Search

Agriculture represents the "cause" and the "victim" of climate change. Almost 30 percent of greenhouse gas emissions come from the agricultural sector. They contribute to global warming and therefore significantly affect the sustainability of agricultural production systems. The aim of the paper is to determine which factors have the greatest influence on the greenhouse gas emission from agriculture. For this purpose, a dynamic panel analysis for 26 members of the European Union in the period from 2013 to 2021 in the paper is conducted. The results of the analysis suggest that the capacity for biofuel production, organic agricultural production and greenhouse gas emissions from the previous period have the greatest impact on the same emissions from agriculture. The results of this research can serve policy makers in formulating strategies for the development of food systems that will pollute the environment to a lesser extent and use available resources more rationally. [ABSTRACT FROM AUTHOR]

The current non-renewable energy-based transportation system is getting us places while simultaneously killing us. The global oil and gas markets are the most sizeable - 4677.45 billion-dollar industries - in the world in terms of revenue due to human dependency on fast transportation. In pre-industrial revolution times, the average rate of global temperature increase was 0.13-degrees Fahrenheit. The introduction of fossil fuel-based vehicles has more than doubled those numbers, thus resulting in accelerated global warming. Electrical vehicles have a few challenges of their own that we have discussed in this paper, finding solutions to them are based on Yoichi Hori's paper to make our model more energy efficient. Our model has been validated by researches done in the past, this paper combines the findings of formerly published papers to produce a working model of our current design with proof of concept. To reduce the carbon footprint of coal and fossil fuel-based electricity production, solar energy has been considered to charge the vehicle. It is not only an efficient choice, but it is also economical. It saves the consumer around $1778 annually in fuel cost and 38.5g/km in carbon emissions. Using a wireless charging station solves a major UX design problem, making charging an effortless experience. This method is 88.05% efficient at 31.5A. Supercapacitors have high power densities, therefore, being a good power source for the EV in theory, however, research shows that current supercapacitor technology is unable to perform as a standalone power source. Hence our model combines supercapacitors with conventional batteries to power the EV, additionally a break recovery system stores energy in the supercapacitor. This powers the car's acceleration. Our model priorities the use of materials that can be repurposed hence carbon-based electrodes are used - Graphene is a potential choice as it consists of high energy cycles. [ABSTRACT FROM AUTHOR]

The unflinching upsurge in global warming has put the world into a state of disarray, and policymakers are not sure of what the future holds for the ecosystem. To get the global environment back on track of sustainability, efforts are relentlessly emanating from both developed and developing economies to identify the hindering and enhancing factors. Given the preceding narratives, this paper investigates the tripartite impacts of renewable and nonrenewable energy, trade openness, and institutions on sustainable environment in 54 African countries from 1996 to 2019. The study employs the two-step system generalized methods of moment (SYS-GMM) in estimating the effects of the regressors on four indicators of sustainable environment. Six findings are prominent from the study. First, nonrenewable energy (NRE) and trade openness (TO) hinder sustainable environment, while renewable energy enhances it. Second, the unconditional impacts of institutions drive the path to a sustainable environment. Third, the interaction of institutions with NRE and TO hinders sustainable environment. However, after conducting institutional enhancement estimations, the interactive terms became supportive of sustainable environment. Fourth, the thresholds are policy-relevant across the specifications. Specifically, a 31.11% utilization of nonrenewable energy and 43.75% openness to trade contribute to a sustainable environment. Sixth, the impacts of economic growth and its square empirically support the inverted U-shaped EKC. This study suggests the adoption of carbon-taxing on nonrenewable energy products, price-subsidization for renewable energy goods and services, and institutional quality reforms as pathways towards achieving a sustainable environment in Africa. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

In response to the challenges of global warming and the development of A low-carbon economy, the integrated electricity and natural gas energy system (IEGES) is known as an important structure for future energy supply; thus, its planning and design must take low-carbon and environmental protection factors into account. Regarding carbon emissions as an optimization criterion, this paper built life-cycle carbon emission models of IEGES components. Then, taking the capacities of the energy resources, storage and conversion units of IEGES as the optimization variables, a multi-objective optimization configuration model was established considering the annual investment operation cost and the life-cycle carbon emissions. The multi-objective model was transformed into a single-objective one by an ε-constraint approach and the polynomial fitting method was employed to obtain the value of ε for obtaining uniformly distributed Pareto sets. Based on the fuzzy entropy weight method and the fuzzy affiliation degree approach, the obtained Pareto sets were ranked and the solution with the highest ranking value was selected as the optimal solution for the original problem. Finally, the configuration schemes were analyzed from the perspectives of economy, carbon emission and renewable energy utilization, and the effectiveness and rationality of the proposed optimization method were verified through MATLAB simulation. [ABSTRACT FROM AUTHOR]

Climate change has become a global challenge due to its critical impact on the natural as well as the human environment. This article focuses on the effects of climate change in the Middle East (ME) region and the strategies suggested to combat its impacts. The research involves reviewing and analyzing published articles from major databases in this domain. The literature shows that countries in the ME region, with a particular focus on the Arab countries, have also realized that urgent actions should be taken to decrease climate change threats. Several countries are committing to international principles, supporting the global effort against climate change, such as adopting renewable sources for efficient energy production. Moreover, some of the ME region countries are considered a hub for emitting CO2 because of their hot climate, which requires the use of energy for air-conditioning, highwater desalination demands due to water scarcity, and the dependence on energy-exhaustive industries. Recently, Saudi Arabia, Qatar, and the United Arab Emirates have proposed strict measures to reduce their energy consumption and move towards renewable energy sources like solar and wind energy. Some countries have also funded projects for developing green buildings to create a sustainable environment. However, this paper emphasizes the need to establish strict regulations to impose policies and practices to achieve the global temperature rise limit below 1.5oC. Moreover, all ME countries must invest in renewable energy sources by promoting education, research, and implementing carbon pricing mechanisms. Nevertheless, as part of the Paris Agreement and other international commitments, there is a growing need to develop more socioeconomic policies to meet this vision. [ABSTRACT FROM AUTHOR]

EV development is being prioritized in order to attain the target of net zero emissions by 2050. Electric vehicles have the potential to decrease greenhouse gas (GHG) emissions, which contribute to global warming. The driving range of electric vehicles is a significant limitation that prevents people from using them generally. This paper proposes a comprehensive model for calculating the amount of energy needed to charge EVs for a scheduled trip. The model contains anticipated consumption energy for the whole trip as well as contingency energy to account for unpredictable conditions. The model is simple to apply to various types of electric vehicles and produces results with sufficient precision. A number of driving tests with different road characteristics and weather conditions were implemented to evaluate the success of the proposed method. The findings could help the users feel more confidence when driving EVs, promote the usage of EVs, and advocate for the increased use of green and renewable energy sources. [ABSTRACT FROM AUTHOR]

Global warming is one of the most challenging issues of the current era. Revolutions in industrial, Information and Communication Technology (ICT) sectors significantly contribute in increasing global warming. Green House Gases (GHG) emissions from industrial, transportation, power and other sectors cause environmental pollution, which results in climate degradation. Environmental experts are well aware of the disastrous consequences of excessive global warming; therefore, several decarbonization strategies are developed and practiced in the recent past. A widely practiced decarbonization strategy is replacing fossil fuels by Renewable Energy Sources (RES) in the power systems. Electricity consumers are also encouraged to shift their consumption load to low carbon emissions' time periods. For accomplishing this task, an estimation of future carbon emissions is required. In this paper, power system's carbon emissions are predicted accurately with the help of a novel and an efficient forecasting model. The proposed model comprises of Spearman Correlation Analysis (SCA) and Improved Shallow Denoising Autoencoder (ISDAE) based feature engineering. Forecasting is performed through an Improved Particle Swarm Optimization (IPSO) based Deep Neural Network (DNN) forecaster. In addition, a comprehensive quantification analysis is also presented in this paper. The impacts of RES integration level on the electricity price, consumption cost and Greenhouse Gases (GHG) emissions are quantified descriptively and graphically. Performance of the proposed forecasting model is evaluated by Normalized Root Mean Square Error (NRMSE), Mean Absolute Error (MAE) and Mean Square Error (MSE). Simulation results prove that the proposed model outperforms Support Vector Machine (SVM) and Multiple Linear Regression (MLR) based carbon emission forecasting models in terms of forecasting accuracy. [ABSTRACT FROM AUTHOR]

This paper explores the effects of climate change on the wind energy input (WEI) to the surface waves (SWs) in the northern Indian Ocean (NIO), a region with great potential for green renewable energy from waves and wind. We used the newly developed Coupled Model Intercomparison Project Phase 6 (CMIP6) model data to predict the spatiotemporal variations of the WEI to the SW. We found that, under the global warming scenario, the WEI to the SWs decreased significantly in most of the NIO, and it will drop by 18% to 27% in the central and southern regions by the end of the 21st century under the SSP5–8.5 scenario. However, the WEI to the SWs increased in the Red Sea, Persian Gulf, northwestern Arabian Sea, and northern Bay of Bengal, with the largest increase in the Persian Gulf region (up to 27%). We also examined the interannual and interdecadal variability characteristics of the WEI to the SW after the accumulation of the whole study region and found that it showed a long-term increasing trend only under the SSP1–2.6 scenario, while it showed a significant decreasing trend under the SSP2–4.5 and SSP5–8.5 scenarios. Furthermore, we show that the WEI to the SWs in the Indian Ocean mainly occurs in summer, followed by winter. [ABSTRACT FROM AUTHOR]

Renewable energy sources are being expanded globally in response to global warming. Solar power generation is closely related to solar radiation and typically experiences significant fluctuations in solar radiation hours during periods of high solar radiation, leading to substantial inaccuracies in power generation predictions. In this paper, we suggest a solar power generation prediction method aimed at minimizing prediction errors during solar time. The proposed method comprises two stages. The first stage is the construction of the Solar Base Model by extracting characteristics from input variables. In the second stage, the prediction error period is detected using the Solar Change Point, which measures the difference between the predicted output from the Solar Base Model and the actual power generation. Subsequently, the probability of a weather forecast state change within the error occurrence period is calculated, and this information is used to update the power generation forecast value. The performance evaluation was restricted to July and August. The average improvement rate in predicted power generation was 24.5%. Using the proposed model, updates to weather forecast status information were implemented, leading to enhanced accuracy in predicting solar power generation. [ABSTRACT FROM AUTHOR]

In the beginning the paper briefly presents the worldwide context determined by the global warming phenomenon evolution, and the foreseen impact on the power sector, with the focus on the massive integration of the RES powered electricity generators. Identifying the TSOs and grid operators as the main actors for implementing the necessary changes, the authors of the paper are proposing data analytics, designed to support the TSOs and grid operators in fulfilling their main functions and responsibilities. The structure and the capabilities (analysis and reports) of the software product are presented, including practical examples for usage, and highlighting the potential usefulness of each analyze and/or report, from TSOs and grid operators’ point of view. [ABSTRACT FROM AUTHOR]

The existing millennium documents the most adverse consequences of global warming which in contrast to pre-industrial era are more devastating. Thus, these prevailing consequences raise numerous concerns regarding the well-being of future and current generation. Scholars, in this regard, are putting efforts punctiliously towards methods that could halt the surging emissions. This paper also attempts to contributes to existing literature by reporting the empirical evidences regarding the role of energy transition technologies, renewable energy production (REP), trade openness, green investment, and carbon taxes in carbon neutrality in Chinse economy covering the time span of 1980–2020. By employing Dynamic Auto-regressive Distributed Lags (DARDL) model to check the association, findings exposed that electricity production from water sources, electricity production from solar sources, REP, trade openness, green investment, and carbon taxes are negatively correlated with CO2 emissions. Study offers policymakers a help in formulating policies related to achieve carbon neutrality using renewable sources of energy production, carbon taxes, and green investment. [ABSTRACT FROM AUTHOR]

In a modern power system, reducing carbon emissions has become a significant goal in mitigating the impact of global warming. Therefore, renewable energy sources, particularly wind-power generation, have been extensively implemented in the system. Despite the advantages of wind power, its uncertainty and randomness lead to critical security, stability, and economic issues in the power system. Recently, multi-microgrid systems (MMGSs) have been considered as a suitable wind-power deployment candidate. Although wind power can be efficiently utilized by MMGSs, uncertainty and randomness still have a significant impact on the dispatching and operation of the system. Therefore, to address the wind power uncertainty issue and achieve an optimal dispatching strategy for MMGSs, this paper presents an adjustable robust optimization (ARO) model based on meteorological clustering. Firstly, the maximum relevance minimum redundancy (MRMR) method and the CURE clustering algorithm are employed for meteorological classification in order to better identify wind patterns. Secondly, a conditional generative adversarial network (CGAN) is adopted to enrich the wind-power datasets with different meteorological patterns, resulting in the construction of ambiguity sets. Thirdly, the uncertainty sets that are finally employed by the ARO framework to establish a two-stage cooperative dispatching model for MMGS can be derived from the ambiguity sets. Additionally, stepped carbon trading is introduced to control the carbon emissions of MMGSs. Finally, the alternative direction method of multipliers (ADMM) and the column and constraint generation (C&CG) algorithm are adopted to achieve a decentralized solution for the dispatching model of MMGSs. Case studies indicate that the presented model has a great performance in improving the wind-power description accuracy, increasing cost efficiency, and reducing system carbon emissions. However, the case studies also report that the approach consumes a relative long running time. Therefore, in future research, the solution algorithm will be further improved for the purpose of raising the efficiency of the solution. [ABSTRACT FROM AUTHOR]

There is increasing interest in migrating to a carbon-neutral power system that relies on renewable energy due to concerns about greenhouse gas emissions, energy shortages, and global warming. However, the increasing share of renewable energy has added volatility and uncertainty to power system operations. Introducing new devices and using flexible resources may help solve the problem, but expanding the domain of the problem can be another solution. Sector coupling, which integrates production, consumption, conversion, and storage by connecting various energy domains, could potentially meet the needs of each energy sector. It can also reduce the generation of surplus energy and unnecessary carbon emissions. As a result, sector coupling, an integrated energy system, increases the acceptance of renewable energy in the traditional power system and makes it carbon neutral. However, difficulties in large-scale integration, low conversion efficiency and economic feasibility remain obstacles. This perspective paper discusses the background, definition, and components of sector coupling, as well as its functions and examples in rendering power systems carbon-neutral. The current limitations and outlook of sector coupling are also examined. [ABSTRACT FROM AUTHOR]

The increasing presence of non-programmable renewable energy plants increases the intermittency of the electricity supply and thus threatens the adequacy of a power system. Hydropower can solve this problem due to its flexibility. This paper applies statistical approaches to assess water availability in the context of hydropower generation and adequacy analysis on a seasonal basis for one site in Sicily and the other in Sardinia, where major hydroelectric plants are present. First, an empirical relationship between soil moisture content (SMC) and potential evapotranspiration (ET0) is evaluated through linear regression analysis. Then, precipitation trends over the last twenty years are analyzed to determine any effects of global warming on water availability. Finally, Monte Carlo algorithms are used for the stochastic generation of hourly precipitation, direct runoff profiles, and daily SMC profiles. Strong positive and negative correlations between ET0 and SMC (p < 0.05), and R2 ≥ 0.5 are found for both sites, except for summer, and R2 ≥ 0.5 is obtained. The cumulative pH-historical precipitation shows changes in seasonal trends, with evidence of a decrease at the annual level. The algorithms used to synthetically generate hourly precipitation and direct runoff profiles, as well as daily SMC profiles, effectively simulate the statistical variability of the historical profiles of these physical quantities. [ABSTRACT FROM AUTHOR]

Renewable energy such as wind generation is a countermeasure against global warming and fossil-energy resource depletion. However, wind-farm (WF) output fluctuates because of unstable wind conditions and the occurrence of long-term fluctuations, which are called ramp events. WF power generation operator needs to observe the grid code (GC) by controlling wind generators themselves or adjusting a WF output with the energy-storage system (ESS). Accordingly, scheduling the operation of WF with ESS and WF output forecast is necessary. Scheduled operation has two parts: scheduling of generation plans (SGP) and operating WF (OWF) outputs with the charge/discharge of ESS. This paper proposes the scheduling method, which can control ramp events and satisfy GC formulation such as mixed integer liner programming in the SGP part, and the balancing method, which can reduce the imbalance energy due to control delay of ESS in the OWF part. We also evaluate these methods by annual numerical simulation. We further confirm the validity and effectiveness of the proposed method, as well as approximate its battery capacity requirement. [ABSTRACT FROM AUTHOR]

World widely, efforts of governments and industry focus on the global sustainability. Facing global warming and rapidly growing electricity demand, it is crucial to develop technologies that will allow humanity use planet resources in the most efficient way, which is possible. Energy storage systems are vast and common concepts nowadays, concerning also small residential energy systems with renewable energy sources like photovoltaic installations. This paper describes different solutions for this issue. Characteristics of mentioned methods include basic features and values, advantages and disadvantages, estimated investing (CAPEX) and operating (OPEX) costs for the investors and issues related with environment like efficiency and emissions. As researched in the document, current technologies base on well-known solutions implemented in residential installations but also there is also possibility to develop new methods and combine few of them to use any possible energy surplus, later when it is needed the most. Description of various energy storage system includes both technical and commercial aspects. As most of storage applications differ from each other, choosing proper energy storage system implies economic and environmental benefits. The review has provided sufficient information to conclude that there is no one-sizefits-all solution to store electricity. Suitable solution should be selected based on size of the installation, geographical conditions as well as economic possibilities. For examined energy storage systems there is still necessity of further research and development but overview of those presented in the article, makes it possible to deduce comparison and conclusion. [ABSTRACT FROM AUTHOR]

The necessity to achieve global sustainability and renewable energy resources to overcome the threat of climate change has led to unparalleled social and economic alterations ubiquitous throughout the world. The environment surrounding pollution correlated with global warming is essential to technological advances for developing energy resources. Renewable and sustainable energy resources are eco‐friendly energy sources that transform heat directly into electrical energy. The transformation of the global energy system underway in various countries can play a predominant role in power sectors. It helps in establishing a low‐power solution with high performance in advance. This review paper highlights technological feasibility within the economic activity of sustainable resources in various sectors. The sustainable resource would represent the world's most advanced technology and cost‐effective global power transition pathway. The present status, prospects, and updated information about these energy resources have been discussed in detail. This review provides a recommendation on which energy would be suitable for electrical energy generation and would establish a green environment for the next generation to survive in the world. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas emissions is urgent for the global community with rising climates. Considering the importance of renewable energy in mitigating climate warming, forecasting renewable energy generation is vital for the Chinese government's future low-carbon and green development plan. This paper proposes a novel multivariable grey model based on historical data on China's renewable energy generation and three industries. A novel information accumulation mechanism with two adaptive factors is designed to improve the traditional multivariable grey modeling defect. Based on the proposed mechanism, this paper optimizes the initial and background values and nonlinear model structure with the whale optimization algorithm. The forecasting results show that the fitting MAPE is 1.13%, comprehensive MAPE is 2.60%, MSE is 50.86, and RMSE is 7.13, which significantly improve the forecasting accuracy of traditional GM(1,N) and are better than other compared models. The forecasting results show that China's renewable energy generation will gradually increase to 5834.02 TWh. The Chinese government should keep the previous Five-Year Plans rising trend of the three industries in the future Five-Year Plans to support renewable energy industries. In China's future energy system, it is necessary to promote incentive policies and capital investment for actively accelerated development to make renewable energy the leading force. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and Russia's war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlighting the need for greater energy diversification and reliance on local, renewable energy sources. However, the early evidence suggests that policymaking worldwide is focused on short-term, seemingly quicker solutions, such as supporting the incumbent energy industry in the post-pandemic era to save the economy and looking for new fossil fuel supply routes for enhancing energy security following the war. As such, the fossil fuel industry may emerge even stronger after these energy crises creating new lock-ins. This implies that the public sentiment against dependency on fossil fuels may end as a lost opportunity to translate into actions toward climate-friendly energy transitions, without ambitious plans for phasing out such fuels altogether. We propose policy recommendations to overcome these challenges toward achieving resilient and sustainable energy systems, mostly driven by energy services. [ABSTRACT FROM AUTHOR]

Over the last decades, renewable and clean energy sources are being rigorously adopted along with carbon capture technologies to tackle the increasing carbon dioxide (CO2) concentration level in the environment. CO2 capture is a quintessential option for tackling global warming issues. In this context, the present paper has reviewed the process intensification equipment called a rotating packed bed (RPB), which is highly industry applicable due to high gravity (HiGee) force. This facilitates strong mass transfer characteristics, a compact design, and low energy consumption. In this review, the current research scenario of RPBs using numerical, computational fluid dynamics (CFD), and mathematical modelling, along with different machine learning approaches in the CO2 capture process, has been reviewed. The different geometry designs, hydrodynamic characteristics, performance parameters, research methods, and their effects on CO2 removal efficiency have been discussed. Furthermore, the latest experimental studies are also summarized, especially in the absorption and adsorption domain. Finally, recommendations have been given to support the RPBs in different industrial and commercial applications of CO2 removal. [ABSTRACT FROM AUTHOR]

This paper studies the effect on the rate of growth of carbon dioxide emission in seaports' atmosphere of replacing a part of the fossil fuel electrical power generation by clean renewable electrical energies, through two different scheduling strategies. The increased rate of harmful greenhouse gas emissions due to conventional electrical power generation severely affects the whole global atmosphere. Carbon dioxide and other greenhouse gases emissions are responsible for a significant share of global warming. Developing countries participate in this environmental distortion to a great percentage. Two different suggested strategies for renewable electrical energy scheduling are discussed in this paper, to attain a sustainable green port by the utilization of two mutual sequential clean renewable energies, which are biomass and photovoltaic (PV) energy. The first strategy, which is called the eco-availability mode, is a simple method. It is based on operating the renewable electrical energy sources during the available time of operation, taking into consideration the simple and basic technical issues only, without considering the sophisticated technical and economical models. The available operation time is determined by the environmental condition. This strategy is addressed to result on the maximum available Biomass and PV energy generation based on the least environmental and technical conditions (panel efficiency, minimum average daily sunshine hours per month, minimum average solar insolation per month). The second strategy, which is called the Intelligent Scheduling (IS) mode, relies on an intelligent Reconfigured Whale Optimization Technique (RWOT) based-model. In this strategy, some additional technical and economical issues are considered. The studied renewable electrical energy generation system is considered in two scenarios, which are with and without storage units. The objective (cost) function of the scheduling optimization problem, for both scenarios, are developed. Also, the boundary conditions and problem constraints are concluded. The RWOT algorithm is an updated Whale Optimization Algorithm (WOA). It is developed to accelerate the rate of reaching the optimal solution for the IS problem. The two strategies simulation and implementation are illustrated and applied to the seaport of Damietta, which is an Egyptian port, located 10 km to the west of the Nile River (Damietta Branch). The scheduling of PV and biomass energy generation during the different year months is examined for both strategies. The impact of renewable electrical energies generation scheduling on carbon dioxide emission and consequently global warming is discussed. The saving in carbon dioxide emission is calculated and the efficient results of the suggested models are clarified. The carbon dioxide emission is reduced to around its fifth value, during renewable energy operation. This work focuses on decreasing the rate of growth of carbon dioxide emission coming from fossil fuel electrical power generation in Egypt, targeting, sustainable green seaports, through three main contributions in clean renewable electrical energies scheduling. The contributions are: 1-presenting the eco-availability mode for minimum gifted biomass and PV energy generation, 2-developing and progressing the IRWOT scheduling strategy for both scenarios (with and without storage unit), 3-defining the scheduling optimization problem boundary conditions and constraints. [ABSTRACT FROM AUTHOR]

This paper analyses recent energy intensity trends for 40 major economies using a structural decomposition analysis. Our focus lies on the question whether improvements in energy intensity were caused by structural change towards a greener economy or by technological improvements. We account for intersectoral trade by using the World Input-Output database and adjust sectoral energy use via the environmentally extended input-output analysis. We find strong differences between consumption and production-based energy consumption across sectors, particularly in the construction and electricity industry. Using the three factor Logarithmic Mean Divisia Index method, our decomposition analysis shows that recent energy intensity reductions were mostly driven by technological advances. Structural changes within countries played only a minor role, whereas international trade by itself even increased global energy intensity. Compared to a previous study only using production-based sectoral energy data, we find structural effects on energy intensity reductions to be systematically weaker under consumption-based data. [ABSTRACT FROM AUTHOR]

Renewable energy is essential for energy security and global warming mitigation. However, renewable power generation is uncertain due to volatile weather conditions and complex equipment operations. It is therefore important to understand and characterize the uncertainty in renewable power generation to improve operational efficiency. In this paper, we proposed a novel conditional density estimation method to model the distribution of power generation under various weather conditions. It explicitly accounted for the temporal dependence in the data stream and used an iterative procedure to reduce the bias in conventional density estimation. Compared with existing literature, our approach is especially useful for the purpose of short-term modeling, where the temporal dependence plays a more significant role. We demonstrate our method and compare it with alternatives through real applications. [ABSTRACT FROM AUTHOR]

Global warming, depleting energy reserve and raising demand have created a upsurge for alternative and environmentally friendly renewable energy sources. Currently, microalgae have recognized as a promising biofuel feedstock’s due to the several unique characteristics includes high productivity, no competition for arable land, fresh water and high CO2 sequestration efficiency. High caloric value, low density and low viscosity make it promising source of renewable energy. They also serve the dual purpose of biofuel production along with the production of potentially valuable biomass, which could be utilize for phyco-remediation, food, animal feeds, fertilizers, drugs etc. In spite of huge opportunity, only few algae species were investigated till date. This review paper presents the brief view on the potential of microalgae for biofuel feedstock, different culturing system, algal conversion technology. In addition, hurdles in commercialization of algal based biofuel technology and strategies were also discussed. [ABSTRACT FROM AUTHOR]

In this paper, the energy performance of a direct expansion solar assisted heat pump has been experimentally assessed with R290 as an alternative to R22 to meet the requirements of Kigali agreement. The experiments have been performed at Calicut climatic conditions (latitude of 11.15° N, longitude of 75.49° E) during the winter climates of 2016. The performance parameters such as, compressor power consumption, condenser heating capacity, energy performance ratio, and solar energy input ratio were evaluated for energy performance comparison. The results showed that, R290 has 6.8% higher energy performance ratio when compared to R22, with 11% reduction in compressor power consumption. Moreover, R290 has negligible global warming impact and zero ozone depletion potential when compared to R22. The effect of wind speed, collector area, ambient temperature, and solar insolation on the system performance found to be with an average value of 0.85%, 12%, 2.5%, and 4.5% for the selected refrigerants, respectively. [ABSTRACT FROM AUTHOR]

• This paper proposes a concept that utilizes historical time-series data from transmission system operators (TSOs) to estimate the optimal day-ahead energy-mix proportion for a power system dominated by converters. • This paper employs a long short-term memory (LSTM) network as a data-driven model to forecast the day-ahead values of key parameters. • To ensure secure system functioning, an energy-mix operation and reserve scheduling model is developed. • This paper emphasizes the importance of power system security in incorporating inverter based resources (IBRs). Advancements in various scientific fields have encouraged the development of novel tools, techniques, components, methodologies, and innovations aimed at addressing the challenges encountered in modern power systems dominated by inverter-based resources (IBRs). This paper focuses on a concept that leverages historical time-series data obtained from transmission system operators (TSOs) to enhance the secure management and operation of power systems. By employing a data-driven model, the day-ahead values of power generation and load consumption are estimated and integrated with a dynamic model of the power system for further analysis. To optimize energy generation and ensure grid stability, an energy-mix operation and reserve scheduling model is utilized. This model optimally combines different power-generating technologies, including synchronous generators (SGs), grid-following converters (GFLs), and grid-forming converters (GFMs), to meet the energy demands of the day while enhancing the overall system strength. The findings are supported by quantitative analysis utilizing variables such as frequency, power production, terminal voltages, and system non-synchronous penetration (SNSP). Simulation results demonstrate that implementing the proposed concept enables the power system under consideration to operate securely, even in the face of a 38% increase in immediate load, with a maximum SNSP ratio of 59%. These findings highlight the effectiveness of the proposed approach in addressing the reliability, system dynamics, stability, control efficiency, and security challenges posed by IBR-dominated power systems. Furthermore, it is believed that this research contributes to the ongoing efforts in decarbonization, renewable energy integration, and combating global warming by facilitating the secure and optimized operation of renewable energy-dominated power systems. [ABSTRACT FROM AUTHOR]

The future buildings and society need to be resilient. This article aims to propose a novel concept of the energy resilience framework and implement a color-based rating system to quantify and rate the energy resilience performance of buildings in Nordic climates. The objective is to conduct a comparative analysis between old (1970s) and new (2020s) single-family buildings integrated with renewable energy sources and storage, assessing their energy resilience performance for heating during power outages, under extreme and typical climatic conditions. The study utilizes dynamic simulation of the buildings and renewable energy systems, conducting parametric studies to calculate proposed resilience indicators and rate their resilience performance, employing both passive and active methods. The total costs of the design variables are also calculated for economic evaluation. Given the complexities arising from climate change, the article uses a simplified method to synthesize regional climate to consider extreme climate change impacts on energy resilience performance. For the old building lacking PV, the robustness duration increased from 1 h to 3 h, and the degree of disruption (DoD) varied from 0.545 to 0.3 in extreme cold to warm climate scenarios, with the higher DoD number indicating worse performance. The impact of the season within the same climate scenario is also evident, as the habitability and robustness durations increased during spring compared to winter. The resilience improved with PV and battery. The new building showed that the robustness duration increased from 3 to 15 h, habitability durations increased, and the DoD varied from 0.496 to 0.22 from extreme cold to warm climates without renewables and storage. With the integration of PV and battery, the new building was able to achieve a lower DoD and better performance with lower PV and battery capacity, compared to the old building. Furthermore, utilizing the color grading method (red to green), optimal technical solutions and corresponding design variables were identified for each building type and climate scenario that could support decision-making. The total cost of the optimal solutions varied, as new buildings required lower costs to reach optimal performance. However, for optimal resilience performance during extreme cold climate scenarios, higher costs are required for each building type. The proposed resilience framework, indicators, color grading system, and costing could potentially support improvements in building regulations, ensuring the development of optimally resilient buildings, particularly in the face of extreme climatic conditions. [ABSTRACT FROM AUTHOR]

The energy demand is increasing due to population growth and economic development. To satisfy this energy demand, the use of renewable energy is essential to face global warming and the depletion of fossil fuels. Photovoltaic energy is one of the renewable energy sources, widely used by several countries over the world. The integration of PV energy into the grid brings significant benefits to the economy and environment, however, high penetration of this energy also brings some challenges to the stability of the electrical grid, due to the intermittency of solar energy. To overcome this issue, the use of a forecasting system is one of the solutions to guarantee an effective integration of PV plants in the electrical grid. In this paper, a PV power ultra short term forecasting has been done by using univariate and multivariate LSTM models. Different combinations of input variables of the models and different timesteps forecasting were tested and compared. The main aim of this work is to study the influence of the different combinations of variables on the accuracy of the LSTM models for one-step forecasting and multistep forecasting and comparing the univariate and multivariate LSTM models with MLP and CNN models. The results show that for one step forecasting, the use of a univariate model based on historical data of PV output power is sufficient to get accurate forecasting with 28.98W in MAE compared to multivariate models that can reach 35.39W. Meanwhile, for multistep forecasting, it is mandatory to use a multivariate model that has historical data of meteorological variables and PV output power in the input of LSTM model. Moreover, The LSTM model shows great accuracy compared to MLP and CNN especially in multistep PV power forecasting. [ABSTRACT FROM AUTHOR]

In a notable change from the position in the past, the Greek government took steps to commit itself to greening the economy and determining policies and actions to boost the utilization of renewable energy. The aim of the paper is, firstly, to present the latest developments on the renewable energy policy in Greece, the current achievements and impediments to the implementation of planned reforms in the accomplishment of its 2020 targets, and the specific policy measures introduced; secondly, to discuss the pace of respective developments in other EU-28 member countries; thirdly, to verify the achievements of the government towards reversing previous bureaucratic, prone-to corruption procedures through a questionnaire survey and stratified interviews with market participants. Research survey results from our survey and interviews conducted in the second semester of 2014 are respectively presented. The majority of respondents expect to see the targets set in the National Renewable Energy Action Plan reached by 2020. The paper and questionnaire survey have been conducted under the auspices of the European research program THALES, aiming to measure various aspects of the shadow economy and the areas of renewable energy trade and finance in Greece. [ABSTRACT FROM AUTHOR]

The 2015 UN Paris Agreement reinforced and declared compatible the two goals of avoiding dire climate change and maintaining global economic growth, and it specified that technological innovation is ‘critical’ to this joint achievement. Unfortunately, any confidence that near-term global economic growth is consistent with a stabilized climate is severely undermined by empirical evidence. Despite the rapid increase of alternative energies in recent decades, global GDP growth continues to require burning greater quantities of climate-destabilizing fossil fuels. The dim outlook for sufficiently reducing CO2while maintaining economic growth is underscored by global data and Germany specific data on the decoupling of GDP from CO2. This paper summarizes pertinent climate science, substantiates the dependence of economic growth on fossil fuels, and uses the Kaya identity to demonstrate the unfavorable prospects for reducing CO2while maintaining GDP growth. [ABSTRACT FROM PUBLISHER]

Energy is crucial to economic progress, but the contemporary worldwide population increase that demands greater energy generated from conventional exhaustible resources, an energy price upsurge, and environmental concerns, imperils sustainable economic growth. Nevertheless, switching to renewable energy produced from naturally replenished resources promotes energy security, likewise addressing issues such as global warming and climate change. This paper aims at exploring the influence and causal relation between renewable energy, both overall and by type, and sustainable economic growth of European Union (EU)-28 countries for the period of 2003-2014. We notice that the mean share of renewable energy in the gross final energy consumption is 15%, while the mean share of renewable energy in transport fuel consumption is 3%, which are below the thresholds of 20% and 10%, respectively, as set by the EU Directive 2009/28/EC. By estimating panel data fixed-effects regression models, the results provide support for a positive influence of renewable energy overall, as well as by type, namely biomass, hydropower, geothermal energy, wind power, and solar energy on gross domestic product per capita. However, biomass energy shows the highest influence on economic growth among the rest of renewable energy types. In fact, a 1% increase of the primary production of solid biofuels increases GDP per capita by 0.16%. Besides, cointegrating regressions set on panel fully modified and dynamic ordinary least squares regressions confirm the positive influence related to the primary production of renewable energies on economic growth. A 1% increase in primary production of renewable energies increases GDP per capita by 0.05%-0.06%. However, the results of Granger causality based on panel vector error correction model indicate both in short-run and long-run a unidirectional causal relationship running from sustainable economic growth to the primary production of renewable energies, being supported the conservation hypothesis. [ABSTRACT FROM AUTHOR]

Fossil fuels are used in the system to cause environmental pollution and global warming. Thus, nowadays, the use of renewable energy sources is becoming very popular in countries around the world. In addition to being environmentally friendly, installing of renewable energy sources has shown significant impacts on the power quality as well as on the operating costs of the system. In this paper, an effective, nature-inspired meta-heuristic approach is applied to research the optimal siting and sizing of distributed photovoltaic units (PVUs) in radial distribution systems. The main objective of this research is to focus on minimizing the power loss of the system while harmonic distortions are kept in the permissible limits of the IEEE Std. 519 and voltage profile is kept within the best range of voltage. The approach is called the Coyote Optimization Algorithm (COA), which is developed based on the behavioral characteristics of the coyote community, is introduced to ensure maximum benefits from the grid integrated PVUs system. This is a simple algorithm in application with few control parameters and it has the ability to expand the search zones and avoid local traps, resulting in a high performance and stability. The effectiveness of the method is demonstrated in comparison to other methods as Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA) in the IEEE 85-bus radial distribution system. The obtained results indicate the outstanding efficiency of the proposed method in maximizing the economic and technical benefits by optimal installation of distributed PVUs. [ABSTRACT FROM AUTHOR]

Presently, there is growing discourse surrounding climate change, global warming, and the possibility of urban smog. Daily, we encounter air pollutants unwittingly, often oblivious to the substantial adverse impacts they may impart on our health. This manuscript furnishes a thorough examination of the shifts in the concentrations of distinct air pollutants, namely, sulphur oxides (SOx), nitrogen oxides (NOx), and particulate matter PM2.5 and PM10, within the contexts of the United Kingdom (a country progressively transitioning to alternative energy sources) and Poland (a country in the EU with the second lowest climate policy evaluation in the climate change performance index or CCPI) from 1970 to 2020. This comparative study between the two countries clearly showed the importance of the transition to clean energy sources. The UK's efforts towards cleaner energy sources have led to reduced emissions of sulphur oxides (SOx) and particulate matter. In contrast, Poland's heavy dependence on energy primarily from coal over the years has resulted in elevated pollution levels, notably in the concentration of pollutants such as particulate matter. This study also revealed that changes in emissions predominantly stem from technological advancements and economic activities. Additionally, political regulations and the gradual phase-out of specific fuels or energy-rich substances and their substitution with alternative energy sources have also imparted considerable influence. [ABSTRACT FROM AUTHOR]

Renewable energy sources are the most effective and cheapest method for combating climate change. Biomass, which is one of the renewable energy sources, is also one of the raw materials for biofuels. Sorghum x Sudan grass hybrid, which is drought tolerant and has a short vegetation period, is a biomass source. This study was carried out to determine the ethanol yield of sorghum x Sudan grass hybrid plants grown in an area with a semi-humid climate and to determine the environmental impacts of biomass. Environmental impacts were assessed using the life cycle assessment method. Environmental impact categories are divided into 11 categories according to the CML-IA Baseline model. As a result, the biomass yield was 49888 kg ha-1 and the ethanol yield was 1674.1 l ha-1. According to the life cycle impact category of sorghum x Sudan grass hybrid biomass production, the highest environmental impact was 79.21%, causing marine aquatic ecotoxicity. According to the life cycle interpretation, it caused a global effect with a rate of 83.87%. In addition, the global warming value was calculated as 0.195 kg CO2-eq kgbiomass -1 (9728.16 kg CO2-eq ha-1). The agricultural phases with the most negative impact on the environment are irrigation and fertilization. [ABSTRACT FROM AUTHOR]

Solar radiation modification (SRM) is increasingly being discussed as a potential tool to reduce global and regional temperatures to buy time for conventional carbon mitigation measures to take effect. However, most simulations to date assume SRM to be an additive component to the climate change toolbox, without any physical coupling between mitigation and SRM. In this study we analyze one aspect of this coupling: how renewable energy (RE) capacity, and therefore decarbonization rates, may be affected under SRM deployment by modification of photovoltaic (PV) and concentrated solar power (CSP) production potential. Simulated 1 h output from the Earth system model CNRM-ESM2-1 for scenario-based experiments is used for the assessment. The SRM scenario uses stratospheric aerosol injections (SAIs) to approximately lower global mean temperature from the high-emission scenario SSP585 baseline to the moderate-emission scenario SSP245. We find that by the end of the century, most regions experience an increased number of low PV and CSP energy weeks per year under SAI compared to SSP245. Compared to SSP585, while the increase in low energy weeks under SAI is still dominant on a global scale, certain areas may benefit from SAI and see fewer low PV or CSP energy weeks. A substantial part of the decrease in potential with SAI compared to the SSP scenarios is compensated for by optically thinner upper-tropospheric clouds under SAI, which allow more radiation to penetrate towards the surface. The largest relative reductions in PV potential are seen in the Northern and Southern Hemisphere midlatitudes. Our study suggests that using SAI to reduce high-end global warming to moderate global warming could pose increased challenges for meeting energy demand with solar renewable resources. [ABSTRACT FROM AUTHOR]

Tourism serves as a crucial means of funding national development and ensuring the sustainability of local livelihoods in growing countries such as Brazil. Nevertheless, the accelerated growth of tourism in various nations might lead to significant environmental consequences due to heightened energy consumption. This surge in energy usage contributes to the exacerbation of global warming through the amplified release of carbon dioxide (CO2). In light of the increasingly evident impacts of climate change on the natural environment, a multitude of endeavors have been undertaken with the aim of attaining ecological sustainability. The objective of this study is to examine the dynamic effects of economic growth, energy consumption, and tourism on carbon emissions in Brazil by analyzing time series data spanning from 1990 to 2019. The stationarity of data was assessed through the application of unit root tests, while an autoregressive distributed lag (ARDL) approach was employed to analyze the relationship between the components, accounting for both the long-term and short-term dynamics. The empirical results indicate that a 1% rise in economic growth, energy consumption, and tourist arrivals leads to environmental deterioration by causing a respective increase in CO2 emissions of 1.37%, 1.06%, and 0.57% in the near term, and 0.72%, 0.62%, and 0.16% in the long term. This article presents policy ideas aimed at achieving carbon neutrality in Brazil by increasing the utilization of renewable energy sources, while simultaneously fostering sustainable tourism as a means to enhance the country's economy. Highlights •This study investigated the tourism-economy-energy-environment nexus in Brazil. •The econometric analysis revealed that tourism, energy use, and economic growth increase CO2 emissions. •This article offers policy suggestions to achieve sustainable tourism and carbon neutrality. [ABSTRACT FROM AUTHOR]

Currently, many countries in the world face the serious consequences of global warming, such as: floods, landslides, excessive heat during summer, drought and many others. The material consequences of climate changes on the economy, on human life and on the environment are very serious. Human activity overloads the atmosphere with carbon dioxide and other emissions that cause global warming, capture heat, slowly increase the planet's temperature and have a significant and harmful impact on our heath, on the environment and on the climate. The increase of providing renewable energy would allow replacing energy sources that have high carbon emissions and would lead to the reduction of global warming. The paper presents aspects regarding the importance of using renewable energy, as alternatives to using conventional energy sources (coal, petrol, wood, etc.). [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are one of a prominent solution for the sustainability issues needing dire attention like global warming, depleting fossil fuel reserves, and greenhouse gas (GHG) emissions. Conversely, EVs are shown to emit higher emissions (measured from source to tailpipe) for the fossil fuel-based countries, which necessitates renewable energy sources (RES) for maximizing EV benefits. EVs can also act as a storage system, to mitigate the challenges associated with RES and to provide the grid with ancillary services, such as voltage regulation, frequency regulation, spinning reserve, etc. For extracting maximum benefits from EVs and minimizing the associated impact on the distribution network, modelling optimal integration of EVs in the network is required. This paper focuses on reviewing the state-of-the-art literature on the modelling of grid-connected EV-PV (photovoltaics) system. Further, the paper evaluates the uncertainty modelling methods associated with various parameters related to the grid-connected EV-PV system. Finally, the review is concluded with a summary of potential research directions in this area. The paper presents an evaluation of different modelling components of grid-connected EV-PV system to facilitate readers in modelling such system for researching EV-PV integration in the distribution network. [ABSTRACT FROM AUTHOR]

In today's energy system, the diffusion of renewable-based technologies is accelerating rapidly. Development of mechanisms that support the large-scale deployment of renewables towards global warming and climate change mitigation continues to remain an issue of utter importance. The most important challenges the energy system of Kosovo faces today is the difficulty to meet all the demand for electricity, low operating efficiency and high release of greenhouse gas emissions, but specifically a large source of carbon dioxide (CO2). Consequently, this influences not only the stability of the system but the society as a whole. This paper addresses several possibilities for designing an adaptable energy system in Kosovo with the ability to balance electricity supply and demand which will meet the requirements for a more efficient, reliable and secure system. A new way of energy generating through integration of new renewable and non-renewable technologies is developed using the EnergyPLAN model. The system is based on available technologies: existing hydro, wind, photovoltaic (PV), combined heat and power (CHP) and new solar thermal, heat pumps and biomass. The baseline scenario 2015 was expanded by four additional scenarios, two for the year 2030 and two for the year 2050. The contribution of renewable sources in the primary energy supply (PES) in the performed scenarios was 14.8%, 34.1%, 38.4%, 69.7% and 68.3% respectively. Further, a very important component of this paper is the investigation of integrating carbon capture and sequestration (CCS) technology in the coal-based power plant as part of the analysis in the second scenario for 2050. The shift to zero-carbon energy system in Kosovo requires additional research and assessment in order to identify the untapped potential of renewable sources. However, from the results obtained it can be concluded that the goal of a secure, competitive and sustainable energy system in Kosovo state which will meet its long-term energy needs can be certainly achieved. [ABSTRACT FROM AUTHOR]

Drastic increases in oil prices and need to reduce global warming are issues that have raised huge public awareness, which in turn encouraged many developed and developing countries to adopt new energy policies. Renewable energy resources are gaining fast attention in solving power supply problems in almost every area to shield the environment. In solving power supply problem standalone microgrid systems including renewable energy sources plays a key role. For a stand-alone renewable power delivery system, battery is the crucial component which allows storing excess renewable energy and further using the energy as and when needed by the load. In order to achieve the best performance and utilization the state of charge of the batteries should be assessed. This paper presents heuristic approaches to evaluate the state of charge (SOC) of lead–acid battery through optimal power generation in a standalone hybrid wind-solar renewable power delivery system. The mathematical analysis is made by the application of modified heuristic techniques, i.e. tuned genetic algorithm (TGA) and improved colliding body optimization(ICBO), for a specific loading condition in India. More optimized power is generated by the renewable distributed energy sources when evaluated by ICBO than that achieved by TGA, for both winter and summer load demands. These optimized value of power generated by the application of ICBO, resulted in low average value of SOC. The low values of SOC further prevent the battery from malfunctioning for a longer period of time. In order, to explore more optimal generation pertaining to good value of SOC parametric studies of modified algorithms, i.e. TGA and ICBO have been carried out. A set of critical operational parameters have also been obtained through parametric study of TGO and ICBO for a specific real time load profiles. Thus the reliable and optimal values lead to a better prospect in utilizing standalone renewable power delivery system for Indian future power scenario. Moreover, a comparative study has also been performed in analysing the performances of conventional and non-conventional methods in this regard. It has been found that the heuristic techniques, viz ICBO and TGA delivered 13% and 17% better result in comparison to that obtained by linear programming method respectively. Thus it can be surmise that the heuristic techniques perform well in considering the uncertainties and approximations of real world problem of generation renewable power, pertaining to better values of SOC. [ABSTRACT FROM AUTHOR]

In Ghana, firewood and charcoal are converted to heat energy traditionally by devices that are inefficient and unsustainable. The use of these devices have devastating consequences on the climate and human health. This study designed, produced and evaluated a multifeed biomass gasifier stove (MFGS) which relies on multiple types of biomass such as agricultural, industrial and forest waste as feedstock. The prototype of the MFGS was evaluated in the laboratory and the field to establish its level of efficiency and cleanliness. The MFGS recorded a maximum thermal efficiency and minimum CO emission of 35.8% and 0.23 g/min as compared to 30.0% and 2.32 g/min, respectively, recorded by the best Ghanaian traditional biomass stove (Gyapa). The total global warming impact recorded by the MFGS represent up to reduction of 99% of that of Gyapa making it a tool for fighting global warming and reducing the health risk of users of wood fuel in Ghana. [ABSTRACT FROM AUTHOR]

The issue of global warming imposes a change of paradigm in the energy sector to mitigate the human impact on the environment. In this perspective, hydrogen can be produced through water electrolysis and used in fuelcell systems with near-zero pollutant emissions. Nevertheless, the distribution system represents one of the main bottlenecks for a future transition to a hydrogen economy. The possibility of transporting hydrogen through the existing pipeline network is economically attractive. Nevertheless, most pipeline steels are prone to hydrogen-induced damage, and their mechanical properties are degraded by hydrogen gas to an extent that could result in sudden component failures. Hydrogen embrittlement can be responsible for undesired releases with potentially catastrophic consequences. This study evaluates the safety of existing European natural gas pipelines for hydrogen transport through machine learning tools. The material susceptibility to hydrogen embrittlement is predicted under different working conditions in order to prevent loss of material integrity and eventual releases. This study aims at bridging the gap between safety and material science, as it can optimize predictive maintenance of hydrogen pipelines, thus promoting the widespread utilization of hydrogen in the forthcoming years. [ABSTRACT FROM AUTHOR]

Containing global warming to 1.5 °C implies staying on a given carbon budget and therefore being able to design net zero carbon buildings by 2050. A case study corresponding to a French residential building is used to assess the feasibility of achieving this target. Starting from an actual construction built in 2016, various improvement measures are studied: lowering heating energy needs, implementing bio-sourced materials and renewable energy systems (geothermal heat pump, solar domestic hot water production, and photovoltaic electricity production). Dynamic thermal simulation is used to evaluate energy consumption and overheating risk in hot periods. Greenhouse gas emissions are quantified using a consequential life cycle assessment approach, considering that during a transition period, exporting electricity avoids impacts corresponding to marginal production on the grid. Avoided impacts decrease and become zero when the grid is ultimately "decarbonized". From this point, the building should be net zero emissions, but there remain unavoidable emissions. Residual GhG (greenhouse gas) emissions account for 5.6 kgCO2 eq/m2 annually. The possibility of offsetting these emissions is investigated, considering sequestration in forests or vegetation systems. A net zero emission level can be achieved, but on a national level, it would require that the whole sequestration potential of forest growth be devoted to offset emissions of new construction. A circular economy for construction products and equipment and considering water use will be needed to further decrease environmental impacts. [ABSTRACT FROM AUTHOR]

Energy consumption in residential, commercial and industrial buildings is one of the major contributors to global warming. Due to the increase in the latter, and growing global energy crisis, more attention is being paid to renewable energy resources (RES). The use of innovative concepts in existing buildings is gaining popularity to provide reduction in energy requirements for electricity, heating and cooling. In this paper, an electricity, heating and cooling cooperation mechanism among neighboring buildings with RES is proposed. It relies on adjusting the RES tariff with a mutual agreement between the neighboring buildings, with an aim to minimize the operational costs. For this purpose, a mathematical model is developed for joint energy cooperation, where surplus energy in one of the buildings is shared with others, thereby reducing dependency on the grid. The optimization structure of the environment friendly energy cooperation is nonlinear, which is linearized using the McCormick envelopes. A scenario for the city of Islamabad, Pakistan, is considered by utilizing its environmental data obtained from public domain websites. The simulation results show more than twenty percent energy cost savings with the proposed cooperation model. [ABSTRACT FROM AUTHOR]

Abstract Offshore wind energy cumulative installed capacity has been increasing sharply in northern Europe since the early 2000s. This renewable energy could make easier the diversification of the energy mix or the mitigation of global warming. Likewise, its deployment might trigger some positive economic effects, such as job creation, GDP contribution or industrial diversification. For these reasons, it could be advisable to shed light on the main drivers that foster the diffusion of the capacity to generate energy from offshore wind. The main aim of this paper is to propose a comprehensive analytical framework of the main drivers behind the deployment of this renewable energy in the leading global markets. The methodological approach consists of descriptive studies and the proposal of a regression specification (country fixed-effect panel model) with a list of factors relating to offshore wind industry classified into three relevant groups. This proposed analysis represents a step ahead from traditional approaches, because it facilitates a systemic analysis of the main policy and market factors, as well as technological and natural drivers behind the deployment of this renewable energy. In addition, as another novelty, the analytical framework takes into account the specific sectoral stage of development and country heterogeneity. Highlights • A systemic methodological proposal for analysing offshore wind energy deployment. • Combination of policy, market and technology-specific variables. • The methodology captures country heterogeneity and sectoral stage of development. [ABSTRACT FROM AUTHOR]

Abstract Due to the increasing global warming, it is anticipated that the number and severity of natural disasters will increase in the coming years. In this regard, this paper proposes a planning model to improve the resilience of distribution systems against natural disasters. A mathematical model is developed to determine the optimal locations of remote‐controlled switches (RCSs), distributed generation units (DGs), and tie lines in distribution systems with complex topologies or lateral branches. Simultaneous occurrence of multiple faults is considered to better simulate the extreme events. Moreover, the concept of multi‐microgrids is used to supply the maximum possible interrupted load after the fault occurrence. To manage the system risk and different failure scenarios, the conditional value at risk (CVaR) is added to the planning model. The optimization model has been formulated as a mixed integer linear programming (MILP) problem, which can be easily solved using various commercial solvers and give the global optimal solution. Finally, to illustrate the effectiveness of the proposed planning model on improving the distribution system resilience, it is implemented on the IEEE 33‐bus system using different case studies and sensitivity analyses.

Sustainable energy development (SED) is a crucial component of the Sustainable Development Goals (SDG), aiming to maintain economic and social progress while protecting the environment and mitigating climate change's effects. SED serves as a transition paradigm for sustainable development, providing a blueprint for energy peace and prosperity for people and all uses. This article presents the history of SED and then uses a critical discourse approach to summarize existing review studies in SED. Ten interlinked themes of SED are identified, with two of them considered to be among the least studied in existing SED reviews and in the current global discussion around climate change. This study explores these two themes, which include energy financing and the need for 100% renewable energy (RE), a sub-theme of decarbonization strategy working towards the 1.5–2.0 °C scenario. The study suggests that the current G20 countries' contributions, if maintained continuously per annum, in addition to 80% more funding from private investment compared to the amount in the 1.5 °C scenario financial requirements for clean energy, are sufficient to limit global warming. In addition to the present drive for 100% RE, the article also discusses emerging issues, such as energy storage options with an indication of hydrogen as the most promising, other energy-related development agendas, and the need for regional security stability to prevent energy wars. Selected SED decarbonization strategies are presented across the power, transport, building, and industrial sectors. The study concludes with progress and directions for future research, mainly the need for re-defining nationally determined contribution (NDC) through an emissions budgeting and centralized global or regional emissions stock-taking strategy working towards the 1.5 °C scenario. [ABSTRACT FROM AUTHOR]

Energy is the need for the future, and to fulfill this need, the use of renewable energy is a must. Furthermore, to counter the problem of global warming and climate change, the transition toward unconventional sources of energy is a requirement. Total global energy is majorly used in three sectors, namely, heating and cooling, transport, and electricity; however, the use and growth of renewable energy among these sectors are different. In this article, we discuss the potential of renewable energy in these sectors, the challenges associated with their large-scale deployment, and the possible solutions. [ABSTRACT FROM AUTHOR]

The climate energy-mix is analyzed in the aspects of the pandemic as well as global warming where the nuclear and renewable energies are considered the cleaner powers. These factors of the pandemic, global warming, and energy-mix are able to be related to each other in the analysis. The simulations are performed by the modeling which has the quantifications of energy-mix study as mitigations, pandemic, and global-warming. Carbon neutrality is connected to global warming via energy-mix and mitigations. In the case of mitigations, energy-mix case oscillated much higher than the non-energy-mix case. In the case of global warming, the relative impact value is higher in the non-energy-mix case. So, global warming is mitigated when the energy-mix is performed. In figure, the 9.875th year has the biggest difference between the two cases when the energy-mix has the highest effect on the global warming aspect. After this pandemic, the leverage of carbon neutrality could be made. [ABSTRACT FROM AUTHOR]