A regional optimisation of renewable energy supply from wind and photovoltaics with respect to three key energy-political objectives

Killinger, Sven; Mainzer, Kai; McKenna, Russell; Kreifels, Niklas; Fïchtner, Wolf

doi:10.1016/j.energy.2015.03.050

Cited by 36 publications

(16 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the developed dataset will be of use for researchers and policy makers who are concerned with the optimized spatial planning of the allocation and expansion of renewable power supply in accordance with the energy policy target triangle comprising security of supply, cost effectiveness, and environmental soundness. Although a number of studies have addressed the spatial resolution of the corresponding energy system models on the level of countries or even world regions [23][24][25][26], more detailed models are relatively scarce [27][28][29] because the required comprehensive and validated datasets are usually not publicly available. The presented data were created at a high resolution and can facilitate the modeling of an efficient spatial connection between renewable energy supply and power demand by providing reliable information on the spatial patterns of already existing renewable energy plants in Germany.…”

Section: User Notesmentioning

confidence: 99%

Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany

Eichhorn

Scheftelowitz

Reichmuth

et al. 2019

Data

View full text Add to dashboard Cite

The expansion of renewable energy technologies, accompanied by an increasingly decentralized supply structure, raises many research questions regarding the structure, dimension, and impacts of the electricity supply network. In this context, information on renewable energy plants, particularly their spatial distribution and key parameters-e.g., installed capacity, total size, and required space-are more and more important for public decision makers and different scientific domains, such as energy system analysis and impact assessment. The dataset described in this paper covers the spatial distribution, installed capacity, and commissioning year of wind turbines, photovoltaic field systems, and bio-and river hydro power plants in Germany. Collected from different online sources and authorities, the data have been thoroughly cross-checked, cleaned, and merged to generate validated and complete datasets. The paper concludes with notes on the practical use of the dataset in an environmental impact monitoring framework and other potential research or policy settings.Dataset: Available as the supplementary file. Spatial distribution of wind turbines, photovoltaic field systems, bioenergy and river hydro power plants in Germany

show abstract

Section: User Notesmentioning

confidence: 99%

Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany

Eichhorn

Scheftelowitz

Reichmuth

et al. 2019

Data

View full text Add to dashboard Cite

show abstract

“…On the basis of the generated electrical load profiles for all sectors in a municipality, the feasible additional development of PV capacity without feeding back power into the electricity network outside the municipality was then determined. The same database was subsequently combined with detailed potentials for wind energy to analyze how different combinations and orientations of PV and wind might best meet the local annual electricity demand in four different types of municipalities according to three key energy policy criteria . More recently, bottom‐up analyses considering energy‐system integration aspects were made in individual case studies for Maribor, Slovenia, and Conception, Chile .…”

Section: Decentralized Energy‐system Modeling Of Low Carbon Technologmentioning

confidence: 99%

“…The second main challenge is to consider integration of the determined PV potentials into the energy system. Although this has already been done by some PV studies, for example, by Mainzer et al., Killinger et al., Srećković et al., and Wegertseder et al., these aspects are typically not considered by wind potential studies. So there is definitely scope to improve these methods, for example, by using real network topology and load flow data and/or also modeling other end‐use sectors.…”

Section: Decentralized Energy‐system Modeling Of Low Carbon Technologmentioning

confidence: 99%

Meeting the Modeling Needs of Future Energy Systems

et al. 2017

Self Cite

View full text Add to dashboard Cite

Structural changes in the energy sector have created considerable challenges for regulators, energy consumers, and suppliers. Energy researchers rely on quantitative modeling approaches to address these challenges. At the Karlsruhe Institute of Technology, we have developed several models to analyze today's and the future's energy markets to address the challenges for electricity networks as a result of intermittent renewable and decentralized power and heat supply and to find solutions for integrating demand response. This paper presents a survey of these approaches and discusses further challenges. The developed models have proved to be suitable for answering a range of research questions related to structural changes. As the energy sector remains in a constant state of flux, these models need to be further developed. This means coupling different energy sectors and markets and improving their technical accuracy as well as their spatial and temporal resolutions.

show abstract

“…Those surpluses may be stored in electrical cars (EV), which are mobile energy storage systems, thus leading to a decrease in carbon dioxide emissions as indicated by Nunes et al [12]. On the other hand Killinger et al [13] focused on regional optimization of wind and solar energy resources exploitation based on meteorological conditions as an input data. In their model they have focused on the realization of the German energy policy which implies: economic feasibility, environmental friendliness and insurance of demand coverage.…”

Section: Literature Overviewmentioning

confidence: 99%

Site selection for wind and solar parks based on resources temporal and spatial complementarity – mathematical modelling approach

Jurasz¹

2017

ELECTROTECHNICAL REVIEW

View full text Add to dashboard Cite

The aim of this paper was the assessment of spatial and temporal complementarity of wind and solar resources based on selected locations in Poland. More specifically, we asked the following questions: a) does the spatial distribution of photovoltaic systems and wind farms own the property of smoothing the energy generation curve? b) is it possible as a result of renewable energy sources distribution over several locations to decrease instances of outliers in terms of energy production? c) to what extent depending on time step exists complementarity of sun and wind energy?. Conducted calculations were based on daily measurements of wind speed and insolation for the period 1984-2004 which were acquired from Institute of Meteorology and Water Management (IMGW) and www.soda-is.com. Obtained results are encouraging since the positive impact of spatial distribution on smoothing the energy generation curve was observed. From the power system point of view an expedient correlation between available wind and solar radiation in yearly time scale exists in analyzed locations. Streszczenie. Celem przeprowadzonych badań było zbadanie czasowej oraz przestrzennej komplementarności energii promieniowania słonecznego oraz wiatru w wybranych lokalizacjach na terenie Polski. W pracy podjęto się odpowiedzi na następujące pytania: a) czy dystrybucja przestrzenna instalacji fotowoltaicznych oraz parków wiatrowych prowadzi do wygładzenia krzywej uzysku energii elektrycznej? b) czy jest możliwym by na skutek rozmieszczenia źródeł energii na kilka lokalizacji zminimalizować występowanie skrajnych wartości uzyskiwanego wolumenu energii c) w zależności od kroku czasowego, jak kształtuje się komplementarność zasobów wiatru oraz energii promieniowania słonecznego. Przeprowadzone analizy operały się na szeregach czasowych średniej dobowej prędkości wiatru oraz sumie nasłonecznienia, które obejmowały lata 1984-2004 i zostały pozyskane z Instytutu Meteorologii i Gospodarki Wodnej-Państwowy Instytut Badawczy oraz platformy www.soda-is.com. Uzyskane wyniki są zachęcające, ponieważ wykazano istnienie pozytywnego wpływu dystrybucji przestrzennej na wygładzenie krzywej uzysku energii. Co więcej zaobserwowano istnienie silnej ujemnej korelacji pomiędzy zasobami energii wiatru i promieniowania słonecznego w ujęciu rocznym. (Wybór lokalizacji pod elektrownie wiatrowe i fotowoltaiczne w oparciu o czasową i przestrzenną komplementarność zasobów-podejście: modelowanie matematyczne).

show abstract

A regional optimisation of renewable energy supply from wind and photovoltaics with respect to three key energy-political objectives

Cited by 36 publications

References 20 publications

Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany

Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany

Meeting the Modeling Needs of Future Energy Systems

Site selection for wind and solar parks based on resources temporal and spatial complementarity – mathematical modelling approach

Contact Info

Product

Resources

About