New Methodology for the Optimization of the Management of Wind Farms, Including Energy Storage

Rodolfo Dufo-López; José Luis Bernal-Agustín; Cláudio Monteiro

doi:10.4028/www.scientific.net/AMM.330.183

Paper Titles

Analysis of Electric Energy Consumption Patterns: A Case Study of a Real Life Office Building
p.158

The Construction and Development of Comprehensive Test Centre Based on Real Transmission Line
p.163

Suggestions on Renewable Portfolio Standard for Wind Power in China
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Design of a Short-Term Load Forecasting System for Small Hydropower in the Context of Electricity Market
p.178

New Methodology for the Optimization of the Management of Wind Farms, Including Energy Storage
p.183

A New Energy Concept to Minimize Electricity Consumption in Industry or Buildings
p.188

Introducing Off-Grid Renewable Energy Systems for Irrigation in Mediterranean Crops
p.198

Numerical Studies on the Performance of a Bubble Pump
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Increasing Efficiency of Overshot Waterwheel with Overflow Keeper Double Nozzle (OKDN) by Using Hydraulic Ram System
p.209

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 330New Methodology for the Optimization of the...

New Methodology for the Optimization of the Management of Wind Farms, Including Energy Storage

Abstract:

Storing energy on wind farms could improve the power generation curve, avoiding the problems associated with abrupt variations and the random nature of wind power. New batteries such as flow batteries or NaS batteries are suitable to be used in storing energy on wind farms in intervals of some hours. A new methodology for the optimization of the management of wind farms, including energy storage, is shown. The objective is to maximize the benefits of selling electricity to the grid within 24 hours. The genetic algorithm technique was used for the optimization.

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Periodical:

Applied Mechanics and Materials (Volume 330)

Pages:

183-187

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.330.183

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Online since:

June 2013

Authors:

Rodolfo Dufo-López, José Luis Bernal-Agustín, Cláudio Monteiro

Keywords:

Batteries, Genetic Algorithm (GA), Management, Optimization, Wind Power

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References

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