Speaker
Description
The Positive Energy District (PED) is an urban development strategy aimed at reducing energy consumption while increasing energy production to mitigate the negative impacts of climate change. This concept is built upon earlier sustainable city initiatives, such as carbon-neutral zones and zero-energy communities. PEDs are districts or neighborhoods that have been transformed to achieve annual net zero emissions, energy self-sufficiency, and renewable energy surplus. The goal of establishing PEDs has been made more attainable with the United Nations' adoption of the Sustainable Development Goals, particularly those focused on affordable and clean energy, sustainable cities and communities, sustainable consumption and production patterns, and climate action. The efforts are boosted via targets to establish 100 PEDs across several European countries by 2025. Furthermore, the increasing frequency of extreme climate events, environmental degradation, and social inequalities pose significant threats to ecosystems, and the impacts of these threats can be mitigated with effective spatial planning such as PED concept.
The study examines the effects of various factors, including environmental and social parameters, in defining the boundaries of PEDs. The approach will utilize a GIS-based spatial framework, employing a multi-criteria decision-making (MCDM) approach. Among MCDM approaches, the TOPSIS method will be utilized, due to the number of large amount of criteria effecting the decision. Furthermore, both two-dimensional (2D) and three-dimensional (3D) geo-spatial data and analyses will be utilized and compared. The spatial datasets required for this analysis, including land cover and land use information, will be sourced from open access repositories, with an emphasis on ensuring data consistency and examining its implications on the results. Validation of the developed methodologies will take place in the Kadıköy district of İstanbul, Türkiye due to the engagement of this district in PED projects. The primary contribution of this study lies in providing data-driven, quantitative recommendations for the establishment of PED boundaries, thereby enhancing the rigor and reliability of spatial analysis in this context.
| Keywords | Positive Energy District; Geographic Information Systems; Multi-Criteria Decision Making |
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| Best Congress Paper Award | Yes |
