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Carvallo, C., Jalil-Vega, F., & Moreno, R. (2023). A multi-energy multi-microgrid system planning model for decarbonisation and decontamination of isolated systems. Appl. Energy, 343, 121143.
Abstract: Decarbonising and decontaminating remote regions in the world presents several challenges. Many of these regions feature isolation, dispersed demand in large areas, and a lack of economic resources that impede the development of robust and sustainable networks. Furthermore, isolated systems in the developing world are mostly based on diesel generation for electricity, and firewood and liquefied petroleum gas for heating, as these options do not require a significant infrastructure cost. In this context, we present a stochastic multi-energy multi-microgrid system planning model that integrates electricity, heat and hydrogen networks in isolated systems. The model is stochastic to capture uncertainty in renewable generation outputs, particularly hydro and wind, and thus design a multi-energy system proved secured against such uncertainty. The model also features two distinct constraints to limit the emissions of CO2 (for decarbonisation) and particulate matter (for decontamination), and incorporates firewood as a heating source. Moreover, given that the focus is on low-voltage networks, we introduce a fully linear AC power flow equations set, allowing the planning model to remain tractable. The model is applied to a real-world case study to design a multi-energy multi-microgrid system in an isolated region in Chilean Patagonia. In a case with a zero limit over direct CO2 emissions, the total system's cost increases by 34% with respect to an unconstrained case. In a case with a zero limit over particulate matter emissions, the total system's cost increases by 189%. Finally, although an absolute zero limit over both, particulate matter and direct CO2 emissions, leads to a total system's cost increase of 650%, important benefits in terms of decarbonisation and decontamination can be achieved at marginal cost increments.
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Ferrada, F., Babonneau, F., Homem-de-Mello, T., & Jalil-Vega, F. (2022). Energy planning policies for residential and commercial sectors under ambitious global and local emissions objectives: A Chilean case study. J. Clean. Prod., 350, 131299.
Abstract: Chile is currently engaged in an energy transition process to meet ambitious greenhouse gas reductions and improved air quality indices. In this paper, we apply a long-term energy planning model, with the objective of finding the set of technologies that meet strong reductions of CO2 emissions and of local PM2.5 concentrations. For this purpose, we use the existing ETEM-Chile (Energy-Technology-Environment-Model) model which considers a simplified version of the Chilean electricity sector that we extend to the residential and commercial sectors and to local concentration considerations. We propose an original approach to integrate in the same framework local and global emission constraints. Results show that to meet the goal of zero emissions by 2050, electrification of end-use demands increases up to 49.2% with a strong growth of the CO2 marginal cost. It should be noted that this electrification rate is much lower than government projections and those usually found in the literature, in certain geographic areas in southern Chile with a wide availability of firewood for residential heating. Regarding local PM2.5 concentrations, our analysis shows that even without a specific emission reduction target, acceptable PM2.5 concentrations are achieved by 2045, due to first the emergence of more efficient, cleaner and cost-effective end-use technologies, in particular, residential firewood heaters, and second the use of drier and therefore less contaminating firewood. Achieving acceptable air quality as early as 2030 is also possible but comes with a high marginal cost of PM2.5 concentration. Our results illustrate the need for implementing effective public policies to (i) regulate the firewood heating market to increase its production and improve its environmental quality and (ii) incentivize the installation of efficient firewood heaters in the residential sector.
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Ferrada, F., Babonneau, F., Homem-de-Mello, T., & Jalil-Vega, F. (2023). The role of hydrogen for deep decarbonization of energy systems: A Chilean case study. Energy Policy, 177, 113536.
Abstract: In this paper we implement a long-term multi-sectoral energy planning model to evaluate the role of green hydrogen in the energy mix of Chile, a country with a high renewable potential, under stringent emission reduction objectives in 2050. Our results show that green hydrogen is a cost-effective and environmentally friendly route especially for hard-to-abate sectors, such as interprovincial and freight transport. They also suggest a strong synergy of hydrogen with electricity generation from renewable sources. Our numerical simulations show that Chile should (i) start immediately to develop hydrogen production through electrolyzers all along the country, (ii) keep investing in wind and solar generation capacities ensuring a low cost hydrogen production and reinforce the power transmission grid to allow nodal hydrogen production, (iii) foster the use of electric mobility for cars and local buses and of hydrogen for long-haul trucks and interprovincial buses and, (iv) develop seasonal hydrogen storage and hydrogen cells to be exploited for electricity supply, especially for the most stringent emission reduction objectives.
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O' Ryan, R., Benavides, C., Diaz, M., San Martin, J. P., & Mallea, J. (2019). Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile. Clim. Policy, 19(3), 299–314.
Abstract: In this paper, initial steps are presented toward characterizing, quantifying, incorporating and communicating uncertainty applying a probabilistic analysis to countrywide emission baseline forecasts, using Chile as a case study. Most GHG emission forecasts used by regulators are based on bottom-up deterministic approaches. Uncertainty is usually incorporated through sensitivity analysis and/or use of different scenarios. However, much of the available information on uncertainty is not systematically included. The deterministic approach also gives a wide range of variation in values without a clear sense of probability of the expected emissions, making it difficult to establish both the mitigation contributions and the subsequent policy prescriptions for the future. To improve on this practice, we have systematically included uncertainty into a bottom-up approach, incorporating it in key variables that affect expected GHG emissions, using readily available information, and establishing expected baseline emissions trajectories rather than scenarios. The resulting emission trajectories make explicit the probability percentiles, reflecting uncertainties as well as possible using readily available information in a manner that is relevant to the decision making process. Additionally, for the case of Chile, contradictory deterministic results are eliminated, and it is shown that, whereas under a deterministic approach Chile's mitigation ambition does not seem high, the probabilistic approach suggests this is not necessarily the case. It is concluded that using a probabilistic approach allows a better characterization of uncertainty using existing data and modelling capacities that are usually weak in developing country contexts. Key policy insights Probabilistic analysis allows incorporating uncertainty systematically into key variables for baseline greenhouse gas emission scenario projections. By using probabilistic analysis, the policymaker can be better informed as to future emission trajectories. Probabilistic analysis can be done with readily available data and expertise, using the usual models preferred by policymakers, even in developing country contexts.
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