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Reactive power pricing using cloud service considering wind energy

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Abstract

This paper proposes a transparent and reliable method between the suppliers and consumers for optimal reactive power pricing. The electric power suppliers compute the optimal reactive power using optimal reactive power dispatch problem by considering nodal voltage stability index ‘I’ as one of the constraints. The computed optimal reactive power of the generator is included in the reactive power pricing. The pricing method to the suppliers based on the opportunity cost method is presented and a detailed analysis using 62 bus Indian utility system has been carried out by considering diverse cases. In this proposed pricing method, the services of the cloud technology have been used to provide transparent pricing based on the demands of the consumers. The power demands at the consumers’ site is calculated without the human involvement using the Internet of Things and the same is uploaded in the cloud. In reactive power pricing, the system operator acts as a mediator between the suppliers and consumers. Based on the demand and availability of power, the system operator provides the cost for the service to the consumer through cloud.

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Correspondence to D. Danalakshmi.

Appendices

Appendices

Synchronous generator The generator reactive power output is limited by its MVA rating. In order to generate the reactive power, a generator has to sacrifice the cost associated with the real power sale [23]. The capability curve of synchronous generator is referred from [23].

This is called the opportunity cost. The operating region of the synchronous generator is defined using the capability curve.\( Q_{base }\)is the amount of the reactive power essential for the generator to maintain its technical requirements.

Regions The generator reactive power output operates in three regions. They are:

  • Over excitation (above \(Q_{base})\) region.

  • Under excitation region.

  • Lost opportunity cost region.

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Danalakshmi, D., Kannan, S. & Thiruppathy Kesavan, V. Reactive power pricing using cloud service considering wind energy. Cluster Comput 21, 767–777 (2018). https://doi.org/10.1007/s10586-017-0896-2

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  • DOI: https://doi.org/10.1007/s10586-017-0896-2

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