"11865" . . "RIV/00216275:25530/14:39898700" . "I, P(EE2.3.30.0058)" . "Heckenbergerov\u00E1, Jana" . "Musilek, Petr" . . "Proceedings of the 2014 15th International Scientific Conference on Electric Power Engineering, EPE 2014" . . . "As the penetration of wind power into generation mix increases, the issue of its integration into the power grid becomes more and more important. The variability of wind power generation is a major concern as wind is highly intermittent. This may result in significant overproduction at times, followed by complete unavailability of wind power at other periods. This intermittency must be compensated for by other, conventional generation sources such as coal and gas fired power plants. This reduces the overall efficiency of the system due to the need of running some generators as spinning reserves, and lowers the overall contribution of renewable generation to the mitigation of greenhouse gas emissions. This paper examines the possibility to optimize the spatial distribution of wind power plants over an extended area to decrease the overall variability of wind power generation in a system. In particular, it considers the integration of spatially distributed wind power generation in the wind-rich province of Alberta, Canada. The distribution of power plants is optimized using simulated annealing and quadratic programming. The results clearly show that the variability of wind power generation can be reduced if the wind resources are integrated over a wide geographic area."@en . . "1"^^ . "New York" . "RIV/00216275:25530/14:39898700!RIV15-MSM-25530___" . "978-1-4799-3806-3" . "As the penetration of wind power into generation mix increases, the issue of its integration into the power grid becomes more and more important. The variability of wind power generation is a major concern as wind is highly intermittent. This may result in significant overproduction at times, followed by complete unavailability of wind power at other periods. This intermittency must be compensated for by other, conventional generation sources such as coal and gas fired power plants. This reduces the overall efficiency of the system due to the need of running some generators as spinning reserves, and lowers the overall contribution of renewable generation to the mitigation of greenhouse gas emissions. This paper examines the possibility to optimize the spatial distribution of wind power plants over an extended area to decrease the overall variability of wind power generation in a system. In particular, it considers the integration of spatially distributed wind power generation in the wind-rich province of Alberta, Canada. The distribution of power plants is optimized using simulated annealing and quadratic programming. The results clearly show that the variability of wind power generation can be reduced if the wind resources are integrated over a wide geographic area." . "Distribution of wind power plants to reduce variability of renewable generation"@en . "3"^^ . "2014-05-12+02:00"^^ . "Debnath, Dhrupad" . "[75B1CCE8C558]" . . . . . . . . . . . "IEEE (Institute of Electrical and Electronics Engineers)" . "Distribution of wind power plants to reduce variability of renewable generation" . "Spatial distribution; Simulated annealing; Quadratic programming; Power plants; Greenhouse gases; Electrical engineering; Electric power generation"@en . "Distribution of wind power plants to reduce variability of renewable generation"@en . . . "Brno" . . . "Distribution of wind power plants to reduce variability of renewable generation" . "6"^^ . . "25530" . .