Mitigation of wind power fluctuations in smart grids

Haan, J.E.S. de; Frunt, J.; Kling, W.L.

doi:10.1109/isgteurope.2010.5638904

Cited by 16 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…pitch angle control [3]), or may be commanded from a higher hierarchical level through the use of VRPP (e.g. wind energy curtailment or usage of rotor inertia to store the additional energy brought by a wind gust as kinetic energy for later conversion, as in [4]). …”

Section: The Smoothing Of Power Fluctuation and The Natural Complmentioning

confidence: 99%

Integration of renewable sources in the electric system using Virtual Renewable Power Plants

Rodrigues

Estanqueiro

2011

11th International Conference on Electrical Power Quality and Utilisation

View full text Add to dashboard Cite

show abstract

Section: The Smoothing Of Power Fluctuation and The Natural Complmentioning

confidence: 99%

Integration of renewable sources in the electric system using Virtual Renewable Power Plants

Rodrigues

Estanqueiro

2011

11th International Conference on Electrical Power Quality and Utilisation

View full text Add to dashboard Cite

show abstract

“…To improve the penetration level of PV power in the distribution grid, PV power fluctuation mitigation techniques have been investigated. Existing research works on this topic can be generally classified into the following three categories: Demand response of local loads: Assuming the local loads are controllable and PV power forecasting is adopted, power fluctuation can be smoothed by adjusting the local loads curve to make up for the PV power curve [5].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Flexible Multi-Microgrid Interconnection Scheme for Mitigating Power Fluctuation and Optimizing Storage Capacity

et al. 2019

View full text Add to dashboard Cite

With the rapid increase of renewable energy integration, more serious power fluctuations are introduced in distribution systems. To mitigate power fluctuations caused by renewables, a microgrid with energy storage systems (ESSs) is an attractive solution. However, existing solutions are still not sufficiently cost-effective for compensating enormous power fluctuations considering the high unit cost of ESS. This paper proposes a new flexible multi-microgrid interconnection scheme to address this problem while optimizing the utilization of ESSs as well. The basic structure and functions of the proposed scheme are illustrated first. With the suitable power allocation method in place to realize fluctuation sharing among microgrids, the effectiveness of this scheme in power smoothing is analyzed mathematically. The corresponding power control strategies of multiple converters integrated into the DC common bus are designed, and the power fluctuation sharing could be achieved by all AC microgrids and DC-side ESS. In addition, a novel ESS sizing method which can deal with discrete data set is introduced. The proposed interconnection scheme is compared with a conventional independent microgrid scheme through real-world case studies. The results demonstrate the effectiveness of the interconnected microgrid scheme in mitigating power fluctuation and optimizing storage capacity, while at the expense of slightly increased capacity requirement for the AC/DC converters and construction cost for DC lines. According to the economic analysis, the proposed scheme is most suitable for areas where the distances between microgrids are short.

show abstract

“…It has been shown that, wind power output has been strong fluctuating by characteristics and only is partly controllable in nature [5,6]. Short-term or ultra-short-term WPP is required for controlling and scheduling of power generation, for self-dispatching of power transmission market [7] and for rating improvement of the overhead line [8].…”

Section: Introductionmentioning

confidence: 99%

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Mohammed

Wang

2017

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Abstract. This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multipoint prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient.Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

show abstract

Mitigation of wind power fluctuations in smart grids

Cited by 16 publications

References 20 publications

Integration of renewable sources in the electric system using Virtual Renewable Power Plants

Integration of renewable sources in the electric system using Virtual Renewable Power Plants

Design and Analysis of Flexible Multi-Microgrid Interconnection Scheme for Mitigating Power Fluctuation and Optimizing Storage Capacity

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Contact Info

Product

Resources

About