• Energy Research
• 2021-2025close
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Data and scripts to replicate the results and the figures presented in "Declining cost of renewables and climate change curb the need for African hydropower expansion"

This repository contains the data, scripts and results for the paper "Demand-side policies for power generation in response to the energy crisis: A model analysis for Italy", https://doi.org/10.1016/j.esr.2024.101329. Results in the paper are divided into three sections, corresponding to the numbers of the folders inside this dataset. They are described as follows: 1 - EU policy impact: What is the impact on the Italian electricity of the european proposal of cutting power demand and shifting it during peak hours on gas consumption, system costs and emissions? 2 - Gas cost sensitivity: Which would be Italy’s most convenient power system considering different gas prices? 3 - DSM in mitigation: What could be the role of demand side measures in power systems with a high penetration of RES?

Script and data to reproduce the main results of "Power system investment optimization to identify carbon neutrality scenarios for Italy"

Abstract Reliability analysis of IESs (Integrated Energy System) is complicated because of the complexity of system topology and dynamics and different kinds of uncertainties. Reliability is often calculated based on statistic methods, which always focus on historical performances and neglect the importance of their dynamics and structure. To overcome this problem, in this paper, a systematic framework for dynamically analysing the real-time reliability of IESs is proposed by integrating different machine learning methods and statistics. Firstly, the bootstrap-based Extreme Learning Machine is developed to forecast the conditional probability distributions of the productions of renewable energies and the energy consumptions. Then, the dynamic behaviour of IESs is simulated based on a stacked auto-encoder model, instead of using traditional mechanism-based simulation models, for improving computational efficiency. Besides, the variables representing the transient properties of natural gas pipeline networks, such as delivery pressures and flow rates, are taken as the indicators for quantifying the energy supply security in natural gas pipeline networks. The time-dependent relationships among these indicators and their statistic correlations are modelled for improving the effectiveness of the analysis results. Finally, the reliability assessment is performed by estimating the probability distribution of each functional state of the target IES. A case study of a realistic bi-directional IES is carried out to demonstrate the effectiveness of the proposed method. The results show that the method is able to effectively evaluate the reliability of IESs, which can provide useful information for system operation and management.

Abstract With environmental concerns and limited natural resources, there is a need for cleaner sources of energy in the transportation sector. Renewable natural gas (RNG) is being considered as a potential fuel for heavy-duty applications due to its comparable usage to diesel and gasoline in vehicles. The idea of compressed RNG vehicles is being proposed especially because it will significantly reduce harmful emissions into the environment. This study examines the feasibility of implementing a nationwide network of compressed RNG refueling infrastructure in order to accommodate a conversion of long-haul, heavy-duty (LHHD) truck fleet from diesel fuel to RNG. Two methods, Constant Traffic and Variable Traffic, along with data about compressed RNG infrastructure and vehicles, were developed and used to predict fuelling requirements for LHHD truck fleet. Then, a detailed economic analysis was conducted on various test cases to estimate how different variables impact the final selling price of RNG. This provided insight with the understanding of what factors go into pricing RNG and if it can compete against diesel in the trucking market. Results disclosed that the cost to purchase RNG is the greatest factor in the final selling price of compressed RNG. Due to the variability in RNG production, however, there is no precise cost, which makes predictions challenging. However, results revealed that it is possible for compressed RNG to be competitive with diesel, with the mean compressed RNG price being 16.5% cheaper than diesel, before being taxed. Future studies should focus on the feasibility of the production of RNG and the associated costs. An in-depth analysis on operational and maintenance costs for compressed RNG refueling stations may also provide predictions that are more accurate. The methodology developed in this feasibility analysis may serve as a useful tool for future techno-economics of RNG refueling stations for other types of internal combustion engine (ICE) fleets or those powered with alternative green fuels.

Co-design approach is increasingly popular in many organizations that address global change and social sustainability challenges, thanks to its unique and diverse methods of engaging relevant people in design processes and decision-making. However, the social distancing led by the COVID-19 pandemic seriously problematized the traditional in-person co-design activities. A sustainable online transition is unprecedentedly pressing. By acknowledging the limitations of online co-design, i.e., lack of means for participant engagement, we argue that gamification holds great promise for online co-design. This paper presents an empirical study to investigate this potential qualitatively. Based on the data collected from three gamified online co-design implementations, we examine the benefits of gamification and how future activities should be designed and implemented from the participants’ perspectives. Based on the participants’ perceptions, we propose several recommendations for designing impactful gamification. The finding suggests that gamification can facilitate online co-design activities in an enjoyable, relaxing, structuring, and creative manner, since they are perceived and recognized by the participants. Moreover, the successful implementation of online co-design implies that great sustainability benefits can be achieved through online transition, i.e., reducing paper consumption and time spent on meetings and unproductive discussions, supporting extensive diversity and density in representation. Online can enable this by overcoming not only the geographic and time limitations but also relevant social issues.

<div class="section abstract"><div class="htmlview paragraph">Turbulent Jet Ignition (TJI) represents one of the most effective solution to improve engine efficiency and to reduce fuel consumption and pollutants emission. Even if active prechambers allow a precise control of the air-fuel ratio close to the spark plug and the ignition of ultra-lean mixtures in the main chamber, passive prechambers represent a more attractive solution especially for passenger cars thanks to their simpler and cheaper configuration, which is easier to integrate into existing engines. The main challenge of passive prechambers is to find a geometry that allows to use TJI in the whole engine map, especially in the low load/speed region, without the use of a second sparkplug in the main chamber. To this end, this works reports a CFD study coupled with an experimental investigation to overcome this limitation. A baseline prechamber configuration able to operate in the whole engine map was firstly studied using the CFD models and validated against the experimental results of a 2.0 L spark-ignition (SI) engine at different equivalent ratios. After the assessment of the proposed approach, different prechamber configurations were investigated to find a proper geometry able to produce similar results of the baseline configuration but with a different spark-plug installation to allow an easier integration into existing engines.</div></div>