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In pursuit of energy transition objectives, Algeria is increasingly focusing on the production and utilization of low-carbon and renewable hydrogen. While hydrogen has predominantly been used in the chemical and refining industries, it holds promise for decarbonizing specific industrial sectors, enabling electricity storage, and powering the transport sector. However, several barriers must be overcome before hydrogen technologies can be widely deployed. Numerous countries, with Japan at the forefront, are heavily investing in this burgeoning market, anticipating the creation of thousands of new jobs. Hydrogen offers Algeria significant potential for greenhouse gas (GHG) reduction and substantial economic benefits. In response, the Algerian government has prioritized energy transition to new and renewable sources as part of its economic recovery plan, aiming for "green" growth through innovative and digital energy technologies. This paper's primary objective is to provide a techno-economic foundation for guiding public policy development, identifying promising opportunities for green hydrogen within Algeria's energy transition context, and outlining sustainable pathways for pilot projects that promote hydrogen adoption within the Algerian society. Additionally, this paper will explore the latest advancements in hydrogen research, technology, and applications relevant to the Algeria's energy transition. The Algerian energy minister, has reaffirmed his desire to "invest in hydrogen", an energy source presented as one of the solutions to the climate crisis. In October 2021, Algeria launched a hydrogen plan worth several billion dinars, including 100 million for research, to enable the country to develop "green" hydrogen, i.e. produced without fossil fuels. • Algeria's energy transition mission focuses on promoting energy transition, innovation, and efficiency. • The Algerian Strategy on Green Hydrogen 2050 intends to establish a supportive framework for hydrogen sector development. • Algeria has set ambitious targets: reducing its GHG emissions by 2030 and lowering its consumption of petroleum products. • Algeria export between 30 and 40 TWh by 2040 of gaseous green hydrogen, liquefied, and derived. [ABSTRACT FROM AUTHOR]

Renewable energy sources, driven by the global concern for climate change and the urgent need to reduce greenhouse gas emissions, are gaining increasing importance. Among them, solar energy stands out as a crucial renewable source and accurate solar irradiance forecasting is vital for its effective utilisation. Deep learning (DL) techniques have emerged as state-of-the-art solar irradiance forecasting methods in past years. However, traditional models that are widely used have inferior accuracy in forecasting. To bridge this gap, this paper presents an improved state-of-the-art model that leverages the convolutional property to forecast the time series data. We got a reduction of 8.32% in MAE compared to the base model. The paper's findings highlight the potential of DL-based approaches to significantly improve the accuracy of solar irradiance forecasts. [ABSTRACT FROM AUTHOR]

Asia, the continent most vulnerable to climate change, presents policymakers with the dual challenges of significant income inequality and a scarcity of alternative energy sources. This paper investigates the impact of climate change on income inequality, and the role of renewable energy in moderating this impact for a panel data set of 36 Asian countries over the period of 1990–2021. Results from panel data analysis techniques show that climate change exacerbates the income inequality while renewable energy not only reduces income inequality but also lessens the detrimental impact of climate change on income equality through the channels of job creation and access to renewable energy. Remarkably, the role of renewable energy becomes stronger in those countries that are more exposed to climate change. The findings are robust with different estimation methods as well as various proxies of climate change and income inequality. These results highlight the critical role of renewable energy policies in promoting both environmental sustainability and socioeconomic equity. Through this paper, we aim to provide invaluable insights that can aid policymakers in making informed decisions to advance a future marked by sustainability, equity, and resilience. [ABSTRACT FROM AUTHOR]

Renewable energy has demonstrated a significantly greater increase in its share of total energy consumption than carbon emissions in recent decades. This rise in renewable energy consumption did not effectively mitigate climate change, as evidenced by the accelerated rate of climate change. This paper aims to determine the cause of this failure by examining the total effect centrality and mediating effects of renewable energy in economic systems in the short run and long run. The total effect centrality and mediating effects of renewable energy illustrate the evolution of its overall impact on the major variables of an economic system and its role in mediating the indirect effects of these variables on carbon emissions, respectively. The study employs a recently developed network analysis that is a pioneer in the estimation of the time-varying total effect centrality and time-varying mediating effects of renewable energy, while also accounting for its cross-associations among all variables in a network. The study derives three conclusions by examining the three countries with the highest carbon emissions in their respective regions: the United States in North America, China in Asia, and Germany in Europe. First, renewable energy has become an essential element of economic systems, having a substantial total effect centrality on macroeconomic systems and, by way of its mediating effects, substantially mitigating the indirect effects of major macroeconomic variables on carbon emissions in the short run. Second, the total effect centrality and mediating effects of renewable energy diminish in the long run, indicating that its capacity to effectively mitigate climate change remains constrained in structural terms. Third, the long-term decline in total effect centrality rises by 0.3, 0.7, and 0.4 for the United States, Germany, and China, respectively. In the same nations, the long-term decline of mediating effects rises by 0.2, 0.4, and 0.2, respectively. The study provides pertinent policy recommendations on how to augment the total effect centrality and mediating effects of renewable energy in economic systems. [Display omitted] • Explains why renewable energy failed in curbing the accelaration of climate change. • Introduces the 'total effect centrality' of renewable energy in economic systems. • Illustrates the time-varying mediation role of renewable energy in economic systems. [ABSTRACT FROM AUTHOR]

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs. • We generate climate change-informed load and renewable energy production profiles. • We extend a design-and-dispatch problem to a two-stage stochastic program. • Cases with high variation in annual renewable output show the methodology's value. [ABSTRACT FROM AUTHOR]

• Analyzes South Asia's energy trilemma balancing energy access, security and sustainability. • Focuses on four major regional countries: India, Pakistan, Bangladesh, and Sri Lanka. • Identifies major challenges as lack of energy access, unreliable gird, and unaffordable prices. • Explores the prospects of renewable energy as the key toward a sustainable energy transition. • Presents stakeholder perspectives on crucial dynamics of energy transition. To address the faced challenges – i.e. rapidly growing energy needs, depleting fossil fuel reserves, surging energy prices, risks to security of supplies, and climate change – the World is targeting a sustainable energy transition. This energy transition is primarily propelled by a global decarbonization drive. South Asia, a developing region housing over 23% of the global population, faces the additional challenge of serious energy deprivation. The subject of energy transition has not been explored in the South Asian context in terms of drivers, challenges, and prospects. This paper investigates the prospects of sustainable energy transition in South Asia in terms of resources, consumption trends, and challenges encountered by countries in the region, particularly India, Bangladesh, Pakistan, and Sri Lanka. It also examines the sustainable and renewable energy options for the region. An original stakeholder survey provides salient behavioral insights into awareness, attitudes and opinions shaping societal response to energy transition. The findings of the study highlight the serious energy security issues faced by the region in terms of lack of access, inconsistent supplies, unreliable grids, and high energy prices. Renewables like solar energy, wind power, and hydropower have the potential to propel regional countries to energy and environmental sustainability. "Lack of consistent policies and regulations", "lack of political will" and "lack of investment" are found to be the three most important challenges to the energy transition. [ABSTRACT FROM AUTHOR]

France is one of the countries that have made commendable progress towards accomplishing sustainable development goals but still struggles with combating environmental challenges. Decarbonizing the energy sector by deploying clean energy and reducing fossil fuels in the energy mix are essential steps. The study uses annual time series data from 1980 to 2021 and employs the ridge regression estimation technique to estimate a twice-differentiable transcendental production function, which approximates the second-order Taylor series to explore the potential for such decarbonization for France. The study finds that substitution possibilities exist between clean energy and fossil fuels, with substantial substitution possibilities coming from nuclear energy. Nuclear energy and renewables are found to be complements that can be deployed concurrently, but since nuclear energy already constitutes a significant proportion of clean energy for France, the study recommends increasing the proportion of renewable energy in the overall energy mix as the most plausible path to decarbonization. Other complementary sustainable energy policies are recommended in the body of the paper. • The substitution elasticities between clean energy and fossil fuels were estimated. • A second-order Taylor series trans-log production function was specified. • Substitutability is found between clean energy and fossil fuels. • Nuclear energy currently dominates France's clean energy mix. • Increasing renewables in the clean energy mix is recommended. [ABSTRACT FROM AUTHOR]

This research paper proposes a novel multi-model approach, integrating the CARIMA-SARIMA-GPM framework, to assess the combined impacts of climate change and land use change on the potential of concentrated photovoltaic (CPV) systems. By considering both climatic variables and land use patterns, this study aims to provide a comprehensive understanding of how these factors influence CPV performance in the context of a changing environment. The proposed methodology offers valuable insights into the future viability and sustainability of CPV technology, enabling informed decision-making for policymakers, energy planners, and investors in the Middle East and Africa. As a result, the ability of the hybrid evolutionary CARIMA-SARIMA-GPM to predict the potential of CPV energy output for assessing the impacts of climate change on it was investigated in Alice Springs, the Middle East, and Africa. The outcome showed that the hybrid model significantly outperformed the other machine learning approaches. The fitted model was used to assess the potential impacts of climate change on CPV generation in Alice Springs, Australia, as well as the Middle East's and Africa's comparable climatic conditions. According to the study, climate change had the greatest impact on solar CPV energy production in Alice Springs, where it decreased the most by 8.577% under moderate forcing scenarios (SSP245) during the boreal summer season; moderately in the Middle East, where it decreased the mode by 2.316% under mitigation scenarios (SSP126) during the boreal summer season; and extremely minimally in Africa, where it decreased the mode by 1.263% under the far future sequencing period (2051–2099). Climate change also increased solar CPV energy production significantly in the Middle East in the far future sequencing period (2051–2099), as well as in Alice Springs, Australia, and Africa in the near future sequencing period (2015–2050). The strongest forcing scenario (SSP585) increased by 7.644% during the boreal autumn season in Africa; moderately increased by 6.502% during the boreal spring season in the Middle East; and had the least beneficial effects in Alice Springs, Australia, with increases of 5.538% during the boreal winter season. On an annual basis, all three regions showed a similar trend. Climate change (CLC) and urban expansion (URE) were also investigated in the Middle East and Africa for their effects on changes in solar CPV energy output. URE had a greater impact in Africa than the Middle East under the effective scenario, with a URE value of 45.45% for Africa and 20.15% for the Middle East, whereas CLC had a greater impact in the Middle East than Africa, with a CLC value of 29.01% compared to 5.47% for Africa. CLC and CPV residual factors, on the other hand, have a greater impact in the Middle East than in Africa, with effects of 29.01% and 50.83%, respectively, compared to 5.47% and 49.09%. The potential difference that drives the remediation of specific pollutants lies in the application of advanced technologies and sustainable practices. By exploring innovative solutions, such as using renewable energy sources like concentrated photovoltaic (CPV) systems, we can effectively mitigate the impacts of climate change and land use changes on pollutant concentrations. These technologies have the potential to significantly reduce pollution levels and create a cleaner and healthier environment for future generations. Assessing the CPV potential in different regions like Alice Springs, Australia, the Middle East, and Africa allows us to identify areas with high solar energy resources that can be harnessed for efficient pollutant remediation. Implementing prompt climate mitigation and adaptation measures is crucial for achieving a net-zero energy transition in the Middle East and Africa by 2050. In this context, prioritizing solar energy as the primary source of renewable energy is imperative for successful low-carbon economic planning in these regions. • CARIMA-SARIMA-GPM outperforms other applicable models • By 2100, the CPV potential in Alice Springs could increase by 0.082–5.338% at 1.5 °C • By 2100, the Middle East's CPV potential could increase by 0.021–0.221% at 1.5 °C. • By 2100, Africa's CPV potential could increase by 0.133–7.644% at 1.5 °C. • Climate change has harmed Alice Springs and the Middle East more than Africa. [ABSTRACT FROM AUTHOR]

Reducing the dependence on traditional energy sources and shifting towards the utilization of renewable energy sources (RES) of energy in the maritime sector is imperative for reducing greenhouse gas emissions. Inherently, RES sources like solar and wind are intermittent and variable, resulting in inconsistent power availability and hence leading to energy supply fluctuations and potential shortages. In this respect, an efficient control strategy to maintain system stability and address intermittency effectively is essential. This work considers a hybrid marine microgrid with various energy sources like photovoltaics (PV), wind energy conversion system (WECS), marine biodiesel generator, Archimedes wave power generation, solid oxide fuel cell, and batteries. A 2-degree of freedom (2DOF) structure is designed and implemented with the tilt-integral-derivative filter (TIDN) to address frequency variations. Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. The stability of the proposed microgrid system is assessed under various combinations of RES availabilities, including real-time data from WECS and PV. The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. Simulation results obtained show that the AOA-based 2DOF-TIDN control strategy achieves shorter settling times in mitigating the changes of marine microgrid systems under different dynamic conditions as compared to the other algorithms. Finally, the controller being proposed in this paper was tested for robustness with parameter deviations of +25%, −20%, and − 40% from the nominal values, and proved to be the proposed 2DOF-TIDN controller parameters demonstrate significant robustness in effectively managing the uncertainties and parametric variations. • Maritime Microgrid system is designed for investigations with RE & storage units. • PV, Wind, MBG, AWPG, SOFC, and battery storage units are considered. • 2DOF-TIDN controller is developed to mitigate the changes in the system. • The AOA method is proposed for optimal gains of the 2DOF-TIDN under uncertainties. • Sensitivity analysis, Time delay analysis, and stability analysis are performed [ABSTRACT FROM AUTHOR]

Open Cycle - Ocean Thermal Energy Conversion (OC-OTEC) is one of the most important renewable energy sources that generate electricity and fresh water from seawater utilizing the temperature gradient between the warm surface seawater and the cold deep seawater. This paper aims to develop non-linear data-driven model-based adaptive Feedback Control (FBC) schemes for the OC-OTEC process to track the output power and a dynamic Feed-Forward Control (FFC) scheme to reject the effects of temperature disturbance on power caused by climate variations in OC-OTEC. The experiments are conducted on a laboratory-scale OC-OTEC experimental setup at the National Institute of Ocean Technology, Chennai. Firstly, linear data-driven models are developed using system identification techniques. Based on the developed models, gain scheduling-based adaptive control schemes are developed: Proportional Integral (PI) control and Model Predictive Control (MPC). Secondly, the closed-loop performances of the developed FBC schemes are analysed under servo and regulatory operations. Furthermore, it is observed from the sensitivity analysis results that the temperature disturbance highly influences output over the manipulated variable. Hence, a dynamic FFC scheme is implemented to reject known disturbance of 1 °C variation in temperature gradient from 18 °C to 19 °C due to Sea Surface Temperature (SST) changes in temperature gradient. The results show that the proposed MPC-based FBC-FF scheme effectively enhances the tracking and disturbance rejection performance compared to the PI-based FBC-FF control scheme with a minimum Integral Square Error (ISE) of 3.055 and Control Effort (CE) of 7.505. This experimental data-based, data-driven modelling and adaptive control research provides a new direction for automating OC-OTEC. Further, these studies will help to develop a rugged and automated upscaling OC-OTEC plant control system with proposed feasible control schemes. [ABSTRACT FROM AUTHOR]

Given the significant energy consumption and carbon emissions associated with buildings, there is increasing interest in improving sustainability of building operations to reduce impact on climate change. A common goal is to operate buildings as "net-zero" energy users in which all energy consumed by the building is balanced against renewable energy purchased from the grid or produced on site. To achieve net-zero status, many buildings will require significant retrofit so as to both reduce energy consumption in the absolute sense and provide the remainder without consuming fossil fuels. Thus, multi-year planning is required to ensure that goals can be met on time. In addition, due to the inherent uncertainty associated with energy consumption and generation, actually achieving net-zero energy use may require discretionary curtailment actions to be taken, and deciding whether such actions are necessary can be challenging. To address these challenges, we propose in this paper a design optimization and operational planning strategy to make the decisions needed to achieve sustainability goals in buildings. The strategy can be applied to schedule design changes over a long horizon to meet annual targets, and it can also be applied in closed loop on a shorter horizon to determine whether curtailment is needed to stay on track. We discuss the formulation of the optimization problem, solution methods, and modeling approaches for key parameters. Application of the strategy is illustrated via examples. Overall, this approach will help automate planning that is often done manually, allowing buildings to take a significant leap forward toward achieving their sustainability goals. • Achieving sustainability goals in buildings requires multi-year planning. • The required design and operational decisions can be made via optimization. • Key problem parameters can be obtained from data-driven modeling. • The strategy allows sustainability goals to be met at minimum cost. [ABSTRACT FROM AUTHOR]

The promotion of renewable energy nowadays is particularly important not only to mitigate the climate change but also to increase the energy independence. Thus, the aim of this paper is to analyse the impacts of attitudes and perception of the war in Ukraine and environmental aspects on selection of green electricity in Lithuania. The survey analysis conducted in early 2023 showed that only 35% of respondents have selected green electricity. Analysis of the main determinants of green electricity selection showed that attitudes towards energy consumption together with the perception of renewable energy environmental impacts (B = 0.13, p < 0.01), as well as attitudes towards the war impact together with the perception of the renewable energy role in solving energy crisis (B = 0.09, p < 0.01), positively and statistically significantly influenced selection of green electricity. Meanwhile, the interaction of attitudes towards the war impact and the perception of the renewable energy role in achieving energy independence insignificantly (B = −0.05, p = 0.06) determined selection of green electricity. From the socio-demographic variables, only age (B = −0.02, p = 0.003) and gender (B = 0.36; p < 0.01) had a significant effect on this behaviour. Thus, this study gives an additional insight for policymakers and green electricity suppliers on how to increase green electricity selection in the context of the war in Ukraine. [ABSTRACT FROM AUTHOR]

Limiting climate heating while meeting basic needs for all necessitates large-scale deployment of renewable energy. Understanding the dynamics of mobilizing materials for the transition requires considering: 1) availability of resources in the environment and technosphere; 2) accessibility depending on resource quality and available technologies; 3) processability depending on energy availability, processing capacity, and impacts on planetary boundaries; and 4) operability depending on social acceptance and geopolitical agreements. Materials can be mobilized through four routes: 1) increasing primary production; 2) diverting existing primary production; 3) repurposing in-use stocks; and 4) re-mining wastes and emissions. The interplay of these enabling factors, material efficiency in design, and substitution with materials that are easier to mobilize determines the maximum possible rate of material mobilization and consequently the energy transition itself. This paper presents and discusses a framework to explore joint energy-material transformations, enabling to consider material aspects in transition modelling and guide technological developments. [ABSTRACT FROM AUTHOR]