• Energy Research
• Closed Access close
• Embargo close
• 11. Sustainability close
• IN close
• CA close
• JP close
• UA close

This paper presents a multi-objective optimization model for a long-term generation mix in Indonesia. The objective of this work is to assess the economic, environment, and adequacy of local energy sources. The model includes two competing objective functions to seek the lowest cost of generation and the lowest CO2 emissions while considering technology diffusion. The scenarios include the use of fossil reserves with or without the constraints of the reserve to production ratio and exports. The results indicate that Indonesia should develop all renewable energy and requires imported coal and natural gas. If all fossil resources were upgraded to reserves, electricity demand in 2050 could be met by domestic energy sources. The maximum share of renewable energy that can be achieved in 2050 is 33% with and 80% without technology diffusion. The least cost optimization produces lower generation costs than the least CO2 emissions, as well as the combined scenario. Total CO2 emissions in 2050 are five to six times as large as current emissions. The least CO2 emissions scenario can reduce almost half of the CO2 emissions of the least cost scenario by 2050. The proposed multi-objective optimization model leads some optimal solutions for a more sustainable electricity system.

Abstract Light wells in the centers of high-rise apartment buildings in Japan are called ‘Voids’. Gas water-heaters built into Voids discharge exhaust gas so a large enough opening has to be designed at the bottom of a Void to keep the indoor air quality (IAQ) acceptable. In order to secure the IAQ in the Void from contamination, a simple calculation method of the ventilation rate induced by wind force and thermal buoyancy through openings at the bottom, along with heat sources such as water-heaters, is presented. The accuracy of this calculation method was examined by wind tunnel testing. As a result, it turned out that the simple calculation methods introduced in this study were valid for predicting the vertical temperature distribution and ventilation rates in Voids.

Biogas is a viable alternative for supplying clean and sustainable energy. Despite all manner of policy measures introduced by the Government of India, biogas is not widely used in India. This article tries to identify factors that influence the decision to adopt biogas at household level. We examine a conceptual framework empirically in which a household wants to maximize utility from biogas by using the India Human Development Survey (IHDS) I, which is a nationally representative, multi-topic survey. By applying both maximum likelihood and penalized likelihood methods (Firthlogit) of logistic regression on a sample size of almost 10,384 households, it has been found that wealthy people are more likely to adopt biogas compared to the marginalized section of the society. We recommend more inclusive policy measures for the weaker section of the society to create an enabling environment to make it a self-promoting technology.

Abstract Recharging infrastructure (RI) deployment plays a vital role in improving the public recharging availability for transport electrification. Decarbonizing transportation using low-emission electricity requires massive RI network. Even though the consumers are reluctant to purchase electric vehicles (EVs) until RIs are sufficiently placed, the investors are not willing to invest in RIs due to recharging demand uncertainties. Therefore, a scientific planning framework is needed to ensure the sustainable deployment of EV-RIs in complex networks. In this study, a lifecycle thinking-based multi-period infrastructure-planning framework is proposed to develop sustainable public EV-RIs in an urban context. This framework consists of a temporal model to find the dynamic EV-RI demands, a stochastic model to obtain travel distances, and a multi-objective optimization model to select the best desirable capacities and locations for potential EV-RIs. A case study of a typical medium-scale municipality in Canada was assessed using the proposed framework and validated using conventional infrastructure planning scenarios. The geo-processing data, regional travel behaviors, and recharging characteristics were used as model inputs. The results of the case study showed that the proposed framework can be used to estimate multi-period public recharging demands, minimize lifecycle costs, maximize service coverage and infrastructure utilization, and ensure reasonable paybacks compared to conventional planning approaches. Moreover, this framework can be used to compare different investment assistances, which are required in the early stages of the RI deployment process to encourage investors. Furthermore, government and private institutions can use this framework to identify recharging demands, permitting, and developing RIs in the long-run.

Abstract The residential sector accounts for most of energy-consumption in developing countries in the form of traditional energy. The use of commercial energy is nominal and confined mostly to urban areas where fuelwood is already monetized. A model, based on an end-use/process analysis approach, is developed on a spreadsheet, which is capable of simulating scenarios to address issues of increasing traditional energy-demand caused by population growth, sustainable supply capacity of the existing energy resources, potential for development of new and renewable energy resources, technology. This paper is divided into two parts: general energy issues and the modelling approach, and the application of this approach to Nepal in the context of fuelwood-supply sustainability.

Abstract Globally, three-quarter of a billion people live without electricity. Besides, hundreds of million use a solar lantern for less than 4 h a day. Most of the access-deprived are in the Global South, predominantly in Sub-Saharan Africa and South Asia. The United Nations framed the seventh Sustainable Development Goal to improve access. Solar photovoltaic powered mini-grids are increasingly extending better service to deprived regions. However, poor load-factor and expensive storage adversely affect viability. Also, these mini-grids do not support infrequent large loads to avoid further loss of load-factor. Electric cooking is efficient and non-polluting; water treatment facilities can save millions from contaminant and pathogen by providing clean water. Besides, both electric cooking and water treatment are less expensive than alternatives. But mini-grids frequently do not support these. Indeed, the presence of sustained productive loads favourably influences the mini-grid economy. This study investigates the role of critical household loads to deliver similar bearing on the mini-grid economy. Results underscore realisation of desirable impact with household collaboration under a demand-response program. Collaborative consumption can lower initial investment by 62% and reduce the unit energy cost to $0.23. Also, cooperation improves the mini-grid load factor and promotes viability. Additionally, fast deployment needs during and after Covid-19 remains inherently supported while mitigating the pandemic induced financial stress of both consumer and mini-grid operator. This study of 88 nation-states underscores that demand response in a mini-grid can not only improve affordability for all consumers, but it can also bring 186 million people within affordable access.

Abstract Natural resources exist independent of human intervention. Although these interventions can and do affect the balance between ecological and biological diversity conditions these resources support, and their use to promote economic development. Currently, the unsustainable use of these resources threatens this balance, calling for more sustainable patterns of natural resource use and conservation. The primary responsibility for ensuring the proper balance lies with governments, leading to various policies and programs to preserve natural resources. The ultimate goal is to make the masses aware of natural assets’ importance and encourage their sustainable use. To successfully implement, however, these government practices require public communication and participation, and the full consideration of public opinion at various levels of governance. A predictive analytics framework is proposed for understanding public opinion on government policies to improve sustainable water governance. An integrated policy initiative to balance water resources use and conservation launched by the Indian government served as a test case for applying the framework in an attempt to accurately classify the opinion polarity related to the policy. The conventional feature extraction is applied to pre-processed datasets to extract the relevant features. Subsequently, swarm-based feature selection is applied to filter out optimal features. Lastly, opinion mining and textual analysis are performed to determine the most relevant water management factors that need immediate attention. The proposed framework serves as a policy evaluation strategy in the water management domain. The paper closes with a discussion of the general applicability of the proposed framework.

Abstract Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO2 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NOx) increased with higher CAVs. Besides, a higher frequency and severity of NO2 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.

Abstract Conversion of carbon contained in the solid residues (tars + biochar) derived from urban biomass gasification named herein TC would allow enhancing the yield of carbon species (CO/CO2) in synthetic gas. For this purpose, three low cost materials have been tested as possible catalysts: iron species (reduced Fe), bone meal (BM), and ashes (ash) recovered from biochar complete oxidation. The parametric study used the following as variables: air GHSV, onset of reaction temperature, reaction time to optimize CO/CO2 molar ratio and tar content in the produced gas. Results showed an autocatalytic effect of biochar leading to the catalytic conversion of approximately 78% of tars by the native metals contained in TC. The catalytic effect was further enhanced by adding Fe, BM, and extra ash. Addition of Fe catalyst resulted in significant heat generation (temperature increase of ca. 500 °C) and a twofold decrease in reaction time to consume all the carbon. Use of ash and BM as catalysts exhibit heat generation comparable to Fe, along with an improved reaction time, complete tars conversion and a CO/CO2 molar ratio to above 1.3 in the produced gas.