GIS-based decision support for solar energy planning in urban environments

Rylatt, Mark; Gadsden, Stuart J.; Lomas, Kevin J.

doi:10.1016/s0198-9715(00)00032-6

Cited by 79 publications

(33 citation statements)

References 2 publications

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“…In order to support the analysis of energy consumption in various buildings, Kim and Degelman developed a computer-aided interface system [287]. As an effective decision-support tool for energy systems planning, a set of computerized decision-support software was developed by Rylatt et al [288]. A specialized group DSS was designed by van Groenendaal for providing long-term support related to energy policy formulation on the island of Java, Indonesia [289].…”

Section: Model-based Decision Support Toolsmentioning

confidence: 99%

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

et al. 2011

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Abstract:Energy is crucial in supporting people's daily lives and the continual quest for human development. Due to the associated complexities and uncertainties, decision makers and planners are facing increased pressure to respond more effectively to a number of energy-related issues and conflicts, as well as GHG emission mitigation within the multiple scales of energy management systems (EMSs). This quandary requires a focused effort to resolve a wide range of issues related to EMSs, as well as the associated economic and environmental implications. Effective systems analysis approaches under uncertainty to successfully address interactions, complexities, uncertainties, and changing conditions associated with EMSs is desired, which require a systematic investigation of the current studies on energy systems. Systems analysis and optimization modeling for low-carbon energy systems planning with the consideration of GHG emission reduction under uncertainty is thus comprehensively reviewed in this paper. A number of related methodologies and applications related to: (a) optimization modeling of GHG emission mitigation; (b) optimization modeling of energy systems planning under uncertainty; and (c) model-based decision support tools are examined. Perspectives of effective management schemes are investigated, demonstrating many demanding areas for enhanced research efforts, which include issues of data availability and reliability, concerns in OPEN ACCESSEnergies 2011, 4 1625 uncertainty, necessity of post-modeling analysis, and usefulness of development of simulation techniques.

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Section: Model-based Decision Support Toolsmentioning

confidence: 99%

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

et al. 2011

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“…However, while applying these analytical approaches to an urban system, the relationship between solar potential and energy consumption patterns can be effectively explored. Indeed, this is the lesson from the ample literature concerning the analysis of urban solar potential, with particular attention to GIS tools [30,31], parametric modelling [10,32,33] and new methodologies for solar urban planning [34] and design [35]. On the other hand, the relationships between the effect of urban geometry and energy consumption are illustrated by Ratti, Baker, and Steemers (2005) [36].…”

Section: Introductionmentioning

confidence: 99%

A Cellular Approach to Net-Zero Energy Cities

et al. 2017

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Abstract:Recent growth in the use of photovoltaic technology and a rapid reduction in its cost confirms the potential of solar power on a large scale. In this context, planning for the deployment of smart grids is among the most important challenges to support the increased penetration of solar energy in urban areas and to ensure the resilience of the electricity system. As part this effort, the present paper describes a cellular approach to a Net-Zero energy concept, based on the balance between the potential solar energy supply and the existing consumption patterns at the urban unit scale. To do that, the Geographical Urban Units Delimitation model (GUUD) has been developed and tested on a case study. By applying the GUUD model, which combines Geographic Information Systems (GIS), parametric modelling, and solar dynamic analysis, the whole area of the city was divided into urban cells, categorized as solar producers and energy consumers. The discussion around three theoretical scenarios permits us to explore how smart grids can be approached and promoted from an urban planning perspective. The paper provides insights into how urban planning can be a driver to optimize and manage energy balance across the city if the deployment of smart grids is correctly integrated in its operative process.

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“…Derived solar parameters are calculated at a spatial resolution up 80 m using a novel terrain disaggregation method and a DTM derived from SRTM-3 data [16,17]. The Solar Energy Planning system (SEP) is a tool developed to support planning and installation of solar water heating panels, photovoltaic panels, passive solar gain; it is implemented in GIS environment (SEPsis) [18,19]. Specific software developed for estimating the yield of photovoltaic systems including effects from near and far shadowing are PVsyst [20] that uses a meteorological database and isotropic sky model, PV*SOL [21] that offers 2-D and 3-D analysis module.…”

Section: Introductionmentioning

confidence: 99%

Solar Irradiance Modelling with NASA WW GIS Environment

Piragnolo

Masiero

Fissore

et al. 2015

IJGI

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Abstract:In this work we present preliminary results regarding a proof-of-concept project which aims to provide tools for mapping the amount of solar radiation reaching surfaces of objects, accounting for obstructions between objects themselves. The implementation uses the NASA World Wind development platform (NASA WW) to model the different physical phenomena that participate in the process, from the calculation of the Sun's position relative to the area that is being considered, to the interaction between atmosphere and solid obstructions, e.g., terrain or buildings. A more complete understanding of the distribution of energy from the Sun illuminating elements on the Earth's surface adds value to applications ranging from planning the renewable energy potential of an area to ecological analyses.

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GIS-based decision support for solar energy planning in urban environments

Cited by 79 publications

References 2 publications

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

A Cellular Approach to Net-Zero Energy Cities

Solar Irradiance Modelling with NASA WW GIS Environment

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