Research on Data Transmission and Information Integration Technology in the Distributed Wind Farm SCADA System

2014 ◽  
Vol 543-547 ◽  
pp. 2641-2646
Author(s):  
Yan Feng Tian ◽  
He Li ◽  
Zuo Xia Xing ◽  
Gang Wang
Keyword(s):  
Wind Power ◽  
Information Integration ◽  
Data Transmission ◽  
Wind Farm ◽  
Integration Technology ◽  
Transmission Grid ◽  
Scada System ◽  
New Form ◽  
Wind Resource ◽  
Grid Resources

Distributed wind power is a new form of wind power generation, which under a limited transmission grid resources condition can makes full use of small wind resource. Therefore, it has economic and practical value to develop distributed wind farm. However, the SCADA system of distributed wind farm is the basic safeguard to ensure distributed wind farm to be safe, reliable and economical operation. Compared to other SCADA system, the SCADA system of distributed wind farm has difficulties in data transmission and information integration. This paper puts forward information integration technology based on OPC XML and data transmission technology based on the combination of ZigBee and 3G wireless network to solve the above problems.

Simulation of a Wind-Power Plant Linked to a Transmission GridPart I: Modeling the Basic Wind Farm

2013 ◽  
Vol 11 (1) ◽  
pp. 545-552
Author(s):  
Jorge Vaschetti ◽  
Juan C. Gomez Targarona ◽  
Jorge Arcurio
Keyword(s):  
Power Plant ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Power Plant ◽  
Transmission Grid

scholarly journals The Influence of the Wind Measurement Campaign Duration on a Measure-Correlate-Predict (MCP)-Based Wind Resource Assessment

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3606
Author(s):  
José V. P. Miguel ◽  
Eliane A. Fadigas ◽  
Ildo L. Sauer
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Target Location ◽  
Resource Assessment ◽  
Measurement Campaign ◽  
Wind Measurement ◽  
Wind Resource Assessment ◽  
Wind Resource

Driven by the energy auctions system, wind power in Brazil is undergoing a phase of expansion within its electric energy mix. Due to wind’s stochastic nature and variability, the wind measurement campaign duration of a wind farm project is required to last for a minimum of 36 months in order for it to partake in energy auctions. In this respect, the influence of such duration on a measure-correlate-predict (MCP) based wind resource assessment was studied to assess the accuracy of generation forecasts. For this purpose, three databases containing time series of wind speed belonging to a site were considered. Campaigns with durations varying from 2 to 6 years were simulated to evaluate the behavior of the uncertainty in the long-term wind resource and to analyze how it impacts a wind farm power output estimation. As the wind measurement campaign length is increased, the uncertainty in the long-term wind resource diminished, thereby reducing the overall uncertainty that pervades the wind power harnessing. Larger monitoring campaigns implied larger quantities of data, thus enabling a better assessment of wind speed variability within that target location. Consequently, the energy production estimation decreased, allowing an improvement in the accuracy of the energy generation prediction by not overestimating it, which could benefit the reliability of the Brazilian electric system.

A Comprehensive Measure of the Energy Resource Potential of a Wind Farm Site

2011 ◽  
Author(s):  
Jie Zhang ◽  
Souma Chowdhury ◽  
Achille Messac ◽  
Luciano Castillo
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Velocity Distribution ◽  
Wind Power ◽  
Wind Velocity ◽  
Wind Direction ◽  
Wind Farm ◽  
Farm Size ◽  
Wind Resource

Currently, the quality of wind measure of a site is assessed using Wind Power Density (WPD). This paper proposes to use a more credible metric namely, one we call the Wind Power Potential (WPP). While the former only uses wind speed information, the latter exploits both wind speed and wind direction distributions, and yields more credible estimates. The new measure of quality of a wind resource, the Wind Power Potential Evaluation (WPPE) model, investigates the effect of wind velocity distribution on the optimal net power generation of a farm. Bivariate normal distribution is used to characterize the stochastic variation of wind conditions (speed and direction). The net power generation for a particular farm size and installed capacity are maximized for different distributions of wind speed and wind direction, using the Unrestricted Wind Farm Layout Optimization (UWFLO) methodology. A response surface is constructed, using the recently developed Reliability Based Hybrid Functions (RBHF), to represent the computed maximum power generation as a function of the parameters of the wind velocity (speed and direction) distribution. To this end, for any farm site, we can (i) estimate the parameters of wind velocity distribution using recorded wind data, and (ii) predict the maximum power generation for a specified farm size and capacity, using the developed response surface. The WPPE model is validated through recorded wind data at four differing stations obtained from the North Dakota Agricultural Weather Network (NDAWN). The results illustrate the variation of wind conditions and, subsequently, its influence on the quality of a wind resource.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

scholarly journals Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 338
Author(s):  
Lorenzo Donadio ◽  
Jiannong Fang ◽  
Fernando Porté-Agel
Keyword(s):  
Machine Learning ◽  
Wind Energy ◽  
Wind Power ◽  
Numerical Weather Prediction ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wind Power Forecasting ◽  
Numerical Weather ◽  
Artificial Neural ◽  
Power Forecasting

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real-time forecasts of wind farm power outputs can help to mitigate the problem. Among the various techniques developed for wind power forecasting, the hybridization of numerical weather prediction (NWP) and machine learning (ML) techniques such as artificial neural networks (ANNs) are attracting many researchers world-wide nowadays, because it has the potential to yield more accurate forecasts. In this paper, two hybrid NWP and ANN models for wind power forecasting over a highly complex terrain are proposed. The developed models have a fine temporal resolution and a sufficiently large prediction horizon (>6 h ahead). Model 1 directly forecasts the energy production of each wind turbine. Model 2 forecasts first the wind speed, then converts it to the power using a fitted power curve. Effects of various modeling options (selection of inputs, network structures, etc.) on the model performance are investigated. Performances of different models are evaluated based on four normalized error measures. Statistical results of model predictions are presented with discussions. Python was utilized for task automation and machine learning. The end result is a fully working library for wind power predictions and a set of tools for running the models in forecast mode. It is shown that the proposed models are able to yield accurate wind farm power forecasts at a site with high terrain and flow complexities. Especially, for Model 2, the normalized Mean Absolute Error and Root Mean Squared Error are obtained as 8.76% and 13.03%, respectively, lower than the errors reported by other models in the same category.

Operation and approximation based on the history of failure modes recorded by SCADA system of Amougdoul Moroccan wind farm using FMECA maintenance model

2021 ◽  
pp. 0309524X2199245
Author(s):  
Kawtar Lamhour ◽  
Abdeslam Tizliouine
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Failure Modes ◽  
Wind Farms ◽  
Scada System ◽  
History Of ◽  
Criticality Analysis ◽  
Maintenance Model ◽  
Reliability And Availability ◽  
Critical Subsystems

The wind industry is trying to find tools to accurately predict and know the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique used to determine critical subsystems, causes and consequences of wind turbines. FMECA has been widely used by manufacturers of wind turbine assemblies to analyze, evaluate and prioritize potential/known failure modes. However, its actual implementation in wind farms has some limitations. This paper aims to determine the most critical subsystems, causes and consequences of the wind turbines of the Moroccan wind farm of Amougdoul during the years 2010–2019 by applying the maintenance model (FMECA), which is an analysis of failure modes, effects and criticality based on a history of failure modes occurred by the SCADA system and proposing solutions and recommendations.

scholarly journals Miniaturization of an Offshore Platform with Medium-Frequency Offshore Wind Farm and MMC-HVDC Technology

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2058
Author(s):  
Zheren Zhang ◽  
Yingjie Tang ◽  
Zheng Xu
Keyword(s):  
Wind Power ◽  
Computer Aided Design ◽  
Wind Farm ◽  
Offshore Platform ◽  
Offshore Wind ◽  
Operating Frequency ◽  
Offshore Wind Farm ◽  
Medium Frequency ◽  
Offshore Wind Power ◽  
System Frequency

Offshore wind power has great development potential, for which the key factors are reliable and economical wind farms and integration systems. This paper proposes a medium-frequency wind farm and MMC-HVDC integration system. In the proposed scheme, the operating frequency of the offshore wind farm and its power collection system is increased from the conventional 50/60 Hz rate to the medium-frequency range, i.e., 100–400 Hz; the offshore wind power is transmitted to the onshore grid via the modular multilevel converter-based high-voltage direct current transmission (MMC-HVDC). First, this paper explains the principles of the proposed scheme in terms of the system topology and control strategy aspects. Then, the impacts of increasing the offshore system operating frequency on the main parameters of the offshore station are discussed. As the frequency increases, it is shown that the actual value of the electrical equipment, such as the transformers, the arm inductors, and the SM capacitors of the rectifier MMC, can be reduced, which means smaller platforms are required for the step-up transformer station and the converter station. Then, the system operation characteristics are analyzed, with the results showing that the power losses in the system increase slightly with the increase of the offshore AC system frequency. Based on time domain simulation results from power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC), it is noted that the dynamic behavior of the system is not significantly affected with the increase of the offshore AC system frequency in most scenarios. In this way, the technical feasibility of the proposed offshore platform miniaturization technology is proven.

scholarly journals A Diode-MMC AC/DC Hub for Connecting Offshore Wind Farm and Offshore Production Platform

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3759
Author(s):  
Kai Huang ◽  
Lie Xu ◽  
Guangchen Liu
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Offshore Wind ◽  
System Control ◽  
Dc Voltage ◽  
Offshore Wind Power ◽  
Offshore Production ◽  
Production Platform ◽  
In Series ◽  
Dc Voltage Control

A diode rectifier-modular multilevel converter AC/DC hub (DR-MMC Hub) is proposed to integrate offshore wind power to the onshore DC network and offshore production platforms (e.g., oil/gas and hydrogen production plants) with different DC voltage levels. The DR and MMCs are connected in parallel at the offshore AC collection network to integrate offshore wind power, and in series at the DC terminals of the offshore production platform and the onshore DC network. Compared with conventional parallel-connected DR-MMC HVDC systems, the proposed DR-MMC hub reduces the required MMC converter rating, leading to lower investment cost and power loss. System control of the DR-MMC AC/DC hub is designed based on the operation requirements of the offshore production platform, considering different control modes (power control or DC voltage control). System behaviors and requirements during AC and DC faults are investigated, and hybrid MMCs with half-bridge and full-bridge sub-modules (HBSMs and FBSMs) are used for safe operation during DC faults. Simulation results based on PSCAD/EMTDC validate the operation of the DR-MMC hub.

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