scholarly journals Modeling of the German Wind Power Production with High Spatiotemporal Resolution

2021 ◽  
Vol 10 (2) ◽  
pp. 104
Author(s):  
Reinhold Lehneis ◽  
David Manske ◽  
Daniela Thrän
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Wind Power ◽  
Power Production ◽  
Electricity Production ◽  
Weather Data ◽  
Specific Power ◽  
Spatiotemporal Resolution ◽  
Renewable Power ◽  
High Degree

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.

scholarly journals Generation of Spatiotemporally Resolved Power Production Data of PV Systems in Germany

2020 ◽  
Vol 9 (11) ◽  
pp. 621
Author(s):  
Reinhold Lehneis ◽  
David Manske ◽  
Daniela Thrän
Keyword(s):  
Time Series ◽  
Numerical Simulations ◽  
Power Production ◽  
Geographical Information ◽  
Weather Data ◽  
Production Data ◽  
Pv Systems ◽  
Spatiotemporal Scales ◽  
High Degree ◽  
Cover Up

Photovoltaics, as one of the most important renewable energies in Germany, have increased significantly in recent years and cover up to 50% of the German power provision on sunny days. To investigate the manifold effects of increasing renewables, spatiotemporally disaggregated data on the power generation from photovoltaic (PV) systems are often mandatory. Due to strict data protection regulations, such information is not freely available for Germany. To close this gap, numerical simulations using publicly accessible plant and weather data can be applied to determine the required spatiotemporal electricity generation. For this, the sunlight-to-power conversion is modeled with the help of the open-access web tool of the Photovoltaic Geographical Information System (PVGIS). The presented simulations are carried out for the year 2016 and consider nearly 1.612 million PV systems in Germany, which have been aggregated into municipal areas before performing the calculations. The resulting hourly resolved time series of the entire plant ensemble are converted into a time series with daily resolution and compared with measured feed-in data to validate the numerical simulations that show a high degree of agreement. Such power production data can be used to monitor and optimize renewable energy systems on different spatiotemporal scales.

Modeling of the power generation from wind turbines with high spatial and temporal resolution

2020 ◽  
Author(s):  
Reinhold Lehneis ◽  
David Manske ◽  
Björn Schinkel ◽  
Daniela Thrän
Keyword(s):  
Numerical Simulation ◽  
Power Generation ◽  
Time Series ◽  
Wind Turbine ◽  
Wind Power ◽  
Temporal Resolution ◽  
Wind Turbines ◽  
Weather Data ◽  
Specific Power ◽  
High Temporal Resolution

<p>The share of wind power in the generation of electricity has increased significantly in recent years and, despite its volatility, variable energy from wind turbines has become an essential pillar for the power supply in many countries around the world. To investigate the effects of increasing variable renewables on power grids, the environment or electricity markets, detailed power generation data from wind turbines with high spatial and temporal resolution are often mandatory. The lack of freely accessible feed-in time series, for example due to data protection regulations, makes it necessary to determine the wind power feed-in for a required region and period with the help of numerical simulations. Our contribution demonstrates how such a numerical simulation can be developed using publicly available wind turbine and weather data. Herein, a novel model approach will be presented for the wind-to-power conversion, which utilizes a sixth-order polynomial for the specific power curve of a wind turbine. After such an analytical representation is derived for a certain turbine, its output power can be easily calculated using the wind speed and air temperature at its hub height. For proof of concept and model validation, measured feed-in time-series of a geographically and technically known wind turbine are compared with the simulated time-series at a high temporal resolution of 10 minutes. In order to determine the power generation for larger regions or an entire country the derived numerical simulation is also carried out for an ensemble of almost 26 thousand onshore wind turbines in Germany with a total capacity of about 44 GW. With this ensemble, first simulation results with municipal and hourly resolution can be presented for an annual period.</p>

scholarly journals Total variation as a metric for complementarity in energy resources time series

2021 ◽  
Author(s):  
Diana Cantor ◽  
Andrés Ochoa ◽  
Oscar Mesa
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Total Variation ◽  
Correlation Coefficients ◽  
Mathematical Concept ◽  
Large Power ◽  
Electric System ◽  
Geographical Scale ◽  
Auto Regressive ◽  
High Degree

Complementarity has become an essential concept in energy supply systems. Although there are some other metrics, most studies use correlation coefficients to quantify complementarity. The standard interpretation is that a high negative correlation indicates a high degree of complementarity. However, we show that the correlation is not an entirely satisfactory measure of complementarity. As an alternative, we propose a new index based on the mathematical concept of the total variation. For two time series, the new index φ is one minus the ratio of the total variation of the sum to the sum of the two series' total variation. We apply the index first to an auto-regressive (AR) process and then to various Colombian electric system series. The AR case clearly illustrates the limitations of the correlation coefficient as a measure of complementarity. We then evaluate complementarity across various space-time scales in the Colombian power sectors, considering hydro and wind projects. The complementarity assessment on a broad temporal and geographical scale helps analyze large power systems with different energy sources. The case study of the Colombian hydropower systems suggests that φ is better than ρ because (i) it considers scale, whereas ρ, being non-dimensional, is insensitive to the scale and even to the physical dimensions of the variables; (ii) one can apply φ to more than two resources; and (iii) ρ tends to overestimate complementarity.

scholarly journals Model and Analysis of Integrating Wind and PV Power in Remote and Core Areas with Small Hydropower and Pumped Hydropower Storage

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3459 ◽  
Author(s):  
Xianxun Wang ◽  
Lihua Chen ◽  
Qijuan Chen ◽  
Yadong Mei ◽  
Hao Wang
Keyword(s):  
Power Systems ◽  
Power System ◽  
Thermal Power ◽  
Power Production ◽  
Total Power ◽  
Energy Integration ◽  
Small Hydropower ◽  
Peak Period ◽  
Renewable Power ◽  
Core Areas

Small hydropower (SHP) and pumped hydropower storage (PHS) are ideal members of power systems with regard to integrating intermittent power production from wind and PV facilities in modern power systems using the high penetration of renewable energy. Due to the limited capacity of SHP and the geographic restrictions of PHS, these power sources have not been adequately utilized in multi-energy integration. On the one hand, rapidly increasing wind/PV power is mostly situated in remote areas (i.e., mountain and rural areas) and is delivered to core areas (i.e., manufacturing bases and cities) for environmental protection and economic profit. On the other hand, SHP is commonly dispersed in remote areas and PHS is usually located in core areas. This paper proposes a strategy to take advantage of the distribution and regulation features of these renewable energy sources by presenting two models, which includes a remote power system model to explore the potential of SHP to smooth the short-term fluctuations in wind and PV power by minimizing output fluctuations as well as a core power system model to employ PHS to shift the surplus power to the peak period by maximizing the income from selling regenerated power and minimizing output fluctuations. In the proposed first model, the cooperative regulation not only dispatches SHP with a reciprocal output shape to the wind/PV output to smooth the fluctuations but also operates the reservoir with the scheduled total power production by adjusting its output in parallel. The results of a case study based on a municipal power system in Southwestern China show that, with the proposed method, SHP can successfully smooth the short-term fluctuations in wind and PV power without influencing the daily total power production. Additionally, SHP can replace the thermal power production with renewable power production, smooth the thermal output, and further reduce the operation costs of thermal power. By storing the surplus power in the upper reservoir and regenerating the power during the peak period, PHS can obtain not only the economic benefit of selling the power at high prices but also the environmental benefit of replacing non-renewable power with renewable power. This study provides a feasible approach to explore the potential of SHP and PHS in multi-energy integration applications.

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 ◽  
...  
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Solar Power ◽  
Renewable Resource ◽  
Hydropower Plant ◽  
Spatiotemporal Resolution ◽  
Continental Scale ◽  
Hydropower Plants ◽  
Energy Modelling ◽  
Electricity Systems

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.

scholarly journals The impact of climatic extreme events on the feasibility of fully renewable power systems: a case study for Sweden

2018 ◽  
Author(s):  
Stefan Höltinger ◽  
Johann Baumgartner ◽  
Christian Mikovits ◽  
Johannes Schmidt ◽  
Berit Arheimer ◽  
...  
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Wind Power ◽  
Extreme Events ◽  
Power Plants ◽  
Thermal Power ◽  
Physical Models ◽  
Cold Weather ◽  
Pv Generation ◽  
The Impact

Future energy systems with high shares of intermittent renewables will be stressed by climatic extreme events. We assess the frequency, duration, and magnitude of such extreme residual load events with a share of VRE generation of about 50% for the case of Sweden. For our analysis, we use 29 years of river runoff and of wind power and PV generation simulated from physical models. Hourly load is simulated from temperature data with a time series model. The resulting time series are combined with historic capacity and ramping restrictions of hydro and thermal power plants in an optimization model to minimize extreme residual load events. Results indicate that under high VRE shares climatic extreme events affect even highly flexible power systems as the Swedish one. Replacing current nuclear power capacities by wind power results on average in three extreme residual load events per year. These events are partly linked to the observation that wind speeds are likely below seasonal average in very cold weather conditions. Deploying PV generation capacities instead of wind increases the number of extreme residual load events by about 6 %, as most events occur during the winter month when solar generation is close to zero.

scholarly journals Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5377
Author(s):  
Abdullah Al-Shereiqi ◽  
Amer Al-Hinai ◽  
Mohammed Albadi ◽  
Rashid Al-Abri
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Wind Power ◽  
Iterative Algorithm ◽  
Wind Farm ◽  
Energy Resources ◽  
Weather Data ◽  
Optimal Size ◽  
Renewable Energy Resources ◽  
The Impact

Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the available renewable energy resources as a fuel-saver simply to reduce fossil-fuel consumption. This is related mainly to the inherently variable and non-dispatchable nature of renewable energy resources, which poses a threat to power system reliability and requires utilities to maintain power-balancing reserves to match the supply from renewable energy resources with the real-time demand levels. Thus, further efforts are needed to mitigate the risk that comes with integrating renewable resources into the electricity grid. Hence, an integrated strategy is being created to determine the optimal size of the hybrid wind-solar photovoltaic power systems (HWSPS) using heuristic optimization with a numerical iterative algorithm such that the output fluctuation is minimized. The research focuses on sizing the HWSPS to reduce the impact of renewable energy resource intermittency and generate the maximum output power to the grid at a constant level periodically based on the availability of the renewable energy resources. The process of determining HWSPS capacity is divided into two major steps. A genetic algorithm is used in the initial stage to identify the optimum wind farm. A numerical iterative algorithm is used in the second stage to determine the optimal combination of photovoltaic plant and battery sizes in the search space, based on the reference wind power generated by the moving average, Savitzky–Golay, Gaussian and locally weighted linear regression techniques. The proposed approach has been tested on an existing wind power project site in the southern part of the Sultanate of Oman using a real weather data. The considered land area dimensions are 2 × 2 km. The integrated tool resulted in 39 MW of wind farm, 5.305 MW of PV system, and 0.5219 MWh of BESS. Accordingly, the estimated cost of energy based on the HWSPS is 0.0165 EUR/kWh.

scholarly journals An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4372 ◽  
Author(s):  
Lingling Bin ◽  
Haiyang Pan ◽  
Li He ◽  
Jijian Lian
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Wind Power ◽  
Wind Power Generation ◽  
Evaluation Framework ◽  
Electricity Production ◽  
Component Importance ◽  
Importance Analysis ◽  
Wind Power Systems ◽  
Power Generation Systems

Wind power systems have great potential due to its inexhaustible nature and benign environmental impacts. Especially in remote areas, where wind is plentiful, but it is difficult to get grid-connected power, an off-grid wind power system is an effective alternative for power supply. Reliable and safe operation of the generating system are essential for electricity production and supply. Importance analysis to identify key components of the system is a critical part of reliability assessment. This paper proposes an importance analysis–based weight evaluation framework for identifying key components of multi-configuration off-grid wind power generation systems under stochastic inputs. In the framework, the joint importance analysis based on Birnbaum importance and Criticality importance are introduced to analyze the system reliability and failure rate. Wind speed with stochastic characteristics, load demand with multiple scenarios, and energy transfer with different paths are also merged into the evaluation framework. The results reveal that the rectifier, battery, discharge load, and valve controller dominate the reliability of the off-grid wind power generation system. High priority should be placed on these components during the design phase and maintenance stage. The proposed approach is a positive step forward in promoting component importance analysis and providing more theoretical supports in system design, reliability analysis, and monitoring scheme formulation.

scholarly journals Modeling of Ethiopian Wind Power Production Using ERA5 Reanalysis Data

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2573
Author(s):  
Kena Likassa Nefabas ◽  
Lennart Söder ◽  
Mengesha Mamo ◽  
Jon Olauson
Keyword(s):  
Wind Power ◽  
Grid Point ◽  
Wind Farms ◽  
Absolute Error ◽  
Power Production ◽  
Realistic Model ◽  
Reanalysis Data ◽  
Specific Power ◽  
Energy Potential ◽  
Performance Error

Ethiopia has huge wind energy potential. In order to be able to simulate the power system operation, hourly time series of wind power is needed. These can be obtained from ERA5 data but first a realistic model is needed. Therefore, in this paper ERA5 reanalysis data were used to model wind power production at two topographically different and distant regions of Ethiopian wind farms—Adama II and Ashegoda. Wind speed was extracted from the ERA5 nearest grid point, bi-linearly interpolated to farms location and statistically down-scaled to increase its resolution at the site. Finally, the speed is extrapolated to hub-height of turbine and converted to power through farm specific power curve to compare with actual data for validation. The results from the model and historical data of wind farms are compared using performance error metrics like hourly mean absolute error (MAE) and hourly root mean square error (RMSE). When comparing with data from Ethiopian Electric Power (EEP), we found hourly MAE and RMSE of 2.5% and 4.54% for Adama II and 2.32% and 5.29% for Ashegoda wind farms respectively, demonstrating a good correlation between the measured and our simulation model result. Thus, this model can be extended to other parts of the country to forecast future wind power production, as well as to indicate simulation of wind power production potential for planning and policy applications using ERA5 reanalysis data. To the best of our knowledge, such modeling of wind power production using reanalysis data has not yet been tried and no researcher has validated generation output against measurement in the country.

scholarly journals Influence of wind power production on electricity market price

2020 ◽  
Vol 24 (1) ◽  
pp. 472-482
Author(s):  
Gunars Valdmanis ◽  
Gatis Bazbauers
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
System Analysis ◽  
Market Price ◽  
Power Market ◽  
Power Production ◽  
Energy System ◽  
Market Prices ◽  
Renewable Power ◽  
The Baltic

AbstractThe study looks for a correlation between the share of wind power and electricity wholesale prices in the selected regions of the Nordic Baltic power market “Nord Pool Spot”. The aim is to see if and how strong an impact of wind power production has on power market prices. This information would help to perform long-term energy system analysis considering growing wind energy penetration. The actual hourly wind production and power consumption data as well as electricity prices from the year 2019 were used in the analysis. Results of the study revealed that in the analysed dataset there is no correlation between the share of wind power and the power prices, i.e. R-squared value is 0.003 for the Baltic region and 0.0064 for both trading areas of Denmark. In contrast, the R-squared value was almost 0.6 for a positive correlation between power demand and prices. The results mean that expected loss of interest to invest due to falling power prices, as a share of renewable power increases, should be examined more carefully and may not fulfil forecasts of policy makers and industry experts.

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