A new method to adequate assessment of wind farms’ power output

Zolfaghari, Saeed; Riahy, G.H.; Abedi, Mehrdad

doi:10.1016/j.enconman.2015.07.001

Cited by 26 publications

(8 citation statements)

References 33 publications

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“…Then, in the next step, they calculated the power output of the wind farms from the wind speed associated power curves. The power curves are mathematical functions provided by the manufacturers to relate the wind speed with the output powers precisely [40]. Jordehi [41], reviewed possible techniques that dealt with the power systems uncertainties and found the Monte Carlo simulation (MCS) and scenario-based analysis (SBA) are simple and easy to be implemented over the point estimate and probabilistic methods.…”

Section: A Output Power Predictionmentioning

confidence: 99%

Grid Integration Challenges of Wind Energy: A Review

et al. 2020

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The strengthening of electric energy security and the reduction of greenhouse gas emissions have gained enormous momentum in previous decades. The integration of large-scale intermittent renewable energy resources (RER) like wind energy into the existing electricity grids has increased significantly in the last decade. However, this integration poses many operational and control challenges that hamper the reliable and stable operation of the grids. This article aims to review the reported challenges caused by the integration of wind energy and the proposed solutions methodologies. Among the various challenges, the generation uncertainty, power quality issues, angular and voltage stability, reactive power support, and fault ride-through capability are reviewed and discussed. Besides, socioeconomic, environmental, and electricity market challenges due to the grid integration of wind power are also investigated. Many of the solutions used and proposed to mitigate the impact of these challenges, such as energy storage systems, wind energy policy, and grid codes, are also reviewed and discussed. This paper will assist the enthusiastic readers in seeing the full picture of wind energy integration challenges. It also puts in the hands of policymakers all aspects of the challenges so that they can adopt sustainable policies that support and overcome the difficulties facing the integration of wind energy into electricity grids. INDEX TERMS Angular stability, energy storage system, fault ride-through capability, frequency response, grid codes, reactive power support, voltage stability, wind intermittency. • Induction generator (squirrel cage (type 1) and wound rotor (type 2))

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Section: A Output Power Predictionmentioning

confidence: 99%

Grid Integration Challenges of Wind Energy: A Review

et al. 2020

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“…Therefore, PSO is applied to determine the optimum economic revenue point of the WPGSS in this paper. The optimal solution (k 1 , k 2 ) * is equal to (5,3), so the combination (k 1 , k 2 ) * = (5, 3) is regarded as the parameters of the WPGSS's coordination and optimization control model obtained by the cooperative game model.…”

Section: Determining the Parameters Of The Wpgss's Model Based On Thementioning

confidence: 99%

“…Owing to its clean and renewable nature, wind power generation has a pollution‐free feature . However, the output power of wind farms is very volatile due to the intermittence and randomness of wind energy, which impacts the stability and security of power systems . Integration of energy storage systems (ESS) into wind farms is an effective way to solve the fluctuations of wind power and dramatically improve the security and stability of wind power connected to the grid .…”

Section: Introductionmentioning

confidence: 99%

A Game Theory‐Based Coordination and Optimization Control Methodology for a Wind Power‐Generation Hybrid Energy Storage System

Han

Liang

et al. 2017

Asian Journal of Control

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The installation of an energy storage system to smooth the fluctuations of wind power output at a certain wind farm can improve the electric quality of wind power connected to the grid. In order to reduce the capacity of the energy storage system and the loss of the battery and make full use of the advantages of the super-capacitor, a game theory-based coordination and optimization control methodology for a wind power-generation and storage system (WPGSS) is presented in this paper. Aiming to maximize the WPGSS's overall profit, the methodology, taking the smoothing effect of the active power, the cost of the hybrid energy storage system (HESS), and the earnings of wind power connected to grid into consideration, builds a coordination and optimization control model based on the ensemble empirical mode decomposition (EEMD) algorithm combined with game theory. In the model, the low-pass filtering signal obtained by the EEMD is used to smooth the fluctuations of wind power output, and the band-pass filtering signal and high-pass filtering signal obtained by the EEMD are used to achieve energy distribution among the HESS. Cooperative game theory is introduced to determine the filter order of the EEMD according to the state of charge (SOC) of the HESS and to achieve the coordination and optimization control of the WPGSS taking the maximization of the WPGSS's overall profit as the game's goal constraint conditions. The genetic algorithm (GA) and particle swarm optimization (PSO) are adopted to solve the model's optimal solution, and the simulation tests were realized to verify the effectiveness of the proposed method, which can provide a theoretical basis for the coordination and optimization control of the WPGSS.

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“…An exhaustive review of the most used criteria is presented in this paper along with a discussion of their advantages and disadvantages. Such criteria include the log-likelihood (ln L) [27,33,56,57], the Akaike and the Bayesian Information Criteria (AIC, BIC) [27,28,30,42,56], the coefficient of determination ( 2 R ) [1, 3, 11, 12, 15-17, 21, 27, 28, 30-32, 35, 37, 39, 46, 49, 50, 58-62], the root mean square error (RMSE) [1,2,9,13,15,16,33,36,37,39,53,56,[60][61][62][63][64][65][66][67][68][69][70][71], the Chi-square test statistic ( 2  ) [1, 2, 13, 15, 27, 28, 32-36, 39, 40, 49, 53, 55, 57, 60, 68, 72], the Kolmogorov-Smirnov test statistic (KS) [9, 13, 27, 30, 32-35, 38-40, 53, 55, 56, 61, 69, 73-75] and the Anderson-Darling test statistic (AD) [32,40,50,76].…”

Section: Introductionmentioning

confidence: 99%

Review of criteria for the selection of probability distributions for wind speed data and introduction of the moment and L-moment ratio diagram methods, with a case study

Ouarda

Charron²,

Chebana

2016

Energy Conversion and Management

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This paper reviews the different criteria used in the field of wind energy to compare the goodness-of-fit of candidate probability density functions (pdfs) to wind speed records, and discusses their advantages and disadvantages. The moment ratio and L-moment ratio diagram methods are also proposed as alternative methods for the choice of the pdfs. These two methods have the advantage of allowing an easy comparison of the fit of several pdfs for several time series (stations) on a single diagram. Plotting the position of a given wind speed data set in these diagrams is instantaneous and provides more information than a goodness-of-fit criterion since it provides knowledge about such characteristics as the skewness and kurtosis of the station data set. In this paper, it is proposed to study the applicability of these two methods for the selection of pdfs for wind speed data. Both types of diagrams are used to assess the fit of the pdfs for wind speed series in the United Arab Emirates. The analysis of the moment ratio diagrams reveals that the Kappa, Log-Pearson type III and Generalized Gamma are the distributions that fit best all wind speed series. The Weibull represents the best distribution among those with only one shape parameter. Results obtained with the diagrams are compared with those obtained with goodnessof-fit statistics and a good agreement is observed especially in the case of the L-moment ratio diagram. It is concluded that these diagrams can represent a simple and efficient approach to be used as complementary method to goodness-of-fit criteria.

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A new method to adequate assessment of wind farms’ power output

Cited by 26 publications

References 33 publications

Grid Integration Challenges of Wind Energy: A Review

Grid Integration Challenges of Wind Energy: A Review

A Game Theory‐Based Coordination and Optimization Control Methodology for a Wind Power‐Generation Hybrid Energy Storage System

Review of criteria for the selection of probability distributions for wind speed data and introduction of the moment and L-moment ratio diagram methods, with a case study

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