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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]

Microbial fuel cell is a promising technology to harvest energy from wastewater, and effective anode catalysts are essential for its applications. In this study, zero-dimension nitrogen-doped carbon dots, as biocompatible efficient modifiers, were synthesized and decorated onto the carbon paper surface to prepare microbial fuel cell anode. The as-fabricated nitrogen-doped carbon dots decorated carbon paper anode was able to enhance electricity generation and efficient wastewater treatment. It was found that the as-fabricated electrode had a high hydrophilicity, which was favorable for the microbial immobilization. Compared with the carbon paper anode, the biofilm on the as-prepared anode was almost twice of thickness. After introducing nitrogen-doped carbon dots, the extracellular electron transfer process from the microorganisms to the anode was enhanced. The microbial fuel cell with the as-developed anode generated a remarkable power output of 0.32 mW, 1.1 times higher than that of the raw carbon paper anode with same measurement area. Moreover, 16 sRNA pyrosequencing analysis shows that the quantity of Pseudomonas on the electrode increased by ∼40%, which also promoted the electron transfer rate by excreting mediators like phenazines or phenazine derivatives. This work developed a new approach to design microbial fuel cell anode material and fabricate a high-efficiency and environmentally friendly anode for electricity generation from wastewater. Image 100697 • Notable power output was obtained from MFC with N-doped CDs@carbon paper electrode. • The carbon paper electrode was highly hydrophilic by decorating with N-doped CDs. • The EET efficiency was enhanced by modifying the electrode with N-doped CDs. • The relative abundance of Pseudomonas was enhanced with N-doped CDs' decoration. [ABSTRACT FROM AUTHOR]

The subsector of pulp and paper presented in 2013 an electric power consumption of 9.3% of electricity consumption in the industrial sector in Brazil. It experienced a significant growth of production in the last 20 years, exceeding 160%, and their consumption of electricity increased by 130%, reaching the level of 19,594GWh. Due to its characteristics, with a known structure and production processes, and its importance in the country's industrial sector, this subsector was selected for study in this paper, to evaluate the behavior of its long-term annual electricity demand, at the horizon of 20 years ahead, in energy efficiency scenarios through bottom-up approach. This approach is data intensive and requires data with good quality; it consists of a hierarchical structure that enables to check how specific actions can affect the results at each level and its effect on higher levels. [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]

[Display omitted] • Various carbon nanotube-based devices are developed for solar energy utilization. • The water evaporation system can generate freshwater (1.28 kg m−2h−1). • The solar-thermoelectric system can output a voltage and charge a cellphone. • The supercapacitor performs an areal specific capacitance of 19.6 mF cm−2. • The hybrid energy system can produce freshwater, generate and store electric power. Nowadays, multi-functional systems driven by solar energy have been explored to alleviate the crisis of energy and freshwater scarcity. However, it remains a great challenge to integrate multi-functions into one hybrid system with a monolithic material, which can harvest, convert and store solar energy synergistically. Here, we firstly propose a multi-functional carbon nanotube paper, which starts from a material level to solve these problems. The carbon nanotube paper is fabricated by vacuum filtration. It exhibits high efficiency of solar-thermal conversion. Secondly, three types of energy conversion/storage systems (e.g., solar-thermal evaporation system, solar-thermoelectric generation system, and supercapacitor) are constructed based on the carbon nanotube paper, which extend the research to a device level. The solar-thermal evaporation system shows an evaporation rate of 1.28 kg m-2h−1 under simulated sunlight irradiation of 1 kW m−2. The solar-thermoelectric generation system demonstrates a stable electric power generation with an output voltage of 100 mV under light irradiation of 1 kW m−2. The supercapacitors perform the energy storage function with an areal specific capacitance of 19.6 mF cm−2. These devices and systems can be used in freshwater generation (0.84 kg m-2h−1, sunlight irradiation of 1 kW m−2), water purification/desalination (inorganic ions rejection larger than 99.9%) and portable solar charging system (maximum output voltage of 5 V). Finally, a hybrid energy system is innovatively proposed from the system level to simultaneously produce freshwater, generate and store electric power. Through the synergetic coupling of solar conversion and storage technologies, the hybrid energy system can supply sustainable freshwater and electricity for remote areas in daily life, highlighting the superiority of multi-energy (thermal energy, electrical energy, and electrochemical energy) complementary. [ABSTRACT FROM AUTHOR]

Highlights • We develop a novel portable and disposable paper-based biobattery. • Our biobattery is on-demand electricity generation activated by a drop of tap water. • A low-cost, simple-structure battery case is created by single layer of paper filter. • We proposed integrated air-cathode paper-based proton exchange membrane. • Proposed battery can be used for paper-based diagnostic devices. Abstract A novel, portable, and disposable paper-based microbial fuel cells (MFC) generating electricity from harmless strain of Escherichia coli (E. coli) has been developed. This MFC is on-demand electricity generation activated by a drop of tap water in a dry anode containing the biofilm of E. coli. A low-cost, simple-structure MFC case was created by a single layer of paper filter with high order of folding, which could support interchangeable dry bacteria-loaded anodes. The paper filter was innovatively engineered to make an integrated air-cathode proton exchange membrane (ACPEM) by coating carbon nanotube mixed with potassium ferricyanide on one surface and spraying hydrophobic solution on the other surface, respectively. The E. coli biofilm pre-inoculated in the anodes made of activated carbon sheet was simply dried in the air for the sake of long-term storage and usage. The dry anodes can be simply set in the MFC case with the readily prepared ACPEM, which can be used for on-demand power generation within seconds after adding water with maximum power density of 8.8μW/cm2. [ABSTRACT FROM AUTHOR]

The central role of electricity in shaping the worldwide economy is broadly acknowledged in the energy literature. Having identified the then ongoing crisis of the electricity sector, the present Awami League government initiated restructuring the energy sector since 2009 to quicken the pace of the developmental activities. All these efforts resulted in landmark achievements in the Bangladesh energy sector, especially in increasing the electricity generation capacity. However, the global Covid-19 pandemic and its aftermath effects on the Bangladesh economy require a policy revision in Bangladesh's energy sector and electricity generation mix. To our knowledge, there is no study to analyse the adverse consequences of the Covid-19 in Bangladesh energy sector. By employing a SARIMA forecasting model, we reveal that electricity demand will remain less than the actual generation in the upcoming two years. Also, the DGE model finds that due to Covid-19, the economic growth rate will be around 4.5 percent in the long-run. We further simulate that the steady-state electricity demand and standard consumption values would fall by 8-10 percent and 6 percent, respectively. We recommend that a review of the power sector master plan is needed for future energy security and economic stability in Bangladesh. [ABSTRACT FROM AUTHOR]

An enormous gap exists between Africa's current electrification rate and the 2030 UN goal to ensure universal access to modern energy. A study by Sanoh et al. published in Renewable Energy in 2014 [1] is a rare example of finding a cost minimal solution for the Africa-wide generation and transmission network. Unfortunately, however, the paper exhibits a number of relatively serious flaws that demand attention given the alarming paucity of such research on Africa. Five issues of the study by Sanoh et al. are identified and discussed in this commentary paper. Specifically, the study does not account for capacity factors when deriving required capacity additions, misses transmission losses when sizing generation capacity, models country-level import constraints incorrectly, introduces a supply option redundancy, and reports optimisation results that can be shown to be mathematically sub-optimal. As a result of some of these issues, the Sanoh et al. significantly underreport the required capacity to meet additional African demand in 2025. In addition to discussing these flaws, this paper provides potential approaches to avoid each of the five issues. [ABSTRACT FROM AUTHOR]

We reported a novel, non-optical technique to analyse and quantify the transportation of bacterial cells in paper-based microfluidics. This approach was based on real-time measurement of the microbial electricity production. Our device was designed to have three hydrophilic regions linked by a channel on a paper layer by patterning hydrophobic barriers in the paper. Each region came into contact with an anodic electrode layer which was stacked with a cathodic compartment through a proton exchange membrane. When bacterial cells were transported to each region by capillary force, the bacteria cells were promoted to adhere onto the anode and the cells completed their respiration by transferring the electrons to the anode. A conductive load connected the anode and cathode to complete the external circuit through which the electrons flowed. The protons generated by the anodic reactions passed through the proton exchange membrane and travelled to the cathode, where they combined with electrons in the reduction process. By measuring the current through the load, bacterial cells’ transportation through the channels in paper was quantitatively investigated according to the pore size of the paper. Further understanding was made by analysing electron microscope examination of the hydrophilic regions. This work will determine more efficient cell movement within a paper material by controlling the paper's microfluidic dimensions and pore size. It will also provide a quantitative understanding of the flow of large organisms for use in paper-based diagnostics. [ABSTRACT FROM AUTHOR]

Chile has a very ambitious energy transition agenda and massive challenges ahead to accomplish it. To integrate the high solar energy potential in the north an the high wind power potential of the south of the country, considerable investments in the electrical grid and new balancing mechanism and storage capacities are necessary. This study addresses the potential of individual industries, particularly the paper industry, to provide flexibility to the electrical system on-site. To achieve this, an optimization model that minimizes energy provision costs is proposed. The model considers the demand of a company including its demand side management potential, combined heat and power generation capacities, as well as on-site renewable energy generation location potential from photovoltaics and wind power. The model is computed under multiple parametrization scenarios to estimate under which conditions it would be advantageous for the company to use renewable electricity. This allows to evaluate how much of the renewable electricity produced in high peaks can be used by the company, and in how far, demand side management and combined heat and power can compensate low generation periods of renewable electricity. The model is feeded with typical hourly electricity and heat demand profiles of a prototypic paper producing company, which were statistically derived from one and a half years of measurements. Moreover, electricity generation time series from photovoltaics and wind power are derived from physical models that rely on ERA5 reanalysis data. The latter data set allows to compute the model in locations all around Chilean territory in a 30 km x 30 km spatial grid. Results are presented in the form of maps of the shares of renewables that would be enabled at avery location by industries of the same characteristics. [ABSTRACT FROM AUTHOR]

There is a large global effort to improve microbial fuel cell (MFC) techniques and advance their translational potential toward practical, real-world applications. Significant boosts in MFC performance can be achieved with the development of new techniques in synthetic biology that can regulate microbial metabolic pathways or control their gene expression. For these new directions, a high-throughput and rapid screening tool for microbial biopower production is needed. In this work, a 48-well, paper-based sensing platform was developed for the high-throughput and rapid characterization of the electricity-producing capability of microbes. 48 spatially distinct wells of a sensor array were prepared by patterning 48 hydrophilic reservoirs on paper with hydrophobic wax boundaries. This paper-based platform exploited the ability of paper to quickly wick fluid and promoted bacterial attachment to the anode pads, resulting in instant current generation upon loading of the bacterial inoculum. We validated the utility of our MFC array by studying how strategic genetic modifications impacted the electrochemical activity of various Pseudomonas aeruginosa mutant strains. Within just 20 minutes, we successfully determined the electricity generation capacity of eight isogenic mutants of P. aeruginosa. These efforts demonstrate that our MFC array displays highly comparable performance characteristics and identifies genes in P. aeruginosa that can trigger a higher power density. [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]

An introduction is presented in which the editor discusses articles in the issue on topics including photovoltaics (PV), silicon-based solar cells and electricity generation.

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 application of renewable energies such as wind and solar has become an inevitable choice for many countries in order to achieve sustainable and healthy economic development [[1]]. The paper "Steady-State Analysis and Output Voltage Minimization Based Control Strategy for Electric Springs in the Smart Grid with Multiple Renewable Energy Sources" by Y. Zou et al. presented a general steady-state analysis and minimal compensating voltage control scheme for the second generation of electric springs in the power system with substantial penetration of intermittent renewable energy sources. The paper "Parallel LSTM-Based Regional Integrated Energy System Multienergy Source-Load Information Interactive Energy Prediction" by B. Wang et al. proposed an energy prediction strategy for multienergy information interaction in regional integrated energy systems from the perspective of horizontal interaction and vertical interaction. [Extracted from the article]

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]

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]

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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]

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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]

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]

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]

In interconnected power systems, operated by several system operators, the participating areas are strongly dependent on their neighbors. In order to identify the economically efficient generation dispatch in each area, a distributed multi-area optimal power flow (OPF) must be solved. Additionally, installation of an increasing number of HVDC lines to deal with increased power flows from renewable generation is expected to change the power system operation paradigm. The controllability introduced by the HVDC lines should be considered and incorporated in the OPF algorithm. In this paper we introduce a formulation for the distributed solution of the OPF problem in multi-area systems consisting of both HVAC and HVDC lines. We show the applicability of this formulation on two different operating schemes for HVDC grids and we compare their performance with a central solution for the mixed HVAC/HVDC grid. The proposed formulations are based on a linearized solution of the OPF problem. The only data to be exchanged between the areas pertains to the border nodes. [ABSTRACT FROM AUTHOR]

Load profile classification is very important in load forecast, planning and management. Although customers are generally grouped by utilities into residential, commercial classes and respective subclasses, there is a lack of systematic framework that can be used to characterize different classes with signatures that are both human-readable and machine-readable. The work presented in this paper attempts to formulate the theoretical framework for customer classification using the annual load profiles. This paper demonstrates how to extract characteristic attributes in frequency domain (CAFD) and use these CAFDs to formulate a hierarchy of load profiles that can be used as the systematic framework for customer load classification. As signatures for customer classes and subclasses, the CAFDs are obtained by using a data mining method called CART (classification and regression tree). The paper presents a load profile classification test to establish the efficacy of the proposed approach which is significant improvement over current practices that provide mostly qualitative labeling. [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]