Local determinants of household gas and electricity consumption in Randstad region, Netherlands: application of geographically weighted regression

Mashhoodi, Bardia; Timmeren, Arjan van

doi:10.1007/s41324-018-0203-1

Cited by 18 publications

(8 citation statements)

References 42 publications

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“…By application of aspatial methods, most of the previous studies have effectively ignored spatial heterogeneity of the determinants of energy poverty. A variety of previous studies, meanwhile, have shown that the best understanding of a wide range of phenomenaamong them academic achievement (Figueroa, Lim, and Lee 2016), effects of ozone pollution (Lin and Lu 2009), vulnerability to terrorism (Eisman, Gebelein, and Breslin 2017), household energy consumption (Mashhoodi 2018;Mashhoodi and van Timmeren 2018) and social vulnerability in slums (Jankowska, Weeks, and Engstrom 2011) is achieved only when spatial heterogeneity of the effects is taken into consideration. The result of this study is beneficial for future studies on energy poverty; there is a central question to start with: what are the spatially homogeneous and heterogeneous determinants of energy poverty?…”

Section: Discussionmentioning

confidence: 99%

Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension

2018

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Since the 1970s, a variety of studies has searched for the sociodemographic, housing and economic determinants of energy poverty. A central question, however, has not been answered by any of the previous studies: what are the national-level determinants, i.e. the determinants that homogeneously provoke a high level of energy poverty in all areas of a country? What are the neighbourhood-specific determinants, i.e. the characteristics that have a heterogeneous impact across the neighbourhoods of a country? This study seeks to answer these questions by analysing the level of energy poverty, the percentage of households' disposable income spent on energy expenditure, in 2473 neighbourhoods of the Netherlands in 2014. By employing a semiparametric geographically weighted regression analysis, the effects of two of the determinants of energy poverty are found to be spatially homogeneous: (i) percentage of low-income households and (ii) percentage of pensioners. The results indicate that the impacts of six of the determinants are spatially heterogeneous: (i) household size, (ii) percentage of unemployment, (iii) building age, (iv) percentage of privately rented dwellings, (v) number of summer days and (vi) number of frost days. Subsequently, the effects of spatially homogeneous and heterogeneous determinants are estimated and mapped; the results are discussed and some policy implications are proposed.

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Section: Discussionmentioning

confidence: 99%

Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension

2018

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“…The incorporation of such a holistic approach is essential, as the Dutch Climate Accord policies aim to phase out gas use for both cooking and heating in all dwellings by 2050 (Ministry of Economic Affairs and Climate Policy, 2019). Supposedly, the spatial pattern of electricity consumption in the dwellings will drastically shift because of these aims (Mashhoodi and van Timmeren, 2018). Therefore, the use of EVs is not about EVs per se.…”

Section: Discussionmentioning

confidence: 99%

The two and half minute walk: Fast charging of electric vehicles and the economic value of walkability

Mashhoodi

Timmeren

Blij

2019

Environment and Planning B: Urban Analytics and City Science

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The number of electric vehicles in the Netherlands has sharply increased over the past decade. This has caused a need for the allocation of a substantial amount of new electric vehicle chargers around the country, which in turn has been acknowledged by a variety of legislative bodies. However, the approach of how these new charging infrastructures need to be spatially distributed has yet to be decided, including the distance that an electric vehicle charger could be allocated from the final destination of its driver. The hypothesis of this study is that if residents walk a longer distance to/from these charging stations, the chargers could be shared by a greater number of electric vehicle owners, and the total cost of the new charging infrastructure could be reduced. By using linear integer programming, the minimum cost of allocating new fastcharging stations in a central, densely populated area of Amsterdam, accounting for 7% of the city's population, is calculated. The results show that if residents were to walk for five minutes (roughly 400 metres) instead of two and half minutes (roughly 200 metres), the overall cost of new electric vehicle chargers could be reduced by more than 1 million euros. The study also found that both the cost of new charging stations and their efficiency of use are vastly affected by the portion of the charging infrastructure that is saved for people visiting the area. The findings of this study are discussed in detail, including the proposal of potential further studies.

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“…In addition to the adaptation of electric mobility, the Dutch Climate Accord (Ministry of Economic Affairs and Climate Policy 2019) aims to phase out residential gas use for heating and cooking before 2050. The transition from gas to electricity in residential buildings will reshape the patterns of electricity consumption (Mashhoodi et al,2018) which alongside urban microclimate (Mashhoodi, 2020) and its future changes can increase the load on electricity substations. Future studies on the optimal allocation of EVs and the impact on range anxiety need to incorporate the overall upcoming demand for electricity.…”

Section: Further Studiesmentioning

confidence: 99%

Drivers’ range anxiety and cost of new EV chargers in Amsterdam: a scenario-based optimization approach

Mashhoodi

Blij

2020

Annals of GIS

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Due to the sharp growth in the adaptation of electric vehicles (EV) in the Netherlands and the objectives of the Dutch Climate Accord is to encourage electric mobility, in the coming decades a substantial number of new EV charging facilities needs to be provided. Efficient planning of EV charging infrastructure is coupled with the notion of range anxiety, which is likely to be severely high in case of soon-to-be EV drivers. This study aims to estimate the cost of developing a new charging infrastructure under five scenarios of range anxiety in Amsterdam East. Employing a Linear Integer Programming optimization model, on the basis of geographic data on car registration, existing EV chargers, and electricity substations, it is obtained that if drivers use 90% of their battery before using a charging facility, the existing charging infrastructure needs to be expanded by only 31% to accommodate almost seven times larger number of EVs-the threshold set by the European Union (EU) legislation on the deployment of alternative fuel infrastructure. If drivers use only 30% of the batteries; however, an increase of 167% in infrastructure is inevitable (accounting for almost five million euro of cost). Second, at any point along the range anxiety spectrum, if the interval between charging session increases for 1 day, the overall cost decreases by more than 30%. These findings are discussed, and two policy approaches are proposed: (1) information technology approach; (2) demand-response approach, on the basis of EU legislation on energy efficiency and deployment of alternative fuel infrastructure.

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Local determinants of household gas and electricity consumption in Randstad region, Netherlands: application of geographically weighted regression

Cited by 18 publications

References 42 publications

Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension

Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension

The two and half minute walk: Fast charging of electric vehicles and the economic value of walkability

Drivers’ range anxiety and cost of new EV chargers in Amsterdam: a scenario-based optimization approach

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