a b s t r a c tLarge amounts of new wind power are currently under construction or planning in many countries. The constantly increasing percentage of wind power in the electricity generation mix has to be taken into consideration when planning power systems. This paper introduces a Monte Carlo simulation based methodology that can be used to assess the effects (e.g. need for new transmission lines, reserves, wind curtailment or demand side management) of large amounts of existing and planned wind power generation on the power system. The presented methodology is able to assess new wind power scenarios spread over a wide geographical area, comprising numerous existing and planned wind generation locations. The Monte Carlo simulation results are verified against measured aggregated wind power generation in Finland from 2008 to 2014. In addition, case studies of future scenarios with 232 individual wind generation locations are presented to show the applicability of the methodology as a tool in power system planning.
As installed wind generation capacity increases, understanding the effect of wind power on the electric power system is becoming more important. This paper introduces a statistical model that can be used to estimate the variability in wind generation and assess the risk of wind generation contingencies over a large geographical area. The analysis of the installed wind generation capacities is separated from the analysis of the spatial and temporal dependency structures. This enables the study of different future wind power scenarios with varying generation capacities. The model is built on measured hourly wind generation data from Denmark, Estonia, Finland and Sweden. Three scenarios with different geographical distributions of wind power are compared to show the applicability of the model for power system planning. A method for finding the scenario with the minimum variance of the aggregate wind generation is introduced. As the geographical distribution of wind power can be affected by subsidies and other incentives, the presented results can have policy implications.
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