Risk-Averse Preventive Voltage Control of AC/DC Power Systems Including Wind Power Generation

Rabiee, Abbas; Soroudi, Alireza; Keane, Andrew

doi:10.1109/tste.2015.2451511

Cited by 32 publications

(17 citation statements)

References 36 publications

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“…The following equations can be yielded [19]: (12) The extracted result of α in (12) is PDT. That is why PDT can be a by-product of CPD optimization computation.…”

Section: Special Constraint For the Application Of Utility Functionmentioning

confidence: 99%

“…It means unit i ramps up with rate r i between the upper and lower limits. Formula (19) ensures that power supply satisfies the threshold of uncertain power deficiency (PDT). Constraint (20) makes operating time (load pickup time) t m within reasonable time interval.…”

Section: A Construction Of the Utility-oriented Optimizationmentioning

confidence: 99%

“…Thirdly, a utility-oriented optimization is formulated to determine the optimal strategy with security constraints. Furthermore, by applying the optimization advantage of CPD [19]- [20] and the linear programming of AC power flow (LPAC) method [21], the utility-oriented optimization converts into a scenario-based linear programming (LP).…”

mentioning

confidence: 99%

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Utility-Oriented Online Load Restoration Considering Wind Power Penetration

Zhao

Wang

Liu

et al. 2019

IEEE Trans. Sustain. Energy

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An efficient load recovery of a bulk system with wind power penetration requires careful consideration of uncertainties related to it, as well as on-line data gathered from measurement devices. From the perspective of uncertainties, a novel utility-based decision-making method is proposed in this paper. The method combines both risk and return of load restoration strategy to assist decision-making in uncertain states, and it also provides utility function to present preference of load restoration strategy. Furthermore, a utility-oriented optimization model is created to select the strategy with the largest utility value with a certain confidence level. To achieve efficient utilization of on-line data, as well as to ensure high computation efficiency, the utilityoriented optimization is transformed into a scenario-based linear programming model. The proposed method fills the gap between on-line data and the optimal load restoration strategy in uncertain condition. Besides, the optimal strategy is provided with adjustable robustness according to security requirements and data exactness. Therefore, it is particularly applicable for on-line load restoration with wind power penetration. The effectiveness of the proposed method is validated using IEEE-30 bus test system and an actual power system from the North-East of Shandong province, China.Index Terms-conditional value-at-risk, power system restoration, uncertain decision, wind uncertainty.

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“…The following equations can be yielded [19]: (12) The extracted result of α in (12) is PDT. That is why PDT can be a by-product of CPD optimization computation.…”

Section: Special Constraint For the Application Of Utility Functionmentioning

confidence: 99%

Section: A Construction Of the Utility-oriented Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Utility-Oriented Online Load Restoration Considering Wind Power Penetration

Zhao

Wang

Liu

et al. 2019

IEEE Trans. Sustain. Energy

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“…The second part of the retailer's revenues includes the sale of capacity to the consumers in the second-side of the market. This revenue is calculated through Equation (36). Total retailer's revenues have been calculated through Equation (37).…”

Section: Retailer's Revenues Modelingmentioning

confidence: 99%

“…Uncertainties in asset management of power transmission systems and congestion management have been managed by using VaR measure. Also, CVaR measure has been used for uncertainty assessment in the determination of optimal spinning reserve and preventive voltage control of AC/DC power systems . In this paper, scenario‐based stochastic programming has been used to model the uncertainty and risk measure has been applied to define risk‐based objective function.…”

Section: Introductionmentioning

confidence: 99%

Modeling of retailer's behavior for participation in the capacity market

Jalili

Eslami

Moghaddam

et al. 2019

Int Trans Electr Energ Syst

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Summary Due to economic reasons, only way for demand side management resources participation in capacity market is their participation by load serving entities, energy service companies, or retailers. To achieve the optimal participation of retailers in the capacity market, it is crucial to model the effective parameters in retailers’ behavior model and how they trade with the independent system operator and the consumers. So a novel method is proposed in this paper for modeling retailers’ behavior, considering demand side management resources availability for their participation in long term commitments. The capacity product of the retailer and its behavior are comprehensively modeled to trade in the capacity market. The competition of retailers is also considered and its effects on the profit of the retailer and consumers are analyzed. A genetic algorithm has been used to solve this problem due to its ability for solving large‐scale real nonlinear Non‐deterministic Polynomial‐time hard (NP‐hard) optimization problems.

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Probability assessment for power system voltage stability margin with renewable energy source using slice sampling

Zhang

Wang²,

Wang

et al. 2017

Int Trans Electr Energ Syst

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Summary With the prevalence of renewable energy source in power system, it is necessary to appraise the voltage stability of the integration system by probabilistic methods. The traditional Markov Chain Monte Carlo (MCMC) simulation could show great calculation precision for the probabilistic assessment, but it is always involved with complicated sampling iterations because of the Gibbs sampling method currently used in MCMC simulation. Instead of Gibbs sampling method, this paper presents the application of slice sampling in MCMC simulation for the voltage stability probabilistic assessment of the power system with renewable source. Firstly, the probabilistic models of renewable source generation are constructed. Then, the sample space of renewable source outputs is obtained by slice sampling, and the samples from the sample space are calculated by power flow. Finally, the voltage stability margin is obtained by the result of the power flow calculation, and the probabilistic assessment of the voltage stability is implemented. Furthermore, the MCMC simulations using Gibbs sampling and slice sampling are compared by Gelman‐Rubin diagnostic and Kullback‐Leibler divergence tests on IEEE 14‐bus system and IEEE 39‐bus system, respectively. The results show that the slice sampling method is simpler and more efficient than Gibbs sampling method in the voltage stability probabilistic assessment.

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Risk-Averse Preventive Voltage Control of AC/DC Power Systems Including Wind Power Generation

Cited by 32 publications

References 36 publications

Utility-Oriented Online Load Restoration Considering Wind Power Penetration

Utility-Oriented Online Load Restoration Considering Wind Power Penetration

Modeling of retailer's behavior for participation in the capacity market

Probability assessment for power system voltage stability margin with renewable energy source using slice sampling

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