scholarly journals A spatiotemporal atlas of hydropower in Africa for energy modelling purposes

2021 ◽  
Vol 1 ◽  
pp. 29
Author(s):  
Sebastian Sterl ◽  
Albertine Devillers ◽  
Celray James Chawanda ◽  
Ann van Griensven ◽  
Wim Thiery ◽  
...  

The modelling of electricity systems with substantial shares of renewable resources, such as solar power, wind power and hydropower, requires datasets on renewable resource profiles with high spatiotemporal resolution to be made available to the energy modelling community. Whereas such resources exist for solar power and wind power profiles on diurnal and seasonal scales across all continents, this is not yet the case for hydropower. Here, we present a newly developed open-access African hydropower atlas, containing seasonal hydropower generation profiles for nearly all existing and several hundred future hydropower plants on the African continent. The atlas builds on continental-scale hydrological modelling in combination with detailed technical databases of hydropower plant characteristics and can facilitate modelling of power systems across Africa.

2021 ◽  
Vol 1 ◽  
pp. 29
Author(s):  
Sebastian Sterl ◽  
Albertine Devillers ◽  
Celray James Chawanda ◽  
Ann van Griensven ◽  
Wim Thiery ◽  
...  

The modelling of electricity systems with substantial shares of renewable resources, such as solar power, wind power and hydropower, requires datasets on renewable resource profiles with high spatiotemporal resolution to be made available to the energy modelling community. Whereas such resources exist for solar power and wind power profiles on diurnal and seasonal scales across all continents, this is not yet the case for hydropower. Here, we present a newly developed open-access African hydropower atlas, containing seasonal hydropower generation profiles for nearly all existing and several hundred future hydropower plants on the African continent. The atlas builds on continental-scale hydrological modelling in combination with detailed technical databases of hydropower plant characteristics and can facilitate modelling of power systems across Africa.


2021 ◽  
Vol 9 ◽  
Author(s):  
Johanna Olovsson ◽  
Maria Taljegard ◽  
Michael Von Bonin ◽  
Norman Gerhardt ◽  
Filip Johnsson

This study analyses the impacts of electrification of the transport sector, involving both static charging and electric road systems (ERS), on the Swedish and German electricity systems. The impact on the electricity system of large-scale ERS is investigated by comparing the results from two model packages: 1) a modeling package that consists of an electricity system investment model (ELIN) and electricity system dispatch model (EPOD); and 2) an energy system investment and dispatch model (SCOPE). The same set of scenarios are run for both model packages and the results for ERS are compared. The modeling results show that the additional electricity load arising from large-scale implementation of ERS is mainly, depending on model and scenario, met by investments in wind power in Sweden (40–100%) and in both wind (20–75%) and solar power (40–100%) in Germany. This study also concludes that ERS increase the peak power demand (i.e., the net load) in the electricity system. Therefore, when using ERS, there is a need for additional investments in peak power units and storage technologies to meet this new load. A smart integration of other electricity loads than ERS, such as optimization of static charging at the home location of passenger cars, can facilitate efficient use of renewable electricity also with an electricity system including ERS. A comparison between the results from the different models shows that assumptions and methodological choices dictate which types of investments are made (e.g., wind, solar and thermal power plants) to cover the additional demand for electricity arising from the use of ERS. Nonetheless, both modeling packages yield increases in investments in solar power (Germany) and in wind power (Sweden) in all the scenarios, to cover the new electricity demand for ERS.


2020 ◽  
Vol 1 (2) ◽  
pp. 41-46
Author(s):  
Alhidayatuddiniyah T W ◽  
Siwi Puji Astuti ◽  
Santy Handayani

In this research, a data logger has been created to record the measurement results of current and electric voltage from a solar power system and wind power. This study aims to make a current and voltage measurement data recorder automatically so that the data retrieval process is easier and more accurate. Data loggers have 10bit ADC accuracy and data can be stored in a Micro SD Card. Data recording by a data logger is done every 100 ms for twenty-four hours then the data is plotted. The results of seven days of collecting current and voltage data for solar power plants obtained graphs such as square waves with maximum voltage and current are 33 volts and 537 mA, for wind power systems the maximum voltage and current were 26 volts and 273 mA. The memory used to record for one day is 5.2MB so the data logger is able to measure the current and voltage of the power generation system and record the measurement data for twenty-four hours continuously


2021 ◽  
Author(s):  
Stanislas Merlet ◽  
Magnus Korpås ◽  
Bjørn Thorud

<p>Solar and wind power continue to dominate the renewable energy expansion, jointly accounting for more than 90% of the new capacity installed in 2019. Hydropower, however, still accounts for 47% of the 2,537 GW of global renewable power in operation. Solar power continued to lead the yearly expansion, for the fourth year in a row, with an annual increase of +20% while hydropower capacity increased by +1%. However, the inherent intermittency and stochastic nature of solar PV is a well-known obstacle to the further large-scale integration of the technology in existing power systems. Large-scale reservoir hydropower offers a cost-competitive, mature and dispatchable alternative that can provide both production flexibility and storage. Nonetheless, the costs of large hydropower are highly site-specific and new capacity development has been more and more constrained by substantial environmental and social impacts in many places worldwide. Solar power and hydropower resources have been identified to be quite complementary and hybrid plants could have many flexibility benefits in addition to the increase of renewable energy production. In this context, floating solar PV (FPV) on hydropower reservoirs is emerging as a relevant solution to accommodate both energy sources at the same location.</p><p>Adding FPV to an existing hydropower plant, aiming at hybridizing the output, might impact its reservoir operations and water-related constraints need to be carefully considered. Solar PV can contribute to saving water on mid- to long-term scheduling considering that solar energy generation corresponds in some extent to non-turbined water, i.e. saved energy. Besides, on the short-term time scale, one of the main benefits is that hydropower could, in some extent, compensate for the variability of PV generation by its rapidly adjustable output. In practice, a utility-scale solar PV plant could lose several MW of generation in seconds, if a large cloud passes, for example. To avoid consequences on the power grid, this energy loss would need to be translated almost immediately (according to available capacity and ramp rates capabilities) to hydropower generation, meaning substantial (and potentially more frequent) surges in released water downstream.</p><p>The presentation investigates these opportunities and challenges linked to reservoir operations of hybrid hydropower-connected floating solar PV plants and provide inputs on optimal solutions.</p>


2021 ◽  
Author(s):  
Hannah C. Bloomfield ◽  
David J. Brayshaw ◽  
Paula L. M. Gonzalez ◽  
Andrew Charlton-Perez

Abstract. Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead-times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms and technical barriers frequently prohibit use by non-meteorological specialists. This paper therefore presents data produced through a new EU climate services program Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data corresponds to a suite of well-documented, easy-to-use, self-consistent daily- and nationally-aggregated time-series for wind power, solar power and electricity demand across 28 European countries. The DOI http://dx.doi.org/10.17864/1947.275 will be activated after the paper has been accepted for publication. In the meantime, the data is accessible via https://researchdata.reading.ac.uk/275/, (Gonzalez et al., 2020). The data includes a set of daily ensemble reforecasts from two leading forecast systems spanning 20-years (ECMWF, 1996–2016) and 11-years (NCEP, 1999–2010). The reforecasts containing multiple plausible realisations of daily-weather and power data for up to 6 weeks in the future. To the authors' knowledge, this is the first time fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and the composite property demand-net-renewables is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead-times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy- and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this.


2021 ◽  
Vol 10 (2) ◽  
pp. 104
Author(s):  
Reinhold Lehneis ◽  
David Manske ◽  
Daniela Thrän

Wind power has risen continuously over the last 20 years and covered almost 25% of the total German power provision in 2019. To investigate the effects and challenges of increasing wind power on energy systems, spatiotemporally disaggregated data on the electricity production from wind turbines are often required. The lack of freely accessible feed-in time series from onshore turbines, e.g., due to data protection regulations, makes it necessary to determine the power generation for a certain region and period with the help of numerical simulations using publicly available plant and weather data. For this, a new approach is used for the wind power model which utilizes a sixth-order polynomial for the specific power curve of a turbine. After model validation with measured data from a single wind turbine, the simulations are carried out for an ensemble of 25,835 onshore turbines to determine the German wind power production for 2016. The resulting hourly resolved data are aggregated into a time series with daily resolution and compared with measured feed-in data of entire Germany which show a high degree of agreement. Such electricity generation data from onshore turbines can be applied to optimize and monitor renewable power systems on various spatiotemporal scales.


2021 ◽  
Vol 13 (5) ◽  
pp. 2259-2274
Author(s):  
Hannah C. Bloomfield ◽  
David J. Brayshaw ◽  
Paula L. M. Gonzalez ◽  
Andrew Charlton-Perez

Abstract. Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms, and technical barriers frequently prohibit use by non-meteorological specialists. This paper therefore presents data produced through a new EU climate services programme Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data correspond to a suite of well-documented, easy-to-use, self-consistent daily and nationally aggregated time series for wind power, solar power and electricity demand across 28 European countries. The data are accessible from https://doi.org/10.17864/1947.275 (Gonzalez et al., 2020). The data include a set of daily ensemble reforecasts from two leading forecast systems spanning 20 years (ECMWF, an 11-member ensemble, with twice-weekly starts for 1996–2016, totalling 22 880 forecasts) and 11 years (NCEP, a 12-member lagged-ensemble, constructed to match the start dates from the ECMWF forecast from 1999–2010, totalling 14 976 forecasts). The reforecasts contain multiple plausible realisations of daily weather and power data for up to 6 weeks in the future. To the authors’ knowledge, this is the first time a fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this.


2014 ◽  
Vol 15 ◽  
pp. 37-41 ◽  
Author(s):  
Neeraj Kumar Sah ◽  
Madhab Uprety ◽  
Sangharsha Bhandari ◽  
Prativa Kharel ◽  
Saurav Suman ◽  
...  

An Integrated Power System (IPS) should have electrical energy generating plants for base load (e.g., nuclear and thermal plants) and peak load (e.g., hydropower plants) so that they can work in coordination in such a way that the demand is met in time. In Nepal, the Integrated Nepal Power System (INPS) is a hydro-dominated system where the base and intermediate power demands are covered primarily by run-of-river hydropower plants and the peak demand by seasonal storage and several diesel power plants of lower capacity. The INPS should have sufficient natural storage and forced storage power plants to improve the system’s reliability. On top of that, daily peak electrical demand could also be adequately covered by demand-side management, using a pumped-storage hydropower plant that can employ a system’s surplus energy during low demand period for pumping. To rectify this extreme imbalance of installed capacity in Nepal, this paper explores the prospect of storage and pumped-storage power plants for enhancing INPS. A case study of Rupa-Begnas pumped-storage hydropower is highlighted for these purposes.DOI: http://dx.doi.org/10.3126/hn.v15i0.11290HYDRO Nepal JournalJournal of Water, Energy and EnvironmentVolume: 15, 2014, JulyPage: 37-41 


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