• Energy Research

Abstract The development of efficient and sustainable energy solutions and the attempt to reduce carbon dioxide emissions are leading to an increasing penetration of Renewable Energy Sources (RES). Effective Electrical Energy Storage (EES) solutions need therefore to be developed to deal with the issue of fitting locally available RES and loads. Hydrogen can become an interesting option because of its high energy density, long-term storage capability and modularity. In particular, in isolated micro-grid and off-grid remote areas, intermittent RES integrated with H2-based storage systems can allow to lower, or even eliminate, the usage of diesel engines and avoid the need for expensive and invasive grid connections. The present study is part of the European REMOTE project, whose main goal is to prove the added value of H2-based energy storage solutions with respect to alternative technologies in terms of economics, technical and environmental benefits. Four demonstration sites supplied by renewable electricity will be installed in either isolated micro-grids or off-grid remote areas throughout all Europe, from Italy (two sites) and Greece to Norway. The aim of this work is to perform a techno-economic analysis and demonstrate the effectiveness of the hybrid H2-battery Power-To-Power (P2P) solution in reducing the usage of external sources (e.g., diesel engines or grid) in a cost-effective way, with different load and environment conditions. The economic viability of the considered scenarios was outlined by computing the Levelized Cost Of Energy (LCOE). For each of the four sites, the innovative renewable configuration was compared with the current/alternative one. The REMOTE project partners provided main input data for the analysis: techno-economic data from the technology suppliers, whereas electricity consumption and RES production values from the end users of the four isolated locations. LCOE values derived using cost inputs both from REMOTE and literature are presented for a comparison. Results from the energy simulations revealed that the need for an external source is significantly reduced thanks to RES together with the hybrid storage system. Moreover, for all the four sites the renewable solution was shown to be more profitable than the current or alternative one, either in the short term or in the longer term.

Abstract The development of efficient and sustainable energy solutions and the attempt to reduce carbon dioxide emissions are leading to an increasing penetration of Renewable Energy Sources (RES). Effective Electrical Energy Storage (EES) solutions need therefore to be developed to deal with the issue of fitting locally available RES and loads. Hydrogen can become an interesting option because of its high energy density, long-term storage capability and modularity. In particular, in isolated micro-grid and off-grid remote areas, intermittent RES integrated with H2-based storage systems can allow to lower, or even eliminate, the usage of diesel engines and avoid the need for expensive and invasive grid connections. The present study is part of the European REMOTE project, whose main goal is to prove the added value of H2-based energy storage solutions with respect to alternative technologies in terms of economics, technical and environmental benefits. Four demonstration sites supplied by renewable electricity will be installed in either isolated micro-grids or off-grid remote areas throughout all Europe, from Italy (two sites) and Greece to Norway. The aim of this work is to perform a techno-economic analysis and demonstrate the effectiveness of the hybrid H2-battery Power-To-Power (P2P) solution in reducing the usage of external sources (e.g., diesel engines or grid) in a cost-effective way, with different load and environment conditions. The economic viability of the considered scenarios was outlined by computing the Levelized Cost Of Energy (LCOE). For each of the four sites, the innovative renewable configuration was compared with the current/alternative one. The REMOTE project partners provided main input data for the analysis: techno-economic data from the technology suppliers, whereas electricity consumption and RES production values from the end users of the four isolated locations. LCOE values derived using cost inputs both from REMOTE and literature are presented for a comparison. Results from the energy simulations revealed that the need for an external source is significantly reduced thanks to RES together with the hybrid storage system. Moreover, for all the four sites the renewable solution was shown to be more profitable than the current or alternative one, either in the short term or in the longer term.

Abstract We investigate the accuracy of wind and photovoltaic time series in individual systems in Norway. To study the accuracy of the available open data sets, we compare the measured production from individual photovoltaic- and wind power plants to the open time series from Renewables.ninja and EMHIRES. Additionally, we try to adjust the wind speed based on the average wind speed from Global Wind Atlas 3.0 and Norwegian water resources and energy directorate's Wind Map to try to achieve more accurate wind speed time series that take into account the local wind conditions, since they are not well represented in the large resolution of the MERRA-2 data set used by Renewables.ninja. The results for photovoltaic production time series are promising, the correlation between production obtained from Renewables.ninja and measured production is above 0.72 and maximum capacity factor difference of 2.5%. For the case of wind production, production time series show considerable deviations depending on the specific wind farm (correlation between 0.51 and 0.91 depending on the case and year). Additionally, the adjustments only improve the time series in some of the wind farms, whereas in others the results are even less accurate than the Renewables.ninja time series compared to the measured data.

Abstract We investigate the accuracy of wind and photovoltaic time series in individual systems in Norway. To study the accuracy of the available open data sets, we compare the measured production from individual photovoltaic- and wind power plants to the open time series from Renewables.ninja and EMHIRES. Additionally, we try to adjust the wind speed based on the average wind speed from Global Wind Atlas 3.0 and Norwegian water resources and energy directorate's Wind Map to try to achieve more accurate wind speed time series that take into account the local wind conditions, since they are not well represented in the large resolution of the MERRA-2 data set used by Renewables.ninja. The results for photovoltaic production time series are promising, the correlation between production obtained from Renewables.ninja and measured production is above 0.72 and maximum capacity factor difference of 2.5%. For the case of wind production, production time series show considerable deviations depending on the specific wind farm (correlation between 0.51 and 0.91 depending on the case and year). Additionally, the adjustments only improve the time series in some of the wind farms, whereas in others the results are even less accurate than the Renewables.ninja time series compared to the measured data.

Abstract Variable electricity generation from wind and solar influences the design of a cost-efficient and reliable energy system. This paper presents a method that uses stochastic programming to represent variable renewable electricity generation in long-term energy system models, and demonstrates this on a Norwegian TIMES model. First, we derive hourly PV- and wind-generation data by modifying satellite-based data, based on a comparison with historical generation data. Second, the satellite-based dataset is transformed into a manageable set of scenarios that is used as an input to the stochastic energy-system model. This is done using six different scenario generation methods. Third, we solve the energy-system model with three of the scenario-generation methods and evaluate the quality of the corresponding model value by stability tests. We demonstrate that scenarios generated from the six methods have significantly different moment-based and Wasserstein distance error relative to the dataset. Further, the energy system model results show that the number of scenarios needed to achieve stability differs between the three used scenario generation methods.

Abstract Variable electricity generation from wind and solar influences the design of a cost-efficient and reliable energy system. This paper presents a method that uses stochastic programming to represent variable renewable electricity generation in long-term energy system models, and demonstrates this on a Norwegian TIMES model. First, we derive hourly PV- and wind-generation data by modifying satellite-based data, based on a comparison with historical generation data. Second, the satellite-based dataset is transformed into a manageable set of scenarios that is used as an input to the stochastic energy-system model. This is done using six different scenario generation methods. Third, we solve the energy-system model with three of the scenario-generation methods and evaluate the quality of the corresponding model value by stability tests. We demonstrate that scenarios generated from the six methods have significantly different moment-based and Wasserstein distance error relative to the dataset. Further, the energy system model results show that the number of scenarios needed to achieve stability differs between the three used scenario generation methods.