Elsevier

Renewable Energy

Volume 138, August 2019, Pages 416-433
Renewable Energy

What if São Paulo (Brazil) would like to become a renewable and endogenous energy -based megacity?

https://doi.org/10.1016/j.renene.2019.01.073Get rights and content

Highlights

  • São Paulo urban energy system is presented using customized and local data approach.

  • Quantification of megacity’s endogenous and exogenous energy resources.

  • Integrated modeling of multisector energy demand projection for São Paulo.

  • City energy services’ access improvement and its energy system implication results.

  • Proposed polices reached 31% of endogenous resources and 43% less GHG emissions.

Abstract

This paper analyses São Paulo megacity’s (Brazil) current and future energy system through the development of an urban energy model, using the Long-range Energy Alternatives Planning System simulation software, covering the period from 2014 to 2030. The paper explores pathways for increasing renewable and endogenous energy resources in the megacity, reducing its dependency on energy imports and its greenhouse gases emissions. Seven scenarios are modelled considering an integrated multisector energy demand projection that combines energy endogenous potential assessment with improving access of the population to city’ energy services. Currently, São Paulo imports 99% of its energy (% of exogenous resources). In 2030, 31% of endogenous resources can be achieved under a Business as Usual scenario, as well as a reduction up to 43% of greenhouse gases emissions from 2014 levels, by promoting both demand-side and supply-side energy efficiency. When considering better energy services’ access for city inhabitants, accompanied by urban energy policies, a maximum of 25% of endogenous energy share in 2030 and an emission decrease of 24% below 2014 emissions is likely to be reached.

Introduction

Cities are acknowledged as responsible for around 64% of global primary energy use, which accounted for 70% of CO2 global emissions in 2013 [1]. The cities role becomes even more prominent with the rise of megacities (cities with 10 million or more inhabitants), mainly located in developing countries1 [2]. Given the magnitude of cities’ impact, urban regions are seen as a potential locus to make the required energy system shift towards decarbonization, increasing energy access to all the urban population, improving inhabitants’ well-being [3], mitigating global emissions, and reducing energy demand through local-scale energy system planning and policy initiatives [4].

Cities have an enormous potential to reduce environmental pressure while enhancing well-being for their inhabitants. This can be made by decoupling cities metabolism from the use of non-renewable energy resources and inefficient processes as part of a transition to a sustainable economy [8], acting on both the demand and supply sides of the Urban Energy System (UES) [5]. According to Rutter and Keirstead (2012), the UES is the combined processes of acquiring and using energy to meet the energy service demands of an urban region [3].

Current scientific literature on UES mostly focuses on some components, as specific economic sectors, or specific end-use energy services, or even specific energy technologies for only one end-use energy service. Regarding the focus on individual economic sectors, examples include works on transports [6] and buildings [7,8]. Examples addressing specific urban energy end-uses include the focus on urban heat demand [9], building’s heat demand [10] and lighting [11], while works focusing specific technology performance regarding energy savings include smart grids [12], net-zero energy buildings [13], and electric vehicles. Electric mobility in urban areas has had special emphasis, namely on energy management strategies for connecting electric vehicles in urban roads [14], fuel and greenhouse gases (GHG) and other pollutant emission savings for light-duty passenger vehicles [15], and cost-benefit analysis for its deployment [16].

Nevertheless, there are few published studies analyzing the whole UES in an integrated approach. Although there is an increasing number of scientific literature applying optimization energy models at the urban scale, (e.g. Ref. [17], analyzing how to optimally integrate renewable energy sources (RES) in UES, or [18,19] proposing a bottom-up supply-demand model to assess the optimal performance of UES), there is still lack of literature regarding the use of simulation models to integrate energy system at the city level.

Since generally, fossil fuels consumption by cities is acknowledge as a major cause of climate disruption [20], there is a growing interest on increasing cities’ energy self-sufficiency potential by promoting a sustainable energy system transition [21]. However, little is known on current megacities’ UES regarding urban energy demand needs per sector and end-use. Likewise, there is a lack of knowledge regarding megacities’ detailed energy supply profile, and particularly their endogenous potential. In this paper, endogenous energy resources refer to the energy resources available within the perimeter of the considered urban area, that include solar, wind, biomass, local hydro possibilities, waste, industrial heat and power.

In this context, some authors underline the need for integrated urban energy infrastructure planning to better assess the energy supply potential of urban areas [22]. In particular, there is no published work modeling the UES of a megacity using a simulation model, nor addressing how its energy supply and demand can be made more sustainable by harvesting its endogenous RES. This article seeks to fill this gap using a city energy system model for the case study of the São Paulo megacity in Brazil applied for the period from 2014 to 2030.

The Long-range Energy Alternatives Planning System (LEAP) energy simulation model, [23] was applied for modeling São Paulo UES in order to characterize the megacity’s current and future energy system concerning energy supply and demand. The model was applied to evaluate possible energy futures, and the goal of the paper is to explore, within the context of a megacity, the possibility for the endogenous and RES energy increase share by 2030 and, by selecting urban energy policies and strategies, simulate the potential for (i) energy savings, (ii) distributed electricity generation increase (by promoting RES and endogenous resources), and (iii) GHG emissions reduction. The paper also provides insights for policy and decision-makers on moving towards a more self-sufficient and socially more inclusive city by explicitly considering improved energy access to 11% of the São Paulo’s population currently living in subnormal housing.

The paper is structured as follows: section 2 describes the methodology used, including basic model description, scenario design, formulation of policy scenarios, and the relevant data used. Results and discussion are presented in Section 3 together with a summary of the main results regarding the city final and primary energy consumption, changes in the urban power sector, GHG emissions reduction and increase in urban RES and endogenous share. Section 4 concludes the paper.

Section snippets

Material and methods

LEAP is a widely used energy-economy model both for simulation or optimization purposes. It builds energy scenarios using integrated planning and bottom-up data on energy demand and primary energy transformation (transmission and distribution, primary energy conversion, and energy resource extraction data can be also added). LEAP is flexible regarding its application level, including region, country, state or local level [23]. The model can be used to estimate GHG emissions from energy use and

Emission data inputs

LEAP_SP considers the following direct GHG and air pollutant emissions from energy use and generation within the city: particular matter (PM), carbon monoxide (CO), non-methane volatile organic compounds (NMVOC), sulphur dioxide (SO2), aldehydes, nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4). This means that the model does not consider CO2 emissions of products and energy carriers imported into the city, except for electricity.

Since this paper considers the energy system inside

Modelled scenarios design

For the purpose of our analysis, seven scenarios were developed, a Reference scenario (REF) and more six along two main socioeconomic pathways: (i) Business as Usual (BAU) and (ii) Better Energy Services (BET), as presented in Table 3.

The REF scenario was developed for calibration purposes of the LEAP_SP model. The REF scenario does not comprise policies of any kind, and consequently the services share and technology stocks, as well as energy policies till 2030 refer as the base year. The

Results and discussion

The results gathered from the modeling exercise were analyzed for the seven scenarios using five key performance indicators, pointing to the most relevant aspects of the city energy system performance and characteristics, namely: 1) city final energy consumption (FEC), total and per sector; 2) city electricity generation; 3) city endogenous energy share, considered as an indicator to achieve the city energy self-sufficiency, defined in terms of city local energy carriers (endogenous resource)

Conclusion

This article presented the LEAP energy system model for the city of São Paulo (Brazil) and its application to assess possible pathways to change the megacity’s current energy system by 2030. Seven scenarios were modelled considering the urban energy system in a holistic approach and paying special attention to the urban potential for endogenous energy resource use. The article estimates the impacts of each of these scenarios on: (i) energy savings; (ii) share of distributed electricity

Acknowledgment

We acknowledge the financial support provided by the Brazilian agency CAPES through the ’Programa de Doutorado-sanduíche no Exterior (PDSE)’, to the Erasmus Mundus, BE MUNDUS Program, and to Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), process nº 2015/03804-9. Also, Heaps, C.G., and Stockholm Environment Institute for providing enough license time to the development of the research. Finally, we would like to thank the anonymous reviewers for their helpful comments.

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