Energy Transition Scenarios Research Articles

Energy Citizenship in Energy Transition: The Case of the Baltic States

The governance of energy systems is undergoing a transformative shift, vital to advancing the energy transition. Understanding the dynamics of energy citizenship and the factors that influence citizen engagement in energy matters is critical for driving social and institutional change. This paper informs on the key results of a comprehensive analysis of 54 energy citizenship cases in the Baltic states (Latvia, Estonia, and Lithuania). The study explores the role of citizens in the energy transition and characterizes the socio-economic and geopolitical factors shaping energy citizenship activities in the region. The governance of energy systems represents a significant transformational shift that is essential for energy transition. A more comprehensive understanding of the current state of energy citizenship and the factors influencing the energy transition process could inform the social and institutional changes necessary for the involvement of citizens in energy matters. This desk study represents a crucial element of the EU Horizon 2000 EnergyPROSPECTS project, which aims to map the landscape of energy citizenship in Europe. This paper presents an in-depth analysis of 54 cases from the Baltic states. The findings provide insight into the role of citizens in the transition process and the underlying factors and conditions that shape energy citizenship activities within the specific socio-economic and geopolitical context of the region. In general, energy citizenship in the Baltic states can be seen to exist on a spectrum between reformative and transformative practices. Overall, progress is being made toward systemic changes in the energy sector, with a focus on the democratization of processes. Nevertheless, additional measures to enhance and reinforce energy citizenship, coupled with the advancement of enabling conditions, are imperative at all levels of governance and across all energy transition scenarios.

The impact of spatial representation in energy transition modelling on systemwide energy return on investment

AbstractAdopting aggregation techniques in power sector modelling led to disregarding the key characteristics of regions in terms of resource use, which may not completely capture the bottlenecks in the energy transition. This study provides a holistic approach to estimate its impact on the transition of the European power system from the perspective of energy return on investment (EROI) by using six energy transition scenarios based on three different spatial representations. The findings indicate that EROI trends are highly dependent on the spatial representation, technology selection and energy mix. Further additional capacities of complementary technologies along with an upsurge in renewable capacities drive EROI values down. Disregarding the physical distances in the energy modelling results in large EROI enhancement due to the artificial smoothing effect of the aggregation method. EROI values of the aggregated scenarios remain between 18 and 24 by 2050. In the case of 20 independent sub‐regions, the lowest EROI is obtained at about 14 by 2050, due to the limitation on optimal resource utilisation. Interconnection of the sub‐regions, which represents the best proximation to the real situation, increases the EROI to 17 by 2050.

ОРГАНІЗАЦІЙНО-ЕКОНОМІЧНІ СКЛАДОВІ ПРОГРАМ РОЗВИТКУ ЕЛЕКТРИЧНИХ МЕРЕЖ

In the article researched the indicators that directly depend on the state of electrical networks. The first of them is the level of reliability of electricity supply, the indicators of which are the SAIDI and SAIFI indices. The domestic indicators of the specified indices significantly exceed the level in the countries of the European Union and to date have no signs of a decrease. Plans for reducing the indicator SAIDI have been analyzed in relation to the method of incentive tariffs for operators of distribution systems. The next considered indicator is high technological losses of electrical energy. It was analyzed that the volume of these losses has a growing trend and also significantly exceeds the average European level. The main reason for these phenomena is the outdated and worn-out condition of electrical grids, which, given the damage caused by missile strikes and shelling, tends to worsen. Proposals have been identified that in the future may help improve the condition of grids and eliminate a number of problematic phenomena Their main problems and approximate volumes of priority grids modernization were summarized. Possible practical measures aimed at helping to reduce technological losses of electricity are considered. The structure of the proposed traditional measures necessary to manage the development of networks and consumers were analyzed. It has also recently started in Ukraine development and approval of a set of documents which are directed to the implementation of the Energy Transition scenario and the implementation of the Smart Grid concept. The further need for the development of system and program documents at both the state and regional levels was identified. It is proposed to include in these documents a number of organizational and economic components which will most effectively contribute to the achievement of the set goals.

President’s Column: SPE@Energy Transition

_ Editor’s Note: This is a summary of the October episode of the President’s vodcast. We encourage you to watch the episode to see the full conversation. In this vodcast, Houzé discusses his views on SPE and the energy transition. _ Last month, I presented a to-do list with five main topics: energy transition, finances, governance, membership, and quality. This month, I will discuss the first topic, energy transition. 1. SPE’s polarized views on energy transition As I mentioned last month, there are significant geographic contrasts within our industry and SPE regarding how the energy transition is perceived and developed. In some SPE venues and regions, energy transition is the dominant, if not the only subject, and the P in SPE is indeed a major obstacle for support, even from our traditional stakeholders. In other regions, stakeholders acknowledge the energy transition, but the situation is essentially business as usual. Major investments are underway to sustain production at current levels or even increase hydrocarbon production to record levels, with development plans spanning over several decades. Even in these regions, most, if not all, new projects are designed from the outset to have a low carbon footprint, including mitigating methane emissions. Energy transition is somehow factored in. So, there are very different narratives, which are reflected in a polite but real polarization within SPE—geographic and, occasionally, demographic. As an SPE President visiting many sections and stakeholders, the contrast is often striking. But we are engineers operating on the same planet, and there must be a single energy narrative that accounts for the reality of the energy transition in whatever form or definition this takes, locally or globally. To do this, we can try to assess in the most objective way possible how our license to operate may evolve in the short to medium term. I will start with something you may have seen many times: the three main energy transition scenarios presented by the International Energy Agency (IEA). These scenarios predict the climate impact by the end of the century based on current and predicted variables, including consumption, population, economics, and technologies. These are just models, but as the statistician George Box pointed out: “All models are wrong, but some are useful.” These IEA models are definitely useful (Fig. 1).

Robots for the Energy Transition: A Review

The energy transition relies on an increasingly massive and pervasive use of renewable energy sources, mainly photovoltaic and wind, characterized by an intrinsic degree of production uncertainty, mostly due to meteorological conditions variability that, even if accurately estimated, can hardly be kept under control. Because of this limit, continuously monitoring the operative status of each renewable energy-based power plant becomes relevant in order to timely face any other uncertainty source such as those related to the plant operation and maintenance (O&M), whose effect may become relevant in terms of the levelized cost of energy. In this frame, the use of robots, which incorporate fully automatic platforms capable of monitoring each plant and also allow effective and efficient process operation, can be considered a feasible solution. This paper carries out a review on the use of robots for the O&M of photovoltaic, wind, hydroelectric, and concentrated solar power, including robot applications for controlling power lines, whose role can in fact be considered a key complementary issue within the energy transition. It is shown that various robotic solutions have so far been proposed both by the academy and by industries and that implementing their use should be considered mandatory for the energy transition scenario.

Demonstrating clean energy transition scenarios in sector-coupled and renewable-based energy communities.

Energy communities facilitate several advantages, including energy autonomy, reduced greenhouse gas emissions, poverty mitigation, and regional economic development. They also empower citizens with decision-making and co-ownership prospects in community renewable projects. Integrating renewable energy sources and sector coupling is a crucial strategy for flexible energy systems. However, demonstrating clean energy transition scenarios in these communities presents challenges, including technology integration, flexibility activation, load reduction, grid resilience, and business case development. Based on the system of systems approach, this paper introduces a 4-step funnel approach and a 4-step reverse funnel approach to systematically specify and detail demonstration scenarios for energy community projects. The funnel approach involves four steps. First, it selects demonstration scenarios promoting energy-efficient state-of-the-art renewable technologies and storage systems, flexibility through demand side management techniques, reduced grid dependence, and economic viability. Second, it lists all existing and planned project technologies, analysing energy flows. Third, it plans actions at different levels to implement the demonstration scenarios. Fourth, it validates the strategies using key performance indicators (KPI) to quantify the effectiveness of the planned measures. Furthermore, the reverse funnel approach delves deeper into the demonstration scenarios. The four steps involve identifying stakeholder perspectives, describing scenario scopes, listing conditions for realisation, and outlining business models, including value chains and economic assumptions. This approach provides a detailed analysis of the demonstration scenarios, considering actors, objectives, boundary conditions, and business assumptions. The methodologies are exemplified in three diverse European energy communities extending across residential, commercial, tertiary, and industrial establishments, allowing power-to-x and sector coupling opportunities. The paper also suggested thirteen KPIs for validating renewable-focused energy community projects. Finally, the paper recommends increased collaboration between energy communities, knowledge sharing, stakeholder engagement, transparent data collection and analysis, continuous feedback, and method improvement to mitigate policy, technology, business, and market uncertainties.

Sulfured FeMo carbides and nitrides catalysts upgrade extra heavy crude oil quality

In the context of the energy transition scenario, effective sulfur management is crucial. Enhancing the quality of extra heavy crude oil (EHCO) through catalytic processes, specifically hydrotreatment, is essential for reducing pollutant emissions like SOx into the atmosphere. Traditional hydrotreatment, utilizing MoS2-based catalysts typically on Al2O3 support, faces challenges with EHCO due to its elevated S and N content, which hampers catalyst efficiency. Metal carbides and nitrides exhibit promising electronic structures that confer resistance to deactivation in the presence of heteroatoms. This study compares the catalytic performances of Fe-promoted Mo sulfides, carbides, and nitrides (FeMoS(C,N)) in the thiophene hydrodesulfurization (HDS) reaction, serving as a model molecule for sulfur removal. Subsequently, we investigate the upgrading of a Venezuelan EHCO in terms of pollutant reduction, API gravity, and feedstock aromaticity. Catalysts were prepared from oxide precursors, varying the (Fe/(Fe+Mo)) atomic ratios (x = 0.00, 0.10, 0.33, 0.50, and 1.00), employing a temperature-programmed reaction protocol. Catalytic upgrading of EHCO was conducted in a stirred batch reactor, and the results were compared with a commercial CoMo-based catalyst. FeMoC(N) outperformed the commercial catalyst in sulfur removal. The elemental composition and nitrogen content of the feed remained constant; however, the sulfur content of asphaltenes decreased. Furthermore, the API gravity of crude oil increased when employing FeMoS and FeMoN catalysts, except with FeMoC, possibly linked to dealkylation reactions and the enrichment of lighter fractions with alkanes. FeMoN increased asphaltene aromaticity, while FeMoC decreased it. These results highlight the promise of FeMoC(N) as catalysts for HDS and upgrading heavy feedstocks.

Exploiting exergy and exergoeconomic analysis as decisional tool for cogeneration plant optimal operating mode: A sugar factory case study

Due to the energy transition scenario, the efficient use of energy and operations flexibility to deal with the market volatility have become the major concerns of the industrial sector. In particular, in those contexts and countries where the grid supply cannot be continuously ensured, the selection of the best operation set up is of critical importance for both stability and profitability of the system. Based on the available data of the Wonji-Shoa sugar factory in Ethiopia, the digital twin of the related Combined Heat and Power generation plant was reproduced by means of ProSimPlus® process simulator. Thanks to the software dedicated tools, the exergy and exergoeconomic analysis were carried out to compare the performances of three possible functioning modes. The study revealed that the highest profitability for the power plant is achieved when it serves both the sugar factory and the electricity grid. With regard to the energy efficiency, the prevention of exergy losses up to 9.63 MW is possible and a 15% heat recovery potential could be viable by implementing a better integration between utility streams. Based on these results, the optimal combined scheduling of power plant and sugar factory will be the object of future studies.

The impact on climate and emissions of clean household cooking energy policies in Tanzania

The transition to cleaner cooking fuels currently ongoing in many low- and middle-income countries may have benefits for health, but also climate. We have studied the climate implications of the SE4ALL policy goal in Tanzania of “75 percent access to modern cooking solutions by 2030” in which mainly firewood and charcoal are replaced by LPG and electricity. To see the long-term climate benefit, we have estimated the reduction in CO2-equivalent emissions (GWP100) and effect on global temperature until 2100 relative to the baseline for three explorative scenarios with different levels of ambition: baseline growth to nearly complete transition to modern cooking. Due to population growth the energy demand and CO2-eq. emissions increase even in the most ambitious energy transition scenario. We model reduction in global temperature in 2100 relative to the baseline to be between −0.63 and −2.9 milli °C. While we confirm the climate benefit of a transition to cleaner cooking fuels in households, the benefit is smaller than previously thought. This is mainly due to a much weaker radiative forcing of black carbon and somewhat stronger radiative forcing for organic carbon, in the climate parameters from IPCC Sixth Assessment Report.

Estimation of useful-stage energy returns on investment for fossil fuels and implications for renewable energy systems

The net energy implications of the energy transition have so far been analysed at best at the final energy stage. Here we argue that expanding the analysis to the useful stage is crucial. We estimate fossil fuelsʼ useful-stage energy returns on investment (EROIs) over the period 1971–2020, globally and nationally, and disaggregate EROIs by end use. We find that fossil fuelsʼ useful-stage EROIs (~3.5:1) are considerably lower than at the final stage (~8.5:1), due to low final-to-useful efficiencies. Further, we estimate the final-stage EROI for which electricity-yielding renewable energy would deliver the same net useful energy as fossil fuels (EROI equivalent) to be approximately 4.6:1. The EROIs of electricity-yielding renewable energy systems, based on published estimations, are found to be higher than the determined EROI equivalent, even considering the effects of intermittency under a range of energy transition scenarios. Results suggest that the energy transition may happen without a decline in net useful energy, countering the view that renewable energy systems cannot replace fossil fuels without incurring a substantial energy penalty.

Drivers and implications of alternative routes to fuels decarbonization in net-zero energy systems

Energy transition scenarios are characterized by increasing electrification and improving efficiency of energy end uses, rapid decarbonization of the electric power sector, and deployment of carbon dioxide removal (CDR) technologies to offset remaining emissions. Although hydrocarbon fuels typically decline in such scenarios, significant volumes remain in many scenarios even at the time of net-zero emissions. While scenarios rely on different approaches for decarbonizing remaining fuels, the underlying drivers for these differences are unclear. Here we develop several illustrative net-zero systems in a simple structural energy model and show that, for a given set of final energy demands, assumptions about the use of biomass and CO2 sequestration drive key differences in how emissions from remaining fuels are mitigated. Limiting one resource may increase reliance on another, implying that decisions about using or restricting resources in pursuit of net-zero objectives could have significant tradeoffs that will need to be evaluated and managed.

Towards Just Energy Transition: Renewable Energy Transition Dynamics and Sectorial Employment in Ghana

Energy transition and the creation of sustainable jobs are major concerns towards achieving Sustainable Development Goals (SDGs) 7 and 13, particularly in emerging petroleum-producing economies such as Ghana. Our study examines Ghana’s sectorial employment vulnerability to the dynamics of energy transition. Employing a dynamic ARDL simulation model, we use quarterly data from 2011 to 2021 from Ghana’s Energy Commission, the Bank of Ghana, and the Public Interest and Accounting Committee. We find that transition scenarios increase industrial sector employment. Also, industrial sector employment changes more favorably under the 5% scenario than under the 1% scenario. Agriculture industry employment is positively impacted by the 1% energy transition scenarios but negatively impacted by the 5% scenarios. Up to the sixth year, both transition scenarios increase employment in the services sector; however, employment opportunities are more affected by the 1% scenario than by the 5% scenario. Therefore, developing a policy architecture that aids Ghana’s transition to renewable energy is essential.

Balancing the books: unveiling the direct impact of an integrated energy system model on industries, households and government revenues

BackgroundThe transition towards a sustainable energy system is reshaping the demand for final energy, driven by the diffusion of new end-use technologies. This shift not only impacts consumers’ energy expenses, but also holds implications for the public budget. Building on data from a German energy transition scenario, we analyse the direct impact of energy costs on industries, low-income households, and changes in government revenues from the taxes and levies on final energy carriers. Our analysis considers the impact of current policies and explores a scenario introducing additional excise tax rates to offset potential revenue losses.ResultsWe found that substantial carbon price increases could generate revenues that offset the losses from excise taxes on fossil fuels while enabling the financing of renewable support from the public budget by the end of this decade. Nevertheless, a decline in government revenues from taxes and levies is anticipated after 2030 until the middle of the century due to the declining use of fossil fuels. Maintaining current excise tax revenues during the transition could be achieved by introducing additional excise taxes on fossil fuels and electricity. Lastly, our analysis indicated a continuous decline in household energy expenditures until 2050, whereas energy-intensive industries face adverse impacts due to decarbonisation.ConclusionsThis research provides valuable insights into the fiscal implications of the energy transition, shedding light on different industrial sectors and households while considering the evolving impact on the public budget. Policymakers may need to consider systemic reforms or alternative financing mechanisms outside the energy system to balance the books.

Synergistic emission reductions and health effects of energy transitions under carbon neutrality target

China's climate and environmental problems remained prominent. Energy transition was the key to improve climate and pollution, and it was at a critical period. Previous studies mostly focused on the impact of climate policies on the reduction of air pollutants and the environmental health impacts of individual sector or pathway policies. Thus, focusing on the synergistic abatement of CO2 and air pollutants and health effects of energy transition in carbon neutrality was significant for building beautiful and healthy China. LEAP-HEA model was constructed to project energy demand, CO2 and air pollutants, and assess energy transition's environmental health effects from 2020 to 2060. LMDI model was adopted to decompose the abatement contribution. Synergistic assessment index was used to estimate the coordinated abatement effects. Cost-effectiveness of energy transition and regional heterogeneity of PM2.5 toxicity were not considered. The results indicated: (1) energy demand would decrease and structure would be optimized significantly under deep energy transition scenario. (2) Deep energy transition could promote earlier realization of carbon neutrality. It would contribute significantly to CO2 and air pollutants abatement with strong synergistic effects. (3) Energy transition would reduce health risks with large economic benefits. Recommendations were proposed based on the conclusions.

The macroeconomic impact of policy measures, technological progress and societal attitude in energy transition scenarios

This paper compares the macroeconomic impacts of different decarbonization storylines until 2050 using two Computable General Equilibrium models. The modeling shocks are harmonized across models to simulate four decarbonization scenarios through three main drivers: technical development, societal attitude, and policies. The study explores the contribution of each of these drivers to the European decarbonization. The results show that the decarbonization scenarios have moderate effects on GDP; decarbonization scenarios rather result in sectoral shifts. The impact of temperature on labor productivity minimally alters expected growth levels, since larger differences in temperature between the scenarios are only expected to occur in 2100, not yet in 2050. Electricity demand is increasing in all scenarios, particularly with stronger political guidance leading to additional tax and subsidy measures to encourage the use of electricity and discourage fossil-based fuels. When society is a driving factor, it is found that circular business models result in an increase in the service industry but might have a slightly negative impact on overall growth due to stronger spillover effects linked to the manufacturing industry. Technology appears to be the only driver to facilitate decarbonization while maintaining steady economic growth.

Understanding the factors that affect households' investment decisions required by the energy transition.

In energy systems' economic models, people's behaviour is often underestimated, and they are generally unaware of how habits impact energy efficiency. Improving efficiency is challenging, and recommendations alone may not be sufficient. Changing behaviour requires understanding the direct impact of needs and habits on energy efficiency. This research introduces a methodology that retrieves human expert knowledge from four key aspects of the current energy transition: everyday appliances, buildings, mobility, flexibility, and energy efficiency. The aim is to examine the causal relationship between energy consumption and human behaviour, gaining a deeper understanding of the links among the factors that drive final energy consumers to change habits through the adoption of energy-saving measures. Working in collaboration with expert panels, this study provides a methodology for extracting expert human knowledge based on a set of future energy transition scenarios aligned with the achievement of the Paris Agreement, a taxonomy of 32 factors that have a strong influence on households' investment decisions, and the results of a survey that characterises the European population through the 32-factor taxonomy and some socioeconomic conditions. In addition, the survey included a sample of the Latin American population to analyse how socioeconomic conditions (region, education, gender, etc.) influence the prioritisation of these factors. We discuss the high priority given to competence and autonomy over financial factors by inhabitants of the European Union residential sector. We provide an analysis of the factors through which other similar projects are focused and on which we converge. In addition, we contribute by presenting the hierarchy of priorities assigned by people. This highlights the importance for policymakers to take these aspects seriously when implementing energy policy interventions that go beyond purely financial measures and fiscal incentives.

Beyond Personal Beliefs: The Impact of the Dominant Social Paradigm on Energy Transition Choices

Energy transition towards a local resilient energy supply is necessary for energy security. Climate change and the threat of economic collapse are reasons to force society to become less dependent on fossil fuel. Small-scale solutions are expected to be more sustainable, as large-scale integrated networks are featured by complexity and difficult-to-notice vulnerabilities, creating system risks. This paper presents the results of empirical research among a sample of Polish business students (N = 205) on the importance of worldviews for the choice of the energy transition scenario (local solutions vs. large-scale solutions). Worldviews are represented here by the Dominant Social Paradigm (defined for the purpose of this study as the belief that liberal democracy, free markets, and technological development are to solve all type of problems). This study addresses two research questions: (1) Is there a difference in preference for the energy transition scenarios? (2) Does adherence to the Dominant Social Paradigm determine the choice of the scenario for energy transition? The results present a preference for non-cooperative solutions (individual household solutions and large-scale solutions), while no significant relation to the worldviews represented by the Dominant Social Paradigm has been found. The results suggest that preferences for individual and large-scale solutions may be influenced more by institutional factors than by personal worldviews. A policy implication is that a change in the socio-political institutions and strengthening local governance may be a prerequisite for a sustainable energy transition.

Optimized ANN for LiFePO4 battery charge estimation using principal components based feature generation

Electric vehicles (EVs) have gained prominence in the present energy transition scenario. Widespread adoption of EVs necessitates an accurate State of Charge estimation (SoC) algorithm. Integrating predictive SoC estimations with smart charging strategies not only optimizes charging efficiency and grid reliability but also extends battery lifespan while continuously enhancing the accuracy of SoC predictions, marking a crucial milestone in sustainable electric vehicle technology. In this research study, machine learning methods, particularly Artificial Neural Networks (ANN), are employed for SoC estimation of LiFePO4 batteries, resulting in efficient and accurate estimation algorithms. The investigation first focuses on developing a custom-designed battery pack with 12 ​V, 4 Ah capacity with a facility for real-time data collection through a dedicated hardware setup. The voltage, current and open-circuit voltage of the battery are monitored with computerized battery analyzer. The battery temperature is sensed with a DHT22 temperature sensor interfaced with Raspberry Pi. Principal components are derived for the collected battery data set and analyzed for feature engineering. Three principal components were generated as input parameters for the developed ANN. Early Stopping for the ANN was also implemented to achieve faster convergence of the ANN. While considering eleven combinations for ten different optimizers loss function is minimized. Comparative analysis of hyperparameter tuning and optimizer selection revealed that the Adafactor optimizer with specific settings produced the best results with an RMSE value of 0.4083 and an R2 Score of 0.9998. The proposed algorithm was also implemented for two different types of datasets, a UDDS drive cycle and a standard cell-level dataset. The results obtained were in line with the results obtained with the ANN model developed based on the data collected from the developed experimental setup.

Systemwide energy return on investment in a sustainable transition towards net zero power systems

The Glasgow Climate Pact articulated the vital importance of renewables in reducing emissions on the way to net-zero pledges. During the power sector transition, foreseeing conditions affecting the plausibility of pathway options is crucial for specifying an optimal system development strategy. This study examines the net energy performance of nine decarbonisation global energy transition scenarios until 2050 by applying a newly developed systemwide energy return on investment (EROI) model. All scenarios result in an EROI value above the upper limit of the net energy cliff, expected to be around 10. EROI trends heavily depend on transition paths. Once achieving higher renewable energy shares begin requiring significant enabling technologies, EROI continually declines as the shares increase. Shortening the transition period leads to a sharper declining of EROI, which stabilises after achieving 100% renewables. The vulnerability arising from natural gas and oil depletions may have worst impact on EROI of fossil fuels dominated systems.

Multi-source data-driven technology research on carbon emission dynamics prediction in electric power industry

Abstract This paper analyzes the trend of power generation structure and carbon emission changes in the power industry and decomposes and analyzes the influencing factors of carbon emission in the power industry by using the LMDI decomposition method. Combined with the analysis of the influencing factors of carbon emissions in the power industry from 2016 to 2022, the carbon emissions of the power industry in the Yellow River Basin are simulated by the scenario analysis method. Four simulation scenarios were constructed based on the economic scale, industrial structure, industrial electricity consumption intensity, thermal power fuel conversion rate, and power supply structure. The IPSO-LSTM model for carbon emission prediction was created after optimizing the LSTM neural network prediction model. Combining the scenario analysis method to set the amount of changes in the high carbon, baseline, and low carbon scenarios of the influencing factors, the carbon emissions from the power sector in different scenarios are predicted for the years 2025-2035. From 2025 to 2035, the carbon emissions from the power sector in the three scenarios, except for the energy transition scenario, show a trend of increasing, then decreasing, and then increasing over the study period. The energy transition scenario shows a pattern of increasing and decreasing carbon emissions from the power sector.