Energy Matching
Key concept for the design of sustainable photovoltaic powered products
PhD Thesis by Sioe Yao Kan, December the 19th 2006
This dissertation will present how, why and under what circumstances a novel Energy Matching Model and associated Figure of Matching algorithm can support industrial designers in developing sustainable photovoltaic powered products. This PhD research project is executed within the framework of the SYN-Energy program which explores the feasibility of a transition towards the use of photovoltaic (PV) cells in consumer and professional products. This program is a part of the ‘Energy Research Stimulation Program’ of the Netherlands Organisation for Scientific Research (NWO). The starting point of this dissertation is the observation that today a vast amount of ‘PV powered’ products are already on the market. However, in these PV powered products quite often the choice of PV cells seems random and PV cells function mostly as add-on units to give the product a ‘green’ energy image. Because of this ‘add- on’ approach, the PV cells remain foreign bodies which are not well-integrated into the total product design. As a result in today’s PV powered products often a sub-optimal matching between the PV cell characteristics, energy storage and the product user contexts. Therefore, the keyword to obtain a mature and sustainably designed PV powered product will be matching.
As a result the research question is formulated as: What systematic matching can be achieved between the elements and interfaces of the energy chain of photovoltaic powered mobile/wireless products?
The emphasis of this dissertation will be on the optimal matching in the energy chain of PV powered products. For this purpose, an Energy Matching Model of the energy chain is developed. The scope of this dissertation is limited to the PV power converter and the electrical energy storage media. All the other elements and interfaces in the energy chain such as the user context defined parameters, energy use inside the product application and environmental parameters will be treated as given exogenous parameters. To quantify how well the matching at the matching interfaces MI:1 through 3 will be, a Figure of Matching algorithm is developed and presented. The higher this ‘Figure of Matching’ the better the matching.
In Chapter 2 the PV power converter is analysed. In particular the analysis will focus on matching the interfaces between this PV converter with both the incident light flux and the energy storage media. For this purpose the spectral Figure of Matching is calculated. The link between this spectral Figure of Matching and the more familiar PV conversion efficiency is determined by the introduction of the power based spectral response SRPPV. It is shown that the spectral Figure of Matching is identical to the conversion efficiency.
In Chapter 3, the storage media are the central part of the energy chain. Therefore, the analysis of the matching between this element and the other two can be divided along the two sides of the storage media. This is on the side of the input - a matching that enables to store as much as possible energy coming from the PV cells into the storage media. On the side of the output matching is achieved that enables the use of the available stored energy as efficient as possible. The Figure of Matching can be determined by calculating the ratio between the areas under the power correlation curve and the PV power output curve. The Figure of Matching for the battery output can be calculated at a certain temperature.
The correlation between the measured battery output voltage and the application voltage demand can be determined by calculating the area enclosed above the tolerance margin line and the battery output voltage in time. The Figure of Matching of this matching interface MI:3 can be determined by calculating the ratio between the correlated battery output voltage area and the area enclosed by the voltage demand curve and the tolerance margins lines of respectively 5% or 10%. With a 5% tolerance window only the + 20 °C pulses have some correlation. The Figure of Matching of these pulses at + 20 °C is about 50%. The - 20 °C pulses have no correlation with the 5% tolerance window. Therefore, the related Figure of Matching is zero. In addition, it has been shown that the output can be improved by the combining of capacitors and batteries.
Chapter 4 presents the energy balance between available energy, energy demand as well as a - specially developed- simulation tool for selecting both products and energy converters namely PowerQuest. With the aid of the spectral Figure of Matching, the spectrally dependent converted power of the PV cell with an area of APV m2 at a certain irradiance Gn can be calculated Or in the opposite case in which the from application demanded power is known the needed PV area can be calculated.
In Chapter 5 a number of benchmarks and demonstration cases were analysed with the aid of the Figure of Matching algorithm. As a result of this analysis the Energy Matching Model was developed and the generic Figure of Matching algorithm was fine tuned.
In Chapter 6 a roundup of the research is presented by summing up the main conclusions and recommendations for further research. The main outcome of this dissertation is an Energy Matching Model and a related Figure of Matching algorithm that is used to analyse and quantify the matching. As a result of the analysis, several matching improvements and design approaches and guidelines were found to facilitate the role of the industrial designer in designing sustainable PV powered products.