Utilization of wind turbines as economic and green production units, poses new challenges to the power system planners, mainly due to the stochastic nature of the wind, adding a new source of uncertainty to the power system. Different types of distribution and correlation between this random variable and the system load makes conventional method inappropriate for modeling such a correlation. In...

The use of multi sources systems of energy progressed significantly in different industrial sectors. Between all the existing sources of energy, batteries and renewable sources, such as photovoltaic and wind, contain the highest specified energy. However, solar and wind energies are not available all the time, their performance is affected by unpredictable weather changes and therefore, it is d...

Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind power generation. However, most research has focused on point forecasting of wind power. In this paper, we develop an approach to producing dens...

The rapid uptake of natural gas-fired units in energy systems poses significant challenges coordinating the electricity and gas systems. Besides, uncertainty caused by integrated renewable such as wind power raises more requirements on robustness operation for system (IEGS). To address these challenges, this paper investigates distributed adjustable robust optimal flow (OPGF) model IEGS. Using ...

The use of renewable energy sources in world will increase, leading to a more sustainable energy mix, reduced greenhouse gas emissions and a lower dependency from oil. Wind power is one of the renewable energy sources that have virtually no environmental problems; it is one of the fastest growing sources of energy in the world. In industry, the wind power creates new jobs, encourages innovation...

The aim of the European Project ANEMOS is to develop accurate and robust models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced statistical, physical and combined modelling approaches were developed for this purpose. Priority was given to methods for on-line uncertainty and prediction risk assessment. An integrated softwa...

The large variability and uncertainty in wind power generation present a concern to power system operators, especially given the increasing amounts of wind power being integrated into the electric power system. Large ramps, one of the biggest concerns, can significantly influence system economics and reliability. The Wind Forecast Improvement Project (WFIP) was to improve the accuracy of foreca...

Over the past years, the share of electricity production from wind power plants has increased to significant levels in several power systems across Europe and the United States. In order to cope with the fluctuating and partially unpredictable nature of renewable energy sources, transmission system operators (TSOs) have responded by increasing their reserve capacity requirements and by requirin...

This paper describes different methods to estimate the uncertainty of wind power forecasts in terms of prediction intervals. The single methods and an ensemble average model have been applied to shortest-term wind power forecasts (forecast horizon = 1, 2, 4 & 8 h) of 62 spatially distributed wind farms in Germany to obtain intervals with a nominal reliability of 90, 95 and 98 %. Furthermore the...