Characterising municipal solid waste to analyse life-cycle energy demand and emissions

A life cycle assessment of waste management in Pyongyang, Korea was undertaken using a characterisation-based method to analyse cumulative energy demand and energy-related carbon dioxide emissions. The study showed that characterising waste fractions by composition, proportion, water content and heating value rather than simply mass was more effective for energy-related analysis in life-cycle assessments. The results indicated that the energy demand and emissions indicators could be used as appropriate proxies of the environmental impacts in life-cycle phases, since they were closely related. The results also revealed that waste incineration could result in energy credit to the national electricity mix, while waste landfill needed to be replaced with sanitary landfill and/or switched to incineration with energy recovery to be more sustainable.

Are Sustainable Aviation Fuels a Viable Option for Decarbonizing Air Transport in Europe? An Environmental and Economic Sustainability Assessment

The use of drop-in capable alternative fuels in aircraft can support the European aviation sector to achieve its goals for sustainable development. They can be a transitional solution in the short and medium term, as their use does not require any structural changes to the aircraft powertrain. However, the production of alternative fuels is often energy-intensive, and some feedstocks are associated with harmful effects on the environment. In addition, alternative fuels are often more expensive to produce than fossil kerosene, which can make their use unattractive. Therefore, this paper analyzes the environmental and economic impacts of four types of alternative fuels compared to fossil kerosene in a well-to-wake perspective. The fuels investigated are sustainable aviation fuels produced by power-to-liquid and biomass-to-liquid pathways. Life cycle assessment and life cycle costing are used as environmental and economic assessment methods. The results of this well-to-wake analysis reveal that the use of sustainable aviation fuels can reduce the environmental impacts of aircraft operations. However, an electricity mix based on renewable energies is needed to achieve significant reductions. In addition, from an economic perspective, the use of fossil kerosene ranks best among the alternatives. A scenario analysis confirms this result and shows that the production of sustainable aviation fuels using an electricity mix based solely on renewable energy can lead to significant reductions in environmental impact, but economic competitiveness remains problematic.

Restructuring of coal mining in Romania between the climate crisis and the energy transition

The Romanian energy market is dependent on about a third of total production on the use of fossil fuels, hard coal and lignite and natural gas, especially in the winter months or dry summers, coal still being of strategic importance in producing electricity and ensuring energetic security. However, the sharp changes in climate in recent years have led to the conclusion of environmental agreements, with objectives aimed at long-term strategies to reduce greenhouse gas emissions and which clearly require a reduction in the capacity to produce one kilowatt of thermal energy and identify solutions for transition to clean energy. Where will the Hunedoara Energy Complex and the Oltenia Energy Complex be located in this context? This paper aims to analyze the process of restructuring coal mining, the competitiveness of coal in the electricity mix and possibly the future prospects of restructured mining areas.

Comparative analysis of AI-based models for short-term photovoltaic power forecasting in energy cooperatives

Energy communities can support the energy transition, by engaging citizens through collective energy actions and generate positive economic, social and environmental outcomes. Renewable Energy Sources (RES) are gaining increasing share in the electricity mix as the economy decarbonises, with Photovoltaic (PV) plants to becoming more efficient and affordable. By incorporating Artificial Intelligence (AI) techniques, innovative applications can be developed to provide added value to energy communities. In this context, the scope of this paper is to compare Machine Learning (ML) and Deep Learning (DL) algorithms for the prediction of short-term production in a solar plant under an energy cooperative operation. Three different cases are considered, based on the data used as inputs for forecasting purposes. Lagged inputs are used to assess the historical data needed, and the algorithms’ accuracy is tested for the next hour’s PV production forecast. The comparative analysis between the proposed algorithms demonstrates the most accurate algorithm in each case, depending on the available data. For the highest performing algorithm, its performance accuracy in further forecasting horizons (3 hours, 6 hours and 24 hours) is also tested.

Small Hydropower Plant for Sustainable Electricity from RES Mix

In the context of the need for an increasing share of renewables in electricity mixes, the paper presents the existing RES mix, PV and wind, for partially covering the electricity consumption of a research institute, ICSTM, and proposes a solution for completion with a third form of RES, a small hydropower plant. Moreover, it is envisaged to include the proposed small hydropower plant as a new real-scale laboratory attached to ICSTM. The method includes the presentation of an existing proposal for increasing installed capacity in new PV panels and propose to install an SHPP to a weir situated a few hundred meters from the institute. The hydropower potential for two possible arrangements is assessed and some types of turbines suitable for this location are presented. The main results demonstrate that building an SHPP is a better solution for completion of PV and wind as source of electricity for ICSTM. The main conclusion of the paper is that by installing new RES capacities, ICSTM can build a real-scale laboratory for new technologies, at the same time fully covering its own electricity consumption and even supplying a green electricity mix into the national power system.

Dynamic LCA of a single-family house, equipped with a micro-cogeneration unit, using a variable share of biomethane

The current study presents the CO2-eq emissions of the operational energy use of a single-family house, equipped with a micro-cogeneration unit. A back-up boiler and electricity from the grid cover the remaining energy demand, not covered by the micro-CHP. Two different technologies are evaluated, i.e. ICE and fuel cell systems, operating with a variable share of biomethane, while two different substrates were considered for the biomethane generation. A dynamic LCA was applied for the electricity mix, coming from the grid, using different time steps. The results show that producing biomethane from biowaste compared to conventional natural gas is beneficial, in terms of CO2-eq emissions, independently of the micro-CHP technology, while the total CO2-eq emissions of the fuel cell technology are higher than those of the ICE, independently of the substrate and the biomethane share.

Preparing the Ecuador’s Power Sector to Enable a Large-Scale Electric Land Transport

The Ecuador’s expansion plans for the power sector promote the exploitation of hydro power potential, natural gas and a small share of alternative renewable energies. In 2019, electricity generation reached 76.3% from hydroelectric power, 21.9% from thermal plants and 1.8% from other renewable resources. Although the power energy mix is mainly based on renewable technologies, the total energy demand is still dependent on fossil fuels, which is the case of the transport sector that alone accounted for 50% of the total primary energy consumed in the country. This paper analyzes the pathway to develop a clean and diversified electricity mix, covering the demand of three specific development levels of electric transportation. The linear optimization model (urbs) and the Ecuador Land Use and Energy Netwrok Analysis (ELENA) are used to optimize the expansion of the power system in the period from 2020 to 2050. Results show that reaching an electricity mix 100% based on renewable energies is possible and still cover a highly electrified transport that includes 47.8% of land passenger, and 5.9% of land freight transport. Therefore, the electrification of this sector is a viable alternative for the country to rely on its own energy resources, while reinforcing its future climate change mitigation commitments.

Influence of Attitudes on Willingness to Choose Time-of-Use Electricity Tariffs in Germany. Evidence from Factor Analysis

Time-of-use (TOU) electricity tariffs are a demand side measure to ease balancing of demand and supply to cope with a rising share of renewables in a country’s electricity mix. In general, consumers require compensation for accepting these tariffs. This study analyzes how attitudes drive consumers’ willingness to choose a TOU tariff in Germany. To identify attitudinal profiles, I use an exploratory factor analysis on items capturing positive and negative attitudes towards TOU tariffs, climate change awareness, and belief in energy saving measures. I use these factors as predictors in an ordered logit specification to estimate consumers’ stated willingness to choose a TOU tariff. Three factors are significant: positive and negative attitudes towards TOU tariffs, and climate change awareness. These findings highlight that decision makers who aim at balancing demand and supply through the use of TOU tariffs should focus on informing consumers about the positive impacts of these tariffs on climate change mitigation, grid stability, and possible energy savings.