Energy Resources Research Articles

Necroecological Trophic Transfer of Microplastics: Insights into the Ecotoxicity of Petroleum-Derived and Biodegradable Polymers.

Although the toxicity of petroleum-derived microplastics (MPs) has been widely investigated, the impact of biomicroplastics (BioMPs) remains controversial, and the necroecological trophic transfer of both is still poorly understood. Our study reveals that biomicroplastics may pose ecotoxicological risks comparable to or greater than those of petroleum-derived plastics, a finding that should raise concern. We aimed to evaluate the possible translocation of polystyrene (PS) and polylactic acid (PLA) MPs from mice to the necrophagous fly Synthesiomyia nudiseta and their potential effects on the larval stage. Mice were inoculated intraperitoneally with different doses of MPs [9 (I) and 90mg/kg (II)] and subjected to the decomposition process (for ten days), allowing colonization by larvae. Our results confirmed the translocation of MPs from mice to S. nudiseta larvae, resulting in a greater accumulation of PLA-MPs compared to PS-MPs. We observed that exposure to MPs significantly influenced biomass accumulation, with larvae from the PS-I and PLA-I groups showing increased biomass. In contrast, those from the PLA-II group exhibited lower biomass. AChE activity was modulated in a concentration-dependent manner, with an increase observed in larvae exposed to PLA-MPs, indicating a potential neurotoxic effect. In addition, there was an increased production of reactive oxygen species (ROS), especially in the groups exposed to higher concentrations of MPs, without a proportional response of antioxidant enzymes, suggesting a redox imbalance and oxidative stress. The elevated serotonin levels and reduced dopamine observed in larvae exposed to MPs indicate a possible redirection of energy resources and changes related to a metabolic adaptation to the stress imposed by MPs. Principal component analysis (PCA) showed that PC1 was strongly influenced by biomarkers such as trypsin, chymotrypsin, AChE, ROS, and dopamine activity, highlighting that PLA-MPs (at the highest concentration) induced more pronounced toxic effects than PS-MPs. This finding was corroborated by discriminant analysis, which revealed a clear separation between the experimental groups, and by multiple regression analysis, which confirmed a strong relationship between MP concentration and larval biomarker responses, indicating that the type and concentration of MPs explained approximately 65% ​​of the variation in the biomarkers evaluated. In conclusion, our study demonstrates for the first time the necroecological trophic translocation of MPs between vertebrates and invertebrates, highlighting the potential risks of biomicroplastics.

Scheduling problems on parallel dedicated machines with non-renewable resource

Abstract We study scheduling problems on parallel dedicated machines and assume that a specific job can only be processed on one specific machine. We concentrate on solving scheduling problems involving convex resource allocation and address three of the most fundamental measures in scheduling theory, i.e., makespan, total load, and total weighted completion time. Firstly, we focus on position-independent workloads, and then we study the setting of general position-dependent workloads, i.e., the workloads are not restricted to be either monotone functions of the job positions or any specific functions. In all problems, we assume a common continuous and non-renewable (limited) resource and adapt known results from scheduling theory to solve the considered problems.

Impact of environmental quality, renewable and non-renewable energy and governance quality on sustainable development: evidence from emerging economies

PurposeThe present study aims to examine the influence of environmental quality, renewable energy, non-renewable energy and quality of governance on sustainable development in two panels of 23 Asian and 8 European emerging countries during the 1996–2022 period.Design/methodology/approachThe present study employed second-generation methods of panel data analysis, which account for cross-sectional dependency and heterogeneity to achieve a more reliable conclusion.FindingsThe augmented mean group and common correlated effects mean group estimation findings exhibit the negative influence of environmental degradation and non-renewable energy on sustainable development, whereas the findings exhibit the positive effect of renewable energy and governance quality on sustainable development.Practical implicationsThe findings point out to policymakers and governments the importance of the adoption and implementation of policies to protect the environment, as well as promoting renewable energy incentive policies. Moreover, enhancing governance quality and striving towards good governance is essential for the successful adoption and implementation of energy and environment policies, as well as achieving sustainable development goals.Originality/valueThe present research contributes to the existing related literature in several ways. Adjusted net saving (ANS) is employed as a comprehensive indicator of sustainable development and ecological footprint (EFP) is employed as an exhaustive indicator of the environment’s quality rather than carbon dioxide emissions. In overall, this study is the first, to the best of our awareness, to simultaneously consider ANS, EFP and governance quality for examining the relationship among energy, environmental quality and sustainable development, especially in Asian and European emerging economies.

A brief review on the progress of MXene-based catalysts for electro- and photochemical water splitting for hydrogen generation.

The development and generation of affordable and highly efficient energy, particularly hydrogen, are one of the best approaches to address the challenges posed by the depletion of non-renewable energy sources. Hydrogen energy, as a green and ecosystem-friendly source with zero carbon emission, can be generated through various methods, including water splitting (HER/OER) via either photo- or electrocatalytic reactions. To implement these reactions effectively in practical applications, it is highly desirable to develop extremely efficient and cost-effective catalytic materials that are comparable to contemporary catalysts. MXenes, a family of newly discovered 2D transition metal carbides, nitrides, or carbonitrides with surface termination groups, such as -OH, -O, and -F, have emerged as promising materials and substrates for photo- and electrocatalytic applications due to their unique characteristics. These include excellent conductivity provided by the transition metals, hydrophilic nature imparted by the surface termination groups, high mechanical stability, fast electronic transmission and extremely high surface area-to-volume ratios. In this review, we provide detailed insights into the synthesis, properties, and catalytic applications of MXenes. We systematically outline the photo- and electrocatalytic water splitting reactions carried out by various MXene-based heterostructures, supported by experimental data. A thorough deliberation on the structure-activity associations of reported catalysts and a basic understanding of the electrocatalytic applications of MXenes are also included. Furthermore, we offer an insight into the upcoming tasks, challenges, prospects and new research strategies for MXenes in water splitting applications. A noteworthy recognition of the design and optimization of extremely efficient MXene-based catalysts in water splitting applications is therefore offered in this review.

Investigate Advanced Techniques for Power System Protection, Fault Detection, and Restoration to Enhance the Reliability and Resilience of Electrical Grids

Investigate Advanced Techniques for Power System Protection, Fault Detection, and Restoration is a critical area of study aimed at enhancing the reliability and resilience of electrical grids. As modern power systems face increasing complexities due to the integration of renewable energy sources, aging infrastructure, and growing demand for electricity, innovative protection strategies have become essential to mitigate risks associated with electrical faults and disturbances. The significance of this topic lies not only in improving the operational efficiency of power systems but also in minimizing economic losses and ensuring public safety. Advanced techniques in power system protection encompass a range of methodologies, including the implementation of digital protective relays, circuit breakers, and sophisticated communication systems. These technologies enable real-time monitoring and rapid fault detection, which are vital for maintaining continuous power supply. The evolution of machine learning (ML) and artificial intelligence (AI) has further revolutionized this field by facilitating self-healing grids that can autonomously detect, diagnose, and restore service after outages, significantly reducing outage durations and enhancing reliability metrics such as the System Average Interruption Duration Index (SAIDI). Despite the advancements, challenges remain, particularly concerning cyber security risks, regulatory compliance, and the adaptation of protection schemes to accommodate fluctuating energy sources. These complexities necessitate ongoing research and development to create adaptive systems capable of responding to dynamic operational conditions while safeguarding infrastructure integrity. Moreover, the integration of emerging technologies must balance innovation with practical application, ensuring that protective measures not only meet current needs but also anticipate future demands within the energy sector. This investigation into advanced power system protection techniques is pivotal for addressing the pressing issues of system reliability and resilience in the face of evolving electrical grid dynamics. It highlights the critical role of technology in modernizing utility operations and lays the groundwork for future advancements in grid management and outage restoration strategies. Key Words: Power system protection, Fault detection, Distributed Energy Resources (DERs), Islanding, Grid reconnection, Fault localization, Microgrid protection, Fault current variability, System resilience

СРАВНИТЕЛЬНЫЙ АНАЛИЗ ДИЭЛЕКТРИЧЕСКИХ СВОЙСТВ ПЕРЕРАБОТАННЫХ ЗЕРНОВЫХ

The purpose of research is to study the dielectric properties of grains processed by mechanical activation using the example of wheat, barley and oats, which are widely used in the agro-industrial complex and the food industry. Objective: to identify the relationship between the dielectric parameters of processed grain and its structural parameters (fraction size) in a wide range of variations in the external electric field from 50 Hz to 1 KHz, which may be useful in optimizing grain processing technologies and choosing optimal storage conditions. A series of experiments was carried out for samples of wheat, oats and barley, varying the degree of fractions from 50 to 1000 μm in a wide frequency range. An algorithm has been developed for calculating dielectric constant and dielectric loss tangent based on measurements of electrical capacitance and conductivity using a certified E7-20 voltage immittance meter and a measuring cell (flat capacitor). An analysis of variations in electrical capacitance, the real part of dielectric constant, electrical conductivity and dielectric loss tangent on the particle size of grain crops was carried out. It has been established that there is a correlation between the dielectric properties of grain processed by mechanical activation and the size of the fractions, which is most significant for small-sized samples with a particle size of no more than 250 microns. A smoothing of variations in dielectric constant and losses was noted as the electric field frequency increased above 100 Hz. The existence of a relationship between the energy properties of the studied fine heterogeneous medium and the degree of grinding in the frequency range under study has been experimentally confirmed. An optimal size for grain processing has been proposed, which will, along with saving energy resources, allow optimizing energy value, improving the quality of food products and the efficiency of agricultural production in general.

Integrating Multiple Control Actions in Advanced Microgrids: an Analogy to Well-Established Inverter Control

This paper proposes multiple control actions applied to centralized advanced microgrids (MGs). The well-established control actions feedback (FB), feedforward (FF), and disturbance decoupling (D) commonly used in current control of distributed energy resources (DERs) are herein extended to advanced MGs. Analytical expressions are derived to show the effect of each control action on the well-established DER current control and then on advanced MG control. Comprehensive comparisons between the feedback and all control action strategies are performed for both DER and MG controls. Simulation and experimental results show a dynamic response improvement in load disturbance rejection when all control actions are considered, as well as a reduction in steady-state error for the grid power flow control. By employing low-bandwidth communication between DERs and central controller, no hardware retrofit is required in comparison to what is needed in other state-of-the-art centralized MG controls.

Dilemma of Harvested Cropland and Land Degradation in Agriculture Growth: Determining the Role of Water and Green Energy Resources

Dilemma of Harvested Cropland and Land Degradation in Agriculture Growth: Determining the Role of Water and Green Energy Resources

Calibration of parameters and predictive control strategy of a wind turbine for improvement of energy harvesting

Applied mathematical modeling of the various energy resources has contributed widely in their design and operation improvements. Among renewable energy sources, wind energy systems have gained a significant attention for their rapid and continuous growth, which resulted from their cost effectiveness and clean power generation. However, research effort on the industry and university levels is still needed to enhance the characteristics of existing wind turbines and allow larger amounts of their share. This thesis presents an accurate model of a wind turbine (TWT-1.65) system for time-based dynamic simulations. The parameters of the power coefficient have been identified, calibrated and verified using different meta-heuristic optimization techniques, which are the Wild Horse Optimizer (WHO), Whale Optimizer (WO), and Genetic Algorithm (GA) to enhance the model accuracy over the previously related studies. The new version of the parameters has resulted in a higher accuracy while being practically meaningful, with the best achieved MSE of 0.006. The system model has been then integrated with two predictive controllers which are the linear Model Predictive Control (MPC) and Neural Network Predictive Control (NNPC) to regulate the pitch angle trends for the target of maximum energy harvesting. With proper selection of the controllers’ parameters, off-line simulation studies have shown improved production trends of the power output with constrained and safe trajectory of the pitch angle, which can be translated to be an improve in the total average harvested power of 34% and 44.5% over the complete time window of 5760 min using NNPC and Linear MPC respectively.

Энергоэффективность экономики России: оценка и прогноз

The relevance of the study is determined by the fact that the current geopolitical situation makes the problem of ensuring energy efficiency of the Russian national economy particularly significant. The indicator "energy intensity of GDP" is used as a key indicator characterizing the efficiency of using energy resources. It is shown that in the period 2012-2022, there was a positive trend towards reducing the energy intensity of GDP due to energy conservation and increased energy efficiency. The regression analysis method was used to evaluate and predict the energy efficiency of the Russian economy. The formed regression model, which includes eight factor indicators, shows that the technological factor is a key driver of reducing the energy intensity of the GDP of the Russian Federation. The performed forecast estimates allow us to state that in the medium term, we should expect a return to the positive downward trend that took place in the period 2012-2022. Current and prospective estimates of the energy intensity of GDP suggest a likely increase in the efficiency of the Russian economy in terms of the use of energy resources.

A Systems View of Circular Economy

In many developing countries, economic growth is often prioritized, sidelining critical issues such as social inequality, pollution, climate change, ocean degradation, and pressing needs for health, education, food, and water management. Traditional linear models in organizations, based on product innovation and hierarchical governance, have been successful in certain contexts but are no longer viable in the face of finite natural resources and environmental degradation. This paper proposes a Systems Approach to Circular Economy as a practical framework for achieving “circular business-driven sustainability”, a concept proposed by major global organizations such as COP-25. This approach redefines sustainability, aiming to generate “sustainable wealth increasing returns” that benefit all key stakeholders, including the environment, society, and the economy. The primary objective of this paper is to introduce a new paradigm that facilitates the transition to more conscious, long-term growth. The proposed circular iterative thinking framework shifts from linear, reductionist thinking to a more holistic, systemic vision, underpinned by disruptive sustainable innovation. This novel paradigm creates positive impacts across the economy, environment, and global geopolitics. The paper demonstrates the application of this framework in two case studies, providing concrete evidence of its utility in real-world scenarios, including Heineken’s sustainable practices at its Meoqui brewery, which recovered methane for energy use, reduced water consumption, and contributed to local irrigation. The results underscore the effectiveness of the Systems Approach to Circular Economy in achieving economic decoupling and enhancing sustainability.

Brushite: a Reclaimed Phosphorus Fertilizer for Agricultural Nutrient Fertilization

Abstract Phosphorus fertilizers are typically produced from mined and chemically processed rock phosphate, which is a diminishing non-renewable resource. Wastewater-reclaimed phosphorus minerals, such as brushite (CaHPO4·2H2O), have the potential to be utilized as agricultural fertilizers. The commercial recovery of brushite from wastewater processing is a recent advancement; however, its efficacy as an agricultural fertilizer has yet to be evaluated. Wastewater-reclaimed brushite was tested in a greenhouse and field setting. In the greenhouse study, two P-limited soils were used to grow corn fertilized using brushite and were compared with struvite (NH4MgPO4·6H2O), another reclaimed P source, and conventional P fertilizers, triple super phosphate (TSP) and monoammonium phosphate (MAP). In the field, corn, wheat, and cotton were grown in two ecoregions for two sites years to compare brushite and struvite with conventional fertilizers. Plants were evaluated for P uptake and yield, and P availability was determined as extractable P. Results indicate that brushite promoted plant productivity similar to conventional fertilizers in P-limited greenhouse soils. Field studies demonstrated similar uptake and assimilation of brushite-P compared to synthetic fertilizers and struvite. Soil acidification occurred across all fertilization treatments. The use of reclaimed brushite as a P fertilizer appears to be as effective as commercially available synthetic fertilizers.

Prudent Electricity Procurement by a Load Serving Entity

Motivated by the projected solar and wind capacity additions around the world, we model the energy procurement decision of a load serving entity (LSE) faced with alternatives of solar power purchase agreements (PPAs), wind PPAs, non-renewable energy forward contracts, and spot energy purchases in a wholesale electricity market with uncertain prices. Using a pseudo-data sample of over one million observations, we estimate a translog cost function to find that the LSE’s own-price elasticity estimates range from −1.87 for nighttime spot MWh demands to −13.1 for forward MWh demands. MWh demands are influenced by solar and wind capacity factors, daytime and nighttime retail sales, and spot energy price forecasts. The LSE’s optimal procurement of solar capacity is roughly twice the wind capacity, corroborating the ratios of projected solar and wind capacity additions in regions around the world. If the LSE’s existing energy mix is nearly all renewable, it becomes carbon-free when solar and wind power purchase agreements have declining energy prices or when forward energy price and spot energy price forecasts increase over time. These results imply that piecemeal policy measures can have conflicting outcomes, calling for integrated resource planning under wholesale market competition and price uncertainty.

Comparative Analysis of Neural Network Models for Predicting Battery Pack Safety in Frontal Collisions

Amid concerns about environmental degradation and the consumption of non-renewable energy, the development of electric vehicles (EVs) has accelerated, with increasing focus on safety. On the road, battery packs are exposed to potential risks from unforeseen objects that may collide with or scratch the system, which may lead to damage or even explosions, thus endangering the safety of transportation participants. In this study, several predictive models aimed at assessing the safety performances of battery packs are proposed to provide a basis for data-driven structural optimization by numerically simulating the deformation of the battery base plate. Initially, a finite element model of the battery pack was developed, and the accuracy of the model was verified by performing modal analysis with various commercial software tools. Then, representative samples were collected using optimal Latin hypercube sampling, followed by collision simulations to gather data under different collision conditions. Next, the prediction accuracy of three models—PSO-BP neural network, RIME-BP neural network, and RBF neural network—was compared for predicting battery pack bottom shell deformation. Finally, the prediction accuracy of the models was compared based on error functions. The results indicate that these neural network models can accurately predict deformation under frontal collision conditions within the specified limits, with the RIME-BP model yielding the best performance beyond those limits. The developed neural network prediction model is able to accurately assess the mechanical response of battery packs under frontal collision, providing support for data-driven structural optimization. It also provides an important reference for improving the safety and durability of battery pack design.

Resourceful Hydrogen Generation through Methanol Steam Reforming Using Rare-Earth Metal Oxide-Modified Delafossite 3D Hollow Spheres.

The world is moving toward the goal of achieving net-zero carbon emissions by 2050, and hydrogen energy is considered an excellent alternative to nonrenewable energy sources. In this regard, developing a catalyst that is both economically valuable and exhibits efficient hydrogen production is a primary task at the current stage. This study utilized a hydrothermal synthesis method to prepare a nanosized 3-dimensional (3D) hollow sphere of CuCrO2-CeO2 for use in the Steam Reforming of Methanol (SRM) process. The characteristics and morphology of prepared CuCrO2-CeO2 hollow sphere were characterized by using various techniques such as XRD, FESEM, HRTEM, FTIR, Raman, etc. The CuCrO2-CeO2 hollow spheres with a 1:2 ratio exhibited the highest hydrogen production efficiency at 550 °C, yielding 6372.73 mL STP min-1 g cat-1 per gram of catalyst. Furthermore, the incorporation of CeO2 not only enhanced the hydrogen production rate of CuCrO2 but also extended the applicability of CuCrO2 nanoparticles to a wider temperature range. The unique 3D hollow sphere structure of the catalyst offers numerous advantages such as low cost, multiple catalytic reaction sites, and easy preparation. Therefore, CuCrO2-CeO2 hollow spheres hold potential for commercial development.

Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm

Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water prediction model by selecting and improving it according to the previous research results in decomposition method, time series prediction model and optimization algorithm. After processing the raw data and setting the model parameters, MAE, RMSE, MAPE and R2 are selected as the evaluation indexes of prediction accuracy, and VMD-GRU model, iCHOA-GRU model, CHOA-GRU model and GRU model are selected as the comparison models to validate the advantages of the VMD-iCHOA-GRU model in the prediction of mine inrush water. The results show that the VMD-iCHOA-GRU model has the best prediction effect on the trend of water inflow, with the evaluation index values of 0.00862, 0.01059, 0.02189%, 0.87079, respectively, and with the smallest MAE, RMSE, MAPE, and the largest R2, and the highest prediction accuracy of the VMD-iCHOA-GRU model.

Geochemistry Characteristics and Coal-Forming Environments of Carboniferous–Permian Coal: An Example from the Zhaokai Mine, Ningwu Coalfield, Northern China

In order to study the geochemical characteristics of coal in the Ningwu Coalfield of Shanxi Province and the coal-forming environments reflected by it, a detailed geochemical study was carried out on the No. 5 coal of the Zhaokai Mine. The results show that the content of major-element oxides SiO2 and Al2O3 is high. The trace elements Ni, Nb, Mo, Cd, Sn, Hf, Ta, W, Th, and U are slightly enriched, while the elements Li and Zr are enriched, indicating an overall LREY enrichment type in the samples. Elemental parameters suggest that the sedimentary environment in the study area is continental sedimentary, and the whole environment is reductive. The macerals in the coal samples are mainly vitrinite, with an average vitrinite reflectance (Ro) of 0.744%. The distribution range of n-alkanes in the coal samples is from n-C14~n-C32, with the main peak carbons being n-C24 and n-C25, showing the post-single-peak type distribution pattern. The average odd–even predominance index (OEP) is 0.40, the average of the light and heavy hydrocarbons ratio (∑C21−/∑C22+) is 0.42, and the average of Pr/n-C17 and Ph/n-C18 are 1.08 and 0.23, respectively. The coal samples also contain various aromatic hydrocarbons, mainly from the naphthalene- and phenanthrene-series compounds. Biomarker parameters indicate that the parent material of the coal samples in the study area is mainly continental higher plants. The maturity is low, and the coal-forming environment is a reduction environment. This study of the No. 5 coal’s geochemical characteristics has laid a foundation for the efficient, green, and comprehensive exploitation of coal resources in this region, and has also provided an important basis for the sustainable development of coal resources.

Polycrystalline Diamond Composite Bit Technology for Sustainable Work

Reducing the auxiliary drilling time and improving the drilling efficiency are not only important technical means to enhance the development and deep exploration of oil and gas reserves, but also have significant implications for ensuring energy security. Bottom hole self-renewal drill bit technology is a new technology that does not require the retrieval of drills from the well bottom, instead directly updating worn drill bits in place. Through the self-renewing structure of the drill bit, the sustainability of the drill bit can be increased. Conducting research on this technology is expected to overcome the technical issues related to the short useable life of drill bits, thus promoting single-trip drilling technology. This article summarizes the scientific progress made by researchers in self-renewal Polycrystalline Diamond Composite (PDC) drill bit technology; for example, the American National Oilwell Varco (NOV) company has developed a mobile self-renewal cone bit technology and introduced the structural characteristics and working principles of three types of rotating self-renewal drill bits: rack-driven, worm-driven, and ratchet-driven. This study compares and analyzes the advantages and disadvantages of these three rotary types of PDC drill bits, providing a detailed introduction to the working principles and modes of the triggering, transmission, limit and locking, and renewal structure devices of the drill bit. Relevant suggestions are proposed for the development of bottom hole self-renewal PDC drill bit technology; namely, strengthening research efforts relating to the intelligent judgment and recognition of cutting tooth wear of the drill bit, as well as the integration of multiple technologies. The sustainability of these novel bits can provide technical support for the development of single-trip drilling technology for deep formations, improve the service life of bits in deep formations that are difficult to drill, and contribute to the efficient development of deep-sea energy resources worldwide.

Perovskite Oxides for Electrocatalytic Hydrogen/Oxygen Evolution Reaction

AbstractSince the excessive exploitation of fossil fuels will cause wars for oil, developing sustainable and eco‐friendly energy resources to solve the energy crisis and realize the carbon‐neutrality goal has been a hot issue. Water electrolysis has been acknowledged as a promising technology for hydrogen (H2)/oxygen (O2) evolution reaction (HER/OER) since the overall water splitting reaction rates can be well controlled by applying appropriate electrode voltage. Whereas the sluggish electrochemical reactions kinetics on both the cathode and anode have greatly restricted the energy conversion efficiency. Thus, developing highly active electrocatalysts to reduce the overpotentials required for electrolytic HER/OER is of great significance in increasing the utilization rates of electrical power and lowering production costs. ABO3‐structured perovskite‐oxides based electrocatalysts possess the merits of low cost, high structural stability, and lattice compatibility, and thus they have attracted intense research attention in recent decays. To inspire both theoretical and experimental researchers to design novel perovskite‐oxide electrocatalysts for efficient HER/OER, the fundamental electrode reaction mechanisms, the effects of synthetic methods on material morphologies, recently reported perovskite‐oxide electrocatalysts and effective tuning strategies on enhancing the electrocatalytic activities of existing perovskite‐oxides have been fully discussed in this review.

Advances in Power and Energy Management for Distribution Systems with High Penetration of Distributed Energy Resources

This Special Issue is dedicated to exploring cutting-edge methodologies and innovative solutions pertaining to the integration of distributed energy resources (DERs) into modern distribution systems, as well as the active control and management of these evolving electrical networks [...]