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This simulation study explores the potential of a novel façade design with integrated control system comprising a dynamic photovoltaic (PV) facade integrated with dimming lighting control to enhance the work environment in office buildings and achieve energy-efficient solutions. Parametric modeling using the Grasshopper plug-in for Rhino software 7, coupled with energy simulation through the Honeybee environmental plug-in for the EnergyPlus program, are used in the methodology. The integrated control strategy was simulated to study in a single office space, utilizing the Daysim engine to assess indoor daylight quality and focusing on Daylight Factor (DF) and Daylight Glare Probability (DGP). Additionally, two artificial lighting control systems were examined for potential integration with the dynamic PV facade to minimize lighting load. The study employs the Galapagos evolutionary solver function embedded within Grasshopper to identify optimum solutions. The dynamic PV façade achieves substantial reductions in overall energy consumption, cutting it by 73% in June, 54% in July, 54.5% in August, and 52.55% in September. The results demonstrate substantial reductions in total energy consumption, with notable savings in heating and cooling due to the dynamic facade's ability to balance and control solar radiation during working hours. Moreover, the dynamic PV facade contributes to electricity generation, demonstrating its potential to improve visual comfort, decrease energy consumption, and generate electric energy through rotational adjustments and varying transparency levels. [ABSTRACT FROM AUTHOR]

We address the shortcomings associated with modelling national aggregate electricity consumption in a large and diverse country with unique regional characteristics. Focusing on Saudi Arabia, we employ an econometric approach to analyse the distinct responses of its regions to electricity prices and income levels. The study employs a general to specific modelling approach, utilizing data from 1990 to 2019 within the conventional energy demand theoretical framework. Our region‐specific estimations reveal income and price as the primary drivers, with the southern region exhibiting a higher sensitivity to income, while the eastern region shows a comparatively smaller response to prices attributed to its significant industrial presence. Elasticities for the central and western regions align with previous research, while eastern and southern regions exhibit larger elasticities. Weather impacts are observed only in the warmest western region, characterised by a substantial share of residential electricity consumption. Furthermore, we utilise our estimated model to project a regional baseline demand for electricity in Saudi Arabia and demonstrate how prices affect regions differently. This information is important for an oil‐exporting country like Saudi Arabia, considering the diverse fuel mix used for electricity generation across regions. Assuming moderate economic growth and no price change, our baseline projections indicate a total electricity demand of 366 terawatt hours (TWh) by 2030. [ABSTRACT FROM AUTHOR]

Hydrogen is increasingly recognized as a pivotal fuel source globally, and the generation of hydrogen from solar energy is playing a crucial role in this trend. Solar energy is highly valued for its renewability, eco-friendliness, cost-effectiveness, and ease of installation. In this present work, we assessed the electricity generation of photovoltaic-thermal and photovoltaic systems which are using solar energy. The water-cooled PV-T system was cooled at three different flow rates (0.3 kg/s, 0.39 kg/s, and 0.48 kg/s) for a total panel area of 108 m2. Electricity generated within both systems was actively utilized for hydrogen production. This electricity was employed in a Proton Exchange Membrane electrolyzer to generate hydrogen. The simulations were carried out utilizing the Engineering Equation Solver for a specific day in July, encompassing the hours from 8 a.m. to 5 p.m., with each hour being considered. Daily electrolyzer performance was affected by the voltage and current density effects of four different electricity generation configurations, as well as the change in ambient temperature. The daily electricity production for PVs and PV-Ts, with cooling flow ratios of 0.3 kg/s, 0.39 kg/s, and 0.48 kg/s, was 338.2 MJ, 344.89 MJ, 351.42 MJ, and 356.08 MJ, respectively. Additionally, the daily hydrogen production with PEM in combination with PVs and PV-Ts, both without cooling and with the same flow rates, was 1617.2 g, 1646.5 g, 1675.3 g, and 1696 g, respectively. The maximum energy efficiency for PEM was 70.01 %, 69.98 %, 69.95 %, and 69.92 %, while the highest exergy efficiency for the same configuration was 59.75 %, 59.72 %, 59.69 %, and 59.67 %, respectively. In summary, the application of cooling to solar panels leads to increased electricity generation, resulting in higher current and voltage for the PEM. This has minimal adverse effects on the energy and exergy efficiencies of the PEM. Despite a slight negative impact, the cooled system outperforms the non-cooled one in hydrogen production. Furthermore, the system achieved its maximum energy and exergy efficiencies, reaching 50.24 % and 9.772 % when using mass flow ratios of 0.48 kg/s and 0.30 kg/s in PV-T on the selected day. • Hydrogen production of the PEM with PVs and PV-Ts. • Thermodynamic performances of PV, PV-T, PEM and overall the systems. • The comparison of the electrical energy production PVs and PV-Ts. • The impact daily ambient temperature and solar radiation on the systems. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The need to replace nonrenewable sources is a global challenge, especially for emerging countries with financial constraints to invest in energy transition. In Brazil, electrical generation is predominantly renewable, since the hydraulic source is responsible for more than half of the domestic electricity supply. Other alternative sources, such as biomass, solar, and wind, complement the renewable portion of the Brazilian electrical matrix. However, periods of drought and climate disturbances threaten the stability of the electrical system and increase dependence on thermal generation. Based on the global movement to intensify the use of renewable sources, which are volatile and influenced by climate variations, the objective of this research is to predict electricity generation using the Heston model. This model, originally applied to predict option prices, assumes nonconstant volatility and has the ability to estimate the average value including the stochastic volatility process. The database is made up of monthly values of the volume of electrical energy generation from biomass, coal, fuel oil, hydraulic, industrial waste, natural gas, nuclear, solar, and wind sources. Compared to the Black‐Scholes model, the chosen method proved to be superior in predicting the generation from coal, hydropower, and solar energy, according to the MAE, MAPE, and RMSE statistics. We conclude that a financial model can be effectively applied to the energy sector and the Heston model can be a useful instrument to assist in the planning and management of the national electrical system. One suggestion for the Brazilian case is to encourage the use of alternative energies and low‐carbon sources, such as solar, wind, and natural gas, providing greater energy security and a more reliable electrical system. [ABSTRACT FROM AUTHOR]

This paper investigates the asymmetric demand for clean energy for a panel of OECD countries. We construct a price index for clean energy based on information on the energy composition of electricity generation, and focus on the possibility of non-symmetric clean and dirty clean consumption due to rising and falling energy prices, and to positive income growth and negative income growth. Using an Autoregressive Distributed Lag (ARDL) model that encapsulates both long-run equilibrium among energy demands, energy prices and income, and short-run dynamics. We find evidence that clean energy demand adjusts more aggressively to a price decline than a price rise. In addition, we find that clean energy consumption is more responsive to negative income changes than to positive income changes. A climate policy implication is that policy should account for reversal effect of clean energy consumption during periods of economic downturn. [ABSTRACT FROM AUTHOR]

As the imperative to address climate change intensifies, understanding the effectiveness of policy interventions becomes paramount. In the context of addressing these urgent challenges and given the inadequacy of current policies to address this issue, this study examines the extent to which Nationally Determined Contributions (NDCs) and Long-Term Targets (LTTs) can contribute to achieving ambitious climate goals. Recognizing the critical need for effective climate action, we employ the advanced modelling tools PROMETHEUS and GCAM to assess the implications of different scenarios–Current Policies (CP), Nationally Determined Contributions (NDC), and combination of NDCs with Long-Term Targets (NDC_LTT)–on the future development of energy system and emission. This study, by employing these well-known models, seeks to provide an improved understanding of the impacts of NDCs on global emission trajectories and whether the integration of NDCs and LTTs can help close the gap towards Paris-compatible pathways. The study analyzes various sectors including buildings, transportation, electricity generation, and industry to provide insights into the limitations of existing policies and the potential of enhanced commitments to drive transformative changes in a global scale. The effectiveness of these policies varies across different sectors, highlighting the challenges that need to be addressed for achieving the required emission reduction targets in the medium- and long-term. Key findings indicate significant shifts in energy consumption, fuel mix, technology adoption, and emission trajectories, particularly under the synergistic action represented by the NDC_LTT scenario. [ABSTRACT FROM AUTHOR]

In this paper, the prioritization and weighting of different methods of using renewable energy, as well as the feasibility of using renewable energy in the management of sports venues in the water and electricity industry of east Azerbaijan province, have been discussed. The D-number theory method has been used to prioritize different renewable energy methods. The information gathered from experts in this field shows that solar energy weighing 0.5345 is the best method for producing electrical energy in sports and welfare venues. Wind energy, with a weight of 0.5183, and water energy, with a weight of 0.5126, are in the next ranks. The indicators used in ranking factors include total costs, energy efficiency, and compatibility with environmental conditions. Based on the results of the feasibility study and the available findings, it can be seen that the total cost of using renewable energy in the sports and welfare venues of East Azerbaijan province is equal to 10093.4 million Rials. Also, the interest return rate of the investment is equal to 19.43%. Therefore, using solar energy as a source of electricity production has technical and economic justification. [ABSTRACT FROM AUTHOR]

[Display omitted] The mounting global energy demand urges surplus electricity generation. Due to dwindling fossil resources and environmental concerns, shifting from carbon-based fuels to renewables is vital. Though renewables are affordable, their intermittent nature poses supply challenges. In these contexts, aqueous flow batteries (AFBs), are a viable energy storage solution. This study tackles AFBs' energy density and efficiency challenges. Conventional strategies focus on altering molecule's solubility but overlook interface's transport kinetics. We show that triggering electrostatic forces at the interface can significantly enhance the mass transport kinetics of redox active molecules by introducing a powerful electrostatic flux over the diffusional flux, thereby exerting a precise directionality on the molecular transport. This approach of controlling the directionality of molecular flux in an all iron redox flow battery amplifies the current and power rating with approximately 140 % enhancement in the energy density. [ABSTRACT FROM AUTHOR]

This article explores the potential and limitations of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in comparison to the human brain. It acknowledges that while AI can mimic the neural networks of the human brain, it falls short in terms of learning efficiency, intuition, and creativity. The article also raises concerns about the significant energy consumption of AI. In contrast, it highlights the energy efficiency of the human brain and the role of neurotransmitters and neuromodulators in its functioning. The author recognizes the contributions of Miklos Palkovits, a researcher in chemical neuroanatomy, and emphasizes the ongoing efforts to understand the complexities of the human brain. The accompanying document provides a comprehensive list of references and citations from scientific articles on neuroscience, AI, and energy consumption, offering diverse perspectives and research findings for library patrons conducting related research. [Extracted from the article]

Purpose: Several studies using life cycle assessment (LCA) have highlighted nuclear electricity's possible role as a low carbon-emitting electricity source. But the variability of results has also been questioned by several published LCA reviews, the latest identified dating back from 2016. This article aims at assessing whether new developments and knowledge confirm this statement. Methods: Meta-analysis is a systematic review approach that allows to assess this variability. It was applied in this study to measure and understand the dynamics behind the greenhouse gases (GHG) emissions of nuclear electricity in a life cycle perspective. From 114 publications identified since 2012, 22 primary studies were selected and analysed to provide a meta-database of 63 estimations of greenhouse gases (GHG) per kWh generated. A descriptive analysis of the meta-database provided a status of the art on the topic in terms of approaches adopted, data sources, etc. Additional data exploitation using boxplot graphs was performed to assess the dispersion and variability of the results around these figures depending on several factors such as extraction mining technique and energy demand, enrichment technology used, reactor's size, and type of LCA practitioners. Results and discussion: The life cycle GHG emissions of nuclear electricity found with the meta-analysis were 3.09 g CO2 eq./kWh (min), 6.36 g CO2 eq./kWh (median), 12.4 g CO2 eq./kWh (average excluding extrema), and 43.2 g CO2 eq./kWh (max), although extremum values were also identified at 53.4, 60.0, and one outlier, based on theoretical scenarios. Using principal component analysis (PCA), the two most influential variables of the environmental performance of nuclear electricity were identified: GHG emissions intensity of the electricity consumed during the enrichment of uranium and energy demand for the extraction of uranium ore. Conclusions: Finally, the contributions of this meta-analysis to current knowledge on the GHG emissions intensity of nuclear electricity generation systems were discussed, including life cycle step breakdown, data gaps, limits, and uncertainties associated to the back end and reactor activities. Among the main areas for improvement for future LCA studies, the study helped identify a need for consolidated industrial data along with harmonised practices regarding system boundary definition. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift fur Wirtschaftspolitik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examines the determinants of modern cooking fuel choices in Korea. The ordered probit model is estimated using an extensive online survey of Korean household energy consumers. Our empirical results showed that age, gender, and education are significant determinants of modern cooking fuel choices among the socioeconomic demographic variables: females, older people, and highly educated people are more likely to prefer electricity. Also, electricity is more likely to be preferred over natural gas by people who have a higher preference for district heating. Two psychological factors significantly influence cooking fuel choices. People whose behaviors are environment-friendly and people who are more health-conscious are more likely to prefer electricity over natural gas or propane. There are three important insights into the cooking fuel transition toward electricity. First, as interest in health and climate change has significantly increased in recent years in Korea, it may stimulate the transition from natural gas or propane to electricity. Second, electrification of cooking methods will be beneficial for the environment if electricity generation becomes less carbon-intensive. Since electricity in Korea is mainly generated by fossil fuels, it is crucial to implement more aggressive policies toward renewable sources in the energy mix for electricity generation. Third, the public should better understand why this problem cannot be overlooked because the energy mix is important in mitigating climate change. The better the people understand the exact relationship between energy consumption and pollutant emissions, the more effective and environmentally sound will the energy mix policy become. [ABSTRACT FROM AUTHOR]

Global concern over socioeconomic activities' environmental impact is undeniable, given their implications for climate and human welfare. In our study, we analyze Pakistan's landscape, with emphasis on the effects of electricity generation and consumption (both symmetric and asymmetric), energy trade, and the role of information and communication technology (ICT). We harnessed data from 1993 to 2020, sourced from World Development Indicators, Climate Watch, and the USA EIA. Our analysis involved application of the Nonlinear Autoregressive Distributed Lag model and the Autoregressive Distributed Lag bounds testing methods. Our results reveal that electricity consumption, whether experiencing positive or negative shocks, exhibits a tendency to elevate emissions over the long term. Similarly, shocks in electricity generation from fossil fuels, whether positive or negative, have adverse environmental consequences both in the short and long run. A negative shock in electricity generation from renewable and alternative sources triggers environmental degradation. Remarkably, nuclear energy plays a pivotal role in bolstering environmental sustainability in Pakistan. Conversely, we identified factors contributing to ecological degradation, including imports of coal, crude oil, metallurgical coke, and ICT usage, in the long run. Equally, trade and natural resources rent emerge as mitigating factors over time. Ultimately, our study underscores the importance of diversifying the energy mix, with a particular emphasis on expanding the renewable sources for reducing emissions and fostering environmental sustainability in Pakistan. Additionally, our research suggests that leveraging natural resources rent and trade capabilities can pave the way for an eco-friendlier future in the country. This study assesses the environmental impact of electricity generation by source, electricity consumption, energy trade, and ICTs in Pakistan. The findings confirm that both positive and negative shocks in fossil fuel electricity generation and consumption detrimentally affect the environment. Coal, crude oil, metallurgical coke imports, and ICTs degrade the environment, while nuclear electricity generation, natural resources rent, and trade improve it. Integrating energy diversification with focus on promoting renewable energy sources has the potential to significantly reduce emissions and advance long-run environmental sustainability. Strategically utilizing natural resources rent and trade capabilities can aid in establishing an environmental sustainability in Pakistan. [ABSTRACT FROM AUTHOR]

Several northern European countries have announced ambitious plans to become carbon neutral already before the year 2050. Recent research has, however, highlighted how potential bottlenecks in raw material and resource availability could significantly delay or hinder wind and solar photovoltaic (PV) expansion and continued biomass usage in parts of Europe. To address this issue, this paper assesses how exposed the national energy and climate plans (NECPs) of Finland, Estonia, Germany, Sweden, and Denmark are to resource limitations and techno-economic risks by reviewing and analysing 2030 NECP targets compared to statistical energy use data in these countries. The results indicate that the NECPs of Denmark and Germany are particularly exposed to risks related to global raw material availability, as Denmark plans to rapidly grow the share of wind and solar PV in electricity generation to 81% and 13% by 2030, respectively, followed by Germany, which outlines a 39% and 16% share of wind and solar PV in its national climate strategy. The NECPs of Finland and Germany are also shown to be vulnerable to limitations in biomass availability, as there is a significant disparity between the projected biomass usage and legally binding European Union (EU) targets for land use, land use change, and forestry (LULUCF) sector emissions in 2030 in these countries. [ABSTRACT FROM AUTHOR]

Electricity distribution has become one of the most essential components of our society since the beginning of human civilization, relying on an abundant, reliable, and affordable power supply. Fossil fuels dominate the production of electricity (89.57 %), emitting 68.7 % of greenhouse gases, polluting water and soil, and depleting fossil fuels. Future energy needs are faced with growing demand for coal (772 million tonnes by 2040) and fluctuating fuel prices. The Indian power sector withdraws over 20 billion m³ of water, whereby coal power plants use around 35 % of freshwater. Among the seventeen sustainable development goals, Goal 7 emphasizes meeting the demand for electricity, the availability of clean fuels, and mitigating air pollution. In 2021, about 747 TWh of energy consumption was met by coal, oil (92 TWh), and solar energy (25 TWh). Renewable power would meet the world’s growing energy needs, reduce greenhouse gas emissions, boost the economy, and strengthen the society. Therefore, renewable energy has gained global attention as a sustainable electricity source. For this, a thorough examination of the economic and social implications of electricity generation technologies must be carried out. This study discusses how fossil fuel-based electricity generation affects global health and the environment and helps achieve Goal 7 of the sustainable development goals. All sectors must work together to stop global warming and water war and make electricity available worldwide for integrated development. [ABSTRACT FROM AUTHOR]

Electricity is one of the most important needs in everyday life due to technological advances. So various efforts are needed to increase electricity production, one way is to build a power plant that can produce productive electricity so that this happens, one way to determine electricity productivity is the value of cycle efficiency. If the value of the cycle efficiency is higher in a generator, then the PLTG performance will be maximized. And if the cycle efficiency value gets smaller, it can be said that the PLTG's performance is not good. Therefore, to maintain PLTG performance, it is necessary to carry out an overhaul to maintain optimal PLTG performance. In this study using cycle efficiency to determine the increase in efficiency before and after overhaul at a load of 100 MW and the causes, after analyzing the efficiency of the brayton cycle increased from 41% to 42%, the cause was a decrease in turbine efficiency from 74 to 91% and compressor efficiency from 73 to 82% after overhaul the increase affected fuel consumption so that the requirement of kcal/kwh decreased to 3196.4 kcal/ Kwh. [ABSTRACT FROM AUTHOR]

Indonesia is committed to achieving Net Zero Emission (NZE) conditions by the year 2060, with policy adjustments and constraints being necessary to realize this goal. The aim of this study is to achieve NZE conditions using a least-cost optimization method for various power plants that rely on fossil and non-renewable energy sources, without specifying a target year. Two scenarios, Business as Usual (BAU) and NZE, were developed for comparison in the optimization analysis. Through the utilization of LEAP and NEMO software, the optimization results suggest that optimal NZE conditions in Indonesia could be attained by 2075, with solar-based electricity generation playing a crucial role in meeting basic electricity demands. The NZE scenario predicts a 28% rise in electricity demand by 2100 compared to the BAU scenario. In 2075, PV will contribute 32.8% (224.3 GW) to total power supply, while BESS will provide 198.8 GW according to the NZE scenario. This study aims to assist the Indonesian government and stakeholders in reaching the NZE goal, while maintaining current efforts to avoid new efficiency and financial challenges. Achieving this goal will involve using a cost-effective optimization approach and implementing energy-efficient technologies and conservation programs. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing urgency among energy-intensive companies to find innovative ways of mitigating the negative financial impacts of rising fuel and electricity prices. Consequently, companies are exploring new technological solutions to lower electricity costs, such as investing in their own power generation sources or storage systems. In this context, this article presents a data-driven optimization-based framework to manage and optimize the operation of a hybrid energy system within industries characterized by substantial power requirements. The framework encompasses several key aspects: electricity generation, self-consumption, storage, and electric grid interaction. The case of an energy-intensive company specializing in wood processing and office furniture production is evaluated. This study explored two system configurations of hybrid energy systems within an energy-intensive company. The result of the analyzed case shows that the system's flexibility is enhanced by its ability to store energy, resulting in electricity cost savings of nearly 72% and total operating cost savings of 20%. [ABSTRACT FROM AUTHOR]

Tidal stream turbines (TST) are a promising option for electricity generation to meet the ever-increasing demand for energy. The actuator disk (AD) method is often employed to represent a TST, to evaluate the TST operating in a tidal flow. While this method can effectively reduce the computational cost and provide accurate prediction of far-wake flow conditions, it falls short of fully characterising critical hydrodynamics elements. To address this limitation, a hybrid method is implemented by coupling AD with the blade element momentum (BEM) theory, using detailed performance data, such as thrust, to enhance the prediction of the wake effects. This work focuses on the development of a hybrid BEM–AD method using Reynolds-Averaged Navier–Stokes (RANS) turbulence models within computational fluid dynamics (CFD). Two variations and a hybrid modification of an AD model are presented in this paper. The first modified variation is a velocity variation that takes into account velocity profile inflow into the disk's configuration. The second modified variation is a radial variation that integrates the blade element theory into the disk's configuration. The hybrid modified model combines both the velocity profiles influenced and blade element theory in the design and analysis of the actuator disk. Several key investigations on some of the pre-solver parameters are also investigated in this research such as the effect of changing velocity and radial distance on the porosity and loss coefficient of the actuator disk performance. Importantly, this work provides an improved method to evaluate the key wake effects from a TST array which is crucial to determine the power performance of the TST array. [ABSTRACT FROM AUTHOR]

Within the modern greenhouse horticultural sector energy usage is planned using mathematical models that simulate the greenhouse's future performance. These models contain parameters whose values can be inaccurate which create errors in model predictions. This reduces the effectiveness of energy management and planning done using these models. This study proposes and demonstrates an algorithm to quantify the impact of parameter errors on greenhouse gas and electric power prediction uncertainty. The proposed algorithm introduces a Polynomial Chaos Expansion as a method for the sensitivity analysis in the domain of greenhouse horticulture. Contrary to commonly used sensitivity analyses, this approach introduces the analysis of higher order interactions into the domain of greenhouse horticultural research. It was found that for both electric power and gas production the HPS lamp power rating was the most influential individual parameter. Moreover, this study found that for power demand the uncertainty in parameters relating to the lamp system were far more impactful than those related to the crop or greenhouse structure, with a respective coefficient of variation of 24 %, 5 % and 5 %. This study makes a notable and novel conclusion that for parameters related to the greenhouse structure, larger groups of parameters were responsible for prediction uncertainty through higher order interactions of second to sixth order. These results reinforce the importance of future greenhouse research considering the impact of higher order parameter interactions on prediction uncertainty using the algorithm proposed in this study. • An electrical power and gas demand uncertainty analysis was performed. • A polynomial chaos expansion was used as part of an uncertainty analysis. • The proposed algorithm shows groups of parameters impacting prediction uncertainty. • Lamp intensity is the key factor for power and gas demand prediction uncertainty. [ABSTRACT FROM AUTHOR]

The development of public transportation is considered a vital issue in reducing traffic as well as urban pollution. City buses play an important role in the city transportation system. In Iran, due to the high average age of city buses, it is necessary to replace the old buses with new ones, To replace the old buses, diesel and CNG, hybrid, and electric buses are proposed as the main alternatives. Global warming and the energy crisis are now considered as two potential serious threats for the world. Therefore, energy consumption and CO2 emissions are examined as two outstanding criteria for comparing candidate buses in this paper. To make an accurate comparison, the amount of energy consumption and CO2 emissions have been calculated based on the well-to-wheel approach. The electric bus well-to-wheel analysis has been done for both electricity generation mix and renewable generation. To perform more accurate calculations and simulations, as a case study, a real driving cycle has been constructed for Tehran. For this approach, a modified micro trip method as a novel solution is presented to synthesize the driving cycle. The results show that due to the high share of fossil power plants (about 92%) in Iran, the use of electric buses in the bus fleet may not have much effect on reducing energy and CO2 eq emissions. By using renewable power plants, the amount of well-to-wheel energy consumption and CO2 emissions decrease significantly (about 56% and 93%, respectively) compared to that for the generation mix. [ABSTRACT FROM AUTHOR]

The current study aims to conduct a comprehensive analysis of the key parameters that affect the energy output of the Bagisli Hydropower Plant, located on the Zap River in the Dicle (Tigris) basin of Turkey. It considers the daily data for the time interval of 2016–2019 related to flow rate, precipitation, and temperature in relation to the generation of electricity. The relationship between energy output and flow rate is evident; however, the energy production is limited by the design flow rate. The largest flow rates were seen during the spring season after the occurrence of peak precipitation, which exhibited a shifting pattern. Similarly, energy generation also reaches its highest level during this time period. Another outcome of this study is that there is no apparent association between daily precipitation and daily energy generation. Moreover, a novel correlation with an R2 value of 0.89 has been proposed, in the deviation band of ±20%, to estimate energy generation when only flow rate data are available. [ABSTRACT FROM AUTHOR]

The renewable electricity quota standard (RES) policy plays an important role in achieving sustainable and green development targets. Thus, it is essential to measure the sustainability of the electric power sectors in the context of RES. In terms of the energy and environmental efficiency (EEE) measurements, few studies divided energy inputs into renewable and non-renewable energy or explored the restricted problem of minimizing resource summation. To fill these gaps, we propose an improved fix-sum energy input data envelopment analysis (FSIDEA) model based on the adjustment strategy of weighted sum minimization of renewable energy inputs. The assurance region (AR) restriction and renewable energy input sum constraint (IC) are, respectively, imposed on the FSIDEA model to achieve the common equilibrium effective frontier (EEF). Finally, this study assesses the EEE of the electric power sectors in China's 30 main regions based on the common EEF. The result reveals that Beijing and Shanghai can be selected as benchmarks after efficiency comparison. In addition, our proposed model can compressively rank all decision-making units (DMUs) compared with traditional efficiency models. [ABSTRACT FROM AUTHOR]

The research on constructed wetland (CW) and microbial fuel cell (MFC) has been separate studies worldwide with crucial achievements being made in both fields. Due to environmentally friendly feature (of CW) and rich microbial population and excellent electrode catalytic activity (of MFC), CW and MFC have their own anticipated application prospect in wastewater purification and biological electricity generation. More significantly, the idea of embedding MFC into CW to form CW-MFC expands the scope for both of them and this has received much interest in recent years due to its striking features of sewage treatment efficiency, electricity generation, sustainability, and environmental friendliness. The increasing interest and the lack of soul of CW-MFC emerging to the new researchers reflect the need to recall the idea and summarize its development with regard to achieving its reality via some key issues This forms the basis of the paper. The paper also includes how to enhance the efficiency of electricity generation and supplement energy consumption, the degradation of emerging pollutants, and the degradation mechanism as well as the potential joint application of CW-MFC with other treatment technique. A mass of CW-MFC design parameters has been synthesized from the literature. Challenges and potential directions of CW-MFC in the future are prospected. It is expected that the paper can serve as a linkage for bridging knowledge gaps for further studies of CW-MFC. [ABSTRACT FROM AUTHOR]

Amid escalating energy demands and growing environmental concerns, educational institutions are transforming into crucibles for enduring innovation. This comprehensive review summarizes the complex relationship between Energy Efficiency and Renewable Energy Systems (EERES) within the sphere of educational institutions. By instituting Energy Efficiency initiatives, organizations can curtail energy consumption, resulting in substantial cost savings and a diminished carbon footprint. Moreover, the integration of renewable energy technologies empowers the localized generation of electricity, ensuring a reliable and sustainable energy source. Noteworthy in this study is the novel linkage of energy usage indicators to the comfort levels experienced in university settings during both summer and winter. An exhaustive examination of consumption indicators, rooted in the diverse activities on college campuses, further enriches the investigation. Beyond technical intricacies, this study scrutinizes the economic viability, environmental advantages, and educational significance of these integrated systems. Embracing EERES not only aligns with the commitment of educational institutions to environmental stewardship but also establishes a paradigm for broader communities. These institutions aspire to exemplify sustainable practices, influencing larger societal behavior positively. Various factors, including the institution's type, energy source, facility nature, building construction, internal activities, weather conditions, and user behavior, wield substantial influence over energy utilization. This study offers a nuanced exploration, shedding light not only on the technical dimensions but also on the broader economic, environmental, and educational implications of adopting EERES. [ABSTRACT FROM AUTHOR]

The optimization of the production scheme for enhanced geothermal systems (EGS) in geothermal fields is crucial for enhancing heat production efficiency and prolonging the lifespan of thermal reservoirs. In this study, the 4100–4300 m granite diorite stratum in the Zhacang geothermal field was taken as the target stratum to establish a numerical model of water-heat coupling of three vertical wells. However, relying solely on numerical simulation for optimization is time-consuming and challenging for the determination of the globally optimal production plan. The present study proposes a comprehensive evaluation method for optimizing the performance of EGS power generation based on the integration of particle swarm optimization with backpropagation neural network (PSO-BPNN) and analytic hierarchy process (AHP). Five different PSO-BPNN models were constructed based on the numerical simulation data to predict different EGS power generation performance indexes, including the production temperature, the injection pressure, the total electricity generation, the electric energy efficiency and the levelized cost of electricity. Based on these PSO-BPNN models, the weights of various thermal development evaluation indexes were calculated by AHP to conduct a comprehensive evaluation of the power generation performance of the three vertical wells EGS. The results show that the PSO-BPNN model has good prediction accuracy for EGS prediction of various performance indicators, with a coefficient of determination (R2) exceeding 0.999. The AHP evaluation of all production schemes reveals that the optimal power generation scheme entails a well spacing of 580 m, water injection rate of 56 kg/s, injection temperature of 38 °C and fracture permeability of 2.0 × 10−10 m2. Over a span of 30 years, this scheme can provide a total power generation capacity amounting to 1775 GWh, with an associated LCOE value of 0.03837 USD/kWh. This not only provides a reference for the development and optimization of geothermal systems in the Zhacang geothermal field but also provides a new idea for the optimization design of other geothermal projects. [ABSTRACT FROM AUTHOR]

Water electrolysis for hydrogen production with renewable electricity is regularly studied as an option for decarbonised future energy scenarios. The inclusion of byproduct electrolytic oxygen capture and sale is of interest for parallel decarbonisation efforts elsewhere in the industry and could contribute to reducing green hydrogen costs. A deterministic hydrogen electrolysis system model is constructed to compare oxygen inclusion/exclusion scenarios. This uses wind and solar-PV electricity generation timeseries, a power-dependent electrolysis model to determine the energy efficiency of gas yield, and power allocation for gas post-processing energy within each hourly timestep. This maintains a fully renewable (and therefore low/zero carbon) electricity source for electrolysis and gas post-processing. The model is validated (excluding oxygen) against an existing low-cost GW-scale solar-hydrogen production scenario and an existing hydrogen production costs study with offshore wind generation at the multi-MW scale. For both comparisons, oxygen inclusion is then evaluated to demonstrate both the benefits and drawbacks of capture and utilisation, for different scenario conditions, and high parameter sensitivity can be seen regarding the price of renewable electricity. This work subsequently proposes that the option for the potential utilisation of byproduct oxygen should be included in future research to exemplify otherwise missed benefits. [ABSTRACT FROM AUTHOR]

As a part of the transition in higher-level energy systems, distributed cross-sectoral energy systems (DCESs) play a crucial role in providing flexibility in covering residual load (RL). However, there is currently no method available to quantify the potential flexibility of DCESs in covering RL. This study aimed to address this gap by comparing the RL demand of a higher-level energy system with the electricity flow between a DCES and the electricity grid. This can allow for the quantification of the flexibility of DCES operation. Our approach was to categorize existing methods for flexibility quantification and then propose a new method to assess the flexibility of DCESs in covering RL. For this, we introduced a new quantification indicator called the Flexibility Deployment Index (FDI), which integrates two factors: the RL of the higher-level energy system and the electricity purchase and feed-in of a DCES. By normalizing both factors, we could compare the flexibility to cover RL with respect to different DCES concepts and scenarios. To validate the developed quantification method, we applied it to a case study of a hospital's DCES in Germany. Using an MILP optimization model, we analyzed the variation in FDI for different technology concepts and scenarios, including fixed electricity tariffs, dynamic electricity tariffs, and CO2-emission-optimized operation. The results of our calculations and the application of the FDI indicate that high-capacity combined heat and power units combined with thermal storage units provide higher flexibility. Additionally, the results highlight higher flexibility provision during the winter period compared to the summer period. However, further application and research are needed to confirm the robustness and validity of the FDI assessment. Nonetheless, the case study demonstrates the potential of the new quantification method. [ABSTRACT FROM AUTHOR]

The use of decentralized renewable energy systems will continue to play a significant role in electricity generation especially in developing countries where grid expansion to most remote areas is uneconomical. The income levels of these off-grid communities are often low, such that there is a need for the delivery of cost-effective energy solutions through optimum control and sizing of energy system components. This paper aims at minimizing the net present cost (NPC) and the levelised cost of energy (LCOE). The study presents a hybrid power system involving a hydroelectric, solar photovoltaic (PV), and battery system for a rural community in Cameroon. The optimization of the system was done using HOMER Pro and validated using a meta-heuristic algorithm known as genetic algorithm (GA). The GA approach was programmed using the MATLAB software. After the HOMER simulation, the optimal power capacity of 3 kW solar PV, 334.89 Ah battery, and 32.2 kW microhydropower was used to meet the load. The village load profile had a daily energy usage of 431.32 kWh/day and a peak power demand of 38.49 kW. The optimized results showed an NPC and LCOE of $90,469.16 and 0.0453 $/kWh, respectively. The system configuration was tested against an increase in hydropower capacity, and it was observed that increasing the hydropower capacity has the ability to significantly reduce the LCOE as well as the battery and solar PV size. A comparative analysis of the two approaches showed that the optimization using GA was more cost-effective than HOMER Pro with the least LCOE of 0.0344 $/kWh and NPC of $86,990.94 as well as a loss of power supply probability (LPSP) of 0.99%. In addition, the GA method gave more hydropower generation than HOMER Pro. This supports the fact that stochastic methods are more realistic and economically viable. They also accurately predict system operation than deterministic methods. [ABSTRACT FROM AUTHOR]

In more recent years Asia has had the highest level of investment in renewables and the highest level of electricity generation from renewable sources. This paper analyzes the determinants of renewable energy consumption in Asia and the Pacific from 1996 to 2018. It explores the major challenges this region has faced in moving towards a more environmentally friendly generation and use of energy. We find that the renewable electricity output, GDP per capita, merchandise trade, the value added of the manufacturing sector and the income share held by the poorest population boost renewable electricity consumption. On the other hand, energy use per capita, access to electricity, energy imports, broad FDI, population growth and the income share held by the richest population lower consumption of electricity from renewable sources. Trade openness and being an island do not seem to have a statistically significant impact in our sample over the observed period. [ABSTRACT FROM AUTHOR]

Electricity and water systems in the Western US (WUS) are closely connected, with hydropower comprising 20% of total annual WUS generation, and electricity related to water comprising about 7% of total WUS electricity use. Because of these interdependencies, the threat of climate change to WUS resources will likely have compounding electricity impacts on the Western Interconnect grid. This study describes a WUS‐wide water system model with a particular emphasis on estimating climate impacts on hydropower generation and water‐related electricity use, which can be linked with a grid expansion model to support climate‐resilient electricity planning. The water system model combines climatically‐driven physical hydrology and management of both water supply and demand allocation, and is applied to an ensemble of 15 climate scenarios out to 2050. Model results show decreasing streamflow in key basins of the WUS under most scenarios. Annual water‐related electricity use increases up to 4%, and by up to 6% during the summer months, driven by growing agricultural demands met increasingly through a shift toward energy‐intensive groundwater to replace declining surface water. Total annual hydropower generation changes by +5% to −20% by mid‐century but declines in most scenarios, with decreases in summer generation by up to nearly −30%. Water‐related electricity use increases tend to coincide with hydropower generation declines, annually and seasonally, demonstrating the importance of concurrently evaluating the climate signal on both water‐for‐energy and energy‐for‐water to inform planning for grid reliability and decarbonization goals. Plain Language Summary: Electricity and water systems in the Western United States (WUS) have a strong dependency. Water fuels hydropower generation and electricity is used to pump, transport, treat, heat, and dispose of water. Climate change poses a serious threat to water availability in the WUS and is likely to also affect hydropower generation and electricity use related to water. This study develops a WUS water system model to evaluate the impact of a set of climate change scenarios on the dynamic interplay between water availability and demand and hydropower generation and electricity use by the water sector by 2050. We find that in many key basins, streamflow decreases under the climate scenarios. At the same time, reliance on groundwater increases to meet growing agricultural water demand. Hydropower generation shows decreases in most cases while energy use related to water increases. Because these hydropower generation declines tend to occur during periods when electricity demand for water grows, electricity grid planners in the Western Interconnect will benefit from this type of study by informing future grid buildouts that maintain reliability and decarbonization goals. Key Points: Interactions among hydro‐climate, hydropower, and water's energy use are critical for evaluating Western US (WUS) water‐energy climate risksUnder climate change, our WUS water model finds declining streamflows, growing agricultural demands, and increased groundwater useWith warming and drying, water‐related energy use grows while hydropower generation decreases under most climate scenarios by mid‐century [ABSTRACT FROM AUTHOR]

The buildings sector is the single most important end-user of final energy in the European Union and a significant contributor to carbon and greenhouse gas emissions. This work focuses on a review of available data that are used to calculate the annual emissions from electricity generation in the European Union and quantify indirect emissions from the use of electricity in the buildings sector. Historical data since 1990 are used to derive simple empirical correlations for the time evolution of emissions factors related to electricity production in each Member State of the European Union. More recent trajectories using data from the last ten years are also presented. The derived correlations can be easily integrated in building stock modeling and national studies to facilitate forward-looking projections of emissions from electricity use in buildings. The EU-27 averages 0.2883 kgCO2-eq/kWhel, ranging from 0.0456 kgCO2-eq/kWhel in Sweden up to 1.0595 kgCO2-eq/kWhel in Poland. As a case study, the derived coefficients are then used to quantify the indirect emissions from the electricity consumption attributed to the building stock in each EU Member State. The calculated total EU-27 GHG indirect emissions attributed to electricity consumption amounted to 215 MtCO2-eq for residential buildings and 201 MtCO2-eq for non-residential buildings. In addition, the proposed correlations are used to demonstrate how they can be used for more realistic future projections of emissions towards the national targets in Greece and Poland. [ABSTRACT FROM AUTHOR]

The significance of this study is underscored by the immense potential of binary power plants in the contemporary world. These plants have a pivotal role to play in supplying heat to homes, facilitating greenhouse heating, and supporting air conditioning systems. The purpose of the study is to provide recommendations on eliminating errors in the processes of improving and implementing geothermal plants and analysing their functioning during electricity generation. The analytical method, classification, functional, statistical, synthesis, and others should be noted among the methods used. The features of geothermal plants in Kazakhstan were noted, their differences were analysed, and errors that are made during the operation of power plants to increase the energy efficiency of consumers and the causes of errors were analysed. Uncertainties in the development and their impact on the functioning of geothermal power plants were identified. The practical value lies in the application of the identified results, solving errors in the development and implementation of a binary power plant to improve the energy efficiency of consumers, the reliability of the use of geothermal plants in the region, considering various factors, which will help provide recommendations for the appropriate use of the mechanism. [ABSTRACT FROM AUTHOR]

Trigeneration provides an effective means of power, heat, and cold production on site. Proper design and well-managed operation of such units can bring in substantial savings in consumed primary energy as well as in the amount of greenhouse gases released to the atmosphere, compared to separate production of all three media. The studied sub-MW-sized trigeneration unit comprises an internal combustion engine combined with an absorption chiller and a heat management system, delivering all three media to a nearby industrial facility. A mathematical model is developed based on available design and process data, a profit function is set up, and the subsequent sensitivity analysis of economic parameters is realized. The lowered efficiency of summer operation is analyzed, and a suitable solution is proposed, with an estimated total investment cost of EUR 114,000 and an anticipated simple payback period less than 2 years. [ABSTRACT FROM AUTHOR]

In this paper, we present an analysis of the properties of the prototype three-phase Multichannel Permanent Magnet Synchronous Generator (MCPMSG) prototype designed and constructed by the authors. Each channel of the generator has electrically separated windings, which allows us to create an island system of electricity generation. The analyzed MCPMSG is intended for critical applications, and it is designed for four-channel operation. The purpose of this work is to analyze various configurations of the generator channels to improve the redundancy of the electricity generation system. The MCPMSG operation with one or two independent sources of energy consumption in the case of a dual-channel or double dual-channel operation was investigated. For the analyzed cases, the original mathematical models of the three-phase MCPMSG were developed. On the basis of numerical and laboratory tests, the influence of individual configurations on the MCPMSG output parameters was determined. An original method for diagnosing the operation of the MCPMSG channels was developed. Numerical and laboratory tests of the proposed diagnostic method based on a single voltage signal were carried out. As part of the laboratory tests, selected operating states under conditions of full winding symmetry and internal asymmetry were analyzed. The advantage of the proposed diagnostic method is the control of the operating state of the channels both under load and in the de-energized state. The proposed diagnostic method for control of the individual channel requires measurement of only one voltage signal. [ABSTRACT FROM AUTHOR]

A prosumer is a consumer who uses tiny, renewable electricity generation units and, in addition to consumption, can also generate electricity. With the increase in the number of prosumers in a power grid, it is expected that the paradigm of network utilization, at least at the distribution level, would change from centralized to decentralized utilization. In this new paradigm, microgrids are essential in the operation of the whole grid. The decentralized control of a stable network of microgrids (i.e., minimal power outages and fluctuations) is a significant challenge. In this paper, we present an architecture for decentralized control that consists of intelligent agents that manage the distribution network provided by the microgrids at the highest level and houses and their devices at the lowest level. The agents, managed by different private companies, dynamically organize themselves in units called holons, follow their defined policies, and can most tolerate network disruptions. In this architecture, self-adaptive agents will play a key role in sustaining network performance by controlling energy consumption and exchange (i.e., in the event of a shortage in a part of the distribution network). In the end, by simulating the architecture, the capabilities are shown. [ABSTRACT FROM AUTHOR]

This study explores the potential of smart piezoelectric materials as a means of clean electricity generation through the conversion of mechanical stresses into electrical potential. A speed bump module outfitted with these materials serves as the experimental model. The materials are modeled and simulated using COMSOL software, and the output is assessed under a range of load states and other parameters. The findings provide a comparative analysis of various piezoelectric materials and their performance characteristics. The overarching aim is to harvest energy from typically inefficient sources such as footsteps, sound, pressure, and vehicular traffic. The practical implementation of these findings could lead to the reuse of power from the main grid for applications like street lighting and signboards, thereby reducing overall energy consumption and environmental impact. A secondary objective of this research is to evaluate the feasibility of implementing renewable energy systems based on smart materials in Libya. This study thereby contributes to the broader discourse on sustainable energy solutions and demonstrates the untapped potential of smart materials in energy harvesting. [ABSTRACT FROM AUTHOR]

The dynamics of consumer price index (CPI) and its influencing factors lie at the heart of economic stability and growth. In this comprehensive research paper, we investigate the multifaceted relationship between consumer price index (CPI) and a set of critical independent variables, including trade (T), primary energy consumption (PEC), electricity generation (EG), exchange rate (ER), and urban population (UP). This research examines a cross-sectional sample of 20 European countries using panel ordinary OLS regression and fixed- and random-effects models for the period of 2000-2020. The findings of this research suggest that there is a notable inverse relationship between Primary Energy Consumption and CPI. The coefficient associated with Primary Energy Consumption carries a negative sign and demonstrates statistical significance at the 5% level and urban population, exchange rate and Electricity generation show positive significant impact on Inflation, while trade does not have any significant impact on inflation. [ABSTRACT FROM AUTHOR]

The aim of this research is to analyse and provide realistic insight that will improve the provisions and investment in wind energy as potential source of energy for electricity generation. The data used for this assessment were obtained from the central database of Nigeria Meteorological Agency Abuja, which includes average wind speed, and direction per day of the selected location, measured at the anemometer height of 10 m, over a period of eleven years (2011-2021). The maximum monthly mean wind speed was found in January and December with a value of 4.9 m/s, and annual extractable energy was found to be 347.97KWh/M2. On average, the annual wind speed through eleven years was found in the range 3.88 - 4.00 m/s. The results revealed that, the wind resource in the study area fall within range and category 3.00 which is considered as marginal or unsuitable for higher wind power development and an excellent for water pumping and small scale electricity generation. [ABSTRACT FROM AUTHOR]

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Copyright of Revista Iberoamericana de Ciencia, Tecnologia y Sociedad is the property of Centro de Estudios sobre Ciencia, Desarrollo y Educacion Superior and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study covers the technical and economic analysis of a grid-connected rooftop 216 kWp photovoltaic (PV) system to meet the average annual energy demand of 45,327 kWh of a dairy farm. According to the results of the analysis, an average of 326,819 kWh/year is received at the output of the panel arrays, while 294,838 kWh/year is supplied to the grid. The amount of energy to be received from the grid was found to be 25,013 kWh/year, and the performance ratio of the system was 0.808. The net present value (NPV) of the system was calculated as $36,463.39, and the levelized cost of electricity (LCOE) was calculated as 0.065 $/kWh. Considering that the annual electricity generation amount of the rooftop PV system evaluated within the scope of the study is 315,152 kWh, it is estimated that 127.419 tCO2 per year of emission release will be prevented annually with the installation of the system. [ABSTRACT FROM AUTHOR]

To overcome its reliance on burning fossil fuels for energy generation and water desalination, Kuwait has pioneered research and cutting-edge projects in renewable energy since the 1980s. This paper examines the power sector in Kuwait and emphasizes the government’s keenness to diversify the country’s electric power supply. It provides a comprehensive overview of Kuwait’s efforts, to emerge as a leading example in the region, fostering collaboration and matchmaking within renewable energy industries. The country’s goal is to meet 15% of the demand for power from renewable energy by 2030, including a reduction in energy use in the building sector by 12% and a decrease in CO2 emissions by 33%. The country’s initiatives revolve around harnessing renewable sources, particularly emphasizing the exploration of solar photovoltaic (PV) systems. Challenges and opportunities are presented to provide information for international institutions, technology companies, designers, researchers, and decision makers, aiming to increase the effectiveness and efficiency of PV project implementation in the country and the region. [ABSTRACT FROM AUTHOR]