Browsing by Subject "Wind"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Open Access Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente(Elsevier, 2017) Yuan, S.; Kocaman, A.S.; Modi, V.For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950�MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration.Item Open Access Fire detection and 3D fire propagation estimation for the protection of cultural heritage areas(Copernicus GmbH, 2010) Dimitropoulos, K.; Köse, Kıvanç; Grammalidis, N.; Çetin, A. EnisBeyond taking precautionary measures to avoid a forest fire, early warning and immediate response to a fire breakout are the only ways to avoid great losses and environmental and cultural heritage damages. To this end, this paper aims to present a computer vision based algorithm for wildfire detection and a 3D fire propagation estimation system. The main detection algorithm is composed of four sub-algorithms detecting (i) slow moving objects, (ii) smoke-coloured regions, (iii) rising regions, and (iv) shadow regions. After detecting a wildfire, the main focus should be the estimation of its propagation direction and speed. If the model of the vegetation and other important parameters like wind speed, slope, aspect of the ground surface, etc. are known; the propagation of fire can be estimated. This propagation can then be visualized in any 3D-GIS environment that supports KML files.