• 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.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.569-571
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• 2003

As a definition of NERC, Available Transfer Capability(ATC) is a measure of the transfer capability remaining in the physical transmission network for the future commercial activity. To calculate ATC, accurate and defensible TTC, CBM and TRM should be calculated in advance. In this paper, we propose a method to quantify TRM using probabilistic load flow based on the method of moment. Generation output, bus voltages, loads, and line outages are considered as complex random variables (CRV) to take into account for uncertainties related to the transmission network conditions. Probability Density Function (PDF) of line flow at the most limiting line is used to quantify TRM with the desired probabilistic margin. Suggested method is compared with the results from conventional CPF method and verified using 24 bus MRTS, and the suggested method based on PLF shows efficiency and flexibility for the quantification of TRM compared with the conventional method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.4
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• pp.195-198
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• 2000

This paper illustrates a new method for constructing composite power system effective load duration curve(CMELDC) at load points. The main concept of proposed method is that the CMELDC can be obtain from convolution integral processing of the outage probabilistic distribution function of not supplied power and the load duration curve given at each load point. The effective load duration curve (ELDC) at HLI plays an important part in probabilistic production simulation, reliability evaluation, outage cost assessment and power supply margins assesment for power system planning and operation. And also, the CMELDC at HLII will extend the application areas of outage cost assessment and reliability evaluation at each load point. The CMELDC at load points using the Monte Carlo method and a DC load flow constrained LP have already been developed by authors. The effective load concept at HLII, however, has not been introduced sufficiently in last paper although the concept is important. In this paper, the main concept of the effective load at HLII which is proposed in this study is defined in details as the summation of the original load and the probabilistic loads caused by the forced outage of generators and transmission lines at this load point. The outage capacity probabilistic distribution function at HLII can be obtained by combining the not supplied powers and the probabilities of the not supplied powers at this load point. It si also expected that the proposed CMELDC can be applied usefully to research areas such as reliability evaluation, probabilistic production cost simulation and analytical outage cost assessment, etc. at HLII in future. The characteristics and effectiveness of this methodology are illustrated by case study of IEEE-RTS.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1100-1102
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• 1997

This paper presents a generalized multi-parameter distribution method for the convolution of linear combination of random variables to calculate system load flow in a conventional probabilistic approach and also presents a conceptual possibilistic approach using fuzzy set theory to manage uncertainties. The probability distribution function is transformed into an appropriate possibilistic representation under the compromise between the transformation consistency and the human updating experience. The IEEE 25-bus system is used to demonstrate the capability of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.533-539
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• 2005

According to NERC definition, Available Transfer Capability (ATC) is a measure of the transfer capability remaining in the physical transmission network for the future commercial activity. To calculate Available Transfer Capability, accurate and defensible Total Transfer Capability, Capacity Benefit Margin and Transmission Reliability Margin should be calculated in advance. This paper proposes a method to quantify time varying Available Transfer Capability based on probabilistic approach. The uncertainties of power system and market are considered as complex random variables. Total Transfer Capability is determined by optimization technique such as SQP(Sequential Quadratic Programming). Transmission Reliability Margin with the desired probabilistic margin is calculated based on Probabilistic Load Flow analysis, and Capacity Benefit Margin is evaluated using LOLE of the system. Suggested Available Transfer Capability quantification method is verified using IEEE RTS with 72 bus. The proposed method shows efficiency and flexibility for the quantification of Available Transfer Capability.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2211-2220
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• 2015

This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.346-354
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• 1992

In the power-system, the active and reactive power levels of load bus randomly vary over days, months, and years which are stochastic in nature. This paper presents an algorithm for optimal Var planning considering the uncertainties of loads. The optimization problem is solved by a stochastic linear programming technique which can handle stochastic constraints to evaluate optimal Var requirement at load bus to maintain the voltage profile which results in probabilistic density function by stochastic Load Flow analysis within admissible range. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.279-286
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• 2010

Unbalanced traffic load offered to the nodes making up a path in the network guaranteeing quality-of-service has been known as a main cause deteriorating the capability of the path in admitting traffic flows. Several path load balancing methods have been developed to resolve this problem which used a feedback control scheme that adjusts the delay budget of a flow allocated to each node according to the conditions of available resource in the path. Because of no consideration about the probabilistic characteristics of the service quality, it is impossible for them to prevent in advance a bottleneck on the path which leads to a native restriction in the improvement of the capability being deteriorated. This paper proposes a preventive intra-path load balancing method applicable to the RSVP system which is based on the probabilistic characteristics of the quality-of-service of the offered load. The results of the simulation of the proposed method on a simple evaluation network showed that it provides the gain of 4~22% compared to the legacy one in terms of the number of admitted flows.