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The increase of renewable based generation as alternative power source brings an added uncertainty to power systems. The intermittent nature of renewable resources, such as wind speed and solar intensity, requires the use of adequate forecast methodologies to support the management and integration of this type of energy resources. This paper proposes a clustering methodology to group historic data according to the data correlation and relevance for different contexts of use. Using the clustering process as a data filter only the most adequate data is used for the training process of forecasting methodologies. Artificial Neural Networks and Support Vector Machines are used to test and compare the quality of forecasts when using the proposed methodology to select the training data. Data from the Brazilian city of Florianopolis, Santa Catarina, has been used, including solar irradiance components and other meteorological variables, e.g. temperature, wind speed and humidity. Experimental findings show that using the proposed method to filter data used for training ANN and SVM achieved promising results, outperforming the approaches without clustering.

Heat Pumps to supply hot-water for domestic consumption are widely used especially in countries where electric energy is also employed for this purpose. Brazil is a country where most of the domestic hot-water requirements are supplied by electric energy, but basically it is done with electric showers. This solution, although cheap for the user in terms of initial investment, has a strong impact on the generation, transmission and distribution – GTD costs. Electric showers have an average power of more than 5 kW, and are a strong contribution to the residential electric energy end use (around 24% in Brazil (Procel/Eletrobras, 2007)). Also, they are partially responsible by the “peak hour” of the power consumption in the residential sector that occurs from 18:00 to 21:00 hours in Brazil. The consumption growth observed in the last years leads to a lack of reliability of the system, and energy efficiency measures are necessary to avoid risks and to postpone investments in GTD. Solar hot-water systems have been used as an effective way to mitigate the problems caused by the intensive use of electric showers, however, this solution faces some problems when used in low-income housing units: absence of hot-water piping, inadequate structure to install collectors and thermal storage, increase of specific thermal energy costs for small systems, and use of an electric shower as the backup system.

The Chilean government has determined that a renewable energy quota of up to 10% of the electrical energy generated must be met by 2024. This plan has already sparked interest in wind, geothermal, hydro and biomass power plants in order to introduce renewable energy systems to the country. Solar energy is being considered only for demonstration, small-scale CSP plants and for domestic water heating applications. This apparent lack of interest in solar energy is partly due to the absence of a valid solar energy database, adequate for energy system simulation and planning activities. One of the available solar radiation databases is 20-40 years old, with measurements taken by pyranographs and Campbell-Stokes devices. A second database from the Chilean Meteorological Service is composed by pyranometer readings, sparsely distributed along the country and available from 1988, with a number of these stations operating intermittently. The Chilean government through its National Energy Commission (CNE) has contracted the formulation of a simulation model and also the deployment of network of measurement stations in northern Chile. Recent efforts by the authors have resulted in a preliminary assessment by satellite image processing. Here, we compare the existing databases of solar radiation in Chile. Monthly mean solar energy maps are created from ground measurements and satellite estimations and compared. It is found that significant deviation exists between sources, and that all ground-station measurements display unknown uncertainty levels, thus highlighting the need for a proper, country-wide long-term resource assessment initiative. However, the solar energy levels throughout the country can be considered as high, and it is thought that they are adequate for energy planning activities although not yet for proper power plant design and dimensioning. (C) 2010 Elsevier Ltd. All rights reserved.

This paper aims at presenting the main products of Solar and Wind Energy Resource Assessment (SWERA) project for Brazil and how this information on solar and wind energy resources can be used to spread out the energy production matrix improving the energy security and reducing the dependency on fossil fuels. The SWERA project were developed in Brazil under the coordination of Climate and Environmental Division of CPTEC/INPE and illustrates how the scientific research in meteorology and climatology can contribute to the energy planning and policies developed in Brazil. The products of SWERA project include information that will be extremely useful to foster capital investments providing private sector and government institutions with reliable database of energy resources. The paper presents the main results in solar and wind energy mapping and discusses some renewable energy scenarios taking in account the technologies in use currently.