Category Photovoltaics for Rural Development in Latin America: A Quarter Century of Lessons Learned
The ORC fluid can be classified into three categories according to the temperature-entropy (T – s) diagrams. It is noteworthy that for some kinds of fluids, the derivative of temperature with respect to entropy on the saturation vapor curve may change from positive value to negative value, e. g. dL of R123 on the saturation vapor curve is positive when T is smaller than 150°C while negative at higher temperature ranges. In this case, dry fluids are generally named for the positive dL in practical operation temperature range from the cold side to the hot side. And wet fluids would have negative dL on the saturation vapor curve. Meanwhile, isentropic fluids have approximately infinite value of dL (nearly vertical curve).
The working fluids of dry or isentropic type are more appropriate for ...Read More
Figure 1 presents the diagram of low-temperature solar thermal electric generation with two – stage collectors and heat storage units. The system consists of FPC and CPC collectors, heat storage, and ORC subsystem. FPCs offer the advantage of accepting high pressure without leakage. The organic fluid flows through FPCs directly and is heated indirectly by CPC collectors with the intermediate of conduction oil. The ORC subsystem consists of evaporator (E), organic fluid/heat storage tank with PCM, turbine (T), generator (G), regenerator (R), condenser, and pumps. The first-stage heat storage is filled with PCM (1), while the second heat storage is filled with PCM (2). Melting point of PCM (1) is lower than that of PCM (2).
Pei Gang, Li Jing, Ji Jie
Department of Thermal Science and Energy Engineering, University of Science and Technology of China, Jinzhai Road 96#, Hefei City, Anhui Province,
People’s Republic of China
Organic Rankine Cycle (ORC) is named for its use of an organic, high molecular mass fluid that boils at a lower temperature than the water. Among many well-proven technologies, the ORC is one of the most favorable and promising ways for low-temperature applications. In comparison to water, organic fluids are advantageous when the plant runs at low temperature or low power...Read More
The building simulation code used for this study henceforth includes a generic model, fully coupled, for the complete modelling of the integration of PV panels in buildings. More and more used in the world, as a means of electricity production using renewable energy, PV systems are of great potential and are subject to numerous research programs. Their inclusion in building envelopes opens the way for zero net energy constructions, whose potential in terms of energy consumption and reduction of global warming is more and more recognised. In a near future, with constant developments and improvements, our building simulation code will be able to predict the energetic behaviourof zero net energy buildings and thus the evaluation and optimisation of their performances.Read More
One possible perspective is to couple the BIPV with MCPs (phase change materials). These are materials capable of changing of physical state within wide ranges of temperatures according to desired applications (building insulation, passive cooling, thermal energy storage, textile industry, etc.).
These materials have the ability to store or to release a large amount of energy as latent heat during phase change liquid-solid. They can be classified into three broad categories:
• The MCP organic (paraffin and fatty acid)
• The MCP inorganic (hydrated salt)
• The MCP eutectic (organic-organic, organic-inorganic, inorganic-inorganic)
The choice of MCPs is based on a number of factors such as latent and sensible heat, thermal conductivity in liquid and solid phases but also the impact on t...Read More
Experimentation data was compared to simulation data. This comparison shows that the thermal model has a good dynamic. However, there are some fairly large differences in amplitude for temperatures of the PV complex wall. To provide some answers to this problem, a sensitivity analysis was run and brought to light the most important parameters on the behaviour of the system. An optimisation procedure is planned, to determine the best set of parameters to lead to the best performance of the BIPV. Adjusting these parameters will considerably reduce the observed difference between measurements and predictions, and lead to the validation of the building envelope model. This important step is in progress and will be presented in future works.Read More
2.7 Thermal Performance of BIPV
The review on BIPV has demonstrated that not only a unique physical model exists, capable of predicting the thermal evolution of the building envelope with the influence of photovoltaic systems in various configurations (integrated-fagade, integrated-roof, integrated-glazing, etc.). This chapter has presented a semi-detailed model of a fully coupled PV model, integrated in a building simulation code. The model was used to predict the temperature field in the complex wall constituted by the PV system and its support wall...Read More
The optimization is the step where the model can be improved and validated. It can be made by using optimization algorithms. In this chapter, we present the use of a free optimization program called GENOPT (Wetter, 2001). This program was set up to allow anyone to use it with his own simulation code. It has been coupled with many building simulation codes like EnergyPlus, TRNSYS, SPARK, IDA-ICE or DOE-2.
GENOPT make the optimization by running simulations of the studied code. It changes values of parameters in the inputs of the program and notes the variation induced on the outputs. As it is shown on fig. 14, it needs only three files to run: the input file, the output file and also the program it has to run...Read More