• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.9
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• pp.487-493
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• 2004

The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RTS. The system performance index for power flow presents the power system stability. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into the case of normal and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking required for security under the deregulated electricity market.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.911-914
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• 1998

This paper presents an algorithm that evaluates the transfer capability of composite power systems using probabilistic approaches. The reliability indices calculated by using probabilistic method are expected maximal flow, expected transfer capability margin, and expected power not supplied. In this paper, a successive linear programming technique is used to evaluate transfer capability named maximal flow. Physical constraints considered in the maximal flow problem are the limits of toad voltage, line overloading, and real & reactive power generation. Numerical results on IEEE RTS show that the proposed algorithm is effective and useful.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1494-1503
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• 2018

This paper proposes a novel probabilistic load flow model for power systems integrated with large-scale wind power, which considers the multi-time scale dispatching features. The ramp limitations of the units and the steady-state security constraints of the network have been comprehensively considered for the entire duration of the study period; thus, the coupling of the system operation states at different time sections has been taken into account. For each time section, the automatic generation control (AGC) strategy is considered, and all variations associated with the wind power and loads are compensated by all AGC units. Cumulants and the Gram-Charlier expansion are used to solve the proposed model. The effectiveness of the proposed method is validated using the modified IEEE RTS 24-bus system and the modified IEEE 118-bus system.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.28-30
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• 2003

Probabilistic Load Flow(PLF) solution based on the method of moments is used for security assessment of bus voltages in power systems. Bus voltages, line currents, line admittances, generated real and reactive power, and bus loads are treated as complex random variables. These complex random variables are known in terms of probability density functions(PDF). Also, expressions for the convolutions of complex random variables in terms of moments and cumulants have been derived. Proposed PLF solution using the method of moments is fast, because the process of convolution of various complex random variables is performed in moment and cumulant domain. Therefore, the method is applied to security assessment of power systems in this paper. Finally, system operator also can be used information of security assessment to improve reliability of power systems.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.134-136
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• 2003

The deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RBTS. also, the system performance index for power flow presents the power system stability. The probabilistic risk index can be classified into normal weather and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking requiring for security under the deregulated electricity market.

• 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.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.297-300
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• 2004

This paper proposes a method for choosing the best composite power system expansion plan considering probabilistic reliability criterion. The proposed method was modeled as the minimization of the investment budget (economics) for constructing new transmission lines subject to not only deterministic(demand constraint) but also probabilistic reliability criterion(LOLE) with considering the uncertainties of the system elements. This is achieved by modeling the power system expansion problem as an integer programming one. The method solves for the optimal strategy using a probabilistic theory based branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. Although the proposed method is applied to a simple sample study, the test results demonstrate a fact that the proposed method is suitable for solving the power system expansion planning problem subject to practical uncertainties for future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.457-466
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• 2013

Wind energy is rapidly becoming significant generating technologies in electricity markets. As probabilistic nature of wind energy creates many uncertainties in the short-term scheduling, additional actions for reliable market operation should be taken. This paper presents a novel approach to evaluate ramping capability requirement for changes in imbalance energy between day-ahead market and real-time market due to uncertainty of wind generation as well as system load. Dynamic ramp rate model has been applied for realistic solution in unit commitment problem, which is implemented in day-ahead market. Probabilistic optimal power flow has been used to verify ramping capability determined by the proposed method is reasonable in economic and reliable aspects. This approach was tested on six-bus system and IEEE 118-bus system with a wind farm. The results show that the proposed approach provides ramping capability information to meet both forecasted variability and desired confidence level of anticipated uncertainty.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.418-428
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are newly defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.