Synthetic wind speed scenarios including diurnal effects: Implications for wind power dimensioning

Suomalainen, Kiti; Silva, C.A.; Ferrão, Paulo; Connors, Stephen R.

doi:10.1016/j.energy.2011.08.001

Cited by 35 publications

(12 citation statements)

References 14 publications

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“…5, pp. [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. URL: http://e-notabene.ru/pr/article_689.html (accessed date: 26.11.2016 [8], Тирацян Г.А.…”

Section: цель статьи -обоснование необходимости специального исследовunclassified

“…3. Methods Appropriate assessment of energy systems requires data of high temporal resolution that reflects diurnal pat-terns (Suomalainen et al 2012), and this resolution is also necessary for evaluating the daily synergy of wind and solar energy. The basic data is provided by three automatic weather stations in Murghab (3,650 m.a.s.l.…”

Section: Abstract: Renewable Energy; Hybrid; Sustainability; Photovolmentioning

confidence: 99%

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2017

SDMT

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“…5, pp. [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. URL: http://e-notabene.ru/pr/article_689.html (accessed date: 26.11.2016 [8], Тирацян Г.А.…”

Section: цель статьи -обоснование необходимости специального исследовunclassified

Section: Abstract: Renewable Energy; Hybrid; Sustainability; Photovolmentioning

confidence: 99%

Untitled

2017

SDMT

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“…The diurnal wind cycle can have a substantial impact on sizing and modeling integrated renewable systems, so it is important to model it properly [32,45,46], but note that the term s(h t ) is removed from Equation (2) when fitting a trend for the daily averages. 3.…”

Section: Markov-switching Vector Autoregressive Modelmentioning

confidence: 99%

A Markov-Switching Vector Autoregressive Stochastic Wind Generator for Multiple Spatial and Temporal Scales

2015

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Despite recent efforts to record wind at finer spatial and temporal scales, stochastic realizations of wind are still important for many purposes and particularly for wind energy grid integration and reliability studies. Most instances of wind generation in the literature focus on simulating only wind speed, or power, or only the wind vector at a particular location and sampling frequency. In this work, we introduce a Markov-switching vector autoregressive (MSVAR) model, and we demonstrate its flexibility in simulating wind vectors for 10-min, hourly and daily time series and for individual, locally-averaged and regionally-averaged time series. In addition, we demonstrate how the model can be used to simulate wind vectors at multiple locations simultaneously for an hourly time step. The parameter estimation and simulation algorithm are presented along with a validation of the important statistical properties of each simulation scenario. We find the MSVAR to be very flexible in characterizing a wide range of properties in the wind vector, and we conclude with a discussion of extensions of this model and modeling choices that may be investigated for further improvements.

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“…The methodology developed to capture the daily patterns [14], [17] of wind speed and load is based on the clustering techniques. With the method, some representational scenarios can be obtained along with their occurrence probabilities.…”

Section: Scenario Generationmentioning

confidence: 99%

“…1. To capture the daily patterns and the correlation of the load and wind speed [14], clustering techniques [15] are utilized to cluster both of them simultaneously to generate scenarios for the planning studies. Then, an approximate analytical model for reliability evaluation of BESS is demonstrated, cooperating with multistate models for DGs [16] and WTGs [12], to assess the reliability performances of various system configurations.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning of stand-alone microgrids incorporating reliability

Wang

Jiao

Guo

et al. 2014

J. Mod. Power Syst. Clean Energy

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This paper proposes a new method for the planning of stand-alone microgrids. By means of clustering techniques, possible operating scenarios are obtained considering the daily patterns of wind and load profiles. Then, an approximate analytical model for reliability evaluation of battery energy storage system is developed in terms of the diverse scenarios, along with multistate models for wind energy system and diesel generating system. An optimal planning model is further illustrated based on the scenarios and the reliability models, with the objective of minimizing the present values of the costs occurring within the project lifetime, and with the constraints of system operation and reliability. Finally, a typical stand-alone microgrid is studied to verify the efficiency of the proposed method.

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Synthetic wind speed scenarios including diurnal effects: Implications for wind power dimensioning

Cited by 35 publications

References 14 publications

Untitled

Untitled

A Markov-Switching Vector Autoregressive Stochastic Wind Generator for Multiple Spatial and Temporal Scales

Optimal planning of stand-alone microgrids incorporating reliability

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