• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.453-463
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• 2013

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1397-1405
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• 2017

As the introduction of wind power is steadily increasing, negative effects of wind power become more important. To operate a power system more reliable, the system operator needs to recognize the maximum required capacity of available generators for a certain period. For recognizing the maximum capacity, this paper proposes a methodology to determine an optimal reserve requirement considering wind power, for the certain period in the mid-term perspective. As wind speed is predicted earlier, the difference of the forecasted and the actual wind speed becomes greater. All possible forecast errors should be considered in determining optimal reserve, and they are represented explicitly by the proposed matrix form in this paper. In addition, impacts of the generator failure are also analyzed using the matrix form. Through three main stages which are the scheduling, contingency and evaluation stages, costs associated with power generation, reserve procurement and the usage, and the reliability cost are calculated. The optimal reserve requirement is determined so as to minimize the sum of these costs based on the cost/reliability analysis. In case study, it is performed to analyze the impact of wind power penetration on the reserve requirement, and how major factors affect it.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1348-1356
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• 2017

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.32-35
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• 2011

The economic value of a wind farm project is influenced by various risk factors such as wind power output and electricity market price. In particular, there is uncertainty in the economic evaluation of a wind farm project due to uncertain wind power outputs, which are fluctuated by weather factors such as wind speed, and volatile electricity market prices. This paper presents a systematic method to assess the economic value and payback period of a wind farm project using Least Square Monte-Carlo (LSMC) simulation. Numerical example is presented to validate the effectiveness of the proposed economic assessment method for a wind farm project.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.74-91
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• 2023

This study provides an in-depth comparison and analysis of various risk assessment models widely used in modern industries, and proposes the most suitable model for risk assessment of offshore wind power in Korea. The assessment models were selected by considering various factors such as the purpose of risk assessment, stakeholder requirements, and characteristics of offshore wind power. We also emphasized the importance of using different risk assessment models in combination in situations of high uncertainty. To systematize the combination of risk assessment models, we used systems engineering which is effective to develop a new system. Systems engineering was used to define the complete, traceable functions from site requirements, and model-based systems engineering was used to manage the design information from requirements to detailed functions in a single model. The developed risk assessment module provide automatic conversion between risk assessment models to enable risk assessment suitable for offshore wind power. The functionality and usability of the offshore wind risk assessment module were verified by the evaluation of three wind power experts.

• Journal of Environmental Science International
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• v.22 no.10
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• Journal of Power Electronics
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• v.10 no.5
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• pp.498-504
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• 2010

The output power fluctuations of renewable energy power plants such as wind turbine generators and photovoltaic systems result in frequency deviations and terminal voltage fluctuations. Furthermore, these power fluctuations also affect the turbine shaftings of diesel generators and gas-turbine generators which are the main power generation systems on isolated islands. Therefore, it is important to achieve torsional torque suppression. Since the measurement of torsional torque is technically difficult, and there is an uncertainty in the mechanical constants of the shaft torsional system. This paper presents an estimation system that estimates torsional torque by using a developed $H_{\infty}$ observer. In addition to the above functions, the proposed shaft torque observer incorporates a parameter identification system that aims to improve the estimation accuracy. The simulation results validate the effectiveness of the proposed $H_{\infty}$ observer and the parameter identification.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of Environmental Science International
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• v.23 no.9
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• pp.1551-1562
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• 2014

To clarify the characteristics of TKE (Turbulence Kinetic Energy) variation for offshore wind power development, several numerical experiments using WRF were carried out in three different coastal area of the Korean Peninsula. Buoyancy, mechanical and shear production term of the TKE budget are fundamental elements in the production or dissipation of turbulence. Turbulent kinetic energy of the south coast region was higher than in other sea areas due to the higher sea surface temperature and strong wind speed. In south coast region, strong wind passing through the Korea Strait is caused by channelling effect of the terrain of the Geoje Island. Although wind speed is weak in east coast, because of large difference in wind speed between the upper and lower layer, the development of mechanical turbulence tend to be predominant. Since lower sea surface temperature and smaller wind shear were detected in west coastal region, the possibility of turbulence production not so great in comparison with other regions. The understanding of the characteristics of turbulence in three different coastal region can be reduced the uncertainty of offshore wind construction.