Electricity markets; Electricity Grids; Renewable energy potential; "Secure" RES Integration
Buffat René, Raubal Martin (2019), Spatio-temporal potential of a biogenic micro CHP swarm in Switzerland, in
Renewable and Sustainable Energy Reviews, 103, 443-454.
Garrison Jared B., Demiray Turhan, Abrell Jan, Savelsberg Jonas, Weigt Hannes, Schaffner Christian (2018), Combining Investment, Dispatch, and Security Models - An Assessment of Future Electricity Market Options for Switzerland, in
2018 15th International Conference on the European Energy Market (EEM), LodzIEEE, USA.
Buffat René, Grassi Stefano, Raubal Martin (2018), A scalable method for estimating rooftop solar irradiation potential over large regions, in
Applied Energy, 216, 389-401.
Veronesi Fabio, Schito Joram, Grassi Stefano, Raubal Martin (2017), Automatic selection of weights for GIS-based multicriteria decision analysis: site selection of transmission towers as a case study, in
Applied Geography, 83, 78-85.
Veronesi F, Grassi S (2016), Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning, in
Journal of Physics: Conference Series, 749, 012001-012001.
Buffat René (2016), Feature-Aware Surface Interpolation of Rooftops Using Low-Density Lidar Data for Photovoltaic Applications, Springer International Publishing, Cham, 337-350.
Veronesi F., Grassi S., Raubal M. (2016), Statistical learning approach for wind resource assessment, in
Renewable and Sustainable Energy Reviews, 56, 836-850.
Eser Patrick, Singh Antriksh, Chokani Ndaona, Abhari Reza S. (2016), Effect of increased renewables generation on operation of thermal power plants, in
Applied Energy, 164, 723-732.
KorfiatiAthina, GkonosCharalampos, VeronesiFabio, GakiAriadni, GrassiStefano, SchenkelRoland, VolkweinStephan, RaubalMartin, HurniLorenz (2016), Estimation of the Global Solar Energy Potential and Photovoltaic Cost with the use of Open Data, in
International Journal of Sustainable Energy Planning and Management, 9, 17-30.
Veronesi Fabio, Grassi Stefano (2015), Comparison of hourly and daily wind speed observations for the computation of Weibull parameters and power output, in
2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), Marrakech, MoroccoIEEE, USA.
Buffat Rene, Grassi Stefano (2015), Validation of CM SAF SARAH solar radiation datasets for Switzerland, in
2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), MarrakechIEEE, USA.
Marseglia G.R., Arbasini A., Grassi S., Raubal M., Raimondo D.M. (2015), Optimal placement of wind turbines on a continuous domain: An MILP-based approach, in
2015 American Control Conference (ACC), Chicago, IL, USAIEEE, USA.
The key issues addressed in the umbrella project "Assessing Future Electricity Markets" (AFEM) require a preliminary quantification of the exploitable potential of stochastic renewable energy (RE) sources and a feasibility analysis of their grid integration. Indeed, existing power systems are designed to accommodate significant variability in the form of changes in load or the loss of generation (either planned or unplanned). However, as stochastically varying renewable power generation increases to higher levels, the additional variability can jeopardize system operation. To account for the added variability, the utility operators must have a increased amount of generation available to cover either a surplus- or a lack of RE production. This flexible generation is referred to as reserve energy. In order to balance generation with load on a minute-by-minute, hourly, or daily basis, the variability of both the generation and the load must be examined, and different types of reserve energy are required, depending on the considered timescale and required amount. While traditional measures such as loss-of-load probability (LOLP) and loss-of-load expectation (LOLE) are used to identify system reliability concerns, reserve requirements represent a key signal concerning power system operating measures and requirements, and more in general the overall system security (e.g. voltage violations and overloads) is also affected by the increased presence of volatile energy sources. As a first step then it is required to assess how much potential there is for renewable energy sources in the Swiss electricity system and where they would be precisely located, which requires a detailed geophysical and geographic modelling and analysis of Switzerland inclusive of climatic and seasonal conditions. Furthermore, possible network expansions will also affect power flow in the grid, but their planning, approval and construction process is considerably onerous, time-consuming and often subject to a certain degree of decisional uncertainty, so that the likelihood that individually planned expansions may be effectively integrated into the grid (and within which timeframe) will have to be assessed. This information can then be employed in a final stage where the impact of renewable energy (RE) sources on system operation (featuring the updated topology) in terms of load supply, reserve requirements and network security will be investigated and numerically established.