligent Algorithm is designed to optimize the performance of the system and to selectthe best available energy source(s) in regard of the input parameters. The enhance function of these Intelligent Controller is to predict the use of available energy resources and turn on thatparticular source for efficient energy utilization. A fuzzy controller was chosen to take thedecisions for the efficient energy utilization from the given resources. The fuzzy logic basedcontroller is designed in the Matlab-Simulink environment. Initially, the fuzzy based ruleswere built. Then MATLAB based simulation system was designed and implemented. Thenthis whole proposed model is simulated and tested for the accuracy of design and performanceof the system.

Energy performance comparison of three innovative HVAC systems for renovation through dynamic simulation

In this paper, dynamic simulation was used to compare the energy performance of three innovativeHVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaustventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilationwith air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation withair-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems Band C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two.All systems were tested with a model of a renovated single family house for varying U-values, climates,infiltration and ventilation rates.It was found that A was the best system for lower heating demand, while for higher heating demandsystem B would be preferable. System C was better than the reference system, but not as good as A or B.The difference in energy consumption of the reference system was less than 2 kWh/(m2a) betweenSimulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also bythe fact that the TRNSYS systems supplied slightly more than the ideal heating demand.