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Metal-organic frameworks (MOFs) have the advantages of tunable pore sizes and porosity and have demonstrated unique advantages for various applications. This study synthesized composite MOF nanomaterials by modifying MOF801 or AlOOH with UIO66. The composite nanomaterials, UIO66/MOF801 and UIO66/AlOOH showed increased Zeta potential than their pristine form, AlOOH, UIO66 and MOF801. For the first time, the composite MOFs were used to fabricate filter paper-based evaporation-driven power generators for spontaneous electricity generation. The MOFs-KBF membrane was constructed by coating filter paper (10 × 50 mm) with composite MOFs and conductive Ketjen Black. The UIO66/MOF801 decorated device achieved a maximum open circuit voltage of 0.329 ± 0.005 V and maximum output power of 2.253 μW. The influence of salt concentration (0.1–0.5 M) on power generation was also analyzed and discussed. Finally, as a proof-of-concept application, the device was employed as a salinity sensor to realize remote monitoring of salinity. This work demonstrated the potential of flexible MOF composites for spontaneous power generation from water evaporation and provides a potential way to enhance the performance of evaporation-driven power generators. [ABSTRACT FROM AUTHOR]

The research presented in this paper introduces a novel environmental energy‐harvesting technology that harnesses electricity from the evaporation of water using porous structural materials. Specifically, a strategy employing paper‐based hydroelectric generators (p‐HEGs) is proposed to capture the energy produced during water evaporation and convert it into usable electricity. The p‐HEGs offer several advantages, including simplicity in fabrication, low cost, and reusability. To evaluate their effectiveness, the water evaporation‐induced electrical output performance of four different p‐HEGs are compared. Among the variants tested, the p‐HEG combining wood pulp and polyester fiber exhibits the best output performance. At room temperature, this particular p‐HEG generates a short‐circuit current and open‐circuit voltage of ≈0.4 µA and 0.3 V, respectively, thereby demonstrating excellent electrical stability. Furthermore, the electrical current and voltage generated by the p‐HEG through water evaporation are able to power an LED light, both individually and in series and parallel connections. This study delves into the potential of electricity harvesting from water evaporation and establishes it as a viable method for renewable energy applications. [ABSTRACT FROM AUTHOR]

The recovery and utilisation of industrial excess heat has been identified as an important contribution for energy efficiency by reducing primary energy demand. Previous works, based on top-down studies for a few sectors, or regional case studies estimated the overall availability of industrial excess heat. A more detailed analysis is required to allow the estimation of potentials for specific heat recovery technologies, particularly regarding excess heat temperature profiles. This work combines process integration methods and regression analysis to obtain cogeneration targets, detailed excess heat temperature profiles and estimations of electricity generation potentials from low and medium temperature excess heat. The work is based on the use of excess heat temperature (XHT) signatures for individual sites and regression analysis using publicly available data, obtaining estimations of the technical potential for electricity generation from low and medium temperature excess heat (60–140 °C) for the whole Swedish kraft pulp and paper industry. The results show a technical potential to increase the electricity production at kraft mills in Sweden by 10 to 13%, depending on the level of process integration considered, and a lower availability of excess heat than previously estimated in studies for the sector. The approach used could be adapted and applied in other sectors and regions, increasing the level of detail at which industrial excess heat estimations are obtained when compared to previous studies. [ABSTRACT FROM AUTHOR]

Demand response (DR) is one of the most cost-effective and logical smart grid terms for power systems that can be used during peak load hours, whereas load shedding (LS) is the last and most expensive solution in emergency grid situations. The aim of them is to satisfy equilibrium constraints between consumption and generation and restore the power system frequency to normal bounds at the least possible time. The rapid increase in power grid costs and limitations on electricity generation resources have resulted in the increasing need for industrial customers' participation as an alternative solution to peak load spikes. Therefore, this paper considers the estimation of imbalance active power in a smart strategy to introduce a critical DR (CDR) in heavy industries (pulp and paper, cement, and medium density fibreboard (MDF)) based on direct load control (DLC) technique in order to reduce the need for LS in frequency restore. To evaluate the proposed model, a real case study including the typical pulp and paper, cement, and MDF industries processes with actual power consumption data is considered. The numerical and graphical results confirm that the proposed CDR can be used as an inexpensive solution to replace the costly spinning reserves and avoid load shedding. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to report the current status of life cycle assessment (LCA) in Saudi Arabia. It summarizes the LCA studies conducted in academia and industry. It also examines LCA collaboration networks and training opportunities. It then points out current gaps in implementing LCA in Saudi Arabia. Finally, it delineates the steps required to promote LCA both as a research methodology and as a sustainability assessment tool in Saudi Arabia. Methods: Using Scopus database and the Internet, a state-of-the-art review was conducted for this paper. "LCA", "Life Cycle Assessment" and "Saudi Arabia" were the key words used for searching scientific studies, industrial reports, training courses and conferences related to application of LCA within Saudi Arabia. The search resulted in 32 scientific documents and one industrial report. Further scrutiny reduced the final sample considered for this paper to eleven scientific documents and one industrial report that used a complete LCA study to report environmental impacts. Results and discussion: Studies considered for this paper were related to fossil fuels, buildings, electricity generation, desalination, and food consumption. However, overall number of publications and industry reports related to LCA in Saudi Arabia is very little as compared to other advanced economies. This sheer lack of studies conducted in Saudi Arabia can be attributed to lack of educational programs, consultancies, and research projects related to LCA. This points to the vast potential for developing LCA both as a research tool and sustainability assessment tool in Saudi Arabia. There is a need to develop a local network of LCA researchers, a local LCI database, and training courses. Conclusions: This study revealed that use of LCA as a sustainability assessment tool is still in its early stages within Saudi Arabia. There are only a handful of LCA studies that are reported in scientific literature related to Saudi Arabia. Additionally, most of these studies relies on non-local databases rendering the results of these studies less reliable. There is an urgent need to promote LCA within Saudi Arabia and academia can play a leading role by offering short courses, training for industry, and participating in joint projects to conduct LCA studies. Furthermore, local LCA databases and consultancies should also be promoted. It is conjectured that in the future, the use of LCA will grow in Saudi Arabia as the county is targeting to become a net zero carbon economy by 2060. [ABSTRACT FROM AUTHOR]

Increased innovation on finding new ways to generate energy from different sources to meet the growing demand of consumers has led to various challenges in controlling the power network when it faces different disruptions. To address these challenges, a new approach has been proposed in this research paper, which combines a controller with a soft computing technique called Particle Swarm Optimization (PSO). The study considers a power system with four units, where three different energy sources are utilized and distributed across two areas. Each area has two power sources, with one area having a combination of thermal and gas power plants, and the other area consisting of a nuclear power plant and a gas power plant. Transmitting power from the nuclear power plant is particularly complex due to its high sensitivity to disturbances. Therefore, an intelligent and efficient controller is needed to ensure robust control in this type of power network that includes nuclear power. The paper also conducts a thorough analysis of the harmful emissions associated with electricity generation from the different power plants considered. The goal is to reduce the carbon footprint associated with power generation. The proposed work and analysis in the paper are implemented using the MATLAB/SIMULINK environment. [ABSTRACT FROM AUTHOR]

The substantial portion areas are customarily habituated across the world is electricity. In need of electricity generation, no equipment, instruments, motor, or any machinery is functioning. The paper portrays consequently footsteps energy carries on exploited and it draws upon non-conventional sources of energy resources. There are many types of electricity generation i.e., solar power, wind conversion system, thermal, hydro-electricity, nuclear energy. Renewable energy and Non-Renewable Energy Sources are inherent notions in the Electricity generation system. The Walking Footsteps are and untapped natural resources. While employing the Walking Footsteps energy its more concise amount of cost means that it’s modest and innocuous for human. The metamorphosis technology is intermingled that electrical energy can proselytize to mechanical energy using footsteps walking of human beings. The consequent equipment’s efficacious used for procedure of footsteps is as supervening like pipe arrangement, nozzle type, unidirectional valve, water reservoir, turbine motor of any type, and DC motor. The occupied conformance is accomplished be pertinent pressure which is strive on the water reservoir; water flows amidst the direction of nozzle into the turbine and generates electrical energy. This type of electrical energy is kept stored in the energy battery storage. There is very much load disturbance in the consumers terminal so that there will be causing global warming and load shedding. This paper defines having advantages of the global warming and load shedding in best way of cleaner the cost-effective way. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS) is popular to abate anthropogenic emissions throughout the world. Previous researchers focused on evaluating ETS policy effect, but ETS design is usually neglected because ETS is already mostly sophisticated worldwide. This is not the case in China, as the Chinese nationwide ETS (CNETS) came into effect in July 2021. Implemented for a brief period, the CNETS lacks implementation details and thus may not achieve mitigation targets cost-effectively. In this paper, we attempt to narrow the research gap by comprehensively designing the CNETS. Our research framework is based on a dynamic recursive computable general equilibrium (CGE) model. The CGE model results show that the appropriate CNETS should include the coverage of the electricity generation and manufacturing sectors, higher carbon price (175 C N Y / t C O 2 ), quota allocation based on the carbon intensity in the previous year, higher quota decline factor (2%) and time-decreasing free quota ratio. Although we have only designed the Chinese ETS in this paper, the research framework may become a paradigm of designing appropriate ETS. [ABSTRACT FROM AUTHOR]

The decision-making of generator start-up sequence plays a pivotal role in the power system restoration process following the blackout. In this paper, an optimized deep Q-learning network (DQN) algorithm is proposed to address this challenge. The generator start-up process is modeled as a Markov Decision Process (MDP) based on its characteristics. The DQN is tasked with deciding both the generator start-up sequence and the corresponding restoration path. To address the limitations of DQN, such as low exploration efficiency and slow convergence, the study incorporates the Artificial Potential Field (APF) algorithm to refine the reward function of it. This integration results in the development of the F-DQN (APF-DQN) algorithm, which enhances training efficiency. The effectiveness of this proposed method is demonstrated through the IEEE 39-bus test system. The results reveal that the DQN algorithm is capable of efficiently solving the model of the generator start-up sequence after the blackout. Moreover, the F-DQN algorithm exhibits superior learning efficiency, faster convergence, and higher-quality optimal solutions compared to the DQN. This paper also discusses the applicability of this method under partial blackouts. When compared to other decision-making algorithms, the proposed method offers a restoration scheme that is both time-efficient and results in increased electricity generation. [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.)

Thin wafers and thin wires are beneficial to the photovoltaic industry for reducing costs, increasing efficiency, and reducing the cost of electricity generation. It is a development trend in solar silicon wafer cutting. Thin wire cutting reduces the kerf between silicon wafers to less than 50 μm. Therefore, it is extremely difficult to supply cutting fluid to the cutting area. And this affects cutting performance. This paper proposes the use of the capillary effect produced by ultrasonic waves in fixed diamond wire slicing to improve the cutting fluid supply and reduce wafer adsorption. To explore the rules of ultrasonic capillary action between two plates and guide the industrial applications, the effects of the distance between parallel plates, the distance from the bottom of the parallel plates to the ultrasonic radiation surface, the non-parallelism between the plates, the temperature of the working fluid, the ultrasonic action time, and the type of working fluid on the liquid level rise height were studied. The conclusions can be used to guide the improvement of the supply of working fluid in fixed diamond wire slicing. [ABSTRACT FROM AUTHOR]

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events. [ABSTRACT FROM AUTHOR]

In this paper, we use the literature to help us better understand carbon capture costs and how these estimates fare against those of avoided costs, focusing on bioenergy carbon capture and storage (BECCS), carbon capture and storage (CCS), as well as direct air capture technologies. We approach these questions from a meta-analysis perspective. The analysis uses meta-analysis tools while applying them to numerical rather than statistical studies. Our analysis shows that avoided costs are, on average, 17.4% higher than capture costs and that the carbon intensity of the feedstock matters: the estimates for coal-based electricity generation capture costs are statistically smaller than those for natural gas or air. From a policy perspective, the literature suggests that the costs of CCS are like the 45Q subsidy of USD 50 per metric ton of carbon captured. [ABSTRACT FROM AUTHOR]

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia. [ABSTRACT FROM AUTHOR]

The daily production and life of human beings are inseparable from electricity. As the power supplier, electric power enterprises provide power demand for the majority of users. In the new era, electric power enterprises are also facing market-oriented reform. The focus of reform is electric power marketing. The formulation of electric power marketing strategy needs scientific decision-making analysis as guidance. With the increase of power demand, the scale of power grid is also expanding continuously. With the introduction of new energy equipment, the power system is becoming more and more complex, and it is difficult for relevant staff to effectively monitor and analyze the system. Combined with the above situation, this paper combined Bayesian network to build a power marketing decision analysis system, and combined Bayesian algorithm to test the power marketing real-time cost control system. The experimental results showed that the average judgment accuracy was 91.90 %, and the average warning time was 0.39 s. From the above data, it can be seen that this algorithm can play a good optimization effect on the performance of the system. In this paper, the elasticity test of the power system was also carried out from the aspect of wind speed, and the results showed that the maximum elasticity value can reach 0.94. It can be seen that the elasticity effect of the power system is good as a whole under different wind speeds. [ABSTRACT FROM AUTHOR]

Several recently signed environmental agreements and protocols emphasize the global need to reduce GHG emissions, with a focus on limiting coal consumption due to high NOx and CO2 emissions. However, many countries, including those in the Western Balkans, rely heavily on coal for electricity generation. The outdated thermal power plant infrastructure in these regions poses a major challenge when it comes to meeting modern environmental standards while maintaining efficiency. This study is part of the more comprehensive research which aims to develop an expert system that utilizes existing measurements to estimate key parameters crucial for both energy production and pollution reduction. The focus is on Serbian thermal power plants, particularly plant Nikola Tesla unit B1. One of the critical parameters for optimizing thermal power plant control loops is the heating value of coal, which is challenging to measure in real time due to the coal's varying chemical compositions and caloric values. This paper examines 74 different parameters measured in 59 instances to estimate the hating value of coal at unit B1. Through detailed analysis and feature selection methods, including linear regression, this research aims to identify the most informative parameters for estimating the heating value of coal, which will improve the control system that enables more efficient and environmentally friendly power generation in coal fired thermal power plants. [ABSTRACT FROM AUTHOR]

In light of the growing integration of renewable energy sources in power systems, the adoption of DC microgrids has become increasingly popular, due to its simple structure, having no frequency, power factor concerns. However, the dependence of DC microgrids on cyber-networks also makes them susceptible to cyber-attacks. Potential cyberattacks can disrupt power system facilities and result in significant economic and loss of life. To address this concern, this paper presents an attack-resilient control strategy for microgrids to ensure voltage regulation and power sharing with stable operation under cyber-attack on the actuators. This paper first formulates the cyber-security problem considering a distributed generation based microgrid using the converter model, after which an attack-resilient control is proposed to eliminate the actuator attack impact on the system. Steady state analysis and root locus validation illustrate the feasibility of the proposed method. The effectiveness of the proposed control scheme is demonstrated through simulation results. [ABSTRACT FROM AUTHOR]

The paper describes the possibility of hybrid electricity generation in already existing wind power plants (WPP) by additional installation of photovoltaic power plants (PVPP) on individual wind turbines (WT). Wind turbines have the lowest generation of electricity in the summer months, while PVPPs have the opposite, the highest generation in those months. Connecting the PVPP to the existing WT (hybrid electricity generation) brings a more even generation and a greater degree of use of the infrastructure of the existing wind farms (HV/MV transformer station, medium voltage cable distribution...). This way the variation of generation in relation to the average annual generation is reduced, which reduces the problems of balancing electricity. [ABSTRACT FROM AUTHOR]

Electric power is the basic industry of a modern country. The rapid development of the power industry has promoted economic development and social progress. With the establishment of the carbon neutrality target of carbon peak, China's power industry is also facing new situations and new challenges. This paper innovatively introduces the concept of allometric growth in biology, and uses the data of provincial electricity consumption and economic development from 1972 to 2017, to study the allometric growth relationship between electricity consumption and economics in China at multiple scales. Combined with the spatial autocorrelation analysis method, the temporal and spatial characteristics of allometric growth between electricity consumption and economic development were researched based on the analysis of spatial correlation of GDP electricity consumption intensity. The results show that: (1) The provincial GDP electricity consumption intensity shows an aggregate distribution, and the local aggregate pattern changed significantly from 1972 to 2017. (2) The High-High Cluster gradually disappeared, and the Low-Low Cluster moved southward, appearing in the middle and lower reaches of the Yangtze River. (3) The differential growth coefficient of electricity consumption and economic development increased initially and decreased from 1972 to 2017. (4) GDP would increase by 7.4%, 20.1%, and 15.6% in the simulation of electricity consumption, increasing 10% at the three stages of China's economic development. (5) The allometric growth coefficients of electricity consumption and economic development are very different in the three economic belts, eight economic zones, and provinces with different characteristics at the different stages of economic development. Formulating differentiated regulation policies for regional economic development and electricity consumption will be conducive to the coordinated development of electric power production and the national economy. [ABSTRACT FROM AUTHOR]

This paper considers two pertinent research inquiries: 'Can an AI-based predictive framework be utilised for the optimisation of solar energy management?' and 'What are the ways in which the AI-based predictive framework can be integrated within the Smart Grid infrastructure to improve grid reliability and efficiency?' The study deploys a Deep Learning model based on Long Short-Term Memory techniques, leading to refined accuracy in solar electricity generation forecasts. Such an AI-supported methodology aids power grid operators in comprehensive planning, thereby ensuring a robust electricity supply. The effectiveness of this framework is tested using performance metrics such as MAE, RMSE, nMAE, nRMSE, and $ R^2 $ R 2 . A persistent model is utilised as a reference for comparison. Despite a slight decrease in predictive precision with the expansion of the forecast horizon, the proposed AI-based framework consistently surpasses the persistent model, particularly for horizons beyond two hours. Therefore, this research underscores the potential of AI-based prediction in fostering efficient solar energy management and enhancing Smart Grid reliability and efficiency. [ABSTRACT FROM AUTHOR]

Iraqi people have been without energy for nearly two decades, even though their geographic position provides a high intensity of radiation appropriate for the construction of solar plants capable of producing significant quantities of electricity. Also, the annual sunny hours in Iraq are between 3,600 to 4,300 hours which makes it perfect to use the photovoltaics arrays to generate electricity with very high efficiency compared to many countries, especially in Europe. This paper shows the amount of electric energy generated by the meter square of crystalline silicon in the photovoltaic (PV) array that already installed in 18 states in Iraq for each month of the year. The results of the meter-square of PV array in three tracking positions are presented in this paper. This paper shows that the average electricity generated in North cities (Dohuk, Al-Sulaymaniyah, and Erbil) are less than the southern cities in the winter season (three positions) by about 40-50%. Iraq has a stable PV electrical generation during all the year in all regions except the North cities while the highest cities in electricity generation are (Najaf and Al-Anbar). [ABSTRACT FROM AUTHOR]

Copyright of Daluyan: Journal ng Wikang Filipino is the property of University of the Philippines - Diliman 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 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]

Over the past few years, the offshore wind sector has been subject to renewed yet growing interest from the industry and from the research sphere, with a particular focus on a recently developed concept, the floating offshore wind (FOW). Because of its novelty, floating research material is found in limited quantity. This paper focuses on the layout optimization of a floating offshore wind farm (FOWF) considering multiple parameters and engineering constraints, combining floating-specific parameters together with economic indicators. Today's common wind farm layout optimization codes do not take into account either floating-specific technical parameters (anchors, mooring lines, inter-array cables (IACs), etc.) or non-technical parameters (operational expenditure, OPEX; capital expenditure, CAPEX; and other techno-economic project parameters). In this paper, a multi-parametric objective function is used in the optimization of the layout of a FOWF, combining the annual energy production (AEP) together with the costs that depend on the layout. The mooring system and the collection system including the inter-array cables and the offshore substation are identified as layout-dependent and therefore modeled in the optimization loop. Using ScotWind site 10 as a study case, it was found with the predefined technical and economic assumptions that the profit was increased by EUR 34.5 million compared to a grid-based layout. The main drivers were identified to be the AEP, followed by the anchors and the availability associated with the failures of inter-array cables. [ABSTRACT FROM AUTHOR]

Bifacial photovoltaic cells can produce electricity from incoming solar radiation on both sides. These cells have a strong potential to reduce electricity generation costs and may play an important role in the energy system of the future. However, today, these cells are mostly deployed with one side receiving only ground reflection, which leads to a profound sub-optimal utilization of one of the sides of the bifacial cells. Concentration allows a better usage of the potential of bifacial cells, which can lead to a lower cost per kWh. However, concentration also adds complexity due to the higher temperatures reached which add the requirement of cooling in order to achieve higher outputs. This way, this paper focuses on the effectiveness of forced air circulation methods by comparing the thermal performance of three specific concentrating bi-facial collector designs. This paper developed a computational model, using ANSYS Fluent intending to assess the thermal performance of a covered concentrating collector with bifacial Photovoltaic (PV) cells. These results have then been validated by outdoor measurements. Results show that even a simple natural ventilation mechanism such as removing the side gable can effectively reduce the receiver temperature, thus resulting in favourable cell operation conditions when compared to the case of an airtight collector. Therefore, compared with a standard model, a decrease of 13.5% on the cell operating temperature was reported when the side gables are removed. However, when forced ventilation is apllied a 22.8% reduction on temperature is found compared to the standard air-tight model. The validated CFD model has proven to be a useful and robust tool for the thermal analysis of solar concentrating systems. [ABSTRACT FROM AUTHOR]

The aggregation of the remaining battery capacity of electric vehicles (EVs) can be used as distributed energy storage to participate in the microgrid optimisation through vehicle‐to‐grid (V2G) technology. However, the reliability of this service to be delivered is affected by the uncertainty of EVs' behaviour. The un‐reliable service will bring risks in the operation of microgrid when EVs' V2G electricity is regarded as an important flexibility resource. This paper, first proposes an analytical method to quantify the reliability of EV aggregation's (EVA's) V2G electricity based on the analysis of historical charging data and compound Poisson process. Based on this model, electric vehicles aggregators can evaluate the V2G bid quantity for any time slot on day t+1 according to the reliability requirements. Secondly, an optimal operation model of microgrid with consideration of V2G's reliability is considered. Finally, a test system with photovoltaics (PVs) and EVA on top of the original IEEE 33‐node system is used to verify the effectiveness of the proposed model. The results show that with the proposed reliability evaluation method of V2G electricity, the optimal operation of the microgrid can be reached with appropriate evaluation of the capability of the EVA. [ABSTRACT FROM AUTHOR]

Due to climate change, emission balancing is a relevant tool to quantify the environmental impact of a building system. The electrification of energy production at a national level, as well as energy supply at a building level, shifts the focus to the emission factor (EF) of the electricity grid. Currently, static EFs are used for calculating the emission balance. However, the electricity grid already shows fluctuations in power generation and EF due to renewable energies. The paper reviews recent literature outlining the research gap and presents the development of a simulation setup and concept, in which the emission balance of the building operation changes, using dynamic EFs that map fluctuations at an hourly resolution. In the first step, we simulate the thermal building and radiance performance. The data are than used in a second step to conduct a system simulation, which analyzes the effects of the dynamic EFs. The results show that the dynamic balance approach for different building system variants deviates considerably from the static approach. By comparing different concepts for the loading strategy, the predictive strategy outperforms a common control strategy, when considering the energy prices and/or the emissions. This is especially true for systems with inert storage units, where charging times significantly influence the balance, as well as for systems with PV integration. This paper outlines the potential of the EFs-optimized control increases when evaluating a potential scenario for the year 2040, factoring in increased seasonal and daily fluctuations in electricity generation. [ABSTRACT FROM AUTHOR]

This study addresses inherent challenges stemming from uncertainty associated with the integration of wind energy into the electricity market. A novel approach is proposed to leverage the capabilities of dynamic transformers to optimize the utilization of uncertain wind power output, thereby enhancing financial investment efficiency for wind power stakeholders. The flexible combination of wind turbines (WTB), transmission transformers (TTS), and Energy Storage Systems (ESS) can actively reserve or provision electricity. Electricity generation control is based on optimal analysis results using linear integer programming algorithms that consider temperature fluctuations, lifespan of transformers, and electricity market prices. Maximizing the dynamic transformer's efficiency as proposed and optimizing revenue and costs from the fluctuating wind power output significantly improves financial performance metrics when investing in wind farm projects. Financial figures highlighted in the paper emphasize notable benefits, particularly for wind farm expansion projects. The potential return on investment ratio is expected to increase up to 5.64 times compared to conventional wind farm investment scenarios, with an improvement to increase from 4.4% to 24.8%. [ABSTRACT FROM AUTHOR]

Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system's frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events. [ABSTRACT FROM AUTHOR]

Ensuring a balance between supply and demand is critical within electricity grids, requiring a supply composition that guarantees consistent service provision in the short and medium term. Between 2008 and 2017, Ecuador's electricity generation capacity expanded significantly, with an investment of approximately USD 8150 million into harnessing the potential energy of water. This led to the construction of five high-capacity hydroelectric projects by 2017, contributing 33.4% of the sector's energy output by 2023. However, it is important to note that if installed hydroelectric projects operate as run-of-river plants, with limited reservoir capacity, they can only regulate water use for electricity generation on an hourly basis. As of 2023, these run-of-river plants represent 68.8% of Ecuador's total hydroelectric capacity within the National Interconnected System (SNI). Consequently, during periods of low inflows, supplementary energy from other power generation plants is necessary to prevent energy crises. This paper addresses the impact on energy storing for electricity generation resulting from the evolution of hydroelectric power plant entry from 2006 to 2023. This aspect has not been thoroughly examined in hydrothermal systems, which primarily focus on potential energy obtained from dams. Our approach involves a statistical analysis of hydroelectric dam reservoir operational levels. We further explore the influence on demand service within Ecuador's electricity system, particularly during observed energy crises towards the end of 2023. [ABSTRACT FROM AUTHOR]

Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions is a complex task. This paper proposes a dispatch engine (DE) based on mixed-integer linear programming (MILP) for the planning and management of hybrid power plants. To maintain the committed electricity output, the dispatch engine will provide schedules for operation over extended time periods as well as monitor and reschedule the operation in real time. Through precise prediction of the load and the photovoltaic (PV) and wind power outputs, the proposed approach guarantees optimum scheduling. The precise predictions of the load, PV, and wind power levels are achieved by employing a predictor of the Feed-Forward Neural Network (FFNN) type. With such a dispatch engine, the operational costs of the hybrid power plants and the use of diesel generators (DGs) are both minimized. A case study is carried out to assess the feasibility of the proposed dispatch engine. Real-time measurement data pertaining to load and the wind and PV power outputs are obtained from different locations in the Sultanate of Oman. The real-time data are utilized to predict the future levels of power output from PV and from the wind farm over the course of 24 h. The predicted power levels are then used in combination with a PV–Wind–DG–ESS–Grid hybrid plant to evaluate the performance of the proposed dispatch engine. The proposed approach is implemented and simulated using MATLAB. The results of the simulation reveal the proposed FFNN's powerful forecasting abilities. In addition, the results demonstrate that adopting the proposed DE can minimize the use of DG units and reduce a plant's running expenses. [ABSTRACT FROM AUTHOR]

Currently, most studies on the optimization of wind farm layouts on flat terrain employ a discrete grid-based arrangement method and result in irregular layouts that may damage the visual appeal of wind farms. To meet the practical requirements of wind farms, a two-step optimization method called "grid–coordinate" based on a genetic algorithm is proposed in this paper. The core idea is to initially determine the number of wind turbines and their initial positions using a grid-based approach, followed by a fine-tuning of the wind farm layout by moving the turbines in a row/column manner. This two-step process not only achieves an aesthetically pleasing arrangement but also maximizes power generation. This algorithm is conducted to optimize a 2 km × 2 km wind farm under three classic wind conditions, one improved wind condition, and a real wind condition employing both the Jensen and Gaussian wake models. To validate the effectiveness of the proposed method, the optimization of configurations based on different wake models was conducted, yielding results including the efficiency, total power output, number of wind turbines, and unit cost of electricity generation. These results were compared and analyzed against the classical literature. The findings indicate that the unit cost of electricity generation using the two-step optimization approach with the Gaussian wake model is higher than that of the initial grid optimization method. Additionally, varying the number of wind turbines can lead to instances of high power generation coupled with low efficiency. This phenomenon should be carefully considered in the wind farm layout optimization process. [ABSTRACT FROM AUTHOR]

The reliable operation of steam turbines is paramount for the sustained performance of electric power generation facilities. Any malfunction or breakdown in these high-speed rotating machines can lead to significant operational disruptions, causing energy production losses and jeopardizing safety. Lubricating oil leaks represent a common challenge faced by power plants, impacting operational efficiency, safety, and environmental sustainability. Despite extensive research efforts to mitigate oil leakage, challenges persist due to the unique design characteristics of power stations. This paper addresses the management of a major lube oil leak in Unit No. 2 of the Sumsel-5 Power Plant in Indonesia, focusing on innovative strategies for mitigation. The aim of this research is to assess the effectiveness of various rectification measures in reducing lubricating oil leaks in steam turbines. Methods employed include detailed inspections, analysis of oil quality, and implementation of targeted rectification strategies. The results demonstrate a significant reduction in the oil leakage rate, from approximately 67-68 liters per day to around 1.5-2 liters per day, following the implementation of rectification measures. This remarkable decrease of around 97.3% underscores the effectiveness of the strategies in mitigating the oil leakage problem. The implications of this study extend beyond operational efficiency to encompass safety and environmental protection. By reducing the volume of oil lost to leakage, safety hazards associated with fire accidents are mitigated, enhancing safety for plant personnel and equipment integrity. [ABSTRACT FROM AUTHOR]

The ESCOM (Electricity Supply Corporation of Malawi) currently faces difficulties in monitoring and controlling critical parameters, such as electricity generation, transmission, and distribution in real-time. Inefficient energy management, lack of fault detection mechanisms, manual interventions, and limited data-driven decision-making capabilities are hindering ESCOM's ability to deliver reliable and efficient electricity services to the people of Malawi. The main objective of this work is to address the pressing challenges faced by ESCOM (Electricity Supply Corporation of Malawi) in effectively managing and optimizing electricity distribution within their infrastructure. This paper introduces an IoT-based industrial management system designed to tackle these challenges and enhance ESCOM's operational efficiency, energy management, and overall performance. [ABSTRACT FROM AUTHOR]

In this paper, the coupled dynamics of the floating platform and the wind turbine rotor are analyzed. In particular, the damping is explicitly derived from the coupled equations of the rotor and floating platform. The analysis of the damping leads to the study of instability phenomena, thus obtaining the explicit conditions that lead to the non-minimum phase zero (NMPZ). Two NMPZs are analyzed, one related to the rotor dynamics and the other one to the platform pitch dynamics. The latter introduces a novelty, and an explicit condition is provided in this work for its verification. In the second part of the paper, from the analysis of the damping of the floating platform, a new strategy for the control of floating offshore wind turbines (FOWTs) is proposed. This strategy allows one to impose on the controller an explicit level of damping in the platform pitch motion that adapts with wind speed and operating conditions without changing the period of platform pitching. Finally the new strategy is compared to one without compensation and one with a non-adapting compensation by performing aero-hydro-servo-elastic numerical simulations of a reference FOWT. Generated power, motions, blade pitch and tower base fatigue are compared, showing that the new control strategy can reduce fatigue in the structure without affecting the power production. [ABSTRACT FROM AUTHOR]

The safety and robustness of Deep Geological Repositories (DGRs) are of paramount importance for the long-term management of spent nuclear fuel from electricity generation. The introduction of a multi-barrier system, which includes the host rock formation and an engineered barrier system (including the bentonite buffer), has been a widely used approach to ensure the safety of DGRs. The assessment of the long-term safety of DGRs involves the mathematical modeling of the coupled thermal–hydraulic–mechanical–chemical (THMC) processes that occur in the near-field of the DGRs and their impact on the behaviour and engineering properties of the bentonite buffer. This paper presents a review of the THMC-coupled processes that arise in the bentonite buffer as well as a mathematical model governing such coupled processes. The model is verified against existing analytical solutions and validated against measured data of a thermal diffusion experiment in a sand bentonite column. Also, scoping analyses were performed to assess the influence of coupled THM processes on solute transport in clayrocks. The results of the numerical model closely matched those of the analytical solutions and experimental data demonstrating the capability of the provided mathematical model as well as the numerical approach in enhancing our comprehension of DGR behaviour. This enhanced comprehension will be valuable for safety prediction and assessment in the context of DGRs. The work presented in this paper is part of the Canadian Nuclear Safety Commission's (CNSC) regulatory research to gain independent knowledge on the safety of the geological disposal of radioactive waste. [ABSTRACT FROM AUTHOR]

The pan‐European power grid is experiencing an increasing penetration of Variable Renewable Energy (VRE). The fluctuating and non‐dispatchable nature of VRE hinders them in providing the Ancillary Service (AS) needed for the reliability and stability of the grid. Therefore, Energy Storage Systems (ESS) are needed along the VRE. Among the different ESS, a particularly viable and reliable option is Pumped Hydro Storage (PHS), given its cost‐effective implementation and considerable lifespan, in comparison to other technologies. Traditional PHS plants with Francis turbines operate at a high head difference. However, not all regions have the necessary topology to make these plants cost‐effective and efficient. Therefore, the ALPHEUS project will introduce low‐head PHS for regions with a relatively flat topography. In this paper, a grid‐forming controlled converter coupled with low‐head PHS that can contribute to the grid stability is introduced, emphasising its ability to provide different AS, especially frequency control, through the provision of fast Frequency Containment Reserve (fFCR) as well as synthetic system inertia. This paper is an extended version of the paper "The Contribution of Low‐head Pumped Hydro Storage to a successful Energy Transition", which was presented at the 19th Wind Integration Workshop 2020. [ABSTRACT FROM AUTHOR]

In today's world, people have been facing different unpleasant phenomena like global warming, water shortage and thermal pollution. Power plants for electricity generation are one of the main sources of greenhouse gases and thermal pollution in aquatic ecosystem. On the other hand, these power plants consume high amount of freshwater for cooling purposes. Water scarcity is a detrimental crisis that the whole world is struggling with it. To combat the thermal pollution, various wet cooling and dry cooling technologies have been introduced and reviewed till today. While wet cooling systems use lots of water, dry cooling ones are not suitable options in warm weather and climates. Here, the need for an alternative element is felt more than ever. So far, water and air have been the main coolants in power generation units. According to specific heat capacities in different substances, hydrogen, by far has the highest amount. So, a novel heat exchanger containing hydrogen and water could be a promising solution for the mentioned issues. This paper focuses on advantages of this heat exchanger from different points of view, however, some assumptions, considerations and calculations should be carried out to have the best performance for this idea. Temperature control is such an important process that should be done in heat exchangers. Hence, a review on a control method has been carried out in this paper. The simulation results have been taken by MATLAB/SIMULINK software. [ABSTRACT FROM AUTHOR]

Renewable energy could solve the problems caused by fossil fuels. The Archimedes hydro screw turbine is a potential tool for generating power from river currents. In this paper, a turbine at a scale of 1:6 has been made. It is installed and tested at various flow rates. The system is optimized using a genetic algorithm to achieve maximum efficiency. Due to the limitations that existed for conducting experimental tests at the optimal flow rate, the turbine at optimal flow rate is studied by CFD. In the turbine numerical simulation, the hydrodynamic characteristics of the turbine, such as rotational speed, power, torque, efficiency, and power coefficient are compared in the optimal flow rate (2.6 (lit/s)) and a flow rate of 2.4 (lit/s) (the closest flow rate to the optimal one). The results show that these values are higher in the optimal flow rate. Furthermore, the behavior of the turbine in these two conditions is compared using velocity, vorticity, pressure, and phase contours, which indicates that the velocity and pressure values are higher, and the vorticity and immersion values are lower in the optimal flow rate. Finally, for economic analysis of operating the turbine at the prototype scale as a hydropower plant, the discounted payback period for the turbine is determined, which varies between 2.55 to 5.93 years depending on the discount rate. It is also shown that operating this turbine at the prototype scale as a hydropower plant in Iran leads to currency savings of 1561 $. [ABSTRACT FROM AUTHOR]

Generating sustainable electricity from ambient humidity and natural evaporation has attracted tremendous interest recently as it requires no extra mechanical energy input and is deployable across all weather and geography conditions. Here, we present a device prototype for enhanced power generation from ambient humidity. This prototype uses both heterogenous materials assembled from a LiCl-loaded cellulon paper to facilitate moisture adsorption and a carbon-black-loaded cellulon paper to promote water evaporation. Exposing such a centimeter-sized device to ambient humidity can produce voltages of around 0.78 V and a current of around 7.5 μA, both of which can be sustained for more than 10 days. The enhanced electric output and durability are due to the continuous water flow that is directed by evaporation through numerous, negatively charged channels within the cellulon papers. The voltage and current exhibit an excellent scaling behavior upon device integration to sufficiently power commercial devices including even cell phones. The results open a promising prospect of sustainable electricity generation based on a synergy between spontaneous moisture adsorption and water evaporation. Generating electricity from air opens a promising way for green energy harvesting. Here, authors present a prototype driven by the integration of moisture adsorption with evaporation to generate continuous electricity for a long duration. [ABSTRACT FROM AUTHOR]

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In this contribution, a unique donor‐acceptor conjugated organic‐small‐molecule photothermal material, namely GDPA‐QCN, is presented. Bulky dendritic triphenylamine (GDPA) was grafted onto quinoxaline‐6,7‐dicarbonitrile (QCN) with a phenyl ring as a bridge to form an "umbrella" architecture. Benefited from the particular molecular structure, in solid state, GDPA‐QCN molecules adopted a loose packing mode due to the steric effect of "umbrella head" dendritic triphenylamine and flexible molecular structure feature, which allows efficient intramolecular motions and consequently elevates energy dissipation by taking the pathway of thermal deactivation within broad absorption range. The GDPA‐QCN solid has high solar‐thermal conversion efficiency with an absorption range from 300 to 1100 nm, which can promote superior water purification and electricity generation performance. [ABSTRACT FROM AUTHOR]

This paper analyses the impacts of electricity generation from solar energy on the Thai electricity industry. In this paper, three scenarios (REF, Solar2015 and Solar2018) are developed to represent an increased levels of electricity produced from solar energy. A Low Emissions Analysis Platform (LEAP) model is employed, in this paper, to assess the impacts for the period 2019-2037. This paper assesses and analyses the scenario impacts in terms of diversification of electricity generation, fossil fuel requirement and emissions of CO2 and SO2. The analysis reveals that increased electricity generation from solar energy would help diversify energy supply for electricity generation, reduce fossil fuel imports, and therefore help improve energy security of the country. Furthermore, it would help mitigating CO2 and SO2 emissions - an issue of environmental significance. Despite several benefits, there are a number of emerging barriers for promoting electricity generation from solar energy in Thailand. These include the intermittency of solar energy, high-capital cost, unsupportable grid infrastructure and unfavourable regulatory framework. This paper, therefore, suggests that the implementation of energy storage system, provision of financial incentives to potential investors, improvement of grid flexibility and the revision of the regulations to support solar energy business could be effective strategies in order to address the barriers facing the Thai electricity industry. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the environmental impact of electricity production from one of the best available gas-fired power plants and to compare it with the current mix of electricity and the supply of electricity from a typical gas plant. The scope of the paper includes gas field exploration, natural gas processing, pipeline transportation, and electricity generation as well as construction and decommissioning of the plant. The influence of efficiency of the plant and natural gas supply from different countries on the results is explored within the sensitivity analysis. The findings indicate that the global warming potential is estimated at 388 g CO2 eq./kWh. The natural gas system described offers major improvements in all considered environmental impacts compared to the typical natural gas electricity generation system, ranging from 4.9% for abiotic depletion potential to 82.1% for acidification potential. Increasing the contribution of natural gas in the electricity mix would reduce only eutrophication, human toxicity, freshwater, and marine aqua ecotoxicity potentials. The lower environmental impacts in this paper are due to the different gas composition, relatively high efficiency assumed as well as the proximity of Turkey to Azerbaijan which reduces transport distances. The results of this study would be of benefit to the future energy market, as natural gas is one of the electricity-producing plants promoted in Turkey. [ABSTRACT FROM AUTHOR]

Background: Renewable energies are key to reduce CO2 emissions and other environmental impacts of fossil-fueled electricity generation. However, renewable energy systems can also cause negative environmental effects. In this paper, we analyze the potential environmental trade-offs associated with different spatio-technical (de)centralization options for a renewable electricity system. For this purpose, we first review the potential environmental life cycle impacts of key technologies for renewable electricity systems. Subsequently, we develop a framework identifying which factors determine actual environmental effects of renewable electricity systems. We apply the framework to four basic spatio-technical (de)centralization options for the future Germany electricity system. Results: Our analysis shows that all (de)centralization options are associated with potential environmental trade-offs. We find that the (de)centralization of the system is a relevant factor determining these trade-offs. For instance, the two more centralized options considered have lower environmental impacts related to PV, whereas the two more decentralized options have lower environmental impacts related to grid infrastructure. However, we also find that the trade-offs depend on the specific way (de)centralization is pursued. For instance, only in one of the two considered more decentralized development options, there is a potential environmental trade-off between higher impacts related to battery storage and lower impacts related to offshore wind power. Conclusions: Our analysis reveals that the spatio-technical (de)centralization of a renewable electricity system plays a role for its environmental trade-offs while further factors like the institutional and stakeholder management in place also shape the environmental trade-offs. Policy makers should acknowledge the identified potential environmental trade-offs and their influencing factors when making policies favoring certain spatio-technical (de)centralization options. Highlights: Review of potential environmental impacts of key renewable technologies Framework on determinants of actual environmental effects of electricity systems Review of electricity system (de)centralization scenarios for Germany Application of framework to four spatio-technical (de)centralization options Environmental trade-off analysis for the four (de)centralization options [ABSTRACT FROM AUTHOR]

Autonomous microgrid is known to lack appropriate inertia and damping for grid stabilization. Due to this, virtual synchronous machine (VISMA) has been introduced to provide necessary ancillary services through control of power converters. In a multi‐VISMA (n‐VISMA) microgrid, relative rotor angle stability of the power system is dependent on the active power balance after small perturbation. Thus, the use of relevant analytical models are essential issues for microgrid stability analysis. This paper presents a comprehensive small‐signal stability analysis to study inherent electromechanical oscillations in the virtual rotors. The subsystems of the microgrid consisting of VISMA, network, load and the outer power control were all modelled in Synchronous Reference Frame. The small‐signal model (SSM) was tested on IEEE‐9 bus system with VISMA replacing electromechanical synchronous machines on the network. To validate the developed numerical analytics, dynamic responses of the SSM are compared with those of the non‐linear (NL) system dynamics and the results reveal that the developed linearized SSM is sufficient to accurately characterize behaviour of the VISMA microgrid when operated in autonomous mode. Eigenvalues analysis and parameter sensitivities of the critical modes were investigated. Oscillatory participations of the VISMAs and steady state stability limit of the microgrid have also been investigated. [ABSTRACT FROM AUTHOR]

Microbial fuel cells (MFCs) have garnered significant attention due to their capacity to generate electricity using renewable and carbon-neutral energy sources such as wastewater. Extensive experimental work and modeling techniques have been employed to dissect these processes and understand their respective impacts on electricity generation. The driving force is to enhance MFC performance for practical applications commercially. Among the various statistical modeling approaches, one particularly robust tool is the Design of Experiments (DoE). It serves to establish the relationships between different variables that influence MFC performance and allows for the optimization of the MFC configuration and operation for scaled-up performances in terms of bioelectricity generation. This study focused on optimizing microbial fuel cells (MFCs) for bioelectricity production using industrial wastewater treatment, employing the Box–Behnken design (BBD) methodology. Through an analysis of response surface models and ANOVA tests, it was found that a combined approach of reduced quadratic, reduced two-factor interaction, and linear models yielded sound results, particularly in voltage yield, COD removal, and current density. Second-order regression models predicted optimal conditions for various parameters, with surface area, temperature, and catholyte dosage identified as critical input variables for optimization. Under these conditions, conducted by the four-factor and three-level Box–Behnken design methodology in a double-chamber MFC unit considering eight output variables—CCV yield, % COD removal, current density, power density, % TSS removal, % CE, and % P O 4 3 − —the optimum values were 700 mV, 54.4%, 54.4 mA/m2, 73.7 mW/m2, 99%, 21.2%, and 100%, respectively. At optimum operating conditions, the results revealed a desirability of 76.6% out of a total of 92 iterations. The paper highlights the effectiveness of statistical ANOVA fit-statistics modeling and optimization in enhancing DCMFC performance, recommending its use as a sustainable bioenergy source. Furthermore, validation results supported the above optimization output response findings and confirmed the viability of biorefinery wastewater as an anolyte for scaling up DCMFC bioelectricity generation. [ABSTRACT FROM AUTHOR]

Power load prediction is fundamental for ensuring the reliability of power grid operation and the accuracy of power demand forecasting. However, the uncertainties stemming from power generation, such as wind speed and water flow, along with variations in electricity demand, present new challenges to existing power load prediction methods. In this paper, we propose an improved Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BILSTM) model for analyzing power load in systems affected by uncertain power conditions. Initially, we delineate the uncertainty characteristics inherent in real-world power systems and establish a data-driven power load model based on fluctuations in power source loads. Building upon this foundation, we design the CNN-BILSTM model, which comprises a convolutional neural network (CNN) module for extracting features from power data, along with a forward Long Short-Term Memory (LSTM) module and a reverse LSTM module. The two LSTM modules account for factors influencing forward and reverse power load timings in the entire power load data, thus enhancing model performance and data utilization efficiency. We further conduct comparative experiments to evaluate the effectiveness of the proposed CNN-BILSTM model. The experimental results demonstrate that CNN-BILSTM can effectively and more accurately predict power loads within power systems characterized by uncertain power generation and electricity demand. Consequently, it exhibits promising prospects for industrial applications. [ABSTRACT FROM AUTHOR]

Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company's potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs. [ABSTRACT FROM AUTHOR]

Morocco, despite its heavy reliance on imported fossil fuels, which made up 68% of electricity generation in 2020, has recognised its significant renewable energy potential. The Nationally Determined Contribution (NDC) commitment is to reduce emissions by 45.5% from baseline levels with international assistance and abstain from constructing new coal plants. Moreover, the Green Hydrogen Roadmap aims to export 10 TWh of green hydrogen by 2030, as well as use it for local electricity storage. This paper critically analyses this Roadmap and Morocco's readiness to reach its ambitious targets, focusing specifically on an energy trilemma perspective and using OSeMOSYS (Open-Source energy Modelling System) for energy modelling. The results reveal that the NDC scenario is only marginally more expensive than the least-cost scenario, at around 1.3% (approximately USD 375 million), and facilitates a 23.32% emission reduction by 2050. An important note is the continued reliance on existing coal power plants across all scenarios, which challenges both energy security and emissions. The assessment of the Green Hydrogen Scenarios highlights that it could be too costly for the Moroccan government to fund the Green Hydrogen Roadmap at this scale, which leads to increased imports of polluting fossil fuels for cost reduction. In fact, the emission levels are 39% higher in the green hydrogen exports scenario than in the least-cost scenario. Given these findings, it is recommended that the Green Hydrogen Roadmap be re-evaluated, with a suggestion for a postponement and reduction in scope. [ABSTRACT FROM AUTHOR]