Spatial analysis of the electrical energy demand in Greece

Tyralis, Hristos; Mamassis, Nikοs; Photis, Yorgos N.

doi:10.1016/j.enpol.2016.12.033

Cited by 25 publications

(9 citation statements)

References 46 publications

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“…In this case, the two methods play a supplementary role. relied upon for making concrete spatial interpretation [41]. It should be used in conjunction with other more robust spatial tools.…”

Section: Comparing Results From Local Indicators Of Spatial Association (Lisa) Analysesmentioning

confidence: 99%

“…Dar-Mousa and Makhamreh [40] used Global Moran's I analysis, a spatial statistical approach to assess patterns in electricity consumption in Amman city, Jordan and found a positive and significant autocorrelation with nearby areas having similar per capita electricity consumption values. A study by Tyralis et al [41] also employed hotspot analysis, cluster and outlier analysis as well as grouping analysis to identify spatial patterns in electricity demand across administrative divisions in Greece. Spatial modelling approaches have also been used to examine and model electricity outages and their relationship with socio-economic and environmental factors at different spatial scales (state, region, county, census block) in the US [2,19,20].…”

Section: Spatial Approaches In Energy Studiesmentioning

confidence: 99%

“…In this study, the load-shedding exposure variable and its transformations are visualized in order to generate an initial picture of their spatial characteristics. However, data visualization alone cannot be relied upon to make spatial inference [41]. As a step towards making complete spatial inference, we further apply spatial statistics tools to the visualized variables.…”

Section: Visualizationmentioning

confidence: 99%

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Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana

2020

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In many developing countries, electricity outages occur frequently with consequences for sustainable development. Moreover, within a country, region or city, the distribution of outages and their resultant impacts often vary from one locality to another. However, due to data constraints, local-scale variations in outage experiences have seldom been examined in African countries. In this study, a spatial approach is used to estimate and compare exposure to electricity load shedding outages across communities in the city of Accra, Ghana. Geographic Information System and statistics from the 2015 rolling blackouts are used to quantify neighborhood-level load shedding experiences and examine for spatial patterns. The results show that annual load shedding exposure varied greatly, ranging from 1117 to 3244 h. The exposure values exhibit statistically significant spatial clustering (Moran’s I = 0.3329, p < 0.01). Several neighborhoods classified as load shedding hot or cold spots, clusters and outliers are also identified. Using a spatial approach to quantify load shedding exposure was helpful for overcoming the limitations of lack of fine-grained, micro-level outage data that is often necessary for such an analysis. This approach can therefore be used in other data-constrained cities and regions. The significant global spatial autocorrelation of load-shedding exposure values also suggests influence by underlying spatial processes in shaping the distribution of load shedding experiences. The resultant exposure maps provide vital information on spatial disparities in load shedding implementation, which can be used to influence decisions and policies towards all-inclusive and sustainable electrification.

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Section: Comparing Results From Local Indicators Of Spatial Association (Lisa) Analysesmentioning

confidence: 99%

Section: Spatial Approaches In Energy Studiesmentioning

confidence: 99%

Section: Visualizationmentioning

confidence: 99%

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Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana

2020

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“…Getis-Ord G i * analysis (hot spot analysis) can also identify the spatial differentiation of the overall accessibility of medical facilities within the study area [ 26 ], the results of which can supplement that of cluster and outlier analysis [ 27 ]. Comparisons can be made accordingly.…”

Section: Methodsmentioning

confidence: 99%

Measuring Spatial Accessibility of Urban Medical Facilities: A Case Study in Changning District of Shanghai in China

Cheng

Lian

et al. 2021

IJERPH

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Medical facilities help to ensure a higher quality of life and improve social welfare. The spatial accessibility determines the allocation fairness and efficiency of medical facilities. It also provides information about medical services that residents can share. Although critical, scholars often overlooked the level of medical facilities, the composition of integrated transportation networks, and the size of service catchment in the literature on accessibility. This study aims to fill this research gap by considering the integrated transportation network, population scale, travel impedance between medical facilities and residential areas, and the impact of medical facilities’ levels on residents’ medical choices. An improved potential model was constructed to analyze the spatial accessibility of medical facilities in Changning District of Shanghai, China. Interpolation analysis was conducted to reveal the spatial accessibility pattern. Cluster and outlier analysis and Getis-Ord Gi* analysis were applied for the cluster analysis. Results show that the spatial accessibility of medical facilities is quite different in different residential areas of Changning District, Shanghai. Among them, the spatial accessibility of medical facilities is relatively high in Hongqiao subdistrict, Xinjing Town, and part of Xinhua Road subdistrict. In addition, residents have overall better access to secondary hospitals than to primary and tertiary hospitals in the study area. This study provides a spatial decision support system for urban planners and policymakers regarding improving the accessibility of healthcare facilities. It extends the literature on spatial planning of public facilities and could facilitate scientific decision making.

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“…A geographical subdivision based on homogeneous energy characteristics has been carried out in many energy planning researches on specific areas (Arabatzis et al, 2017) (Kousksou et al, 2015), usually recalling the administrative boundaries at regional or municipal level (Tyralis et al, 2017) (Alsayegh et al, 2018), and reducing data complexity and dispersion .…”

Section: Methodsmentioning

confidence: 99%

A GIS-based model to assess electric energy consumptions and usable renewable energy potential in Lazio region at municipality scale

Santoli

Mancini

Garcia

2019

Sustainable Cities and Society

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The ongoing energy transition processes need a rapprochement between the places of energy production and consumption with the aim of creating innovative and integrated territorial models. Consequentially, models and strategies for increasing the use of local and renewable energy sources (RES) play a key rule for enhancing energy independence and sustainability of the considered areas. The main objective of this study is to analyse the energy system of the Lazio Region in Italy, comparing electricity consumptions and production from renewable sources at municipality scale. In order to estimate the electricity consumptions and the local production by RES, the main sectors of electricity consumption together with the potential of the available RES for the electricity production have been analysed. The obtained results pinpointed the main critical aspects of the Lazio region, that are mainly focalized in the city of Rome and in the most densely inhabited municipalities. Furthermore, research outputs provide an overall framework on the regional RES potential and allowed the formulation of proposals aimed at overcoming the identified criticalities and increasing the share of electricity production from renewables. Finally, the research approach could be replicated in other areas, providing a useful process for decision makers and stakeholders.

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Spatial analysis of the electrical energy demand in Greece

Cited by 25 publications

References 46 publications

Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana

Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana

Measuring Spatial Accessibility of Urban Medical Facilities: A Case Study in Changning District of Shanghai in China

A GIS-based model to assess electric energy consumptions and usable renewable energy potential in Lazio region at municipality scale

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