Biogas Desulfurization with Regenerable Polymeric Adsorbent for Renewable Electric Energy Production

The most important factor responsible for the quality of energy production forecasts in wind farms is the accurate wind speed forecast. An extensive statistical analysis of meteorological data (NWP) from 16 base nodes of the "300" grid in the "Łódź" area was made. The intention of the statistical analysis was to select potential explanatory variables for models predicting wind speed in the remaining 206 nodes of the grid’s mesh. Next, tests of selected prognostic methods were performed in order to compare their effectiveness with bilinear method which is not computationally complex. It should be emphasized that the main problem in spatial wind speed forecasting is the very large number of nodes for which the forecasts are calculated. As a consequence, more advanced and computationally complex forecasting methods cannot be applied in practice due to too long calculations time and difficulties in huge amounts of data processing. Conclusions with proposals of preferred forecasting methods that could be used in practice were developed.

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An Energy Ontology Focusing on Demand Side Management in Smart Homes

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.19.124 ◽

2016 ◽

Vol 19 ◽

pp. 124-131

Author(s):

Beate Naser ◽

Franziska Schäfer ◽

Jörg Franke

Keyword(s):

Energy Production ◽

Power Plants ◽

Renewable Energy Sources ◽

Electric Energy ◽

Smart Homes ◽

Demand Side Management ◽

Demand Side ◽

Conceptual Foundation ◽

Available Energy ◽

Solar Power Plants

By increasing the share of renewable energy sources, the volatility of available energy is rising. More and more fluctuating power generation by solar power plants and wind turbines has to be integrated into the power grid. Demand side management (DSM) represents one possible solution to achieve this goal by including energy production and energy consumption simultaneously. In this paper, we especially focus on the field of electric energy in smart homes. Considering the implementation of different DSM devices, an ontology-based approach can serve as a conceptual foundation for a necessary knowledge base. We propose an advanced energy ontology for smart homes, integrating important aspects for a successful DSM. We describe how power producers, storages and consumers are represented in our ontology. Finally, we show the scenario-based utilization of our approach.

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Research of Compensating Weights of Cascade Hydropower Stations

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.198-199.721 ◽

2012 ◽

Vol 198-199 ◽

pp. 721-725

Author(s):

Gan Yi Wang ◽

Xiang Lin Wu ◽

Hong Sheng Song

Keyword(s):

Analytic Hierarchy Process ◽

Energy Production ◽

Electric Energy ◽

Analytic Hierarchy ◽

Cascade Hydropower Stations ◽

Calculation Results ◽

Hydropower Stations ◽

Hierarchy Process

The compensation benefits distribution weights model of cascade hydropower stations has been proposed. The method of compensation weights calculation has been discussed. The subjective weights in the station indexes are calculated by analytic hierarchy process and the objective weights by variance coefficient and the combination weights by Topsis. The calculation results will be evaluated. The increased benefits of the system will be distributed by the objective weights. The enthusiasm for electric energy production of each station will be increased because they can receive compensations from the whole increased benefits.

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