Determining roof surfaces suitable for the installation of PV (photovoltaic) systems, based on LiDAR (Light Detection And Ranging) data, pyranometer measurements, and distribution network configuration

Srećković, Nevena; Lukač, Niko; Žalik, Borut; Štumberger, Gorazd

doi:10.1016/j.energy.2015.12.078

Cited by 20 publications

(14 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, this study assumed that there was more than enough non-shaded optimal surface area to allow for distributed generation with PV, but it did not explicitly calculate siting for the 1544 GW of PV necessary to replace all of fossil fuel electricity production in the U.S. The nuances of territory and siting at both the large scale for PV output [115], as well as DG benefits [116,117] and roof top [118][119][120][121][122] as well as façade [123] locations have been covered extensively. Here, the conservative assumption about locating the PV systems was based on a distributed generation model where the PV would be located following population density in each state across the U.S.…”

Section: Limitationsmentioning

confidence: 99%

Could 79 People Solarize the U.S. Electric Grid?

Pearce

Prehoda

2019

Societies

View full text Add to dashboard Cite

Although wealth inequality has many established negatives, this study investigates a potential positive, unprecedented wealth concentration makes it possible for solutions to large and seemingly intractable problems to be deployed by convincing a relatively small number of individuals to invest. In order to probe this potential outcome of inequality, this study quantifies the number of people necessary to radically reduce the greenhouse gas emissions responsible for global climate destabilization from the U.S. electric grid, which is one of the largest sources of emissions. Specifically, this study determined that 1544 GW of solar photovoltaic (PV) technology must be deployed to eliminate the use of fossil fuels on the U.S. electric grid, if PV is conservatively deployed as a function of population density. The results showed that only 79 American multi-billionaires would need to invest in PV. This investment would still leave each investor with a billion dollars of liquid assets as well as substantial long-term profits from PV. The analysis also concluded that 79 people is a conservative upper estimate of those that would need to be convinced of the usefulness of moving to a solar U.S. grid and that this estimate is likely to decrease further in the future.

show abstract

Section: Limitationsmentioning

confidence: 99%

Could 79 People Solarize the U.S. Electric Grid?

Pearce

Prehoda

2019

Societies

View full text Add to dashboard Cite

show abstract

“…Also in the case of PV, the work of Lukač et al [107] in 2014 and Jakubiec and Reinhardt [111] in 2013 (presented in the section of only GIS-based estimations of PV potential) described methodologies which were already able to generate PV potential data in high spatiotemporal resolution for entire cities, but they did not make further use of the data. It was only in 2016 that Srećković et al [172] extended the methodology of Lukač et al [107] to improve the evaluation of suitability of surfaces for PV. These authors included the high temporal resolution energy output of every potential surface and the electricity demand profiles of buildings in a distribution network model to assess which of the installations would lead to the highest reduction of network losses per year.…”

Section: Spatiotemporal Modelling For Renewable Energy Planningmentioning

confidence: 99%

Spatiotemporal modelling for integrated spatial and energy planning

Camargo

Stoeglehner

2018

Energ Sustain Soc

View full text Add to dashboard Cite

The transformation of the energy system to a renewable one is crucial to enable sustainable development for mankind. The integration of high shares of renewable energy sources (RES) in the energy matrix is, however, a major challenge due to the low energy density per area unit and the stochastic temporal patterns in which RES are available. Distributed generation for energy supply becomes necessary to overcome this challenge, but it sets new pressures on the use of space. To optimize the use of space, spatial planning and energy planning have to be integrated, and suitable tools to support this integrated planning process are fundamental. Spatiotemporal modelling of RES is an emerging research field that aims at supporting and improving the planning process of energy systems with high shares of RES. This paper contributes to this field by reviewing latest developments and proposing models and tools for planning distributed energy systems for municipalities. The models provide estimations of the potentials of fluctuating RES technologies and energy demand in high spatiotemporal resolutions, and the planning tools serve to configure energy systems of multiple technologies that are customized for the local energy demand. Case studies that test the spatiotemporal models and their transferability were evaluated to determine the advantages of using these instead of merely spatial models for planning municipality-wide RES-based energy systems. Spatiotemporal models allow a more detailed estimation of RES potentials and serve to find not only optimal locations but also optimal sizes for individual RES plants. While the potential of variable RES based on yearly energy generation values can be considerably larger than the energy demand, only a fraction of it can be deployed without compromising the quality and reliability of the local energy supply system. Furthermore, when spatiotemporal models are used, it can be seen that technological diversity is beneficial for the supply quality. Similarly, the advantages and limits of the deployment of storage systems and of combinations of RES-based technologies to cover the local demand were determined and evaluated. Finally, the results from the analyses provide sufficient information to define road maps of installations deployment to achieve desired RES penetration objectives.

show abstract

“…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

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

Determining roof surfaces suitable for the installation of PV (photovoltaic) systems, based on LiDAR (Light Detection And Ranging) data, pyranometer measurements, and distribution network configuration

Cited by 20 publications

References 29 publications

Could 79 People Solarize the U.S. Electric Grid?

Could 79 People Solarize the U.S. Electric Grid?

Spatiotemporal modelling for integrated spatial and energy planning

Meeting the Modeling Needs of Future Energy Systems

Contact Info

Product

Resources

About