58 research outputs found
A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe
Studies have shown that a large geographic spread of installed capacity can reduce wind power variability and smooth production. This could be achieved by using electricity interconnections and storage systems. However, interconnections and storage are not totally flexible, so it is essential to understand the wind power correlation in order to address power system constraints in systems with large and growing wind power penetrations. In this study the spatial and temporal correlation of wind power generation across several European Union countries was examined to understand how wind ‘travels’ across Europe. Three years of historical hourly wind power generation data from ten countries were analysed. The results of the analysis were then compared with two other studies focused on the Nordic region and the United States of America. The findings show that similar general correlation characteristics do exist between European country pairs. This is of particular importance when planning and operating interconnector flows, storage optimisation and cross-border power trading
Gas generation and wind power: A review of unlikely allies in the United Kingdom and Ireland
No single solution currently exists to achieve the utopian desire of zero fossil fuel electricity generation. Until such time, it is evident that the energy mix will contain a large variation in stochastic and intermittent sources of renewable energy such as wind power. The increasing prominence of wind power in pursuit of legally binding European energy targets enables policy makers and conventional generating companies to plan for the unique challenges such a natural resource presents. This drive for wind has been highly beneficial in terms of security of energy supply and reducing greenhouse gas emissions. However, it has created an unusual ally in natural gas. This paper outlines the suitability and challenges faced by gas generating units in their utilisation as key assets for renewable energy integration and the transition to a low carbon future. The Single Electricity Market of the Republic of Ireland and Northern Ireland and the British Electricity Transmission Trading Agreement Market are the backdrop to this analysis. Both of these energy markets have a reliance on gas generation matching the proliferation of wind power. The unlikely and mostly ignored relationship between natural gas generation and wind power due to policy decisions and market forces is the necessity of gas to act as a bridging fuel. This review finds gas generation to be crucially important to the continued growth of renewable energy. Additionally, it is suggested that power market design should adequately reward the flexibility required to securely operate a power system with high penetrations of renewable energy, which in most cases is provided by gas generation
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Sunny windy Sundays
Rapid expansion of wind and solar capacity in Great Britain presents challenges for managing electricity systems. One concern is the reduction in system inertia during periods where renewables provide a high proportion of demand which has led to some networks imposing system nonsynchronous penetration limits. However, given the lack of operational data, the relationship between
renewable generation and demand for the full range of meteorological conditions experienced in Great
Britain is poorly understood. This study uses reanalysis datasets to determine the proportion of
demand from renewable generation on an hourly resolution for a 36-year period.
The days with highest penetration of renewables tend to be sunny, windy weekend days between May
and September, when there is a significant contribution of both wind and solar generation and demand
is suppressed due to human behaviour. Based on the current distribution of wind and solar capacity,
there is very little curtailment for all system non-synchronous penetration limits considered. However,
as installed capacity of renewables grows the volume of generation curtailed also increases with a
disproportionate volume occurring at weekends. The total volume of curtailment is highly dependent
on ratio of wind and solar capacity, with the current blend close to the optimum level
Influence of Wind Power Forecasts on Equitable Distribution Method of Wind Power Curtailment
Techno-economic analysis of energy storage within network constraint groups for increasing the share of variable renewable energy
Development of Ireland's power system, 1927 to 1997
Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:m03/20488 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
Loss‐of‐mains protection system by application of phasor measurement unit technology with experimentally assessed threshold settings
Economic assessment of high renewable energy penetration scenario in 2030 on the interconnected Irish power system
Current methods and advances in forecasting of wind power generation
Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised
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