Transmission Congestion Management Considering Uncertainty of Demand Response Resources’ Participation

Tabandeh, A.; Abdollahi, A.; Rashidinejad, M.

doi:10.22061/jecei.2016.400

Document Type : Original Research Paper

Authors

Department of Electrical Engineering, Shahid Bahonar University, Kerman, Iran

https://doi.org/10.22061/jecei.2016.400

Abstract

Under the smart grid environment, demand response resources (DRRs) are introduced as a virtual power plant to enhance power system adequacy. DRRs often fail to reduce their load due to some external factors. In this paper, a reliability model of a DRR is constructed as multi-state conventional generation units, where the probability, frequency of occurrence, and departure rate of each state can be acquired. DRRs as consequence of demand response program implementation can be applied to transmission congestion management. Therefore, this paper presents an optimal model of congestion management (CM) by means of multi-state DRRs, namely CM_DRR. In the proposed approach, in addition to DRRs, independent system operator relieves the existing transmission line congestions using the combination of generating unit rescheduling and involuntary load shedding. The hourly historical data associated with the Connecticut region in New England is employed to achieve the DRRs’ participation regime. Moreover, the impact of different capacities of DRRs on the congestion management cost and load shedding cost is evaluated. Results of applying the aforementioned model to the 24-bus Reliability Test System (RTS) indicate the efficiency of CM_DRR framework.

Keywords

20.1001.1.23223952.2015.3.2.2.8

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Journal of Electrical and Computer Engineering Innovations (JECEI)

Transmission Congestion Management Considering Uncertainty of Demand Response Resources’ Participation

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Volume 3, Issue 2 - Serial Number 6
July 2015
Pages 77-88

Transmission Congestion Management Considering Uncertainty of Demand Response Resources’ Participation

References

References

Send comment about this article

Volume 3, Issue 2 - Serial Number 6July 2015Pages 77-88

Volume 3, Issue 2 - Serial Number 6
July 2015
Pages 77-88