Application of Probabilistic Load-Flow Methods for High Voltage Grid Planning

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Supervisor:
Szabó László
Department of Electric Power Engineering

The power system developement planning is done by the analysis of future network states. The stochastic load-flow calculation is a tool to model uncertainties of load-flow input data. The input and output parameters of the calculation are described with probability and statistic tools. With the analysis of huge amounts of network states, the results give a deeper insight into the behaviour of the network. With the method, uncertainties of future loads and wind generation can be taken into account. Two mathemathical approaches can be used for the calculation, the convolution method and the Monte Carlo simulation, both of which need heavy computing capacity. Both methods need approximations to limit calculation times. The Monte Carlo simulation needs fewer constraints and its accuracy increases with the calculation time. The comparison of the methods showed that the Monte Carlo algorithm gives accurate results with less running time. Another advantage of the method is that the computation can be made parallel more easily. The drawback of the stochastic load-flow calculation is that it analyses the possible outcomes of only one future system state.

To handle the time dependence of nodal injections, more future states have to be modelled. This was achieved with a time-sequence simulation program, which analyses 8760 states of the power system in a future year (one state for every hour). The time-sequence simulation can be expanded with Monte Carlo simulation for each hour to get insight into the expected and possible future states of the system. The increased calculation capacity claim could be handled with multi core processor computers connected in a local area network.

With the time-sequence simulation and its Monte Carlo expansion, future power system problems can be identified, probabilities of their occurences can be calculated, and their dependence from input uncertainties can be determined. These calculations provide more information than conventional deterministic load-flow calculation, supporting the decision-making in network developement planning.

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