Electrical Energy Research Articles

Smart grid deployment: from a bibliometric analysis to a survey

Smart grids are one of the last decades' innovations in electrical energy. They bring relevant advantages compared to the traditional grid and significant interest from the research community. Assessing the field's evolution is essential to propose guidelines for facing new and future smart grid challenges. In addition, knowing the main technologies involved in the deployment of smart grids (SGs) is important to highlight possible shortcomings that can be mitigated by developing new tools. This paper contributes to the research trends mentioned above by focusing on two objectives. First, a bibliometric analysis is presented to give an overview of the current research level about smart grid deployment. Second, a survey of the main technological approaches used for smart grid implementation and their contributions are highlighted. To that effect, we searched the Web of Science (WoS), and the Scopus databases. We obtained 5,663 documents from WoS and 7,215 from Scopus on smart grid implementation or deployment. With the extraction limitation in the Scopus database, 5,872 of the 7,215 documents were extracted using a multi-step process. These two datasets have been analyzed using a bibliometric tool called bibliometrix. The main outputs are presented with some recommendations for future research.

Experimental investigation of a hybrid photovoltaic-thermal energy system for hot air production

Solar energy as a non-fossil alternative energy source has become the best choice to overcome the problem of energy demand in most countries in the world. There are two different techniques to convert solar energy: photovoltaic (PV) panels to produce electricity and thermal collectors to generate heat. The two technologies can be combined to provide electrical and thermal energy either simultaneously or separately. In order to optimize the performance of a hybrid photovoltaic-thermal (PVT) solar air heater, it is necessary to collect experimental data on solar irradiation and temperature. This paper emphasized the development of a PVT energy system for hot air production in a temperature range of 50-55 °C. Additionally, experiments were constructed to monitor the information acquired from the proposed PVT solar air heater and the environment, such as hot air temperature, ambient temperature, and solar irradiation. The real-time monitoring system was set for five sample days. A microcontroller unit was used to control the hot air temperature and save the measurement data into memory. The experimental results showed that the proposed PVT solar air heater is capable of maintaining a certain level of hot air temperature throughout the day and night.

Enhancing battery system identification: nonlinear autoregressive modeling for Li-ion batteries

Precisely characterizing Li-ion batteries is essential for optimizing their performance, enhancing safety, and prolonging their lifespan across various applications, such as electric vehicles and renewable energy systems. This article introduces an innovative nonlinear methodology for system identification of a Li-ion battery, employing a nonlinear autoregressive with exogenous inputs (NARX) model. The proposed approach integrates the benefits of nonlinear modeling with the adaptability of the NARX structure, facilitating a more comprehensive representation of the intricate electrochemical processes within the battery. Experimental data collected from a Li-ion battery operating under diverse scenarios are employed to validate the effectiveness of the proposed methodology. The identified NARX model exhibits superior accuracy in predicting the battery's behavior compared to traditional linear models. This study underscores the importance of accounting for nonlinearities in battery modeling, providing insights into the intricate relationships between state-of-charge, voltage, and current under dynamic conditions.

The implementation of an optimized neural network in a hybrid system for energy management

In the face of increasing global energy demand and volatile energy prices, many countries are searching for solutions to ensure their energy independence. One of the most popular solutions is to incorporate renewable energy sources in their energy systems. While there are many advantages to integrating renewable energy sources, it is important to note that their intermittent operation can present challenges. Energy storage and smart grid management systems are key solutions to overcome these challenges and ensure sustainable, reliable use of renewable energy sources. In this article, we present an intelligent electrical energy management system for hybrid energy systems. This management system is based on a multi-layer neural network that has undergone an architecture optimization phase to improve the accuracy of real-time energy management and simplify its implementation. The management model that was built demonstrated highly good performance across a range of test circumstances.

Improving the protection system in the distribution networks integrated with photovoltaic cells by changing the ratio of X/R

Due to the increased demand for electrical energy, many countries were prompted nowadays to search for new sources. One important source is the photovoltaic energy. However, despite the great benefits of this source, some defects where observed when linking to distribution networks (negative impact on the protection system). Hence, an approach of improving the protection system in distribution networks integrated with photovoltaic cells is presented in this paper. The protection system improvement is proposed by changing the impedance to resistance ratio (X/R) values of the networks cables, which leads to increasing the overcurrent relays' response speed when a fault occurs. A comparative analysis with different cable reactance values was conducted. The electrical transient analyzer program (ETAP) software was used to investigate and validate the effects on the relay’s response times. Amriya Fallujah power station, located in Iraq, was investigated as a case study. Simulation results show that it is possible to increase the response speed of the overcurrent relay by reducing X/R of the network cables. For more validation, the distance relay was used to compare the best improvement results of changing the X/R ratio with the results of changing the type of relay, which also shows the strength of the proposed method.

Techno-economic study of a hybrid photovoltaic-diesel system for a remote area in southwest Algeria

Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.

Comprehensive evaluation of a novel pilot-scale UVA-LED photoreactor for water treatment applications: Characterization, catalytic efficiency, energy performance and economic viability

A comprehensive assessment was conducted on a novel pilot plant employing a tubular photo-reactor configuration integrated with UVA-LED technology for advanced municipal wastewater treatment applications. The plant consists of eight UVA-LED strips (150 LEDs/strip, 348–400 nm with peak emission at 370 nm) achieving a maximum irradiance of 28.1 W/m2 at 100 % power of the LED, symmetrically distributed across two borosilicate tubes. The iron concentration (0.025–0.100 mM) and UVA-LED irradiance (1.4–28.1 W/m2) combined effect on the photo-Fenton process efficiency was thoroughly examined in synthetic tap water and synthetic municipal wastewater treatment plant (MWWTP) secondary effluent using sulfamethoxazole as model microcontaminant. In general, an LED intensity threshold from which process efficiency reaches a plateau maximum value was found. The determination of the electrical energy per order (EEO) showed higher energy efficiencies as LED intensity decreases, iron concentration increases, and the water matrix is simpler. The lowest EEO obtained was 0.009 kWh/m3·order for 0.10 mM iron concentration in synthetic MWWTP secondary effluent at 5 % LED intensity. The economic study revealed that the weight of operating costs is more significant than the weight of investment costs, regardless of the selected operating conditions. Working with an iron concentration of 0.10 mM helps reduce the total costs, while operating either under excess LED intensity or insufficient LED intensity negatively impacts the total treatment cost. The lowest treatment cost (0.19 €/m3) was obtained with 0.10 mM iron concentration at only 10 % LED intensity. A comparison with the same process driven by natural solar radiation in a raceway pond reactor demonstrated the feasibility of the novel photo-reactor design in terms of treatment cost.

Advanced control scheme of doubly fed induction generator for wind turbine using second sliding mode control

This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator(DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC).Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.

Tổng hợp vật liệu LiNi0,9Mn0,05Co0,05O2 bằng phương pháp phản ứng pha rắn (NMC9.5.5-PR) ứng dụng chế tạo pin ion liti

Nickel-manganese-cobalt (NMC) transition metal oxide-based layered structural materials are evaluated a promising material for applications as cathode in lithium-ion batteries. In this study, we have successfully synthesized nickel-rich NMC material LiNi0.9Mn0.05Co0.05O2 by solid-state reaction method (NMC9.5.5- PR). The CR2032-type lithium-ion battery is also successfully fabricated from NMC material to serve the study of electrochemical properties. The NMC9.5.5-PR material exhibits outstanding discharge specific capacity when providing a maximum specific capacity of up to 212.4 mAh/g at a current density of 10 mA/g. However, the cycle efficiency survey results show that the NMC9.5.5-PR material has some disadvantages (only maintaining 81.6% of the discharge specific capacity after 50 continuous charge-discharge cycles at current density of 10 mA/g). These electrochemical properties indicate that it is necessary to further improve the cyclic efficiency of NMC9.5.5-PR material but preserving its outstanding electrical energy storage capacity. Successfully accomplishing this goal, we believe that NMC-9.5.5-PR or a material based on NMC9.5.5-PR will be one of the suitable materials to fabricate positive electrodes used in lithium-ion batteries.

Particle swarm optimization based sliding mode control for maximum power point tracking in solar PV systems

One of the most significant renewable energies is photovoltaic (PV) energy, however it has a low efficiency due to its variable maximum power point that depends on weather conditions. In order to guarantee the system's best performance, intelligent algorithms can effectively track this point in real-time utilizing the maximum power point tracking (MPPT) method. Consequently, it is crucial to maximize the use of the solar energy that has been captured as well as the PV system's generated electricity. Variations in solar irradiance affects the amount of electric energy obtained from solar arrays. For efficient extraction of electricity from solar PV systems, MPPT algorithms are required. Sliding mode control (SMC) can be used in the control of nonlinear systems. However, the effectiveness of SMC can be improved by the choice of the sliding coefficients. In this paper, optimal search using particle swarm optimization (PSO) is used in the design of the sliding manifold. Results obtained via simulations showed that MPPT tracking efficiencies obtained for the PSO based SMC and the conventional SMC are 99.65% and 96.79% respectively. That means, PSO based SMC is 2.86% better than conventional SMC.

ANALISA SISTEM ELEKTRONIK POWER STEERING UNTUK PENGEMBANGAN KENDARAAN LISTRIK FAKULTAS TEKNIK UNRAM

Recenly conventional vehicles use fossil fuels, however these fuels are non-renewable energy sources and their availability in nature is very limited. If they are explored continuously then one day they will run out, so it is very necessary to save and innovate to use these sources. Other renewable energy sources, one of which is electrical energy, where this electrical energy can be generated from various sources such as water, solar, biomass and so on. Besides that, the use of electrical energy for vehicles is currently very relevant because it is environmentally friendly, that is, it does not produce CO or CO2 gas like conventional vehicles, so this energy is known as green energy. Indonesia has the potential to produce electric cars because the availability of nickel is very abundant to be processed into batteries, as a provider or energy storage for electric cars, our country has a very big opportunity to produce electric cars. To make this happen, it is deemed necessary to carry out comprehensive studies such as power steering so that comfort and safety can be achieved. The most suitable power steering is the electric power steering (EPS) type because the energy required comes from the battery. The method applied in this research is an experimental method, by measuring torque requirements on various roads, the roads chosen are asphalt roads, block paving roads and dirt roads. Based on this data, an EPS test bench then created which was able to measure the input and output torque of the EPS and look for the power consumed by the system. Road conditions can cause differences in torque requirements, in block paving road conditions the greatest torque requirement is 2.77 Nm and the smallest occurs in asphalt road conditions at 1.62 Nm. EPS testing shows that it is only loaded up to 25% with an input torque of 1,652 Nm resulting an output torque of 3,924 Nm with an electrical power consumption of 6,31 watts.

Smart Car Parking System and Generation of Piezoelectric Energy

Abstract: In the past few years, parking has become a costly commodity in virtually every major urban region on the earth, and scarcity is a contributing factor to traffic jam and air pollution in urban areas. The most popular method to obtain a parking place is to do it manually, in which the drivers looks for a parking area either through experience or by luck. This method takes time and effort, and it may result in the worst-possible situation of not finding a parking place if vehicle is in a place with a high vehicle density. An effort is made here to park the vehicle as well as to find a parking space for the vehicle with a framework of Smart Parking System(SPS) which is based on the law of conservation of energy in we basically convert the elements from mechanical energy into electrical energy. This document Allow user to Automatically find a free site for parking at low cost without wasting much fuel and time.

Artificial Intelligence Assisted Smart Self‐Powered Cable Monitoring System Driven by Time‐Varying Electric Field Using Triboelectricity Based Cable Deforming Detection

AbstractCable monitoring is essential for the prevention of machine malfunctions as machines are operated dynamically. Traditional methods of cable monitoring, conducted through portable or fixed devices, possess the inherent limitations in real‐time damage detection and precise location identification. Herein, a self‐powered, smart cable monitoring system is proposed, utilizing a triboelectric nanogenerator (TENG) as a sensor for the cable and an electric field energy harvester (EFEH) as a power source of the system. Also, the generated electrical outputs from the EFEH are theoretically and experimentally investigated according to the EFEH‐layer numbers, and the optimal number of EFEH‐layers is determined, generating an average electrical power of 2.04 mW. Through hybridization of TENG and EFEH, a synergistic effect is confirmed, resulting in a remarkable 155% enhancement in electrical energy. Consequently, the proposed system is endowed with self‐powered wireless communication capabilities. Additionally, employing a pre‐trained long short‐term memory‐based model, the system can predict the remaining lifespan of the cable with an accuracy rate of 93.7%. Considering these results, the proposed system demonstrates significant potential for industrial cable monitoring applications in the near future.

Thermodynamic performance investigation of environmentally friendly working fluids in a geothermal integrated pumped thermal energy storage system

Abstract Among the available energy storage technologies, pumped thermal energy storage (PTES) is emerging as a potential solution for large-scale electrical energy storage with no geographical limitations and high roundtrip efficiencies. However, PTES requires a low-cost, high-temperature heat source to achieve reasonable roundtrip efficiencies. Moreover, organic Rankine cycle-based PTES systems require high-performance and environmentally friendly working fluids. In this study, the thermodynamic performance of a geothermal integrated PTES system using environmentally friendly working fluids is investigated. The mathematical model of the geothermal integrated PTES system is developed using the first and second laws of thermodynamics and implemented in Engineering Equation Solver (EES). With the developed model, the thermodynamic performance of the PTES system for different working fluids, including Butene, cyclopentane, iso-butane, R1233zd(E), R1234ze(Z), R1224yd(Z), HFO1336-mzz(Z), R365mfc, n-hexane, and n-pentane was investigated. For geothermal fluid outlet temperatures between 60°C and 120°C and geothermal fluid inlet and outlet temperature differences across the evaporator between 20°C and 60°C, the net power ratio i.e., the ratio of the electrical energy discharged to the electrical energy used to run the charging cycle, is between 0.25 and 1.40. This shows that the system has the potential to give back more than 100% of the electrical energy used during charging under certain conditions. High net power ratios are obtained for a combination of high source temperatures and low geothermal fluid inlet and outlet temperature differences.

Optimal energy scheduling for residential consumers with demand management strategies

ABSTRACT The enhancement of energy networks and cost reduction can be achieved through the implementation of solutions like optimal energy scheduling for residential consumers. This paper proposes day-ahead electrical and thermal energy scheduling for residential sections in energy networks as a bi-criteria optimization approach. The bi-criteria optimization approach is modeled to minimize the operation cost and maximize the reliability of the energy system. Demand management strategies such as demand reduction and demand shifting are considered for residential consumers. The participation of residential consumers in demand management is presented considering electricity prices in the energy markets. The solving bi-criteria optimization approach is done via the weight sum method and LINMAP procedure-based-fuzzy approach. The proposed modeling is implemented in GAMS optimization software for verifying the demand management strategies in optimal energy scheduling in two case studies.

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNCREWED UNDERWATER VEHICLES

Abstract As oceans cover over 70% of the planet's surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal, hydraulic, kinetic, and electrical, dependent on a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering float type UUVs such as the Solo II float. This reduces the cost for battery replacement and expands the float's mission time. For this purpose, we developed a model consisting of hydraulic and electrical systems, designed to provide the electrical power needed by the UUV. The hydraulic and electrical systems are implemented using MATLAB-Simulink. The model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

A two-tier bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism for coupled electricity and carbon markets

To facilitate the coupling of electricity and carbon markets, a two-layer bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism is proposed. The upper layer models the bidding strategies of renewable energy units and thermal power generating units, and the lower layer is the market clearing layer. A multi-stage offer‑carbon joint incentive clearing mechanism is proposed. In the pre-clearing stage, the environmental benefit factor of the carbon market is introduced to adjust the bidding strategy of the units, the carbon emission intensity enters the market in the form of price, the environmental benefit of the generating units is fully considered, and the carbon quota allocation model of units is established; in the second stage, carbon trading cost is added based on the pre-clearing model to further optimize the unit output; in the third stage, the clearing model with the minimum cost of electricity energy is established for tracking the clearing price. Under this mechanism, the carbon trading cost is traded on the market and unit offers are combined with carbon element to participate in market trading. Three bidding models with different clearing mechanisms are set up, and the results of the arithmetic example show that the proposed model can realize the balance between the economic and low-carbon goals of market clearing, and can achieve the maximum carbon emission reduction based on no increase in the total cost of electric-carbon coupling. As the share of renewable energy increases, the clearing price will decrease. A reasonable offer from renewable energy sources can avoid their interests being jeopardized. Concurrently, increasing the initial carbon price can effectively guide the electricity market to develop in a cleaner direction.

Enhancing Visual Comfort and Energy Efficiency in Office Lighting Using Parametric-Generative Design Approach for Interactive Kinetic Louvers

The number of desk workers who frequently conduct their jobs at home has increased dramatically during Covid-19. Work-from-home flexibility makes it attractive for workers and companies, resulting in a “Work-Style Reform” after the Covid-19 pandemic. However, the quick conversion of home spaces into workplaces cannot always sufficiently respond to users’ visual comfort and daylight performance needs which are primary contributors to occupant well-being and productivity. Therefore, this study adopts a mixed-methodology method that integrates parametric thinking, biomimetic, conceptual design, kinetic strategy and the DIVA approach to develop a real-time parametric-generative circular design for multi-objective adaptability that optimizes visual comfort and electric lighting energy efficiency for multiple occupants simultaneously. Parametric simulations of 1458 different options (five different runs per case: a total of 7290) were conducted to assess how the louvers perform regarding daylight, glare, and electric energy usage. Implementing an interactive kinetic louver greatly improved daylight performance in all orientations while simultaneously avoiding visual discomfort for multiple occupants. Furthermore, the use of this façade modification resulted in a substantial decrease in electrical lighting energy consumption, reducing the values from 14.22 to 0.2 kWh/m2/year, 8.1 to 0.18 kWh/m2/year, and 12.88 to 0.18 kWh/m2/year for South, East, and West orientations, respectively. Integrating users' lighting level preferences and the dynamic transitory sensitive area on the façade considerably reduces electric lighting consumption by around 99% compared to the ASHRAE 90.1 standard's lighting profile.

First‐Principles Investigations of Lithium Manganese Phosphate Cathode Materials: Advances and Prospects

Lithium manganese phosphate (LiMnPO4) has been considered as promising cathode material for electric vehicles and energy storage. However, its durability and capability still face challenges. The first‐principles calculations are a powerful tool to explore the fundamentals of LiMnPO4 cathode materials. Hereby, the recent advances and prospects in the application of first‐principles calculations boosting LiMnPO4 cathode material for lithium‐ion batteries are analyzed and reviewed. Based on the results from density functional theory calculation and experimental research verification, the micromechanism research progress of the influence of ion doping on the electronic conductivity, lithium‐ion diffusion, working voltage, and stability of LiMnPO4 are summarized in detail. On top of a brief outlook, further elaboration is made on the direction of continuing relevant research.

Scrap Steel Recycling: A Carbon Emission Reduction Index for China

Accurately assessing carbon emissions from recycling scrap steel is essential for reducing emissions in the steel industry, especially in China, the world’s largest crude steel producer. In this study, a carbon emission reduction index was introduced to evaluate the effectiveness of recycling scrap steel in reducing emissions. The index considers the three processes used in scrap steel recycling: blast furnace ironmaking, converter steelmaking, and electric arc furnace steelmaking. This study developed an evaluation model using fuzzy analytic hierarchy process and iterative cluster analysis to determine the reduction of carbon emission. From a life cycle perspective, this study identified primary factors contributing to emissions, including fuel, raw materials, electric energy, and auxiliary materials. Then, the carbon emission reduction index for scrap recycling was developed by examining the production of one ton of steel and each additional ton of scrap steel, which can provide valuable insights into the environmental impact of scrap recycling. Finally, the study forecasts the future Carbon Emission Reduction Index for steel scrap recycling. The study indicates an increase in the carbon emission reduction index for scrap recycling prior to 2017, followed by a decrease about 11.8% from 2017 to 2018 and increases from 2018 to 2021. Finally, it dropped by 8.7% per cent in 2022. Similarly, the carbon emission reduction index for electric furnace steelmaking increased prior to 2019, then subsequently decreased. It is changing by ten per cent a year. Additionally, the scrap recycling index experienced a significant decrease of 90% in 2015, followed by a gradual increase until 2017 and then a consistent decrease every year thereafter. The index suddenly rose in 2021 and then decreased change for policy reasons. The forecast results suggest a gradual increase in the carbon emission reduction index per ton of steel scrap in the future. In conclusion, the practicable modeling methodology has the ability to assist government organizations and private enterprises in devising efficient green and low-carbon development tactics.