Microgrid Operations Planning Based on Improving the Flying Sparrow Search Algorithm

Microgrid operations planning is crucial for emerging energy microgrids to enhance the share of clean energy power generation and ensure a safe symmetry power grid among distributed natural power sources and stable functioning of the entire power system. This paper suggests a new improved version (namely, ESSA) of the sparrow search algorithm (SSA) based on an elite reverse learning strategy and firefly algorithm (FA) mutation strategy for the power microgrid optimal operations planning. Scheduling cycles of the microgrid with a distributed power source’s optimal output and total operation cost is modeled based on variables, e.g., environmental costs, electricity interaction, investment depreciation, and maintenance system, to establish grid multi-objective economic optimization. Compared with other literature methods, such as Genetic algorithm (GA), Particle swarm optimization (PSO), Firefly algorithm (FA), Bat algorithm (BA), Grey wolf optimization (GWO), and SSA show that the proposed plan offers higher performance and feasibility in solving microgrid operations planning issues.

MODERN APPROACHES TO DIAGNOSTICS AND REPAIR OF LOW-POWER SWITCHING POWER SUPPLIES

Рассмотрены вопросы оптимизации технологических процессов поиска и устранения неисправностей маломощных DC-DC преобразователей, изготавливаемых ООО «АЕДОН». Перечислены наиболее характерные неисправности, встречающиеся у импульсных источников питания малой мощности. Рассмотрены основные методы поиска и устранения неисправностей, применяемые в процессе диагностики импульсных преобразователей. Предложен подход, основывающийся на комбинировании различных методов диагностики и ремонта, позволяющий увеличить эффективность поиска и устранения неисправностей импульсных DC-DC преобразователей. Рассматриваемый подход позволил повысить оперативность технической диагностики и ремонта в условиях серийного производства, а также был эффективно использован при первоначальной подготовке молодых специалистов участка регулировки и тестирования. В качестве примера представлена процедура поиска и устранения причин повышенного напряжения холостого хода в маломощных импульсных источниках питания. Рассмотрены причины появления дефекта как в одиночных модулях, так и во всей партии. Проведено экспериментальное исследование влияния обратной связи на выходное напряжение модуля в режиме холостого хода, показано влияние возможных неисправностей. В результате применения данной процедуры в короткий срок была произведена диагностика и ремонт маломощного импульсного источника питания (ИИП), выполнена регулировка обратной связи по напряжению The article considers the issues of optimization of technological processes for troubleshooting low-power DC-DC converters manufactured by company AEDON. We listed the most typical malfunctions that occur in low-power switching power sources. We considered the main methods of troubleshooting used in the process of diagnostics of pulse converters. We propose an approach based on the combination of various diagnostic and repair methods, which allows one to increase the efficiency of troubleshooting of pulsed DC-DC converters. The considered approach allowed us to increase the efficiency of technical diagnostics and repair in the conditions of mass production, and was also effectively used in training of young specialists of the adjustment and testing subdivision. As an example, we present the procedure for finding and eliminating the causes of increased idle voltage in low-power switching power sources. We considered the reasons for the appearance of the defect both in single modules and in the entire batch. We carried out an experimental study of the effect of feedback on the output voltage of the module in the idle mode. We showed the influence of possible failures. As a result of the application of this procedure, we performed diagnostics and repair of a low-power switching power supplies in a short time and adjusted the voltage feedback

Possibilities of Powering Military Equipment Based on Renewable Energy Sources

Nowadays, the land forces of the Republic of Poland use mainly two forms of powering their equipment and military devices: by connecting various devices to the national power grid and by diesel-electric generators of individual vehicles. With the first solution, power cuts have to be taken into account. In the latter case, it is necessary to ensure large fuel deliveries on a timely manner. It entails a search for new solutions able to effectively meet the needs of an individual soldier and command posts. It has inspired engineers to work on renewable energy sources. This review paper presents a concept for photovoltaic cells usage and a concept for air turbines used to charge electric power sources of different powers for the individual needs of soldiers and command posts. Examples of solutions for mobile energy systems are presented in the research work. They were verified in terms of their suitability for military applications. The concept of using a personal device to supply power for charging batteries and elements of individual soldier equipment, including low-power radio stations, has been presented as well.

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques

Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. Computational Intelligence (CI) techniques have been recognized as effective methods in generating and optimizing renewable tools. The complexity of this variety of energy depends on its coverage of large sizes of data and parameters, which have to be investigated thoroughly. This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. The performance of the given methods in the literature is assessed by a new taxonomy. This paper focus on conducting comprehensive state-of-the-art methods heading to performance evaluation of the given techniques and discusses vital difficulties and possibilities for extensive research. Based on the results, variations in efficiency, robustness, accuracy values, and generalization capability are the most obvious difficulties for using the learning techniques. In the case of the big dataset, the effectiveness of the learning techniques is significantly better than the other computational methods. However, applying and producing hybrid learning techniques with other optimization methods to develop and optimize the construction of the techniques is optionally indicated. In all cases, hybrid learning methods have better achievement than a single method due to the fact that hybrid methods gain the benefit of two or more techniques for providing an accurate forecast. Therefore, it is suggested to utilize hybrid learning techniques in the future to deal with energy generation problems.

A Novel Model Predictive Control for Stability Improvement of Small Scaled Zero-inertia Multiple DGs Micro-grid

A zero-inertia micro-grid is a power system consisting of multiple renewable energy power sources and energy storage systems without the presence of conventional synchronous generators. In such a system, a large variation of the load or source sides during the islanded mode of operation extremely degrades the micro-grid's voltage and frequency stability. This study presents a virtual inertia-based predictive control strategy for a small-scale zero-inertia multiple distributed generators (DGs) micro-grid. In islanded mode, Voltage Model Predictive Control (VMPC) was implemented to control and maintain the voltage and frequency of the micro-grid. However, instabilities in frequency and voltage may rise at the Point of Common Coupling (PCC) due to large variations at both source and load sides. Therefore, the proposed virtual inertia loop calculates the amount of active power to be delivered or absorbed by each DG, and its effect is reflected in the estimated d current component of the VMPC, thus providing better frequency regulation. In grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. The control approach also enables the DG plug and play characteristics. The performance of the control strategy was investigated and verified using the PSCAD/EMTDC software platform.

Crosslinked Chitosan Binder for Sustainable Aqueous Batteries

The increased percentage of renewable power sources involved in energy production highlights the importance of developing systems for stationary energy storage that satisfy the requirements of safety and low costs. Na ion batteries can be suitable candidates, specifically if their components are economic and safe. This study focuses on the development of aqueous processes and binders to prepare electrodes for sodium ion cells operating in aqueous solutions. We demonstrated the feasibility of a chitosan-based binder to produce freestanding electrodes for Na ion cells, without the use of organic solvents and current collectors in electrode processing. To our knowledge, it is the first time that water-processed, freestanding electrodes are used in aqueous Na ion cells, which could also be extended to other types of aqueous batteries. This is a real breakthrough in terms of sustainability, taking into account low risks for health and environment and low costs.

Configuration design and screening of multi-mode double-planetary-gears hybrid powertrains

Hybrid powertrains with planetary gearset(PG) have been widely used. However, there are few types of powertrains in use, more powertrains have not been found. Based on the principle of organic chemistry, a design and screening method of multi-mode 2-PGs hybrid powertrain is proposed, which is divided into five stages. Firstly, powertrains are expressed in the form of molecules. Secondly, powertrains split into the libraries of PGs and power sources. The power sources can be mutually identified to construct new library. Thirdly, the mode switching rules are defined to screen power source group. Fourthly, two libraries interact with each other to promote the generation of new molecules, namely, new powertrains. And the more modes, the greater the vehicle performance potential. Powertrains are screened with mode richness theory firstly. Finally, taking the comprehensive evaluation of power performance and fuel economy as the optimal standard, powertrains are screened and evaluated twice. Through the method, hybrid powertrains with smooth mode switching, simpler structure, and optimal power and economy can be obtained.

Fatal weather-related carbon monoxide poisonings in the United States

Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the U.S. using death certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8,300 CO fatalities occurred in the U.S. during the 20-year study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities.

Electric Power Sources Based on the Seebeck Effect of Manganese Sulfides with Rare Earth Substitution

The thermoelectric properties of compounds with variable valence Mn1-ХReХS (0 ≤ X ≤ 0.2) in the temperature range of (80 – 1100) K are studied. The maxima on the temperature dependences of the Seebeck coefficient (thermal EMF) for all substitution concentrations and the change of the sign of the Seebeck coefficient from positive to negative with an increase in the substitution concentration in Mn1-XYbXS are determined. A model of impurity donor 4f-states is proposed and a satisfactory agreement with the data on the thermal EMF is obtained.

Study on Distribution Characteristics of Metro Stray Current and Evaluation of Cumulative Corrosion Effect

Stray current directly affects the regular operation of electrical equipment and facilities in the subway DC traction power supply system. Therefore, it is worthwhile to study the stray current distribution characteristics during train operation and the quantitative corrosion of buried pipelines. This paper introduces the traction characteristics of power carriages and power wheelsets of subway vehicles into the DC traction process. A finite element model considering the dynamic distribution of stray current under the actual operation of subway vehicles is established. The interference characteristics of stray current and the contribution of power sources under the multiparticle model are analyzed. The rail insulation damage caused by long service time and the quantitative calculation of rail and buried pipeline corrosion is considered. The model results show that the stray current in the buried pipeline under the multiparticle model is more accurate and more suitable for the protection in the actual subway. The quantitative corrosion of the buried pipeline is stronger than the partial insulation damage environment when the rail is not insulated. The rail and buried pipeline corrosion at both ends of the insulation damage position is relatively severe. The stray current distribution model established in this paper gives full play to the solution advantages of the finite element method and provides a new idea for the quantitative calculation of buried pipeline corrosion.