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 Optimizing Disruption Recovery Operations for Wind Farms considering Power Generation Loss and Repair Time Uncertainty

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dongmei Zhang ◽  
Jiangang Jin ◽  
Qingchang Ji ◽  
Xintong Zhang
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Operations Management ◽  
Wind Farm ◽  
Programming Model ◽  
Wind Farms ◽  
Repair Time ◽  
Mixed Integer ◽  
Chance Constrained Programming ◽  
Disruption Recovery

The development of wind power in China shows a dramatic growth in the past decade in terms of installed capacity. However, wind power companies mainly focus on the construction of new wind farms continuously, while operations management once wind farms are built is seldom paid attention to. The problem is crucial for ensuring efficient power generation, especially when wind turbines’ performance declines over time and disruption/failure often occurs. Efficient disruption recovery operations are critical for restoring the failures of wind turbine generators as fast as possible. This paper aims to optimize the disruption recovery operations for wind farms by determining the maintenance schedule and route for multiple maintenance teams. This optimization problem is formulated as a deterministic mixed integer linear programming model with the objective of minimizing the loss of power generation due to failure. In view of the high uncertainty of repair time, a chance-constrained programming model and a cutting-plane solution algorithm are further proposed. A case study based on a real wind farm demonstrates (1) the proposed model is applicable for solving real-world-sized problems; (2) the optimal maintenance route often shows a crossing pattern, which is quite different from that of traditional vehicle routing problems; and (3) the working time limit violation for maintenance teams due to uncertain repair time can be effectively avoided. Overall, the proposed optimization model provides decision-making support for wind farm maintenance work and shows a great potential in wind farm energy management.

Optimal Operation Planning of Wind Farm Installed BESS Using Wind Power Forecast Data of Wind Turbine Generators Considering Forecast Error

2013 ◽  
Vol 14 (3) ◽  
pp. 207-218 ◽  
Author(s):  
Kazuki Ogimi ◽  
Shota Kamiyama ◽  
Michael Palmer ◽  
Atsushi Yona ◽  
Tomonobu Senju ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Farm ◽  
Forecast Error ◽  
Energy Resource ◽  
Optimal Operation ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Wind Power Forecast ◽  
Forecast Data

Abstract In order to solve the problems of global warming and depletion of energy resource, renewable energy systems such as wind generation are getting attention. However, wind power fluctuates due to variation of wind speed, and it is difficult to perfectly forecast wind power. This paper describes a method to use power forecast data of wind turbine generators considering wind power forecast error for optimal operation. The purpose in this paper is to smooth the output power fluctuation of a wind farm and to obtain more beneficial electrical power for selling.

scholarly journals The Effect of a Renewable Energy Certificate Incentive on Mitigating Wind Power Fluctuations: A Case Study of Jeju Island

2019 ◽  
Vol 9 (8) ◽  
pp. 1647
Author(s):  
Woong Ko ◽  
Jaeho Lee ◽  
Jinho Kim
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Wind Power ◽  
Wind Farm ◽  
Optimization Problems ◽  
Mixed Integer ◽  
Renewable Portfolio Standard ◽  
Flexible Resources ◽  
Power Fluctuations ◽  
Revenue Models

As renewable energy penetration in power systems grows, adequate energy policies are needed to support the system’s operations with flexible resources and to adopt more sustainable energies. A peak-biased incentive for energy storage systems (ESS) using the Korean renewable portfolio standard could make power system operations more difficult. For the first time in the research, this study evaluates the effect of imposing a renewable energy certificate incentive in off-peak periods on mitigating wind power fluctuations. We design a coordinated model of a wind farm with an ESS to model the behavior of wind farm operators. Optimization problems are formulated as mixed integer linear programming problems to test the implementation of revenue models under Korean policy. These models are designed to consider additional incentives for discharging the ESS during off-peak periods. The effects of imposing the incentives on wind power fluctuations are evaluated using the magnitude of the renewable energy certificate (REC) multiplier.

Coordinated control and parameters optimization for PSS, POD and SVC to enhance the transient stability with the integration of DFIG based wind power systems

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jawaharlal Bhukya ◽  
Talada Appala Naidu ◽  
Sandeep Vuddanti ◽  
Charalambos Konstantinou
Keyword(s):  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Transient Stability ◽  
Parameter Tuning ◽  
Test System ◽  
Parameters Optimization ◽  
Coordination Mechanism ◽  
Three Phase ◽  
Simulation Results

Abstract This paper presents stability enhancement of a test system that is connected with a Wind Farm (WF) by using Power System Stabilizer (PSS) for Synchronous Generator (SG) and Power Oscillation Damper (POD) for Static Var Compensator (SVC). This paper also proposes a coordination mechanism for the controller to effectively damp out the oscillations and make the power system more stable by considering the uncertainties. The uncertainty is considered as wind speed variation and wind power penetration and different locations. The Particle Swarm Optimization (PSO) is used to overcome the controller parameter tuning drawbacks and controller coordination. The SG rotor speed deviation is selected as an objective function with various constraints for PSO. The transient stability analysis is carried out by considering large disturbance that is a three-phase fault. The nonlinear dynamic simulation results are obtained by integrating WF and SG replacement with the same rating WF. Evaluation and analysis are performed for various cases and different combination of without and with controllers. From the simulation results, it is noticed that oscillations in the system are minimized, and stability is enhanced at the maximum level. It also observed that the capability of SG and DFIG under three-phase fault is intensified by using PSO for optimized coordinated controller parameters. The robustness and effectiveness of the proposed approaches are evaluated on the IEEE-11 bus test system.

scholarly journals A Bilevel Multiobjective Optimisation Approach for Solving the Evacuation Location Assignment Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ahmed W. A. Hammad
Keyword(s):  
Assignment Problem ◽  
Programming Model ◽  
Decision Makers ◽  
Mixed Integer ◽  
Multiobjective Optimisation ◽  
Proposed Model ◽  
Level Problem ◽  
Location Assignment ◽  
Optimisation Model

In this paper, a bilevel multiobjective optimisation model is proposed to solve the evacuation location assignment problem. The model incorporates the two decision-makers’ spaces, namely, urban planners and evacuees. In order to solve the proposed problem, it is first reformulated into a single-level problem using the Karush–Kuhn–Tucker conditions. Next, the problem is linearised into a mixed-integer linear programming model and solved using an off-the-shelf solver. A case study is examined to showcase the applicability of the proposed model, which is solved using single-objective and multiobjective lexicographic optimisation approaches. The model provides planners with an ability to determine the best locations for placement of shelters in such a way that the evacuees’ traffic assignment on the existing network is optimised.

Comparison of Different Methods for Fault Ride through Ability of Fixed-Speed Wind Generation Systems

2013 ◽  
Vol 278-280 ◽  
pp. 1427-1431 ◽  
Author(s):  
Lei Tian ◽  
Tong Wang ◽  
Ya Miao
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Transient Stability ◽  
Low Voltage ◽  
Cost Effective ◽  
Constant Speed ◽  
Effective Solution ◽  
Constant Frequency ◽  
Fault Ride Through ◽  
Stability Enhancement

In recent years, with the increasing of wind farm's capacity, requirements of the ability of fault ride through for wind farm are getting more and more stringent. The article analyzes the methods improving the low voltage ride through capability of the constant speed constant frequency wind power generation system. Static Synchronous Compensator (STATCOM) and Series Dynamic Breaking Resistor (SDBR) have recently been reported as stabilization methods for fixed-speed wind generator systems. Simulation results demonstrate that the STATCOM is a cost-effective solution for transient stability enhancement and minimization of voltage fluctuations, while the BR is the simplest in structure and a cost-effective solution for transient stability enhancement. Then a method is prompted, which Combines STATCOM and SDBR to promote the fault ride-through ability of constant speed constant frequency wind power system. By this way, the system validity and stability can be improved while costs can be cut down.

scholarly journals An application of ensemble/multi model approach for wind power production forecasting

2011 ◽  
Vol 6 (1) ◽  
pp. 35-37 ◽  
Author(s):  
S. Alessandrini ◽  
P. Pinson ◽  
R. Hagedorn ◽  
G. Decimi ◽  
S. Sperati
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Forecast Error ◽  
Meteorological Data ◽  
Forecast Accuracy ◽  
Mountain Area ◽  
Production Forecasting ◽  
Wind Power Forecast ◽  
Model Output Statistic ◽  
Meteorological Models

Abstract. The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.

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