54 research outputs found

    Criteria of Hydropower Sustainable Development Analysis

    No full text
    2003 m rugsėjo 11 d. Lietuvos Respublikos vyriausybė patvirtino „Nacionalinę darnaus vystymosi strategiją“, kurioje įsipareigojo teikti paramą atsinaujinantiems energijos šaltiniams, tarp jų ir hidroenergetikai. Žymaus elektros gamybos padidinimo iš atsinaujinančių energijos šaltinių siekia ir ES, priėmusi Elektros, pagamintos iš atsinaujinančių energijos šaltinių, skatinimo direktyvą (Directive on the promotion of the Use of Energy from Renewable Sourses; RES, 2009/28/EB). Tačiau Bendrosios vandens politikos direktyvos (Water Framework Directive; WFD, 2000/60/EC) vykdymas reikalauja pasiekti gerą būklę visuose vandens telkiniuose 2015 metais, o tai tampa kliūtis naujų hidroelektrinių statymui bei visos hidroenergetikos vystimuisi. Geriausia galima išeitis – hidroelektrinių sertifikavimas. Hidrojėgainės, kurios atitiktų aplinkosauginius reikalavimus, gautų žaliosios elektros energijos žymą. Šis darbas skirtas įvertinti užsienyje esamų žaliųjų sertifikavimo sistemų pritaikomumą Lietuvos sąlygomis.In September 2003 Lithuanian Government approved the “National Sustainable Development Strategy“ in which committed to provide support for alternative energy sources, including hydropower. Approving Directive on the promotion of the Use of Energy from Renewable Sources, EU is seeking significant increase in electricity produced from renewable sources. However Water Framework Directive requires achieving good status in all water bodies in 2015. This is an obstacle to constructions of new hydroelectric power plants ant to whole hydropower development. Hydropower certification is the best possible solution. Hydropower plants, that will meet environmental requirements, will receive green label. This work is intending to evaluate adaptability of existing foreign green certification systems in Lithuanian conditions.Žemės ūkio akademijaVytauto Didžiojo universiteta

    Probability distributions of wave heights in the Lithuanian coast

    No full text
    Since discovering that signals of random waves submit to the known laws of probability, this became widely used in engineering and energetics for probability distributions analysis of wave height. From an energetic point of view, it is necessary to know the average wave height in, for example, highly wavy (1% probability), medium wavy (25 % probability) or non-wavy (95% probability) years. Whereas, maximum multi-year value of wave height characteristics is essential for engineering resistant wave energy converters that could withstand severe marine conditions. Average and maximum annual values of wave height data collected from Klaipeda coastal hydrometeorological station are used for this study. Probability distributions of average and maximum wave heights in the Lithuanian coast are analysed in this paper. The best fitting is obtained using HYFRAN and EASY FIT software. Both, a test for independence (Wald- Wolfowitz) and stationarity test (Kendall) are carried out for every time series using HYFRAN software. Maximum likehood method is selected for distribution estimation. Fitting is determined using chi-square test and the best fining is verified with comparison (BIC and AIC) criterion. Fitting for one of the most commonly used distributions in the analysis of wave climate - Rayleigh distribution - cannot be determined with HYFRAN software. For this purpose. EASY FIT software is used additionally. The fit of the distribution is evaluated via the chi-square test similarly. Calculated wave heights based on lognormal probability distribution that fits best according to HYFRAN softvsa-e are similar to those calculated using Rayleigh probability distributionVytauto Didžiojo universitetasŽemės ūkio akademij

    Lithuania

    No full text
    Vytauto Didžiojo universitetasŽemės ūkio akademij

    Lithuania

    No full text
    Vytauto Didžiojo universitetasŽemės ūkio akademij

    A case study of the wind-wave relationship in the Lithuanian coast of the Baltic sea

    No full text
    In the Lithuanian coastal observations registers missing data of visual wave observations occur because of the fog, ice, evaporation or other meteorological phenomenon. There is also inconsistency in instrumental measurements of wave heights in the Lithuanian coast due to technical issues. First step to fill the gaps in the wave height data is to find a correlation between wind speeds and wave heights. In this study correlation coefficients for Nida and Klaipėda coastal hydrometeorological stations data both taking and not taking into consideration wind blowing directions were calculated. Every data set used in this study was treated separately and it was revealed that applying nonlinear regression the most common model for wind-wave relationship analysis on Lithuanian coast is DR-Hill model, while applying multivariable regression it is Full Cubic model. Relationship between wind speeds and waveVytauto Didžiojo universitetasŽemės ūkio akademij

    Assessment of the Baltic sea near-shore wave energy resources along the coast of Klaipėda

    No full text
    Darbo tikslas – įvertinti jūros bangų energetinius išteklius Baltijos jūros priekrantei ties Klaipėda, atsižvelgiant į jų sklaidą laike ir erdvėje. Darbo tikslui pasiekti sprendžiami šie uždaviniai: 1. Apskaičiuoti ir įvertinti Baltijos jūros bangų energetinių išteklių Baltijos jūros priekrantėje ties Klaipėda pasiskirstymą laike, naudojantis gautais projektinių metų vidutiniais bangų aukščiais ir sudarant pasiskirstymo diagramas. 2. Apskaičiuoti ir įvertinti Baltijos jūros bangų energetinių išteklių Baltijos jūros priekrantėje ties Klaipėda pasiskirstymą erdvėje, taikant skaitmeninį modeliavimą, įvertinant gylio, bangavimo krypties bei vėjo greičio įtaką bangų energetiniam potencialui. 3. Apskaičiuoti ir įvertinti Baltijos jūros bangų energetinius išteklius ties Klaipėdos valstybinio jūrų uosto molais.The aim of the study – to assess the Baltic Sea near-shore wave energy resources along the coast of Klaipėda, taking into consideration their temporal and spatial distribution. To achieve this aim, these three tasks were identified: 1. To evaluate and assess the temporal distribution of the Baltic Sea near-shore wave energy resources along the coast of Klaipėda, using calculated design years‘ average wave heights and scatter diagrams. 2. To evaluate and assess the spatial distribution of the Baltic Sea near-shore wave energy resources along the coast of Klaipėda, using the results of numerical modelling, calculating the impacts of depth, wave propagation direction and wind on wave energy resources. 3. To evaluate and assess the Baltic Sea wave energy resources alongside the Klaipėda Seaport breakwaters.Žemės ūkio akademijaVytauto Didžiojo universiteta
    corecore