Diversification Of Energy Sources Research Articles

A Case Study on Deep Learning for Photovoltaic Power Forecasting Combining Satellite and Ground Data

The increasing demand for clean energy presents challenges in energy supply management, largely due to their intermittency. Photovoltaic power generation, in specific, is greatly affected by weather factors, which may render power grids susceptible to instability, quality and balance issues. In this context, photovoltaic power generation forecasting is crucial not only to enhance the management of diverse energy sources through generation planning, but also to ensure widespread adoption of photovoltaic energy. To address the predictability issue in generation, this study aims to investigate the combination of satellite data with meteorological data to predict the energy generation potential in photovoltaic panels within 30, 60, 120, and 180-minute horizons. For this purpose, images from the GOES-16 satellite are used in combination with data from a ground-based weather station, located at Florianópolis – Santa Catarina – Brazil. The data is fed to a convolutional neural network, where convolutions are employed to extract features from the satellite images, aiming to establish a relationship with solar irradiation. The output of the convolutional network serves as input for a multilayer perceptron network, which utilizes the data to predict the Global Horizontal Irradiance (GHI). Our results support that models incorporating satellite images provide forecasts approximately 41% better for the 30-minute horizon and 21% better for the 180-minute horizon, when compared to models without satellite images.

Russian-Ukraine War and its Impact on the European Economy

This study examines the impact of the Russian-Ukraine war on the economy of Europe, concentrating on trade disruptions, energy security, foreign direct investment (FDI) flows, and the socioeconomic ramifications of the war[1]induced refugee crisis. This study employs the descriptive research design, qualitative research method and a secondary source of data collection. The research uncovers the problems and possibilities coming from the war, as well as the larger implications for economic growth, development, and stability in the area. The results reveal severe interruptions to commercial links between European nations, especially Russia, and Ukraine, with key sectors such as energy, manufacturing, and agriculture facing considerable disruptions. Energy security emerges as a significant worry, spurring attempts to diversify energy sources and lessen dependence on Russian supply. Meanwhile, the war has resulted in a drop in FDI inflows to Russia and Ukraine, aggravating economic concerns in both nations and hurting their growth prospects. Furthermore, the research shows the burden on social welfare systems in European nations hosting migrants, since the inflow of refugees exerts great demands on resources and capabilities. Investments in housing, health care, education, and social welfare are vital for satisfying the different needs of displaced people and facilitating their long-term integration into society. However, issues connected to social cohesiveness, community connections, and political dynamics within host nations also occur. The study recommends diplomatic resolution of the dispute through peaceful discussions, involving European Union (EU) member states- Russia, Ukraine, and other parties. This could involve neutral mediation, de-escalating initiatives, and confidence-building measures.

Reducing uncertainties of climate projections on solar energy resources in Brazil.

The share of solar power in Brazil's electrical grid has rapidly increased, relieving GHG emissions and diversifying energy sources for greater energy security. Besides that, solar resource is susceptible to climate change, adding uncertainty to electrical grid resilience. This study uses satellite and reanalysis data to evaluate the performance of CMIP6 models in replicating and predicting surface solar irradiance (SSR) in Brazil. The results from the most reliable models indicate an increase in SSR by 2% to 8% in most regions, with a decrease of around 3% in the South. These findings highlight the potential for increased photovoltaic (PV) yield if backed by supportive public policies while underlining the importance of uncertainty assessment of climate models.

Comparative Policy Analysis of Renewable Energy Expansion in Mongolia and Other Relevant Countries

The study aims to conduct a comparative analysis of policies governing the expansion of renewable energy in Mongolia and selected countries. Against the backdrop of global energy transitions and Mongolia’s recent energy challenges, this research aims to identify and evaluate policy frameworks that facilitate the sustainable growth of renewable energy sources. The study delves into the unique socio-economic and geopolitical context of Mongolia, emphasizing the nation’s energy dependence on Russia. The findings of this comparative analysis provide valuable insights for Mongolian policymakers, offering recommendations for enhancing domestic policies that encourage the diversification of energy sources and attract foreign investment. By drawing on successful practices from some countries, this paper aims to contribute to the formulation of effective and context-specific strategies for Mongolia to achieve a more sustainable and resilient energy landscape.

Anthropogenic impacts on the terrestrial subsurface biosphere.

The terrestrial subsurface is estimated to be the largest reservoir of microbial life on Earth. However, the subsurface also harbours economic, industrial and environmental resources, on which humans heavily rely, including diverse energy sources and formations for the storage of industrial waste and carbon dioxide for climate change mitigation. As a result of this anthropogenic activity, the subsurface landscape is transformed, including the subsurface biosphere. Through the creation of new environments and the introduction of substrates that fuel microbial life, the structure and function of subsurface microbiomes shift markedly. These microbial changes often have unintended effects on overall ecosystem function and are frequently challenging to manage from the surface of the Earth. In this Review, we highlight emerging research that investigates the impacts of anthropogenic activity on the terrestrial subsurface biosphere. We explore how humans alter the constraints on microbial life in the subsurface through drilling, mining, contamination and resource extraction, along with the resulting impacts of microorganisms on resource recovery and subsurface infrastructure.

The Economic Shockwaves of the Russia-Ukraine Conflict and Energy Sources Prices – The Impact on International Energy Markets

The Russia-Ukraine conflict has raised concerns regarding the stability of the global energy sector, considering that Russia is a big player in the industry, producing and exporting crude oil and natural gas globally. This study aimed to empirically investigate the impact of the conflict on the prices of energy sources in international markets. The analysis was conducted using secondary data. The data was for prices of various commodity products, including diesel, petroleum, natural gas, and crude oil. The data was collected on multiple international markets for periods from January 1, 2021 to November 30, 2023. The analysis was conducted using trend analysis and event study. The capital asset pricing model (CAPM) was adopted to run the event study analysis. The results indicated that immediately after the Russian invasion of Ukraine, major energy products such as US crude oil, European crude oil, and the global energy index experienced a sharp rise in price, followed by significant price volatility over the following up to seven months. The review of OPEC energy prices also indicated an increase in prices, and volatility was experienced in countries producing and exporting oil products. The event study further revealed that there was a sharp increasing trend immediately after the event date and an upward trend for more than ten months after the event, resulting in the highest prices recorded in the event window. The study suggested three policy implications - conflict should serve as a wake-up call on diversification of energy sources, investment in alternative, sustainable and green sources of energy to reduce the dependence on oil, and promotion of international cooperation on energy security.

Analysing the impact of diverse factors on electricity generation cost: Insights from Sri Lanka

The primary responsibility of a power system utility is to provide continuous, high-quality electricity at a fair and competitive price. To maintain low generation costs while utilising diverse energy sources, optimisation methodologies are crucial. Water value and generation costs exhibit significant variability on seasonal, daily and timely basis and reflect dynamic interactions between electricity demand and power plant availability. Currently, power system planners often overlook these seasonal and time-of day dependent variations in water value and generation costs. This research paper addresses this gap by analysing how fluctuations in electricity demand and power plant availability affect generation costs in the Sri Lankan power system. It introduces a novel economic dispatch model and presents three methods for estimating water value to calculate seasonal and time-of-day electricity costs. The discussion highlights how these findings can utilise policymaking, particularly in the context of electricity pricing debates and water management for agriculture versus electricity generation, as well as in calculating the water value for each reservoir.

Sustainable mega-seaports with integrated multi-energy systems: Life-cycle environmental and economic evaluation

Ports play a critical role in modern society by acting as crucial links between water and land transportation, and integrating transportation with energy systems. This integration results in a high demand for various types of energy uses, with polluting emissions produced by the diverse energy sources. Integrated renewable energy systems represent promising solutions to achieving high levels of energy supply while lowering carbon footprints. In this research, a framework is proposed for a port multi-energy system that encompasses solar energy, wind energy, a hydrogen system and a number of energy storage systems. The proposed framework is tailored for implementation at Ningbo Zhoushan Port, the largest port globally. Different system design schemes are compared based on the number and rated power of wind turbines. Then, a comprehensive life-cycle economic and environmental assessment of the system is conducted through simulation. The economic and environmental metrics such as LCOE, REF and CO2 emissions are considered. The outcomes demonstrate that the design scheme incorporating two wind turbines with high rated power outperforms others in both environmental and economic metrics. Over the life-cycle, the renewable energy fraction exceeds 72%, and the levelized cost of energy plummets to 0.46 yuan/kWh. The implementation of the proposed port integrated multi-energy system yields substantial environmental and economic benefits. Specifically, it allows for a reduction of 66.68% in CO2 emissions and a cost reduction of 70.94%. These outcomes highlight the potential that the proposed system holds for enhancing environmental sustainability and economic efficiency within the port context.

Comparative Analysis of Hybrid Geothermal-Solar Systems and Solar PV with Battery Storage: Site Suitability, Emissions, and Economic Performance

Renewable energy integration has become a critical focus in the global effort to reduce carbon emissions and diversify energy sources. In regions with distinct geographic features, such as Türkiye, combining different renewable technologies can offer enhanced energy security. This study investigates the site suitability and economic and environmental performance of hybrid geothermal-solar systems and solar PV systems with battery storage across the provinces of Osmaniye, Hatay, and Kilis, of Türkiye. Using the fuzzy-AHP method, site suitability is evaluated, addressing a key gap in comparing these systems' adaptability to varying geographic conditions. This study is the first to directly compare these two renewable energy technologies in terms of site suitability. The findings reveal significant differences in site suitability, with solar PV systems with battery storage demonstrating broader applicability across the region. The suitable sites (20-100% suitability) cover 1260.82 km² for solar PV systems with battery storage and only 122.18 km² for hybrid geothermal-solar systems. In terms of environmental impact, hybrid geothermal-solar systems exhibit significantly lower carbon emissions, averaging 44.6 kg CO₂/MWh, compared to 123.8 kg CO₂/MWh for solar PV systems with battery storage. Economically, hybrid geothermal-solar systems also outperform with a lower levelized cost of electricity of $0.091/kWh versus $0.254/kWh for solar PV systems. These results highlight the environmental and economic advantages of hybrid geothermal-solar systems, while also emphasizing their limited scalability to regions with geothermal activity. Conversely, solar PV systems, despite their higher emissions and costs, offer greater flexibility and potential for widespread deployment.

Desertification indirectly affects soil fauna by reducing complexity of soil habitats and diversity of energy sources

Soil fauna is closely linked to ecological functions such as biogeochemical cycling, soil structure, ecosystem sustainability and trophic interactions. However, little consideration has been given to how desertification influences the abundance and diversity of soil fauna in arid areas. In this study, soil fauna was sampled in four desert habitats (gravel, sand, salt and mud desert) in northwest China. At the same time, the plant traits, geographic location and soil properties were investigated. We also measured contribution of environmental factors explained faunal community diversity and abundance, and by what pathways desertification controls soil fauna. The results showed that total abundance and diversity of soil fauna in the mud desert were significantly (P < 0.05) higher than salt, sand and gravel deserts. Soil fauna diversity, composition and community were more sensitive to desertification-induced changes in soil properties than to changes in plant traits and geographic locations (changes in soil properties explained 68.9 % and 73.7 % of the variation in diversity and abundance of soil fauna community, respectively). Among them, the available phosphorus, volumetric water content had a significant positive effect on community diversity and abundance, while pH had a significant negative effect (P < 0.01). The results of piecewise structural equation modeling imply that desertification may have mainly indirect impacts on soil fauna community, and that direct effects are almost zero. In summary, regardless of the type of desertification, it will affect the material cycle, energy flow and information transfer of ecosystems by destroying the soil habitats and vegetation conditions, and will affect the structure and diversity of soil fauna from the bottom up.

Optimizing sustainable energy integration: A novel approach using concentrated solar plant and hybrid power supply

This study pioneers sustainable energy solutions amidst escalating demand and fossil fuel depletion. Its primary novelty lies in proposing an integrated energy system, encompassing a concentrated solar plant, thermal energy system, and hybrid power supply within the solar energy domain. This integration substantially enhances overall system performance. The architectural design integrates various energy conversion components, including wind turbines, energy storage devices, and electric heaters, fostering synergistic collaboration. The optimization of energy usage is a key focus, utilizing heating and electricity costs as pivotal signals for participation in an Integrated Demand Response program (IRD). The demand response model, encompassing both thermal and electric loads, incorporates a sophisticated price elasticity matrix. Addressing challenges associated with renewable energy intermittency, phased carbon emissions, and the advantages of demand response, this study introduces an advanced system operation optimization model to effectively curtail operational costs. In the realm of methodology, this research breaks new ground by proposing an enhanced optimization algorithm that ingeniously combines the Whale Optimization Algorithm (WOA) with the Wavelet Transform (WT). This novel amalgamation significantly enhances the algorithm's search capabilities, providing superior performance in tackling the complexities inherent in the optimization problem. The proposed model undergoes rigorous evaluation in a comprehensive study featuring diverse energy sources and multiple scenarios. The outcomes of this evaluation distinctly showcase substantial reductions in overall operational costs compared to conventional approaches. This multifaceted contribution positions the study at the forefront of endeavors to revolutionize energy systems for enhanced sustainability and efficiency.

Dynamic model of integrated electricity and district heating for remote communities

District heating networks offer promising solutions for remote communities, providing centralized heat supply, improved efficiency, and diverse energy sources, especially with existing diesel generation. Hence, this paper bridges gaps in the existing literature by developing comprehensive dynamic models of combined district heating networks within existing electric power networks in remote communities, which allows identifying challenges and benefits of district heating networks for these communities. It is shown that district heating networks allow utilizing waste energy to enable energy exchanges between the electricity and heating systems, enabling the provision of necessary ancillary services for remote microgrids with renewable energy sources. The presented dynamic district heating network model incorporates particular considerations in remote, northern communities such as soil limitations, extreme cold conditions, and piping insulation to minimize heat loss. It also addresses accurate sizing of heat pumps based on realistic thermal load requirements, weather conditions, and consumer profiles, proposing demand management controls to enhance frequency regulation for the integration of variable renewable energy sources. The main contributions of the paper include detailed dynamic modeling for district heating network operation, heat pump demand response control system design, and a comparative analysis between centralized district heating networks and decentralized electric thermal storage units that have been deployed for thermal supply in remote areas. The presented dynamic models are applied, tested, and validated in an existing electric microgrid at Kasabonika Lake First Nation in Northern Ontario, showcasing the role of a potential district heating network in facilitating renewable energy sources integration in isolated microgrids.

POWER SECTOR MANAGEMENT FAILURE AND LOAD SHEDDING IN ZAMBIA

This paper examines the management failures within Zambias power sector and their direct linkage to the persistent issue of load shedding. It highlights the critical role of ZESCO, the state-owned utility, in navigating financial constraints while attempting to meet the electricity demands of both domestic consumers and export contracts. The study identifies key factors contributing to load shedding, including inadequate infrastructure, demand forecasting failures, and political influences that prioritize short-term gains over sustainable energy solutions. Furthermore, the paper discusses the potential of diversifying energy sources, such as solar and wind, to mitigate reliance on hydroelectric power and enhance resilience against climate variability. Recommendations for comprehensive strategies to address the energy crisis and improve load management are provided, emphasizing the need for long-term planning and investment in renewable energy initiatives.

Reorientation of energy policy and management: Integrated Energy Planning (IEP) framework implementation for Renewable and Thermal Energy Systems (RTES)

To bridge the critical implementation gap in Renewable and Thermal Energy Systems (RTES) sector, this study proposed a groundbreaking Integrated Energy Planning (IEP) framework. Existing policy analysis methods for RTES often fall short. This limitation was addressed by investigating the disconnect between policy vision and execution within intricate energy landscape. This analysis was extended beyond Pakistan, incorporating energy policies from leading developed and developing nations alongside a comprehensive existing energy modeling efforts for RTES. By leveraging these insights, the potential of IEP was demonstrated to account for trade-offs and seamlessly integrate diverse energy sources. This paves the way for a more sustainable, secure, and efficient RTES for future.

Renewable Energy Consumption Determinants: Do They Differ between Oil-Exporting Countries and Oil-Importing Ones?

This paper delves into the critical determinants of renewable energy consumption, focusing on the contrasting roles of oil imports and exports. It aims to bridge the knowledge gap by comparing these determinants across both oil-importing and oil-exporting nations, offering a comprehensive and nuanced perspective to inform policy recommendations. Using annual data from 1990 to 2018 sourced from the World Bank database, the study employs panel multiple regression analysis and adopts a fixed effects model to explore two main questions: What drives the use of renewable energy sources? How does a country’s oil importer or exporter status affect these factors? The findings reveal a significant but inverse relationship between oil rents and renewable energy consumption (REC) for both types of countries. Additionally, there is a notable negative correlation between GDP growth and REC for both oil-exporting and oil-importing countries. Interestingly, the crude oil average closing price and inflation show an insignificant impact on REC in both contexts. The study also highlights that net energy imports significantly affect REC, with a much stronger inverse relationship in oil-importing countries compared with oil-exporting ones. For oil-importing countries, diversifying energy sources is a crucial investment. Governments should prioritize research and development in renewable energy to spur technological advancements, enhancing efficiency and affordability. Economic growth-promoting policies, such as tax incentives and subsidies for renewable energy businesses, are vital for encouraging sustainable practices. Consistent, long-term policies are essential for providing investor confidence and supporting the transition to renewable energy. For oil-exporting countries, similar strategies are recommended. Additionally, allocating a portion of oil revenues to renewable energy infrastructure and funding research and development in renewable technologies through local universities and startups are crucial steps. This dual approach will not only enhance energy diversification but also foster innovation and sustainability in the energy sector.

Advanced AI and renewable energy sources for unified rotor angle stability control

Maintaining a reliable electricity supply amidst the integration of diverse energy sources necessitates optimizing the stability of power systems. This paper introduces a groundbreaking method to enhance the efficiency and resilience of power grids. The increasing dependence on renewable energy sources poses significant challenges to traditional power networks, thereby demanding innovative solutions to uphold their stability and security. To address these challenges, we propose an architecture that seamlessly unifies dynamic, transient, and static rotor angle stability (RAS) controls into a single, streamlined system. Utilizing reinforcement learning and real-time decision-making, we present Lazy Deep Q Networks (LDQNs) as a novel approach to RAS control. LDQNs provide real-time rotor angle instructions to RAS devices, enabling precise and efficient stability management. The incorporation of mass-distributed energy storage further augments the system's responsiveness and flexibility, mitigating fluctuations and promoting overall stability. This study advances the application of AI methods to RAS control, building on prior research in frequency and voltage stability frameworks. The proposed system outperforms conventional RAS control methods by integrating LDQNs with mass-distributed energy storage, offering superior performance and adaptability. Case studies validate the effectiveness of the unified RAS framework, demonstrating its advantages over traditional approaches across various power system configurations.

Demand for electric cars and oil prices: A wavelet approach

ABSTRACT The paper explores the worldwide co-movement between the demand for electric cars and oil prices from January 3rd, 2020, to March 6th, 2023, utilizing wavelet methodology. The main finding shows a strong link between electric car demand and oil prices when oil prices are highly volatile in the short term. When oil prices suddenly drop, people’s preference for electric cars decreases in the very short term. However, in the short term, the demand for electric cars is influenced by how much oil prices change and the anticipation of future trends, causing a shift between traditional and electric cars. These results hold true even when considering factors like geopolitical risks, pandemics, the health of the car industry, and the cost of metals used in car batteries. The findings have crucial implications in the socio-economic environment, being very useful to both policy-makers and car market actors. In this light, on the one hand, the outputs can offer support in shaping policies able to reduce fossil fuel dependency and address climate change. On the other hand, this insight aids in correcting the market dynamics across automotive and energy sectors under oil price volatility. Furthermore, these dynamics can affect economic indicators like inflation, trade balances, unemployment, and GDP growth. Not least, transitioning to electric cars can mitigate emissions reduction, improve air quality, diversify energy sources, and enhance energy security.

The future of renewable energy in Iran's energy policy

Renewable energy has become a very important issue in the world. Access problems, high prices, and environmental issues of fossil fuels have caused the world to turn to renewable energy. Using the quantitative-qualitative combined methodology and the theoretical framework of energy security, this research has tried to answer the question of what the future of renewable energy in Iran is. The hypothesis of this research is that despite the adoption of programs and policies for the productivity and development of renewable energy in Iran, sanctions and investment problems make the development of renewable energy in Iran a structural problem. The findings of the research indicate that in the long term, solving structural challenges such as sanctions and investment and encouraging investment in renewable energy can provide a transition path by diversifying energy sources. So, the article tries to analyze the situation of renewable energy in terms of opportunities and challenges and show a vision of the future of this energy in Iran.

Enhancing Load Frequency Control of Interconnected Power System Using Hybrid PSO-AHA Optimizer

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller’s effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources.

Comparative genomic analysis of an emerging Pseudomonadaceae member, Thiopseudomonas alkaliphila.

Thiopseudomonas alkaliphila, an organism recently classified within the Pseudomonadaceae family, has been detected in diverse sources such as human tissues, animal guts, industrial fermenters, and decomposition environments, suggesting a diverse ecological role. However, a large knowledge gap exists in how T. alkaliphila functions. In this comparative genomic analysis, adaptations indicative of habitat specificity among strains and genomic similarity to known opportunistic pathogens are revealed. Genomic investigation reveals a core metabolic utilization of multiple oxidative and non-oxidative catabolic pathways, suggesting adaptability to varied environments and carbon sources. The genomic repertoire of T. alkaliphila includes secondary metabolites, such as antimicrobials and siderophores, indicative of its involvement in microbial competition and resource acquisition. Additionally, the presence of transposases, prophages, plasmids, and Clustered Regularly Interspaced Short Palindromic Repeats-Cas systems in T. alkaliphila genomes suggests mechanisms for horizontal gene transfer and defense against viral predation. This comprehensive genomic analysis expands our understanding on the ecological functions, community interactions, and potential virulence of T. alkaliphila, while emphasizing its adaptability and diverse capabilities across environmental and host-associated ecosystems.IMPORTANCEAs the microbial world continues to be explored, new organisms will emerge with beneficial and/or pathogenetic impact. Thiopseudomonas alkaliphila is a species originally isolated from clinical human tissue and fluid samples but has not been attributed to disease. Since its classification, T. alkaliphila has been found in animal guts, animal waste, decomposing remains, and biogas fermentation reactors. This is the first study to provide an in-depth view of the metabolic potential of publicly available genomes belonging to this species through a comparative genomics and draft pangenome calculation approach. It was found that T. alkaliphila is metabolically versatile and likely adapts to diverse energy sources and environments, which may make it useful for bioremediation and in industrial settings. A range of virulence factors and antibiotic resistances were also detected, suggesting T. alkaliphila may operate as an undescribed opportunistic pathogen.