Analysis of future power grid loading considering uncertainties for application of risk based grid planning

• Applicant: Professor Dr.-Ing. Christian Rehtanz
• Subject Area: Electrical Energy Systems, Power Management, Power Electronics, Electrical Machines and Drives
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 394516645

The integration of renewable energy plants, the simultaneous dismantling of conventional power plants, the new loads because of sector coupling and the liberalization of energy markets lead to great uncertainties in the future generation of electrical energy and thus also in the load of energy grids. Due to long planning horizons for power lines and cables, investments for grid expansion must be made under existing uncertain future developments.Within the scope of the project, the institute of energy systems, energy efficiency and energy economics from Prof. Christian Rehtanz (ie³) and the research group energy systems (GISE) at the University of Asuncion from Prof. Gerardo Blanco will jointly develop a mathematical and technical overall model that can be used to plan the transmission grid under uncertainties. This enables the determination of future grid loads, taking into account real uncertainties, and the deduction of optimal investment decisions from these. Therefore, the uncertainties must be analyzed and modeled stochastically in a first step. The uncertainties resulting from the localization of the power generation (uncertainties of stage one) are represented using the scenario technique for different time steps. The uncertainties of the second stage, which result after the determination of the localization of the power generation, e.g. through weather uncertainties, are represented by multivariate distribution functions. For this purpose, the copula is used, a function which can determine the relationship between the marginal probability distribution of individual variables. Subsequently, an overall model is derived, which assigns multivariate distribution functions to each scenario of the first stage, so that the input variables for each grid node are modeled by probability density functions (PDF) and their correlations. The results are the input values for the probabilistic load flow calculations which determine the PDF of the line load. For this purpose, the approaches of the point-estimate method are developed further to enable the usage of the method for real grids. The developed method will be verified by Monte-Carlo-simulations. In order to plan the energy grid, a method is then required which makes optimal investment decisions under uncertainties based on the expected line loads. For this purpose, the results of the grid analysis are evaluated first and are concentrated afterwards. Subsequently, a cost function is deducted, which is used as the basis for the application of real option analysis. The approach of path integrals is used for this purpose.This procedure represents a completely new approach compared to the state of the art, where the uncertainties are hardly taken into account and the methods of probabilistic load flow calculations work only on small test grids. Also the coupling of the probabilistic load flow calculations with real option analysis has not taken place, yet, and offers a lot of new possibilities.

• DFG Programme: Research Grants
• International Connection: Paraguay
• International Co-Applicant: Professor Dr.-Ing. Gerardo Blanco