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Optimal parameter setting of performance based regulation with reward and penalty

Authors: Nuo Xu; Minxing Huang; Fushuan Wen; Zhaoyang Dong;

Optimal parameter setting of performance based regulation with reward and penalty

Abstract

The employment of performance based regulation (PBR) in distribution systems could provide some incentive for improving operating efficiency and reducing electricity prices. However, if the PBR mechanism is not properly designed, the enforcement of the PBR may have a negative effect on the supply reliability. In this paper, a mathematical model for optimally setting the parameters of the PBR with a reward/penalty structure is presented, with the minimization of the costs associated with the enforcement of the PBR as the objective and the required reliability level for the distribution system operation as the constraint. Finally, the well-known genetic algorithm is employed for solving the optimization problem. The effectiveness of the approach is demonstrated on a sample example.

Related Organizations
Keywords

E1, 660301 Electricity transmission, 290901 Electrical Engineering, Electricity market, Performance based regulation, Reward/Penalty mechanism, Distribution company, Reliability

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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