Energy Supply Patterns Research Articles

Leveraging machine learning to optimize renewable energy integration in developing economies

The integration of renewable energy sources into power grids is a critical challenge for developing economies, where infrastructure limitations, unpredictable energy demand, and policy gaps hinder effective energy transitions. Machine learning (ML) offers transformative potential in addressing these challenges, enabling more efficient and reliable energy systems through advanced data analytics, predictive modeling, and real-time decision-making. This review explores how ML can optimize renewable energy integration by improving forecasting accuracy, enhancing grid stability, and optimizing resource allocation in solar, wind, and hydropower systems. Machine learning algorithms are particularly effective in predicting energy demand and renewable resource availability, allowing for better alignment between energy supply and consumption patterns. By leveraging ML-based predictive models, grid operators can mitigate the risks of energy shortages or oversupply, improve grid stability, and reduce operational costs. Furthermore, the application of ML in renewable energy systems provides opportunities for developing economies to leapfrog traditional energy infrastructure limitations by adopting smart grids that integrate real-time data to enhance decision-making and efficiency. This review also reviews case studies from Africa and Latin America, highlighting successful implementations of ML in renewable energy systems. These examples underscore the potential for ML to accelerate the deployment of sustainable energy solutions, while also addressing technical, economic, and policy barriers that exist in developing contexts. With continued advancements in machine learning, combined with supportive regulatory frameworks and investment in digital infrastructure, developing economies have the potential to realize substantial gains in renewable energy integration. This review concludes by discussing future trends, challenges, and opportunities for leveraging machine learning to optimize renewable energy integration, ultimately contributing to sustainable development and energy security in emerging markets.

Enhanced lipid metabolism reprogramming in CHF rats through IL-6-mediated cardiac glial cell modulation by digilanid C and electroacupuncture stimulation combination.

Cardiac lipid metabolism reprogramming is recognized as a critical pathological factor in the progression of chronic heart failure (CHF). The therapeutic potential of digilanid C and electroacupuncture stimulation (ES) in enhancing lipid metabolism and cardiac function has been established. However, the optimal synergistic regulatory strategies of these interventions on cardiac lipid metabolism have yet to be elucidated. This study aimed to comprehensively evaluate the impact of a digilanid C-ES combination on cardiac steatosis remodeling in CHF. Assessments were conducted across various dimensions, including myocardial oxygen consumption, mitochondrial function, and lipid metabolism. Additionally, we sought to uncover the underlying neuromolecular mechanisms. Our findings, at both molecular and morphological levels, indicated that the synergistic application of digilanid C and ES significantly inhibited myocardial fibrosis and steatosis. This combination therapy facilitated the repair of cardiac neuro-vascular uncoupling and induced a reprogramming of lipid metabolism. Notably, the digilanid C-ES combination ameliorated cardiomyocyte apoptosis and enhanced mitochondrial biogenesis in CHF, leading to a restructured energy supply pattern. Cardiac immunofluorescence analyses revealed the aggregation of cardiac glial cells (CGCs) at sites of abnormal neurovascular coupling, a response to cardiac lipid degeneration. This was accompanied by a marked reduction in the abnormally elevated expression of interleukin 6 (IL-6) and glutamatergic signaling, which correlated with the severity of cardiac steatosis and the aberrant activation of CGCs. The combined therapy was found to activate the Janus kinase 1 (JAK1)/signal transducer and activator of transcription 3 (STAT3) pathway, effectively attenuated lipid accumulation and over-recruitment of CGCs and deprivation of glutamatergic nerves. These findings underscore the potential of digilanid C and ES combination therapy as a novel approach to modulate the complex interplay between neurovascular dynamics and metabolic dysregulation in CHF.

Decentralized AIoT based intelligence for sustainable energy prosumption in local energy communities: A citizen-centric prosumer approach

The role of prosumers who are consumers who produce, store, and consume energy is vital to the uptake of renewable energies in Local Energy Communities (LEC). However, the integration of prosumers in the smart grid to facilitate bidirectional flows of energy and information depends on intelligent operations of energy systems and flexible structures of the existing energy markets. But existing energy trading mechanisms are faced with issues of trust, privacy, security, and energy pricing determination. Also, there are fewer studies based on a citizen-centric prosumer approach. Thus, there is need to provide reliable solutions that addresses the aforementioned challenges faced by prosumers in LEC. Advancements in disruptive technologies, such as Distributed Ledger Technologies (DLT), Artificial Intelligence (AI), and the Internet of Things (IoT) have transformed a broad spectrum of intelligent systems in smart cities. Therefore, this study examines the integration of AI and IoT as AIoT and DLT towards a citizen-centric prosumer approach for decentralized energy markets trading. Additionally, this article develops an architectural model for energy prosumption in LEC using design science approach based on a user-centred design method that shows a possible implementation concept to support energy sharing and trading in LEC. The architectural model supports trust, data privacy, security, and energy pricing determination using AI and smart contracts to provides real-time energy trading monitoring, easy access, control, and immutable logs to unearth underlying energy demand and supply patterns thereby supporting citizen-centric prosumer approach. Finally, a use case scenario of DLT and AIoT for prosumption operations is presented.

Significant Differences in Coral Trophic Status Between Nearshore and Offshore Reefs Recorded by δ15N of Coral Symbiotic Zooxanthellae and Host Tissue in the South China Sea in the SCS

AbstractSignificant differences in environmental conditions between nearshore and offshore coral reefs lead to different symbiotic zooxanthellae density (ZD) of corals. From the perspective of energy supply, different ZD lead to different energy provided by the photosynthesis of zooxanthellae to the coral host. However, few studies have conducted a comparative analysis of coral trophic status (i.e., autotrophic photosynthesis of zooxanthellae and heterotrophic feeding of the host) between nearshore and offshore reefs. In this study, 70 coral samples of Favia palauensis were collected from the nearshore Sanya reefs, and offshore Xisha, Nansha reefs in the South China Sea (SCS). The ZD, δ15N of seawater particulate organic matter (δ15NPOM), host tissue (δ15Nh), zooxanthellae (δ15Nz) and the difference between δ15Nh and δ15Nz (i.e., △h−z 15N = δ15Nh−δ15Nz) were measured and statistically analyzed. The purpose is to elucidate the differences in the energy maintenance mechanisms of corals between nearshore and offshore reefs. Results show that ZD is significantly positively correlated with δ15Nz in all three reefs (p < 0.05). Corals in nearshore Sanya have higher autotrophic abilities than corals from offshore Xisha and Nansha reefs. By contrast, corals in offshore reefs are more dependent on heterotrophic feeding of the host to obtain energy. Our research demonstrate that corals can adjust their trophic status, especially improve their heterotrophic feeding intensity to meet energy needs under different environmental conditions. This dynamic adjustment of energy supply patterns is of great significance to improve coral's environmental adaptability.

Performance and Techno-Economic Analysis of Optimal Hybrid Renewable Energy Systems for the Mining Industry in South Africa

This paper presents an exploration of the potential of hybrid renewable energy systems (HRESs), combining floating solar photovoltaics (FPV), wind turbines, and vanadium redox flow (VRF) battery energy storage systems (BESSs) to expedite the transition from conventional to renewable energy for the mining sector in South Africa. The feasibility study assesses how to enhance the overall efficiency and minimize greenhouse gas emissions from an economic standpoint by using the Hybrid Optimization of Multiple Energy Resources (HOMER) grid software version 1.11.1 and PVsyst version 7.4. Furthermore, the BESS Covariance Matrix Adaptation Evolution Strategy (CMA-ES) dispatch algorithm is proposed to make the most of the battery storage capacity and capability, aligning it with the dynamic energy demand and supply patterns of an HRES. The proposed HRES includes a highly efficient SFPV with a performance ratio of 0.855 and an annual energy production of 15,835 MWh; a wind turbine (WT) operating for 2977 h annually, achieving a 25% wind penetration rate; and a dynamic VRF-BESS with a 15,439 kWh life throughput and a 3 s dispatch response time. This HRES has a CapEx of R172 million, a 23.5% Internal Rate of Return (IRR), and an investment payback period of 4.9 years. It offers a low Levelized Cost of Energy (LCoE) at 4.27 R/kWh, a competitive Blended Cost of Energy (BCoE) at 1.91 R/kWh, and a positive net present cost (NPC), making it economically advantageous without external subsidies. Moreover, it annually reduces CO2 emissions by 1,715,468 kg, SO2 emissions by 7437 kg, and NOx emissions by 3637 kg, contributing to a significant environmental benefit.

Response of lipid metabolism, energy supply, and cell fate in yellowstripe goby (Mugilogobius chulae) exposed to environmentally relevant concentrations atorvastatin

The usage of typical pharmaceuticals and personal care products (PPCPs) such as cardiovascular and lipid-modulating drugs in clinical care accounts for the largest share of pharmaceutical consumption in most countries. Atorvastatin (ATV), one of the most commonly used lipid-lowering drugs, is frequently detected with lower concentrations in aquatic environments owing to its wide application, low removal, and degradation rates. However, the adverse effects of ATV on non-target aquatic organisms, especially the molecular mechanisms behind the toxic effects, still remain unclear. Therefore, this study investigated the potentially toxic effects of ATV exposure (including environmental concentrations) on yellowstripe goby (Mugilogobius chulae) and addressed the multi-dimensional responses. The results showed that ATV caused typical hepatotoxicity to M. chulae. ATV interfered with lipid metabolism by blocking fatty acid β-oxidation and led to the over-consumption of lipids. Thus, the exposed organism was obliged to alter the energy supply patterns and substrates utilization pathways to keep the normal energy supply. In addition, the higher concentration of ATV exposure caused oxidative stress to the organism. Subsequently, M. chulae triggered the autophagy and apoptosis processes with the help of key stress-related transcriptional regulators FOXOs and Sestrins to degrade the damaged organelles and proteins to maintain intracellular homeostasis.

Multi-omics analysis revealed the mitochondrial-targeted drug combination to suppress the development of lung cancer.

The incidence and mortality of lung cancer are continuously rising in recent years. Mitochondrial energy metabolism malfunction is found to be crucial in cancer proliferation and bioenergetic reprogramming, especially for lung cancer. In this study, we attempted to use mitochondrial-targeted drug therapy to change the energy metabolism pattern of cancer cells to inhibit the development of lung cancer, and investigated its mechanism of action and key targets through multi-omics studies. In this study, we established the in vivo tumor mouse mode, treated mice with multiple mitochondrial-targeted drug combinations and DDP, severally. Then, we investigated the differences between the 7-drug group with the control group and the DDP treatment group by transcriptomics, proteomics and metabolomics to find the therapeutic targets. We found that mitochondria-targeting drug cocktail therapy, especially the 7-drug regimen, effectively improved mitochondrial metabolism, changed energy supply patterns in lung cancer cells, significantly increased NK cells in tumor tissues, and decreased tumor markers in plasma. Multi-omics analysis informed that the combination of 7-drug could up-regulate mitochondrial oxidative phosphorylation, ATP synthesis and autophagy related genes, and down-regulate proliferation and immune-related genes compared with the control group. By further mapping the protein interaction network, we identified a key target for 7-drug therapy to reverse tumor metabolic reprogramming and validated it in metabolomics. Mitochondrial-targeted drug cocktail therapy can effectively inhibit the occurrence and development of tumors, through the reprogramming of energy metabolism and the increase in immune cells in tumor tissues. Thus, we provide a novel approach for the treatment of lung cancer and present evidence-based clues for the combined use of targeted mitochondrial drugs.

Evaluation of surplus hydroelectricity potential in Nepal until 2040 and its use for hydrogen production via electrolysis

The abundant hydro resources in Nepal have resulted in the generation of electricity almost exclusively from hydropower plants. Several hydropower plants are also currently under construction. There is no doubt that the surplus electricity will be significantly high in the coming years. Given the previous trend in electricity consumption, it will be a challenge to maximize the use of surplus electricity. In this work, the potential solutions to maximize the use of this surplus electricity have been analysed. Three approached are proposed: (i) increasing domestic electricity consumption by shifting the other energy use sectors to electricity, (ii) cross-border export of electricity, and (iii) conversion of electricity to hydrogen via electrolysis. The current state of energy demand and supply patterns in the country are presented. Future monthly demand forecasts and surplus electricity projections have been made. The hydrogen that can be produced with the surplus electricity via electrolysis is determined and an economic assessment is carried out for the produced hydrogen. The analysis of levelized cost of hydrogen (LCOH) under different scenarios resulted values ranging from 3.8 €/kg to 4.5 €/kg.

Lithium-Ion Battery State-of-Charge Estimation from the Voltage Discharge Profile Using Gradient Vector and Support Vector Machine

The battery monitoring system (BMoS) is crucial to monitor the condition of the battery in supplying and absorbing the energy when operating and simultaneously determine the optimal limits for achieving long battery life. All of this can be done by measuring the battery parameters and increasing the state of charge (SoC) and the state of health (SoH) of the battery. The battery dataset from NASA is used for evaluation. In this work, the gradient vector is employed to obtain the trend of the energy supply pattern from the battery. In addition, a support vector machine (SVM) is adopted for an accurate battery accuracy index. This is in line with the use of polynomial regression; hence, points V1 and V2 are obtained as the boundaries of the normal-usage phase. Furthermore, testing of the time length distribution is also carried out on the length of time the battery was successfully extracted from the classification. All these stages can be used to calculate the rate of battery degradation during use so that this strategy can be applied in real situations by continuously comparing values. In this case, using the voltage gradient, SVM method, and the suggested polynomial regression, MAPE (%), MAE, and RMSE can be obtained against the battery value graph with values of 0.3%, 0.0106, and 0.0136, respectively. With this error value, the dynamics of the SoC value of the battery can be obtained, and the SoH problem can be resolved with a shorter usage time by avoiding the voltage-drop phase.

Design of a high-efficiency electrolytic energy conversion system based on equilibrium analysis of electric-field and flow-field through simulation and experiments

In the context of sudden changes in global energy supply patterns, promoting the diversification of energy supply is an important movement for the sustainable development of the economy. Nuclear energy as a green and clean energy source has undergone rapid development. About 60 wt% of the world's fluorine production is used to produce uranium, a fuel for nuclear power plants. However, fluorine as a necessary raw material facing the challenges of high energy consumption and short lifespan of the electrolysis system. To overcome these drawbacks, this study aims to develop a high-efficiency electrolytic energy conversion system. Therefore, to optimize the design of the electrolysis system, the relationships between the electric field, the flow field and the electrode/electrolyzer geometry are simulated. Then, the simulation results are verified and further corrected by corrosion experiments. Subsequently, the key factors affecting the performance of the electrolyzer are obtained from the bubble separation experiment and simulation. Finally, a high-efficient electrolysis system is established and successfully put into industrial operation. In conclusion, in the course of model calculations, the method of reducing energy consumption is put forward, and the energy consumption is reduced from 17,000 to 14,980 kWh/ton by actual production, and the service life of carbon anode is extended from 90 days to 243 days. The breakthrough in fluorine electrolysis provides practical guidance for improving the performance of the electrolysis process.

Energy Consumption Connection of Industrial Sector Based on Industrial Link Theory: A Case Study of China

China’s energy consumption and its growth trend determine the domestic energy production and supply pattern. The understanding of energy consumption and its changes will help to enhance urban resilience. Based on the improved input-output model and hypothesis extraction model, this paper aims at constructing the energy-industry connection model, analyzing the energy transfer implied in the economic activities of various industrial sectors, and examining the energy transfer effect between the supply-side (SS) and demand-side industry sectors of the Shaanxi Province. The results showed that, in 2017, the energy industrial sector was the most energy consumption industry in Shaanxi Province. The industrial energy sector belonged to the net energy output industrial sector, and the energy products were transferred to other industrial sectors. This paper can provide a scientific basis for the energy SS reform, adjusting the industrial layout of regions in the Yellow River Basin.

Spatial and temporal considerations of implementing local renewable energy sources and decentralised heat recovery for domestic heat

A UK case study area containing over 33,000 households has been used to investigate spatial and temporal conflicts in meeting domestic heat demand through renewable electrical energy supply and low-grade decentralised heat recovery from the urban drainage network. The case study area was selected as its water infrastructure and population density were representative of the conditions experienced by the majority of the UK's urban population. The findings suggest that adopting an optimised and integrated water-energy system would lead to a 60% reduction in current carbon emissions, compared to a natural gas based system. The integrated water-energy system proposed for domestic heating showed an annual surplus of renewable energy of 716 GWh. However, a non-renewable source of energy of 114 GWh is required to deal with the intermittency of the demand and renewable energy supply. Given the renewable surplus, it would be possible to eliminate carbon emissions from domestic heating with the addition of local low efficiency inter-seasonal energy storage. Taking a broader perspective, the calculated 60% carbon emission saving is significant as the domestic housing sector contributes 15% of the UK carbon emissions. A progressive adoption of such locally based schemes throughout the country would be able to make tangible reductions to national carbon emission targets. • Quantified spatio-temporal patterns of energy supply and heat demand 33,000 households. • Optimised integrated water-energy system reduced domestic heating CO 2 emissions by 60%. • Considerable annual surplus of renewable energy and low-grade heat given heat demand. • Sub daily energy supply-demand imbalances occur throughout whole year. • Relatively low-efficiency thermal energy storage could mitigate imbalance.

Energy Transition Policy Analysis in Indonesia

This article aims to identify several aspects of the problem in Indonesian energy supply, describe the energy transition policy as a solution to overcome the problems, and study the energy transition in several other countries, especially in Asia, to be used as an example in formulating the right energy transition policy for this country. This problem is focused on the pattern of energy supply in Indonesia and why the energy transition policy has not been optimal. This study used the theoretical reference from Donald S. Van Meter and Carl E. Van Horn: policy target standards, resources, communication between organizations and strengthening activities, characteristics of implementing agents, and social, economic, and political conditions. The data used are studies in the form of reports, papers, or articles in a mass media news column. To encourage the energy transition policy, it is necessary to have a Renewable Energy Subsidy. The analysis was conducted qualitatively. This study's results show that the People's Representative Council of the Republic of Indonesia needs to finalize the regulations that are being drafted, namely the New and Renewable Energy Bill, which is then translated into the vision of the Ministry of Energy and Mineral Resources into an integrated policy framework to overcome obstacles to the development of Renewable Energy. Renewable energy subsidies are needed to encourage energy transition policy to reduce the electricity bills generated from Renewable Energy technology.

Characterizing the Energy Burden of Urban Households in Mexico: The Impact of Socioeconomic and Temperature Conditions Across Metropolitan Areas

The transition toward sustainable cities requires evaluating current energy policies to reshape established patterns of energy supply and use. Ignoring socioeconomic and geographic differences among households in the energy policy-making process jeopardizes the government's ability to achieve a fair distribution of resources and advance energy equity. Hence, tailored urban energy strategies that address specific opportunities to improve local sustainable development and energy justice are needed. In this paper, we use the energy burden, i.e., the share of household income spent on energy services, as a metric to characterize energy affordability for urban households in Mexico. We estimate the electricity and gas consumption as well as their resulting financial burden for 17,850 urban households in 72 metropolitan areas. The calculated median monthly energy consumption of Mexican urban households is 453 kWh and is dominated by gas consumption. This results in a median energy burden of 3.5%. However, we observe a large diversity among households in energy consumption and, consequently, in energy burden, due to variations in energy use among urban households derived from their socioeconomic and geographic conditions. In addition, we analyze the role of the temperature-based residential electricity subsidy. We find that even with subsidized electricity prices, the current subsidy scheme is insufficient to alleviate energy vulnerability in urban Mexico, and at the same time, it has a regressive effect by benefiting those consuming more. Based on the analysis of the energy burden at the city level, we highlight evident problems and potential solutions missed by one-size-fits-all energy policies. This analysis provides a better understanding of the drivers and distribution of energy burden in urban households. It also presents practical insights that could help policymakers ensure that energy is available to all households according to their needs and that demands for reductions in energy consumption as well as for adoption of clean energy technologies and energy efficiency measures come from each according to their capacity.

Scenarios for different ‘Future Indias’: sharpening energy and climate modelling tools

ABSTRACT India is crucial to the future of the global energy system, and hence to efforts to mitigate climate change. However, projecting India’s energy future is challenging because of a number of structural uncertainties related to its still emergent development process – there are multiple ‘future Indias’. This is particularly so given India’s unusual historical development pattern and economic structure. This paper reviews more than 40 energy system scenarios for India to 2050 including scenarios of different policy stringency. This analysis suggests that the task of drawing policy insights is hampered by widely divergent, often non-transparent and insufficiently discussed, assumptions about GDP and its structural attributes as implied by sectoral energy consumption, industrial intensity of GDP, and sectoral demand patterns. It is these assumptions that crucially drive the divergence in scenario results, even more than assumptions about energy and climate policy per se. While divergent results are important for exploring the range of possible future pathways, policy insights can only be generated if scenario producers adequately convey a sense of causality, probability and desirability underpinning their scenarios. This requires linking more detailed socio-economic scenario storylines with the input assumptions and output results of energy system scenarios. To improve modelling for policy insight, the paper proposes that more attention be devoted to developing overarching socio-economic development scenarios, linking these to sector dynamics, and unpacking and interpreting model results. Key policy insights India’s development pathway is characterized by a relatively low level of industrialization, precocious growth of services, and low and slow urbanization compared to similar countries. The unusual features of India’s development pathway have a material impact on its energy system. There is a wide range of uncertainty pertaining both to India’s future rate of GDP growth, but also to the persistence or reversal of the aforementioned structural characteristics. Existing modelling studies do not adequately detail and contextualize assumptions about India’s macro-scale development pathway, and its links to micro-scale patterns of sectoral energy demand and supply, leading to a wide divergence of results and uncertainty over how to interpret them. Addressing these lacunae requires enhanced transparency and discussion of overarching socio-economic development scenarios for development, linking these to sector dynamics, and unpacking and interpreting model results.

Aggregated World Energy Demand Projections: Statistical Assessment

The primary purpose of this research is to assess the long-range energy demand assumption made in relevant Roadmaps for the transformation to a low-carbon energy system. A novel interdisciplinary approach is then implemented: a new model is estimated for the aggregated world primary energy demand with long historical time series for world energy, income, and population for the years 1900–2017. The model is used to forecast energy demand in 2050 and assess the uncertainty-derived risk based on the variances of the series and parameters analysed. The results show that large efficiency savings—up to 50% in some cases and never observed before—are assumed in the main Roadmaps. This discrepancy becomes significantly higher when even moderate uncertainty assumptions are taken into account. A discussion on possible future sources of breaks in current patterns of energy supply and demand is also presented, leading to a new conclusion requiring an active political stance to accelerate efficiency savings and lifestyle changes that reduce energy demand, even if energy consumption may be reduced significantly. This will likely include replacing the income-growth paradigm with other criteria based on prosperity or related measures.

Application of Business Model Canvas for Solar Thermal Air Conditioners

Growing populations, burgeoning economies, and technology-driven lifestyles demand an increasing supply of energy. The existing energy supply pattern primarily depends on fossil fuels that have initiated climate change–provoking myriad problems. Integration of renewable energy sources in the existing energy supply system is a complex and challenging task keeping in view the depleting fossil fuels and prevailing environmental challenges. The existing cold storage farms are working on traditional compressors and the HVAC system, causing more use of electricity. Similarly, existing data centers and supermarkets are also using conventional refrigerants. These systems also use hazardous environmental refrigerants, which make these systems more dangerous. In the summer season, comfort cooling and refrigeration requirements rise to peak in hot climate areas forcing utilities to supply more electrical energy to meet the demand. Therefore, a solar thermal cooling system employing a solar absorption chiller operated through a hot water stream generated by a solar evacuated glass tube collector with CO2 as a refrigerant is simulated in the TRNSYS® simulation environment. The results are generated for the hot climate of Multan, Pakistan, and the average obtained temperatures of the three rooms, cold storage, office, and kitchen room, were 18.43, 26.25, and 29.83°C, respectively. However, every startup or new idea needs a proper business model before entering into the market. This article offers a complete insight and a future perspective for the reader to develop a precise business model for the commercialization of his or her project. A business model is designed for solar thermal air conditioners for domestic, cold storage, and data centers applications in the world, after reviewing and interviewing manufacturers and customer segment in air conditioning fields. Data were collected through semi-structured one-to-one interviews from a convenient sample of 10 national and international respondents, and their views were thematically analyzed. The implementation of a business model using a case for the Pakistani market is presented. A business model for a solar cooling system utilizing abundant CO2 as a refrigerant is presented in this article. This business model is equally suitable for designing a business model for any renewable energy product in the world.

What lies ahead for energy and carbon emissions post covid-19

Energy supply and demand patterns changed as the response to the COVID-19 pandemic evolved and remained uncertain. The outbreak has been a one-of-a-kind situation unlike anything seen in the last one hundred years. As a result of various measures put in place by governments, travel was vastly reduced, and air travel diminished to near zero. Consumption and the price of fossil fuels decreased significantly and hundreds of millions of metric tons of CO2 emissions were prevented. The impact of Covid-19 on the worldwide energy industry and greenhouse gas emissions has been drastic but seemingly temporary. In 2020, wildfires in western United States more than made up for the reduction in global emissions in the first half of 2020 due to the pandemic. Renewable energy has made major advances recently, but fossil fuels still supply 84% of the global energy. Advancements in aircraft efficiency and extensive utilization of electric vehicles charged with renewable sources of electricity offer remarkable opportunities for improving our environment. Without major changes in the energy and transportation industries, greenhouse gas emissions are likely to return to their 2019 levels before long. © 2021, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

Geological Structure and Oil and Gas Exploration of the Eastern Mediterranean

Qian, X., 2020. Geological structure and oil and gas exploration of the Eastern Mediterranean. In: Hu, C. and Cai, M. (eds.), Geo-informatics and Oceanography. Journal of Coastal Research, Special Issue No. 105, pp. 119–123. Coconut Creek (Florida), ISSN 0749-0208.The continental shelf of the Eastern Mediterranean contains abundant hydrocarbon resources. With the continuous development of exploration technology, many large and superlarge oil and gas fields have been discovered in the Levant Basin and the Nile Delta Basin. The hydrocarbon reservoirs in the Levant Basin are mainly distributed in the Oligocene–Lower Miocene Tamar sandstone and Miocene shale caprock. The shallow-water area of the Nile Delta Basin has a high degree of exploration and complete production facilities, making it the best area for rolling exploration; the mid- to deep-water Oligocene section will be the main potential area for the future discovery of large- and medium-sized natural gas fields; the ultra-deep-water area has the exploration potential of large-scale Miocene and Pliocene biogas reservoirs. The discovery of offshore gas fields may quickly change the situation of long-term energy shortages and is potentially of great significance to changing the energy supply pattern in the region.

Integrating emerging and existing renewable energy technologies into a community-scale microgrid in an energy-water nexus for resilience improvement

Rapid urbanization around the world, especially in developing countries, has resulted in a dramatic increase in the need for energy and water resources. This global trend calls for a sustainable shift in energy supplies for urban areas that can deliver robust, economic, environmental, and social benefits. This paper presents a novel planning strategy, along with an integrated system design of microgrids (MGs), to help realize sustainable energy supply patterns in a decentralized manner for improving community resilience and environmental sustainability. The exploration started with the screening of emerging and existing renewable energy technologies that can be integrated and deployed in a community-scale MG. Seamless integration of energy and water technology hubs was examined to develop a sustainable system design of MG in an energy-water nexus within the community under study. Then, a multi-objective programming model was formulated for decision analysis by systematically considering the cost, greenhouse gas (GHG) emissions, and water consumption of the MG. In comparison with existing utility grids, the multi-objective decision analysis helps find a suite of tradeoffs among three economic and environmental indicators, i.e., cost, GHG emissions, and water consumption. Case studies show that the proposed system design of the MG for the urban community can cut more than 75.5% GHG and 75.6% water consumption, compared to the benchmark in a centralized utility system. Case studies also show that this planning strategy can harmonize environmental, economic, and social benefits, making the traditional wide-area synchronous grid greener, cheaper, and more reliable. It is indicative that the system design of MG in an energy-water nexus will improve the reliability of energy supplies and strengthen community resilience, thereby increasing overall economic benefits in the long run.