3 resultados para weather variables

em Dalarna University College Electronic Archive


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The work presented in this thesis concerns the dimensioning of an Energy Storage System (ESS) which will be used as an energy buffer for a grid-connected PV plant. This ESS should help managing the PV plant to inject electricity into the grid according to the requirements of the grid System Operator. It is desired to obtain a final production not below 1300kWh/kWp with a maximum ESS budget of 0.9€/Wp. The PV plant will be sited in Martinique Island and connected to the main grid. This grid is a small one where the perturbations due clouds in the PV generation are not negligible anymore. A software simulation tool, incorporating a model for the PV-plant production, the ESS and the required injection pattern of electricity into the grid has been developed in MS Excel. This tool has been used to optimize the relevant parameters defining the ESS so that the feed-in of electricity into the grid can be controlled to fulfill the conditions given by the System Operator. The inputs used for this simulation tool are, besides the conditions given by the System Operator on the allowed injection pattern, the production data from a similar PV-plant in a close-by location, and variables for defining the ESS. The PV production data used is from a site with similar climate and weather conditions as for the site on the Martinique Island and hence gives information on the short term insolation variations as well as expected annual electricity production. The ESS capacity and the injected electric energy will be the main figures to compare while doing an economic study of the whole plant. Hence, the Net Present Value, Benefit to Cost method and Pay-back period studies are carried on as dependent of the ESS capacity. The conclusion of this work is that it is possible to obtain the requested injection pattern by using an ESS. The design of the ESS can be made within an acceptable budget. The capacity of ESS to link with the PV system depends on the priorities of the final output characteristics, and it also depends on which economic parameter that is chosen as a priority.

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This thesis evaluates different sites for a weather measurement system and a suitable PV- simulation for University of Surabaya (UBAYA) in Indonesia/Java. The weather station is able to monitor all common weather phenomena including solar insolation. It is planned to use the data for scientific and educational purposes in the renewable energy studies. During evaluation and installation it falls into place that official specifications from global meteorological organizations could not be meet for some sensors caused by the conditions of UBAYA campus. After arranging the hardware the weather at the site was monitored for period of time. A comparison with different official sources from ground based and satellite bases measurements showed differences in wind and solar radiation. In some cases the monthly average solar insolation was deviating 42 % for satellite-based measurements. For the ground based it was less than 10 %. The average wind speed has a difference of 33 % compared to a source, which evaluated the wind power in Surabaya. The wind direction shows instabilities towards east compared with data from local weather station at the airport. PSET has the chance to get some investments to investigate photovoltaic on there own roof. With several simulations a suitable roof direction and the yearly and monthly outputs are shown. With a 7.7 kWpeak PV installation with the latest crystalline technology on the market 8.82 MWh/year could be achieved with weather data from 2012. Thin film technology could increase the value up to 9.13 MWh/year. However, the roofs have enough area to install PV. Finally the low price of electricity in Indonesia makes it not worth to feed in the energy into the public grid.

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This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists