Hydrogen energy plays a crucial role in integrating renewable, reducing carbon emissions, and boosting the operational flexibility of multi-energy microgrids (MEMG), owing to its substantial storage capacity and clean characteristics. However, a key challenge arises in the coordinated dynamic dispatch between power flows and the multi-stage hydrogen value chain, which includes production, conversion, utilization, and waste heat recovery. To address this, we introduce a novel multi-time scale operational framework for MEMG that considers electricity-hydrogen coupling and encompass the entire hydrogen process chain. This framework operates on a three-phase model: day-ahead scheduling aimed at minimizing daily operating costs; intraday rolling optimization every 15 min to adjust for renewable energy fluctuations; and real-time adjustments to fine-tune key conversion devices. Additionally, a carbon emission flow is integrated into the day-ahead phase to guide the dispatch of hydrogen and electricity towards low-carbon operations. Case studies demonstrate that our proposed framework lowers total operating costs by 6.64% and cuts carbon emissions by 13.06% compared to traditional day-ahead scheduling. This work offers a practical, system-level operational strategy to enhance both the economic and environmental performance of future flexible energy systems.
Production of electric energy or power. Powerplants. Central stations
Eunice Estrella De Guzman, Tzu‐Hsuan Wang, Michael Angelo B. Promentilla
et al.
Green electricity‐driven electrocatalytic CO2 reduction (e‐CO2RR) has emerged as a promising approach to upcycle CO2 into valuable chemicals and fuels, paving the way for a carbon‐neutral economy. The success of such a device relies on the development of cost‐effective catalysts that can efficiently and selectively catalyze e‐CO2RR. In the present contribution, the high activity and selectivity of graphene‐supported CoPc (graphene‐CoPc) are demonstrated toward CO generation from e‐CO2RR by encapsulating graphene|CoPc into Perlite–Metakaolin‐based geopolymer (geopolymer|graphene‐CoPc). The high electric conductivity (3.52 ± 0.4 S m−1) and CO2 adsorption capability (0.16 mmol CO2 g−1) of the geopolymer matrix, obtained through the systematic investigation and optimization of synthetic conditions, facilitate the charge transfer and provide high local CO2 concentration. Consequently, this significantly enhancing both turnover frequency (2.3 ± 0.3 s−1) and Faradaic efficiency (93.7 ± 3.1%) of geopolymer|graphene‐CoPc for CO production from the low‐concentration CO2 (≈40%) in simulated biogas atmosphere at a low η of 0.69 V as compared to the pristine graphene‐CoPc (turnover frequency: 1.37 ± 0.1 s−1 and Faradic efficiency: 46.3 ± 2.0%).
Environmental technology. Sanitary engineering, Renewable energy sources
Microbial fuel cells (MFCs) are promising for realizing wastewater remediation and electricity co-generation, which may significantly promote the formation of an environmentally friendly, clean energy society. Unfortunately, most of the available MFCs show relatively low electricity generation. Anodes, the major component of MFCs, play the most critical role in electron transfer and organic decomposition, which directly determine the performance of MFCs. In the past decades, various carbonaceous materials and carbon-supported conductive composites have been extensively exploited to optimize the electron transfer on the anode due to their versatile properties, such as large surface area and excellent electrical conductivity. The development of anode materials with a particular structure and performance to satisfy field-scale long-term operation of MFCs remains a huge research challenge, which attracts great attention and urgently needs in-depth exploration of the material engineering of anodes for MFCs. In this review, recent advances in the development and optimization of anodes for MFCs are summarized, and applications of MFCs with advanced anodes in the remediation of different types of wastewater are discussed. Advances of anodes for promoting electron transfer, microbial attachment and organic decomposition are the main focuses. The superiorities of MFCs on different aspects of wastewater remediation are elucidated, along with perspectives on future research of MFCs, aiming to provide useful guidance in related fields.
Materials of engineering and construction. Mechanics of materials
Power transformers, as essential equipment for electricity transmission, may fail due to insulation degradation. Predicting the failure rate of power transformers precisely is beneficial to decision-making. Currently, uncertainties of the prediction have not been deeply discussed. Besides, prediction accuracy is not high enough. This paper proposes a decomposition-based Bayesian deep learning (BDL) method to predict the failure rate of power transformers. Both the model uncertainty related to distribution of the model's weights and the inherent uncertainty associated with random noise can be captured by BDL. Uncertainties of prediction results are depicted with confidence intervals. Moreover, prediction accuracy is improved using variational mode decomposition (VMD). Numerical experiments have been carried out based on oil chromatographic data of power transformers from the Chongqing grid to validate effectiveness of the proposed method.
Isaac Amoussou, Eriisa Yiga Paddy, Takele Ferede Agajie
et al.
Abstract This study examined the optimal size of an autonomous hybrid renewable energy system (HRES) for a residential application in Buea, located in the southwest region of Cameroon. Two hybrid systems, PV-Battery and PV-Battery-Diesel, have been evaluated in order to determine which was the better option. The goal of this research was to propose a dependable, low-cost power source as an alternative to the unreliable and highly unstable electricity grid in Buea. The decision criterion for the proposed HRES was the cost of energy (COE), while the system’s dependability constraint was the loss of power supply probability (LPSP). The crayfish optimization algorithm (COA) was used to optimize the component sizes of the proposed HRES, and the results were contrasted to those obtained from the whale optimization algorithm (WOA), sine cosine algorithm (SCA), and grasshopper optimization algorithm (GOA). The MATLAB software was used to model the components, criteria, and constraints of this single-objective optimization problem. The results obtained after simulation for LPSP of less than 1% showed that the COA algorithm outperformed the other three techniques, regardless of the configuration. Indeed, the COE obtained using the COA algorithm was 0.06%, 0.12%, and 1% lower than the COE provided by the WOA, SCA, and GOA algorithms, respectively, for the PV-Battery configuration. Likewise, for the PV-Battery-Diesel configuration, the COE obtained using the COA algorithm was 0.065%, 0.13%, and 0.39% lower than the COE provided by the WOA, SCA, and GOA algorithms, respectively. A comparative analysis of the outcomes obtained for the two configurations indicated that the PV-Battery-Diesel configuration exhibited a COE that was 4.32% lower in comparison to the PV-Battery configuration. Finally, the impact of the LPSP reduction on the COE was assessed in the PV-Battery-Diesel configuration. The decrease in LPSP resulted in an increase in COE owing to the nominal capacity of the diesel generator.
In the present scenario, Distributed Energy Resources (DERs) are included into power grid distribution networks to withstand power outages. Restoration is a smart and efficient method for self-healing systems to maintain functionality and re-configure themselves in response to outside breakdowns or attacks. Intelligent decision making framework is required for ensuring that the system as a whole survives external breakdowns and attacks by autonomously reconfiguring itself. Further, the power grid faces serious security concerns, network congestion delay, and packet loss due to improper grid adjustments. As a result, in this research Edge computing assisted Intelligent Decision Model (EC-IDM) has been proposed to address the issue of breakdowns and attacks in real time. The emergence of edge computing has substantially improved the smart grid's ability to operate effectively and communicate effectively by reducing the effects of security concerns, packet loss, latency, and overloaded networks. The integration Smart Grid's peripheral index (SSGPI) optimizes the system's performance and operating efficiency. This research presents a real-time EC-IDM for fixing the electricity grid that can automatically develop the restoration plan and identify the blackout scenario. For restoration choices across several time-and-space axes in EC-IDM, an improved hierarchical coordination technique and a local object optimization method are integrated to optimize breakdowns and attacks in real time. EC-IDM utilizes Smart grid self-healing using distributed automation (DA) to address issues of dependability and reliability of power. The simulation results demonstrates that the suggested approach achieves best in security concerns, optimizes network congestion delay, and packet loss security, improves efficiency and performance compared to the other conventional methods.
This research relies on several kinds of Volterra-type integral differential systems and their associated stability concerns under the impulsive effects of the Volterra integral terms at certain time instants. The dynamics are defined as delay-free dynamics contriobution together with the contributions of a finite set of constant point delay dynamics, plus a Volterra integral term of either a finite length or an infinite one with intrinsic memory. The global asymptotic stability is characterized via Krasovskii–Lyapuvov functionals by incorporating the impulsive effects of the Volterra-type terms together with the effects of the point delay dynamics.
Abstract Geothermal heat pumps are one of the most growing and cost-effective renewable energy technologies based on the temperature difference between the ground and the environment. In the cold seasons, the temperature inside the soil or water is higher than the ambient temperature. Therefore, the heat pump is used to extract the warm temperature of the ground into the house or any other controlled space. In the summer, the air temperature is higher than the temperature of the soil or water. This temperature difference is used again to cool the house or any other environment. This paper examines the energy and exergy assessments of a hybrid system in Shanghai, China, that employs a geothermal heat pump with an economizer for winter heating and a wind turbine to provide clean electricity. The complete set of procedures, as well as every component and every aspect of the hybrid system, have all been carefully examined. The heat pump's coefficient of performance is 3.916, its net power output is 22.03 kW, its overall energy efficiency is 77.2%, and its exergy efficiency is 25.49%. Graphical Abstract
Aous Abd Al-jabar Hashim, Abdul Mun’em Abbas , Layth Abed
et al.
Ocean energy represented by waves is considered as a one of the renewable energy sources. This study aims to evaluate the methods that enhancing the ocean wave energy convertor performance. The mechanism of wave energy convertor is by converting mechanical energy to an electricity energy using DC generator and running by the pulling of wire due to ocean wave movement. Moreover, the test and analyze of converting the wave energy to electricity are conducted. Firstly, the role of numerical modeling lies in fabricating the tested rig in addition to study and analyze the buoyancy and stability in fluid mechanics as results of converting the kinetic energy derived from sea waves into rotational energy. The experimental tests were achieved locally at the Arabic gulf-South of Iraq/Basra (Khor Alzubayr). the tests were performed in two cases named: after happening the tidal (tested in one direction) and at the increasing of the sea water (tested in bidirectional). The results of local tests (at the sea) show that the maximum power of test was recorded value about 68 W in case of happening the tidal with an increase percentage of 92.6% over the case of bidirectional. These findings encouraging for more investigation in the methods that could increase energy harvesting from ocean waves since it is an enormous amount of energy.
Engineering machinery, tools, and implements, Mechanics of engineering. Applied mechanics
Non-intrusive load monitoring (NILM) considers different approaches for disaggregating energy consumption in residential, tertiary, and industrial buildings to enable smart grid services. The main feature of NILM is that it can break down the bulk electricity demand, as recorded by conventional smart meters, into the consumption of individual appliances without the need for additional meters or sensors. Furthermore, NILM can identify when an appliance is in use and estimate its real-time consumption based on its unique consumption patterns. However, NILM is based on machine learning methods and its performance is dependent on the quality of the training data for each appliance. Therefore, a common problem with NILM systems is that they may not generalize well to new environments where the appliances are unknown, which hinders their widespread adoption and more significant contributions to emerging smart grid services. The main goal of the presented research is to apply a domain adversarial neural network (DANN) approach to improve the generalization of NILM systems. The proposed semi-supervised algorithm utilizes both labeled and unlabeled data and was tested on data from publicly available REDD and UK-DALE datasets. The results show a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>%</mo></mrow></semantics></math></inline-formula> improvement in generalization performance on highly uncorrelated data, indicating the potential for real-world applications.
Purpose. The main objective of this study is to assess the phenomena that affect the parameters of power quality, to consider ways to counteract the deterioration of power quality, to assess the effect of electromagnetic interference on the human body, and to review the available devices for measuring the parameters of electric energy. Methodology. To obtain relevant data, the authors conducted a literature review on the topic of the work using full-text and abstract databases. The main causes of electromagnetic compatibility (EMC) violations and ways to counteract these violations are considered. The main parameters of electricity quality, conditions for their measurement and permissible ranges according to the State Standards of Ukraine (SSU) are highlighted. A review of devices for measuring the parameters of electricity quality and the search for a suitable one that meets Ukrainian standards was carried out. Findings. The authors have proved: 1) the problem of measuring electricity quality parameters is relevant and important for its accurate accounting; 2) control of electricity quality parameters and compliance with state standards allows avoiding negative impact on the electricity supply system; 3) the use of modern digital measuring devices provides greater measurement accuracy than analog ones, and they are able to take into account more parameters in one measurement. Originality. The authors conducted a study in the field of electromagnetic compatibility in the field of electromagnetic compatibility using a digital device that gives more accurate and reliable results of power quality parameters. Practical value. Based on the results obtained, it is possible both to correct the personal research of individual scientists or teams of scientists and to predict further prospects for the development of the subject area «Electromagnetic Compatibility» in traction power supply systems in railway transport. The research can also be useful in the study of the disciplines «Electromagnetic Compatibility of Railway Automation Systems» and «Electrical Circuits and Lines of Railway Automation», organization of scientific and practical seminars, advanced training courses, etc.
Biofuel cells have been in the spotlight for the past century because of their potential and promise as a unique platform for sustainable energy harvesting from the human body and the environment. Because biofuel cells are typically developed in a small platform serving as a primary battery with limited fuel or as a rechargeable battery with repeated refueling, they have been interchangeably named biobatteries. Despite continuous advancements and creative proof-of-concept, however, the technique has been mired in its infancy for the past 100 years, which has provoked increasing doubts about its commercial viability. Low performance, instability, difficulties in operation, and unreliable and inconsistent power generation question the sustainable development of biofuel cells. However, the advancement in bioelectrocatalysis revolutionizes the electricity-producing capability of biofuel cells, promising an attractive, practical technique for specific applications. This perspective article will identify the misconceptions about biofuel cells that have led us in the wrong development direction and revisit their potential applications that can be realizable soon. Then, it will discuss the critical challenges that need to be immediately addressed for the commercialization of the selected applications. Finally, potential solutions will be provided. The article is intended to inspire the community so that fruitful commercial products can be developed soon.
Production of electric energy or power. Powerplants. Central stations, Industrial electrochemistry
Carlos A. Saldarriaga Cortés, Ricardo A. Hincapié Isaza, Harold Salazar
Currently the world faces a great challenge, to achieve a sustainable production of energy, which allows the adequate development of humanity but at the same time does not irreversibly affect the environment. For this, it is absolutely necessary to make optimal and effective use of the available energy resources, in order to aim for energy transition objectives that result in the rational and efficient use of energy, the penetration of renewable resources, and social development. This requires that at a technical level, methodologies be proposed that allow for a holistic analysis of the different interactions and synergies present in the energy system. Therefore, it is essential to delve into the knowledge associated with the interaction between the electricity and natural gas networks, since natural gas is expected to be the energy source that supports the increase in generation from intermittent renewable energy sources. It is for the above that this research work analyzes the reliability of the electric power distribution network based on the impact associated with a contingency in the natural gas distribution network, when both networks are coupled through natural gas-based distributed power generators. A novel non-supplied energy index and a single contingency criterion are used for estimation purposes, considering failure rates and repair times of the natural gas network to obtain a more accurate in the estimation. Numerical results show that significant penetration of natural gas-based distributed generation can compromise the reliability of the power distribution network if the natural gas network is of low reliability.
The mitigation strategies and actions for mitigating the emission of greenhouse gas (GHG) from the energy sector become more important and urgent. The main aim of this paper was to present a trend analysis of the emissions of GHG from the Taiwan’s energy sector, which was issued by the central competent authority through the Intergovernmental Panel on Climate Change (IPCC) methodology. The data also complied with the procedures of measurement, reporting and verification. Based on the official database, the statistics on energy supply, energy consumption and GHG emissions will be connected to analyze the trends of environmental and energy sustainability indicators over the past decades. It showed that the trends of the relevant sustainability indicators based on GHG emissions from the energy sector indicated two development stages: the growth period (annually 5.6%) of 1990–2005, and the decoupling period (annually 0.5%) of 2005–2018. This result could be ascribed to the Taiwan government by promulgating some regulatory measures on energy saving improvement and renewable energy supply during this period. It was worthy to note that the installed capacities of photovoltaic (PV) power increased from 888 megawatt (MW) in 2015 to 5817 MW in 2020. These technological, behavioral, managerial and policy advancements are in accordance with global mitigation strategies. Under the authorization of the energy-related regulations, some promotional actions or programs for efficient energy use and renewable electricity supply were also announced to reach the targets of GHG emissions reduction in the sustainable development goals (SDGs).
Meisam Mahdavi, Hassan Haes Alhelou, Nikos D. Hatziargyriou
et al.
Distribution systems play an important role, delivering the electric power of generation system to individual consumers. Distribution system reconfiguration (DSR) is a large-scale combinatorial optimization problem. For the last 45 years, the DSR problem has been widely studied; nowadays, DSR, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a literary framework for DSR specialists. A categorization of solution methods, case studies, and novelties of the most relevant works regarding DSR are provided. In order to establish a complete background, not only traditional approaches, but also those involving uncertainty, reliability, electricity market, power quality, distributed generation, capacitor placement, and switching time in DSR are highlighted. This framework can help researches to improve previous formulations and methods and can propose more efficient models to better exploit the existing infrastructure.
This paper analyzes the impact of policy changes on the Romanian renewable energy producers. Attracted by a generous subsidy scheme, foreign and domestic investors flocked to the market. Consequently, the sector witnessed remarkable progress, especially in the wind power category. Romania fast approached the national target set by the European Union concerning the share of the country’s energy consumption from renewable sources. However, frequent changes in the support scheme and in the regulations issued by public authorities led to chaos. The aim of the paper was to emphasize the evolution of renewable energy policy in Romania, to investigate the incentives and their effects, and to critically assess the impact of the changes on renewable energy producers. It highlights, by means of an exploratory study and several interviews with executives of renewable energy companies, the challenges and shortcomings of policymaking. The main finding was that the revision of the subsidy scheme and the changes in energy policy that followed are the major determinants for the declining financial performance of renewable energy producers. Subsequently, some recommendations for improved policymaking are suggested, so as to re-establish the trust of investors and to promote the sustainable development of the sector.
Ariane Sagasti, Jon Gutiérrez, Andoni Lasheras
et al.
We present an exhaustive study of the magnetoelastic properties of 24 strips with different rectangular dimensions, cut from a long ribbon of Metglas<sup>®</sup> 2826MB3. The strips have a length-to-width ratio <i>R = L/w</i> ranging from 2 to over 20. Significant variations of the apparent saturation Young’s modulus and the <i>ΔE</i> effect with strip geometry, changing from 160 GPa and 4% for <i>L</i> = 10 mm, <i>w</i> = 5 mm and <i>R</i> = 2, to 164 GPa and 9.6% for <i>L</i> = 35 mm, <i>w</i> = 1.7 mm and <i>R</i> = 20.6, have been observed. In order to obtain the highest values of the <i>ΔE</i> effect, the magnetomechanical coupling coefficient, <i>k</i>, and the quality factor of the resonance, <i>Q</i>, a value <i>R</i> > 14 is needed. The effective anisotropy field <i>H<sub>k</sub><sup>*</sup></i>, taken as the minimum of the <i>E(H)</i> curve, and its width <i>ΔH</i>, are not as strongly influenced by the <i>R</i> value, and a value of <i>R</i> > 7 is enough to reach the lowest value. From our measurements we infer that the formerly predicted value of <i>R</i> > 5 needed for a good magnetic and magnetoelastic response of the material must be actually regarded as the lowest limit for this parameter. In fact, we show that the demagnetizing factor <i>N</i>, rather than the length-to-width ratio <i>R</i>, is the parameter that governs the magnetoelastic performance of these strips.
Nur Arifatul Ulya, Efendi Agus Waluyo, Adi Kunarso
Micro Hydro Powerplant (MHP) is one form of water utilization in upper Musi watershed to generate electricity. This paper aims to analyse the feasibility of the development and management of self-help MHP to support forest resource conservations. Financial and economic analysis are applied to determine the feasibility of the development and management of the self-help MHP. The result indicates that the construction and management of the self-help MHP in the research area are not feasible, so that they do not guarantee the sustainability of the MHP in the long term period. Development and management of MHP will be financially feasible when it uses postpaid electricity tariff scheme of State Electricity Company (SEC) for power limit up to 450 VA, and economically feasible if it uses postpaid electricity tariff scheme for power limit (SEC) up to 1,300 VA. It is necessary to increase the capacity of the community both technical and economic aspects in the management of MHP for the sustainability of electricity supply from the MHP. Water utilization for the MHP increases the collective awareness to conserve forest resources.