Method for computing probability distributions of available transfer capability

Chang, Rung-Fang; Tsai, Cheng-Yu; Su, Chun‐Lien; Lu, Chan‐Nan

doi:10.1049/ip-gtd:20020334

Cited by 28 publications

(16 citation statements)

References 7 publications

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“…These variations in system operating condition are the information which requires large data storage. However, operation practice does not allow storing a large number of systems operating condition data [10][11][12]. To overcome the problem, a small number of system operation conditions are pertinent only for data storage and then it is used in the probabilistic method such as the non-parametric bootstrap technique to produce large number of system operating condition with uncertainty.…”

Section: Estimation Of Transfer Capability Uncertainty Using Parametrmentioning

confidence: 99%

“…On the other hand, considering the fact that ATC is an estimate of the future power transfer availability [10][11][12], therefore, it is important to determine TRM based on a future distribution of ATCs. In this analysis, the historic or inherent variables of ATC (ATC n ) are used as a guide to estimate future distribution of ATCs (ATC n,b ¼ q1 ) for the TRM determination.…”

Section: Trm Determination Using Bootstrap Techniquesmentioning

confidence: 99%

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Determination of transmission reliability margin considering uncertainties of system operating condition and transmission line outage

Zaini

Othman

Musirin

et al. 2010

Euro. Trans. Electr. Power

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SUMMARYThe uncertainty of system operating conditions is a part of consequences which may cause to the volatility of a transmission system. This will hinder the performance of transmission system to effectively transfer the power between areas. Therefore, accurate estimation of transmission reliability margin (TRM) is required to ensure effective power transfer between areas during the occurrence of uncertainties. The power transfer is also called as the available transfer capability (ATC) in which it is the information required by the utilities and marketers to instigate selling and buying the electric energy. The TRM is estimated by taking into account the uncertainties of line outages and system parameters generated by the bootstrap technique. A case study of Malaysia Power System is used to verify the robustness of bootstrap technique in the TRM determination. The results show that the combined impact of several uncertainties which significantly affect the value of TRM.

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Section: Estimation Of Transfer Capability Uncertainty Using Parametrmentioning

confidence: 99%

Section: Trm Determination Using Bootstrap Techniquesmentioning

confidence: 99%

Determination of transmission reliability margin considering uncertainties of system operating condition and transmission line outage

Zaini

Othman

Musirin

et al. 2010

Euro. Trans. Electr. Power

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“…Considering the fact that ATC is an estimate of future power transfer availability [6,7,8], therefore it is important to determine TRM based on the future condition of system parameters. Since the future system parameter conditions are not known in this analysis, therefore TRM is obtained based on the system parameter at base case condition.…”

Section: A Transmission Reliability Margin Formulationmentioning

confidence: 99%

“…These variations in system parameter will lead to a large storage of data and the operation practice does not allow storing of a large number of system parameter conditions data [6,7,8]. To overcome the problem of data storage, an improved technique is required in providing large amount of uncertainty from a small sample size of system parameters.…”

Section: A Transmission Reliability Margin Formulationmentioning

confidence: 99%

Determination of Available Transfer Capability Incorporating Transmission Reliability Margin

Othman

Mohamed

Hussain

2006

2006 IEEE International Power and Energy Conference

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In a deregulated power system, determination of available transfer capability (ATC) should incorporate the amount of transmission reliability margin (TRM) so that the transmission network is secure under a reasonable range of uncertainty that occur during a power transfer. This paper presents a new approach to evaluate the TRM with an extensively large amount of uncertainty. The approach uses the standard uncertainty method which incorporates the parametric bootstrap technique and the normal probability density function. The uncertainty of system parameters that used in the TRM estimation is the uncertainty of transmission line impedances and forecasted peak load. ATC is then estimated by considering the outages of critical transmission line and critical generator unit and the TRM. A case study of IEEE 300 bus system is used to verify the robustness of the TRM method in estimating the ATC. Comparison in terms of accuracy in evaluating the TRM is made between the standard uncertainty and standard deviation of uncertainty techniques that used in the TRM methods.Index Terms-Available transfer capability, transmission reliability margin, parametric bootstrap technique, standard uncertainty method.

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“…The genetic algorithm [4,5], particle swarm optimization [6], optimal power flow method [7], probability analytical method, stochastic programming method [8], Monte Carlo simulation [9,10], and the enumeration method [11] were adopted for this purpose. For describing the wind power uncertainty, the statistical probability method [12][13][14][15] and scene analysis method [16] are adopted.…”

Section: Introductionmentioning

confidence: 99%

Optimal Available Transfer Capability Assessment Strategy for Wind Integrated Transmission Systems Considering Uncertainty of Wind Power Probability Distribution

et al. 2016

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Abstract:Wind power prediction research shows that it is difficult to accurately and effectively estimate the probability distribution (PD) of wind power. When only partial information of the wind power probability distribution function is available, an optimal available transfer capability (ATC) assessment strategy considering the uncertainty on the wind power probability distribution is proposed in this paper. As wind power probability distribution is not accurately given, the proposed strategy can efficiently maximize ATC with the security operation constraints satisfied under any wind power PD function case in the uncertainty set. A distributional robust chance constrained (DRCC) model is developed to describe an optimal ATC assessment problem. To achieve tractability of the DRCC model, the dual optimization, S-lemma and Schur complement are adopted to eliminate the uncertain wind power vector in the DRCC model. According to the characteristics of the problem, the linear matrix inequality (LMI)-based particle swarm optimization (PSO) algorithm is used to solve the DRCC model which contains first and second-order moment information of the wind power. The modified IEEE 30-bus system simulation results show the feasibility and effectiveness of the proposed ATC assessment strategy.

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Method for computing probability distributions of available transfer capability

Cited by 28 publications

References 7 publications

Determination of transmission reliability margin considering uncertainties of system operating condition and transmission line outage

Determination of transmission reliability margin considering uncertainties of system operating condition and transmission line outage

Determination of Available Transfer Capability Incorporating Transmission Reliability Margin

Optimal Available Transfer Capability Assessment Strategy for Wind Integrated Transmission Systems Considering Uncertainty of Wind Power Probability Distribution

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