Energy Resources Research Articles

Damping Characteristics Improvement of Wind-PV Hybrid System by Coordinated Optimization of SVC-POD Controller Parameters

Background: With the increasing penetration of new energy resources such as wind farms and photovoltaic power plants, there is concern about the stability of power systems. Methods: Aiming at the low-frequency oscillation issue of the wind-PV hybrid system, a coordinated optimal design strategy based on Static Var Compensator (SVC) and Power Oscillation Damping (POD) control is proposed. Modal analysis is used to locate the controller, then the Whale Optimization Algorithm (WOA) is introduced to optimize the SVC-POD controller parameters. To solve the wind-PV hybrid energy system's low frequency oscillation issues, the damping ratio and angular velocity of the generator rotor are considered in the objective function. Results: Taking IEEE four-machine two-area system as an example, several working conditions are designed, including changing the power of the contact line. The eigenvalue analysis and simulation findings verify that the suggested proposed method can successfully raise the damping ratio of the system, keep the generator speed stable, and restrain the occurrence of low-frequency oscillation. Conclusion: Simulation results demonstrate that this method efficiently suppresses the lowfrequency oscillation and increases the robustness of the system.

Tidal current power in Capalulu strait, North Maluku: A feasibility study

The Indonesian government has set goals for increasing the use of renewable energy in the coming years. Currently, Indonesia relies heavily on non-renewable energy sources, which poses a threat to the environment due to the country's growing energy needs. This study aims to assess the potential for developing a tidal power plant in Capalulu Strait, North Maluku. Using hydrodynamic modelling, the study identified two potential locations at coordinates 1.877°S – 125.328°E (Capa-2) and 1.863°S – 125.323°E (Capa-4) which were selected for having median current speeds exceeding 1.8 m/s and maximum current speeds exceeding 3.5 m/s. The study tested a hypothetical implementation of KHPS Gen5 instrument(s) by Verdant Power, a 5 m diameter turbine with a rated nominal power of 37 kW and a maximum rated power of 56 kW. A power plant layout was designed to be placed at Capa-2 and Capa-4, each location accommodating 45 turbines. The development of this power plant is estimated to produce up to 22 GWh per year. Financial analysis resulted in a LCOE of IDR 5,930/kWh. However, this price is still high compared to the national electricity tariff of IDR 1,027.70/kWh. Variations in the number of turbines also may not result in a lower LCOE than the national tariff. Nevertheless, the estimated cost of generating electricity is still competitive compared to diesel, which is around IDR 5,804/kWh.

International EV policies: A comparative review of strategies in the United States and Nigeria for promoting electric vehicles

This paper provides a comprehensive comparative analysis of the strategies employed by the United States and Nigeria in promoting electric vehicles (EVs) within their respective national contexts. As the world shifts towards sustainable energy solutions, EVs have emerged as a pivotal component in reducing greenhouse gas emissions and mitigating climate change. Drawing upon a range of scholarly literature, governmental reports, and policy documents, this study examines the policy frameworks, incentives, and challenges faced by both countries in fostering the adoption of EVs. In the United States, a diverse array of federal, state, and local initiatives have been implemented to incentivize EV adoption, including tax credits, rebates, infrastructure investments, and regulatory mandates. Moreover, collaborations between the government, industry stakeholders, and research institutions have facilitated technological advancements and market growth in the EV sector. However, challenges such as range anxiety, high upfront costs, and inadequate charging infrastructure continue to impede widespread adoption. Conversely, Nigeria, while grappling with its own set of socio-economic and infrastructural challenges, has exhibited a nascent interest in promoting EVs as part of its broader sustainable development agenda. Despite lacking a comprehensive national policy framework, various initiatives such as tax exemptions, import duty waivers, and pilot projects have been introduced to stimulate EV uptake. Moreover, Nigeria's abundant renewable energy resources offer a promising opportunity for leveraging EVs to enhance energy security and reduce dependence on fossil fuels. Nevertheless, significant barriers such as limited infrastructure, affordability constraints, and institutional capacity gaps pose formidable obstacles to scaling up EV adoption in the country. By juxtaposing the experiences of the United States and Nigeria, this study contributes valuable insights into the diverse approaches and lessons learned in crafting effective international EV policies amidst varying socio-economic contexts. Through a nuanced understanding of the policy landscape, policymakers, industry stakeholders, and researchers can identify strategies for overcoming barriers and accelerating the transition towards a sustainable transportation paradigm.

Advancements in Expanded Clay Manufacturing Using "Clay-Desert Sand-Oil Sludge" Sludge Composite Materials

This study explores the development of resource-saving expanded clay technology utilizing underutilized clay raw materials and oil extraction waste. Traditional expanded clay production is energy-intensive and often employs high-quality clay; however, our research identifies technological modes and parameters for producing expanded clay through plastic molding, incorporating substandard raw materials and oil sludge. This method eliminates the need for costly energy-releasing additives and reduces energy costs associated with drying and firing by 25-30%. The research aims to demonstrate the feasibility of this novel production technique in the Republic of Kazakhstan, considering the local availability of raw materials, energy resources, and regional demand for thermal insulation materials in industrial and civil construction. Our findings suggest that integrating 'Desert Sand-Oil Sludge' into the batch composition can effectively produce granulated porous thermal insulation material, aligning with the region's development strategy and offering significant economic and environmental benefits.
 Highlights:
 
 Resource Utilization: Uses oil waste and substandard clay to produce expanded clay, reducing reliance on high-quality materials.
 Energy Savings: Cuts energy costs for production by 25-30% through innovative processing.
 Regional Benefit: Aligns with Kazakhstan's strategy by utilizing local resources and supporting construction needs.
 
 Keywords: Expanded Clay, Oil Sludge, Desert Sand

Decarbonising transportation: empirical insights into electric vehicles, carbon emissions and energy consumption

Purpose This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020. Design/methodology/approach This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients. Findings This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries. Research limitations/implications The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources. Practical implications Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources. Originality/value This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.

A Study on the Feasibility and Strategy of Developing Photovoltaic Integrated Shading Devices in Street Canyons

The measurement and analysis of the spatial attributes of the street canyon hold significant importance in the advancement of photovoltaic integrated shading devices (PVSDs). This study offers the space aspect ratio index AR(h) as a more efficient method for determining the optimal location for installing PVSDs on building facades in various street canyons. The AR(h) index addresses the limitations of the current quantitative index. This study examined the evolving regulations of indoor thermal conditions, natural lighting, and the performance of PVSDs in various street canyons. It assessed the viability of implementing PVSDs in different canyons and suggested development plans based on the variation law. The findings demonstrated that AR(h) is capable of effectively assessing and directing the implementation of PVSDs. When AR(h) is below 0.6, the shade of surrounding buildings has the least impact on the photovoltaic power output and building energy consumption in various street canyons. In this scenario, the building has the largest yearly energy-saving rate, making it highly ideal for implementing PVSDs on the building façade. In summary, the suitability of the AR(h) index in various street sceneries was assessed, offering valuable insights for the widespread implementation of PVSDs and street planning, thereby optimizing the utilization of solar energy. The findings of this study will be advantageous in diminishing the utilization of non-renewable energy sources in urban areas and mitigating carbon emissions to safeguard the environment.

An Empirical Study on Wind-solar Energy Reserve in Inner Mongolia in the Context of Carbon Neutrality

This study explores the empirical research of wind and solar energy reserves in the Inner Mongolia region within the broader context of carbon neutrality. Through detailed surveys and data analysis of wind and solar energy resources, we comprehensively assess their potential, reserves, and sustainability. Our findings reveal Inner Mongolia’s abundant wind and solar resources, pivotal in advancing carbon neutrality strategies. However, overcoming challenges such as cost, efficiency, sustainability, and grid coordination of energy storage technologies is imperative to fully leverage this potential. Therefore, this paper proposes suggestions for improvement, including technological innovation, planning optimization, and energy coordination measures. These recommendations aim to address current challenges and enhance the utilization of wind and solar resources in Inner Mongolia, providing valuable insights for future energy planning and policy formulation. This study is a guiding framework for promoting sustainable energy development in the region.

Evaluating the Perceptions of the Portuguese Population on the Economic Impacts of Biotechnology-Based Technologies

Biotechnology-based technologies have the potential to act as catalysts for economic development by fostering innovation, creating new job opportunities, stimulating industry growth, and promoting environmental sustainability. This study aims to evaluate the perceptions of the Portuguese population regarding the economic impacts of using these technologies in areas such as the environment, energy resources, agriculture, industry, and health. For this purpose, a questionnaire was developed and distributed in Portugal to a sample consisting of 559 individuals of both genders, aged between 16 and 82 years old. The findings suggest that, although there is a higher perception of the economic impact of these technologies, participants reveal difficulties in perceiving impacts on health, industry, and energy resources. Moreover, metrics for quantifying participants’ overall perception and improvement potential are provided. These metrics are particularly important as they enable the formation of participant groups with similar characteristics, facilitating the development of tailored intervention strategies. Additionally, a model based on artificial neural networks was presented to predict the perceptions of the Portuguese population regarding the economic impacts of using the mentioned technologies. The proposed model performs well, achieving accuracy rates of 93.0% for the training set and 90.9% for the test set.

Exploring the Influence of Dynamic Indicators in Urban Spaces on Residents’ Environmental Behavior: A Case Study in Shanghai Utilizing Mixed-Methods Approach and Artificial Neural Network (ANN) Modeling

The main aim of this article is to evaluate the impact of dynamic indicators associated with urban spaces on the environmental behavior of residents in Shanghai, China. With the city experiencing rapid urbanization and increasing environmental concerns, it is crucial to understand how the design and management of urban spaces can encourage pro-environmental attitudes and actions among the population. The study specifically focuses on dynamic indicators, namely vitality, accessibility, quality, and walkability, to develop a comprehensive understanding of the utilization and experience of urban spaces. The research outcomes will make valuable contributions towards Shanghai’s objectives of achieving environmental sustainability, while also providing insights that have broader relevance to sustainable urban development globally. As the built environment significantly influences energy consumption, resource utilization, pollution generation, and overall human wellbeing, attaining urban sustainability is of paramount importance. The findings of this study will aid in informing strategies and policies that promote sustainable practices, not only benefiting Shanghai but also serving as a valuable resource for urban development initiatives worldwide. Sustainable urban design principles, including compactness, density, mixed land use, greening, and walkability, have been associated with pro-environmental behaviors, including reduced reliance on automobiles, increased walking and cycling, and heightened environmental consciousness. Nevertheless, the relationship between the built environment and sustainability behaviors is intricate and is influenced by multiple factors. Consequently, further research is necessary to comprehend how specific spatial and temporal dynamics impact environmental behaviors within urban settings. In this study, an artificial neural network (ANN) was developed to estimate the quality and walkability of an area and environmental behaviors by considering the augmented vitality and accessibility factors. The ANN’s predictions demonstrate that higher levels of vitality and accessibility positively contribute to improved walkability and environmental behaviors. The accuracy of the ANN’s predictions was assessed using linear regression, which yielded acceptable error rates when compared with experimental results.

Sustainable Processes and Physico-Chemical Characterization of Artisanal Spontaneous Gluten Free Sourdough (Quinoa, Amaranth and Brown Rice) Compared to Wheat Sourdough

The industry predominantly depends on synthetic or artificial additives, occasionally permitting the inclusion of natural molecules sourced from plants or replicated from their original counterparts. The production of bakery products increasingly uses sourdough to improve the quality of bread or to obtain “clean label” products (free of artificial additives). The additive production sector contributes to this concern through the synthesis of potentially harmful compounds, the utilization of hazardous chemicals and solvents, the management of resulting by-products, and reliance on non-renewable resources for manufacturing. One percent of the world’s population suffers from celiac disease. Celiac disease is treated by excluding gluten from the diet. Most gluten-free bakery products have low nutritional and sensory quality. Therefore, sourdough is being used to replace chemical yeast to improve the sensory and nutritional quality and increase the shelf life of gluten-free bakery products. Three gluten-free sourdoughs were prepared with different flours: brown rice, quinoa and amaranth, in order to compare them with traditional sourdough (wheat) and optimize the most suitable temperature for the conservation of sourdoughs. Physicochemical analysis (pH, titratable acidity and color), antioxidant activity (FRAP, ORAC and ABTS), total phenolic compound content (Folin–Ciocalteu), total aflatoxin content, lactic and acetic acid content and microbiological analysis (mold and yeast content and bacterial and fungal composition (microbiota composition)) were carried out during the elaboration process and at different storage temperatures. A higher microbiological quantity of molds and yeasts (7.97 log CFU/mL), non-Saccharomyces yeasts (7.78 log CFU/mL) and lactic acid bacteria (8.10 log CFU/mL) and fungal composition were observed in the amaranth sourdough. The wheat sourdough obtained a higher total content of phenolic compounds (33.03 mg GAE g−1) and antioxidant capacity in ABTS and FRAP, but the quinoa sourdough had the highest ORAC content. In addition, it was observed that the adequate temperature for the conservation of the doughs is 25 °C, due to the predominance of Lactobacillus spp. and Pediococcus spp. bacteria in the sourdough. Therefore, pseudocereal sourdoughs (quinoa and amaranth) could be an alternative to incorporate into the preparation of gluten-free bread, since their microbial composition, physicochemical composition, antioxidant activity and total phenolic compounds would contribute to gluten-free bread and thus produce health benefits for people with celiac disease.

Theoretical and experimental investigations of vanadium pentoxide–based electrocatalysts for the hydrogen evolution reaction in alkaline media

AbstractA key approach towards better realization of intermittent renewable energy resources, namely, solar and wind, is green electrochemical hydrogen production from water electrolysis. In recent years, there have been increasing efforts aimed at developing noble metal-free electrocatalysts that are earth-abundant and electroactive towards hydrogen evolution reaction (HER) in alkaline electrolytes, wherein an initial water dissociation step is followed by a two-electron transfer cathodic reaction. Although relatively earth-abundant, vanadium-based electrocatalysts have been sparsely reported due to subpar electroactivity and kinetics towards water electrolysis in general and alkaline electrolysis in specific. Herein, we investigate the fine-tuning of orthorhombic V2O5-based electrocatalysts as candidates for HER through a scalable two-step sol–gel calcination procedure. Briefly, surface-induced anionic oxygen deficiencies and cationic dopants are synergistically studied experimentally and theoretically. To that end, first-principle facet-dependent density function theory (DFT) calculations were conducted and revealed that the coupling of certain dopants on V2O5 and co-induction of oxygen vacancies can enhance the catalytic HER performance by the creation of new electronic states near the Fermi level (EF), enhancing conductivity, and modulating surface binding of adsorbed protons, respectively. This was reflected experimentally through kinetically non-ideal alkaline electrochemical HER using Zn0.4V1.6O5 whereby − 194 mV of overpotential was required to attain − 10 mA/cm2 of current density, as opposed to pristine V2O5 which required 32% higher overpotential requirement at the same conditions. The disclosed work can be extended to other intrinsically sluggish transition metal (TM)–based oxides via the presented systematic tuning of surface and bulk microenvironment modulation. Graphical Abstract

Feasibility of physiotherapist-led rheumatology triage: A randomized study.

Given global shortages in the rheumatology workforce, the demand for rheumatology assessment often exceeds the capacity to provide timely access to care. Accurate triage of patient referrals is important to ensure appropriate utilization of finite resources. We assessed the feasibility of physiotherapist-led triage utilizing a standardized protocol, in identifying cases of inflammatory arthritis (IA), as compared to usual rheumatologist triage of referrals for joint pain, in a tertiary care rheumatology clinic. We performed a single-center, prospective, non-blinded, randomized, parallel-group feasibility study with referrals randomized in a 1:1 ratio to either physiotherapist-led versus usual rheumatologist triage. Standardized information was collected at referral receipt, triage, and clinic visit. Rheumatologist diagnosis was considered the gold-standard for diagnosis of IA. 102 referrals were randomized to the physiotherapist-led triage arm and 101 to the rheumatologist arm. In the physiotherapist-led arm, 65 percent of referrals triaged as urgent were confirmed to have IA versus 60 percent in the rheumatologist arm (p=0.57) suggesting similar accuracy in identifying IA. More referrals were declined in the physiotherapist-led triage arm 24 versus 8 (p=0.002) resulting in less referrals triaged as semi-urgent 6 versus 23 (p < 0.003). One case of IA (rheumatologist arm) was incorrectly triaged, resulting in significant delay in time to first assessment. Physiotherapist-led triage was feasible, appeared as reliable as rheumatologist triage of referrals for joint pain, and lead to significantly fewer patients requiring in-clinic visits.

The impact of renewable energy sources on the environment

The use of renewable energy sources is becoming a modern phenomenon that saves energy costs and protects the environment in the long term. The contribution is mapping selected energy and environmental aspects and evaluating renewable energy sources' impact on the environment. At present, energy supply is still mostly provided by sources coming from fossil or nuclear reserves. Although the concept of the "upper limit of exhaustibility" of these resources is increasingly used, there are still disagreements between experts in the field of the life expectancy of the reserves. Population growth means higher consumer demands, which also results in higher consumption of energy resources. Environmental degradation has become a global problem that requires the emphasis of recent studies. Non-renewable energy is a significant factor in environmental degradation. Therefore, policymakers have focused on supporting the production and consumption of energy from renewable sources in all economic activities to ensure a low-carbon economy.

Experimental study on ash reduction by classification flotation

ABSTRACT Poor endowment conditions, with abundant reserves of high-impurity and low- quality coal resources, characterize the coal resources in our country. As the primary source of carbon emissions, the coal industry faces a critical challenge in actively contributing to environmental protection and carbon reduction within the context of striving for carbon peak and carbon neutrality. With the widespread application of mechanized coal mining and the deteriorating geological conditions of coal resources, coal slurry particles have become increasingly fine. Additionally, a large amount of gangue minerals mixes with the coal slurry, resulting in an increase in ash content and a decrease in floatability. This places higher demands on the separation of high-ash, difficult-to-float coal slurry. This issue has become a core concern that needs to be addressed within the coal industry. This study employs a classification flotation technology to reduce ash content and improve the quality of low-quality coal slurry. The research primarily focuses on the flotation ash reduction effects of the grain size of −0.5 mm and classified grain-size coal slurry under various pulp concentrations, collector concentrations, and frother concentrations. It also analyzes the impact of a rougher and two cleaner flotation processes on the flotation efficiency. Experimental results indicate that the optimal reagent concentrations and process parameters differ for each particle size of the coal slurry. Under the best flotation conditions, the experimental results for the rougher and two cleaner flotation processes are as follows: For the grain size of −0.5 mm coal slurry, the clean coal yield is 48.40%, with an ash content of 11.02%. For the grain size of − 0.5 + 0.125 mm coal slurry, the clean coal yield is 50.53%, with an ash content of 10.72%. For the grain size of − 0.125 + 0.045 mm coal slurry, the clean coal yield is 49.56%, with an ash content of 9.24%. For the grain size of −0.045 mm coal slurry, the clean coal yield is 48.73%, with an ash content of 10.97%. Notably, the classified grain-size coal slurry exhibits higher clean coal yields and lower ash content than the grain size of −0.5 mm coal slurry, highlighting the significant importance of classification flotation for coal slurry.

Prediction of wind energy with the use of tensor‐train based higher order dynamic mode decomposition

AbstractAs the international energy market pays more and more attention to the development of clean energy, wind power is gradually attracting the attention of various countries. Wind power is a sustainable and environmentally friendly resource of energy. However, it is unstable. Therefore, it is important to develop algorithms for its prediction. In this paper, we apply a recently developed algorithm that effectively combines the tensor train decomposition with the higher order dynamic mode decomposition (TT‐HODMD). The dynamic mode decomposition (DMD) is a data‐driven technique that does not need a prior mathematical model. It is based on the measurement data or time slots. As demonstrated, for prediction it is important to use the higher order DMD (HODMD). In turn, HODMD might lead to very large scale arrays that are sparse. The tensor train decomposition provides a highly efficient way to work with such arrays. It is demonstrated that the combined TT‐HODMD algorithm is capable of providing quite accurate prediction of wind power for months ahead.

Using genetic algorithm for optimal sizing of stand-alone hybrid energy system

When planning a hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources—those that rely on fossil fuels—the primary considerations are the total cost of the system and the CO? emissions. In this paper, we will investigate the typical hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources involving a detailed simulation process that may require specific inputs, models, and data. Then, we employed dual optimization methods: genetic algorithm (GA) and particle swarm optimization (PSO). The consequences of GA and PSO execution in the bus timetabling problem depict that the GA algorithm is better at finding the optimal solution in terms of accuracy and iteration. Additionally, the GA algorithm is also superior to the straightforwardness of the techniques used. So, in this work, we employed a Genetic Algorithm Optimization (GA)–-based optimal sizing technique for HES configurations that include sustainability wind turbines (WTs), battery storage (BS), and diesel generators (DGs). HES improved power delivery to a rural community in the Wasit Province, Iraq, situated at 46° - 36° and 32° - 31° in the country's southeastern central region. Throughout the project's 25-year lifespan, the optimization primarily aims to minimize the total cost (CT) and total CO? emissions (ECO2T). The outcomes demonstrate that the GA algorithm may, with continuous electricity supply, minimize the objectives while meeting the load demand.

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed &gt; 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

The global gas transit: new supply chains

The aggravation of relations between Russia and Western countries in early 2022 has marked the formation of new supply chains for energy resources, particularly gas exports. Global energy transit is closely linked to fundamental problems in the world economy, which were aggravated during the coronavirus pandemic. Empirical evidence illustrates that new hydrocarbon supply chains have dramatically changed the balance of power in the global market. The reasons for this were the pricing policy as well as the supply and demand conditions in the market. Considering the gas market as a system of interrelated participants: producers and consumers, the study concludes that energy transit will be determined by the outcome of the economic competition between Russia and the West, as well as the speed of building the infrastructure necessary for the creation and transportation of liquefied natural gas. At the same time, the prospects for low-carbon energy are not so obvious. First of all, the high costs and the unwillingness of many countries to make significant investments hamper a transition. The study concludes that the restructuring of global energy supply chains is in the interests of some developed countries. In general, the current processes in the global energy sector represent a fundamental trend that is associated with the transition period of the world economy. The paper contributes to the knowledge by providing a comprehensive overview of the new processes in the energy sphere. 

Accounting and Monitoring System of Electricity Expenditures Based on Geospatient Data Consumers Location

The purpose of the research is considers the development and implementation of a system of accounting and monitoring of electricity costs with visualization of geospatial location data by consumers, which provides technical accounting and analysis of the structure of electricity consumption, estimation of electricity consumption for the tasks of planning production volumes and purchasing electricity from producing companies based on consumer expenditure statistics, prevention of losses associated with unauthorized electricity extraction.Methods. When creating a project and software implementation of a system for monitoring and controlling energy consumption, methods of system analysis, methods of designing software for information systems, a unified object-oriented modeling language Unified Modeling Language (UML), DBMS SQLServer, development environment Microsoft Visual Studio Code (VS Code.) were used.Results. During the project, software for a monitoring and control system for electricity consumption with visualization of geospatial data on the location of consumers was developed and implemented.Тhe project was implemented, tested and introduced into the activities of JSC АtomЕnergoSbyt when planning and accounting for electricity supplies to consumers.Тhe testing results showed that the software system fully satisfies the functional requirements, is ready for use and was demonstrated at the exhibition center.Conclusion. А system for recording energy consumption data with visualization of the territorial location of consumers has been developed in order to control consumption and payments. Тhe developed system will solve the problem of delay in receiving readings from metering devices in the data collection system. Visualization of energy resource con- sumption data by objects and their territorial location with linked personal accounts, meters and consumption volumes will allow you to quickly control the volume of supplies and energy consumers. availability of payment, which will reduce unproductive losses and unauthorized connections.For the company JSC Аtomenergosbyt, operational visualization of consumer data makes it possible to analyze the coverage of consumers by territorial basis and plan new connections.

An iterative auction-based method for multi energy trading in a microgrid considering renewable energy uncertainties

Due to the significant strides made in renewable energy generating units, they are now an appealing choice for supplying energy with various benefits. Furthermore, the aggregation of different energy generators and resources and the rise of energy conversion facilities, like combined heat and power (CHP), have paved the way for a new category of multi-energy prosumers. This research presents an innovative model for a local energy market structure consisting of an aggregator, prosumers, electricity, gas, and heat utility grids, and consumers. The interplay between these entities is handled as an auction model with proposed bidding strategies in which each player participates to maximize their own objective function. The numerical analysis reveals the impact of the pricing strategy on the prosumers' willingness to provide more energy during peak demand periods. Furthermore, the study highlights the potential for mutually beneficial collaborations between prosumers, which leads to reduced energy costs.