Reliability constrained congestion management with uncertain negawatt demand response firms considering repairable advanced metering infrastructures

Tabandeh, Abbas; Abdollahi, Amir; Rashidinejad, Masoud

doi:10.1016/j.energy.2016.03.118

Cited by 42 publications

(17 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Picciolo et al (2008) use such a model to identify the maximum periodic inspection interval in engines. Tabandeh et al (2016) use the Markov chain to model the uncertainty of demand response resources to power reduction. Min et al (2016) describe a method of risk assessment for ramping capability shortage.…”

Section: Markov Chainsmentioning

confidence: 99%

Maintenance strategy selection in electric power distribution systems

Carnero

Gómez

2017

Energy

View full text Add to dashboard Cite

Section: Markov Chainsmentioning

confidence: 99%

Maintenance strategy selection in electric power distribution systems

Carnero

Gómez

2017

Energy

View full text Add to dashboard Cite

“…In [9], the congestion management of power system with renewable resources is carried out considering contingency condition using grey wolf optimisation method. The reliability constrained congestion management is carried out by considering the demand response and forced outage rate of advance metering infrastructure [10]. However, the methods reviewed above do not consider the congestion management issue of power system including PEVs and RES.…”

Section: Literature Surveymentioning

confidence: 99%

Congestion management of power system with uncertain renewable resources and plug‐in electrical vehicle

Prajapati

Mahajan

2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…assumed that DR will never fail to respond during the period of DR events. Surely some studies [29]- [32] have considered the uncertainty of DR: a probabilistic framework for optimal DR scheduling in the day-ahead planning of transmission networks is proposed in [29], and the results show that the proposed DR scheduling improves both reliability and economic indices; a new framework for congestion management utilizing a reliability model of DR resources is proposed in [30] and the multistate model of DR resources considering repairable advanced metering infrastructures is also presented; a framework for reliability assessment and risk implications of post-fault DR in smart distribution networks is presented in [31]; a reliability model of the demand resource is developed to represent the customer behavior, and the reliability indices of power systems are calculated in [32]. Nevertheless, the literature above only addresses the steady reliability model of DR and the long-term steady reliability assessment of power systems.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Reliability Assessment of Generating Systems Considering Demand Response Reliability

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Demand response (DR), one kind of flexible resources, can decrease the operating costs of power systems and improve their reliability. However, DR is not absolutely reliable due to its inherent uncertainty, so its function of improving system reliability is restricted. In order to estimate the risk of generating systems during the period of DR events, the short-term reliability assessment of generating systems considering DR reliability is studied in this paper. Firstly, a multi-state continuous-time Markov chain (CTMC) model of DR response capacity is established and the state division of response capacity is performed by the method of mean-standard deviation (MSD) classification. Secondly, the transition matrix of DR response capacity is estimated according to the sequence of DR response capacity. Thirdly, the CTMCs of demand response providers' (DRP) response capacity and those of generating units' (GU) output capacity are converted into universal generating functions (UGF) by Lz-transform. Finally, the transient distribution of DR response capacity and GU output capacity are derived, and the short-term reliability assessment method for generating systems considering DR reliability is proposed. A case study on a revised IEEE-RTS79 system shows the application of the presented method. The method proposed in this paper can assist system operators to evaluate the reliability of generating systems during the period of DR events. INDEX TERMS Demand response reliability, Markov chain, mean-standard deviation classification, short-term reliability assessment of generating systems, universal generating function.

show abstract

Reliability constrained congestion management with uncertain negawatt demand response firms considering repairable advanced metering infrastructures

Cited by 42 publications

References 21 publications

Maintenance strategy selection in electric power distribution systems

Maintenance strategy selection in electric power distribution systems

Congestion management of power system with uncertain renewable resources and plug‐in electrical vehicle

Short-Term Reliability Assessment of Generating Systems Considering Demand Response Reliability

Contact Info

Product

Resources

About