Electrical Storage Research Articles

Optimization of electric charging infrastructure: integrated model for routing and charging coordination with power-aware operations

With the increasing adoption of electric vehicles (EVs), optimizing charging operations has become imperative to ensure efficient and sustainable mobility. This study proposes an optimization model for the charging and routing of electric vehicles between Origin-Destination (OD) demands. The objective is to develop an efficient and reliable charging plan that ensures the successful completion of trips while considering the limited range and charging requirements of electric vehicles. This paper presents an integrated model for optimizing electric vehicle (EV) charging operations, considering additional factors of setup time, charging time, bidding price estimation, and power availability from three sources: the electricity grid, solar energy, and wind energy. One crucial aspect addressed by the model is the estimation of bidding prices for both day-ahead and intra-day electricity markets. The model also considers the total power availability from the electricity grid, solar energy, and wind energy. The alignment of charging operations with the capacity of the grid and prevailing bidding prices is essential.This ensures that the charging process is optimized and can effectively adapt to the available grid capacity and market conditions. The utilization of renewable energies led to a 42% decrease in the electricity storage capacity available in batteries at charging stations. Furthermore, this integration leads to a substantial cost reduction of approximately 69% compared to scenarios where renewable energy is not utilized. Hence, the proposed model can design renewable energy systems based on the required electricity capacity at charging stations. These findings highlight the compelling financial advantages associated with the adoption of sustainable power sources.

Optimal scheduling of a community Multi-Energy system in energy and flexible ramp markets considering Vector-Coupling storage Devices: A hybrid Fuzzy-IGDT/Stochastic/Robust optimization framework

Community multi-energy systems (CMESs) are emerging as a pivotal solution to address the pressing issues of the current energy crisis and environmental pollution. This paper introduces a comprehensive multi-horizon risk-averse scheduling strategy for CMESs, targeting participation in energy and flexible ramp markets while meeting the demands of electric, natural gas, and hydrogen vehicle charging stations, data centers, and residential and commercial buildings. The proposed CMES incorporates power-to-x vector coupling storage (PtX-VCS) systems, enabling the storage of electricity in various forms to cater to multi-energy demands. Additionally, an integrated demand response (IDR) program, incorporating incentive and load-shifting strategies, is applied to enhance operational efficiency and system flexibility. To manage uncertainties effectively, a hybrid stochastic/robust/fuzzy information gap decision theory (IGDT) method is employed. This approach, formulated as a tri-level optimization model, is transformed into a single-level model using strong duality theory. The results demonstrate a notable reduction in daily operational costs by approximately 5% and 4% through the implementation of the IDR program and PtX-VCS technologies, respectively. Moreover, the CMES’s potential to participate in the flexible ramping market leads to an approximately 7% reduction in total operational costs.

DIGITAL FOUNDATIONS FOR BUSINESS DEVELOPMENT IN THE FIELD OF RENEWABLE ENERGY

The article focuses on specifying the digital foundations for the development of entrepreneurship in the field of alternative energy. It's proven that these technologies are a catalyst for innovation, process optimization, and the creation of new business models that contribute to the industry's sustainable development. The components that guide the digitalization of processes related to the production, distribution, storage, and sale of electricity have been identified in the following areas: intelligent energy systems, Internet of Things networks and Big data systems, digital platforms, and marketplaces. The components that adjust the digital development of each individual or company engaged in business related to the production, distribution, storage, or sale of renewable energy have been identified in the following areas: 3D printing, robotics, and blockchain technology. It has been established that the digital foundations for thе entrepreneurship development in the field of alternative energy are directed towards process optimization, increased efficiency, cost reduction, and the creation of new business models.

Maximizing renewable energy and storage integration in university campuses

The worldwide demand increase and climate change constraints are leading to integration and maximization of renewable energy sources (RESs) share in the energy production. This represents a key aspect to reduce the pollutant emissions and facilitate the transition to a cleaner future. Many agreements and incentives were discussed and imposed in order to limit the fossil fuel use and thus reducing the pollutant emissions to limit global warming. With this considerations, the renewable energy sources are installed with continuous share increase. To support this implementation and used simultaneously with providing a power reserve for these intermittent power sources, energy storage systems are becoming more and more used and necessary. Simultaneously with these changes, hydrogen is becoming more and more used, being a means by which electricity can be produced without generating greenhouse gas emissions (GGE). A power supply system with multiple sources is presented and its operation is analysed, the system contains photovoltaic panels, wind system, fuel cell, hydrogen generator, electricity and hydrogen storage system to supply the consumption of a student dormitory from a university campus in Romania with prosumer possibilities.

Space electric field impacts on softening and cell wall modification of strawberry during cold storage

As an emerging non-contact cold chain preservation technology, the impact of the DENBA+ on plant cell wall metabolism and its mechanism of inhibiting softening have not been addressed. In this study, strawberries were used as an experimental model to investigate the effect of space electric field storage on cell wall metabolism. Compared with the control, 500 V DENBA+ treatment was able to reduce the firmness loss of strawberries by 18.3 % on 18 d. Additionally, the DENBA+ exhibited a pronounced ability to suppress fruit softening enzyme (FaPG1 and FaβGal4) expression, delay the rise in polygalacturonates (PG), pectin methyl esterase (PME), cellulase (Cx), and β-galactosidase (β-Gal) activities, postpone the decline in cell wall matrix (CWM), insoluble solid pectin (ISP), and colloidal soluble pectin (CSP) content along with hemicellulose and cellulose levels while attenuating water-soluble pectin (WSP) accumulation during cold storage period. These findings contribute to the maintenance of fruit cell wall structural integrity with the aim of sustaining strawberry firmness and retarding the progression of aging.

Cost-Effective Planning of Hybrid Energy Systems Using Improved Horse Herd Optimizer and Cloud Theory under Uncertainty

In this paper, an intelligent stochastic model is recommended for the optimization of a hybrid system that encompasses wind energy sources, battery storage, combined heat and power generation, and thermal energy storage (Wind/Battery/CHP/TES), with the inclusion of electric and thermal storages through the cloud theory model. The framework aims to minimize the costs of planning, such as construction, maintenance, operation, and environmental pollution costs, to determine the best configuration of the resources and storage units to ensure efficient electricity and heat supply simultaneously. A novel meta-heuristic optimization algorithm named improved horse herd optimizer (IHHO) is applied to find the decision variables. Rosenbrock’s direct rotational technique is applied to the conventional horse herd optimizer (HHO) to improve the algorithm’s performance against premature convergence in the optimization due to the complexity of the problem, and its capability is evaluated with particle swarm optimization (PSO) and manta ray foraging optimization (MRFO) methods. Also, the cloud theory-based stochastic model is recommended for solving problems with uncertainties of system generation and demand. The obtained results are evaluated in three simulation scenarios including (1) Wind/Battery, (2) Wind/Battery/CHP, and (3) Wind/Battery/CHP/TES systems to implement the proposed methodology and evaluate its effectiveness. The results show that scenario 3 is the best configuration to meet electrical and thermal loads, with the lowest planning cost (12.98% less than scenario 1). Also, the superiority of the IHHO is proven with more accurate answers and higher convergence rates in contrast to the conventional HHO, PSO, and MRFO. Moreover, the results show that when considering the cloud theory-based stochastic model, the costs of annual planning are increased for scenarios 1 to 3 by 4.00%, 4.20%, and 3.96%, respectively, compared to the deterministic model.

Research on Influencing Factors of Cost Control of Centralized Photovoltaic Power Generation Project Based on DEMATEL-ISM

The high cost of centralized photovoltaic power generation projects is an important problem affecting industrial development, which needs to be solved urgently. It is particularly important to explore the influencing factors of cost control and the interaction between them. This paper takes a centralized photovoltaic power generation project as the research object, and determines the index system of influencing factors of cost control from the perspective of the life cycle. Secondly, the logical relationship between influencing factors is judged by the method of combining DEMATEL (decision-making trial and evaluation laboratory) and ISM (interpretive structural modelling). Finally, the multi-order recursive interpretation structure model is obtained, and the action mechanism between various factors is obtained. The results show that national policies and standards are the most profound influencing factors, and their cause degree reaches 2.155; the reason degree of market changes is the second, which is 1.586; bidding and contract management are the factors with the highest centrality, which is 7.120; and transmission and the storage of electricity and equipment repair and maintenance are the most direct factors affecting cost control. Finally, some suggestions are put forward for different types of influencing factors. The research results can better help photovoltaic power generation enterprises solve the problem of cost control.

Coordinated configuration of hybrid energy storage for electricity-hydrogen integrated energy system

This paper proposes an optimal coordinated configuration method of hybrid electricity and hydrogen storage for the electricity‑hydrogen integrated energy system (EH-ES) to promote the renewable energy source (RES) utilization and reduce the deployment cost. To simulate the practical operation of EH-ES, an energy hub framework with a discrete state space system matrix is designed to characterize the internal interconnection topology and quantify the steady-state production, storage, conversion and utilization processes of electricity and hydrogen energy carriers within EH-ES. A chronological operation simulation based electricity and hydrogen storage configuration model over a year-round time horizon is formulated to collaboratively optimize the capacity of the electrolyzer, fuel cell, battery energy storage (BES) and hydrogen storage tank. In this model, the power and capacity complementarity of BES and generalized hydrogen storage is fully exploited to compensate for power and energy imbalances, and additional capacity configuration of BES is considered to mitigate the drastic electrolytic power fluctuation. Besides, a typical source-load scenario reduction method based on K-means and ordered clustering is developed to avoid a large number of operation variables due to year-round hourly simulation. Comparative studies demonstrate that the proposed methodology can achieve the RES consumption rate of 98.873 % while the equipment investment cost can be reduced by 10.034 %.

Plasma-assisted ammonia synthesis under mild conditions for hydrogen and electricity storage: Mechanisms, pathways, and application prospects

Plasma-assisted ammonia synthesis under mild conditions for hydrogen and electricity storage: Mechanisms, pathways, and application prospects

Two-stage optimization model for day-ahead scheduling of electricity- heat microgrids with solid electric thermal storage considering heat flexibility

Traditional electricity-heat microgrid (EHM) is limited in flexibility due to real-time balancing between the supply and demand of electric and heat system. The heat flexibility (HF) can be released by thermal inertia and heat storage characteristics of district heating systems (DHS) and heat storage units, and it can be used to increase the electric power flexibility (EF) of EHM. In this paper, the quantitative relationship between HF and EF is investigated, and a two-stage optimization model for day-ahead scheduling of EHM with solid electric thermal storage (SETS) is established. Firstly, the electric-heat flexibility conversion coefficient (EHFC) is developed to decide the allocation of HF among different electricity-heat coupling units, such as CHP and SETS, and EF supply model of EHM based on HF is built. Secondly, a two-stage optimization model is proposed for day-ahead scheduling of EHM to improve EF and economy of EHM by optimizing the heating power and HF's allocation. Thirdly, the equivalent energy storage of the DHS is quantitatively analyzed, providing a reference for planning and operating of EHM's flexibility resource. Finally, the case study shows that by considering HF and deploying SETS, the total cost can be reduced by 18.8 % and 22.6 %, respectively.

Working fluid pair selection of thermally integrated pumped thermal electricity storage system for waste heat recovery and energy storage

Global issues such as the energy crisis and carbon emissions impulse the development of waste heat recovery and energy storage technologies. In most practical industrial scenarios, the electricity supply and consumption cannot be perfectly matched and effective utilization of waste heat is in urgent need. In the present study, we develop a mathematical model to evaluate the thermally integrated pumped thermal electricity storage (TI-PTES) system to achieve off-peak electricity storage along with low-grade waste heat recovery. A double-layer optimization for screening working fluid pairs with high round-trip efficiency is carried out from 24 fluids of the heat pump and 21 fluids of the Organic Rankine cycle (ORC). In the first-layer multi-objective optimization, 3 types of working fluid pair combination strategies are compared and the great improvement of round-trip efficiency by using zeotropic fluids is proved. Among 7 energy storage temperatures covering from 393.15 K to 423.15 K with an increment interval of 5 K, the highest round-trip efficiency of 101.29% is achieved by adopting the zeotropic fluid pair [90Diethyl ether_10Pentane - 80Butane_20Pentane] at 398.15 K. Furthermore, in the second-layer single-objective optimization, the thermo-economic performance indicators of TI-PTES is evaluated and compared under different designing weighting factor groups, which effectively contributes to the screening of working fluids according to designer's trade-off. Finally, through varying energy storage temperatures and designing weighting factors, optimal working fluid pair recommendations including pure fluids and zeotropic ones were proposed to the fluid selection of TI-PTES.

Modeling electrical particle thermal energy storage systems for long-duration, grid-electricity storage applications

Particle-based thermal energy storage technologies could facilitate increased penetration of variable renewable energy resources by decreasing the costs of providing dispatchable, carbon-free generation resources. However, the technology is not yet commercially available, and its performance has not been thoroughly characterized. This work creates a system modeling platform for particle-based thermal energy storage systems that can characterize performance and is transferable to emerging forms and applications of particle-based thermal energy storage. A library of key component models developed for particle-based thermal energy storage is described and benchmarked against high-fidelity models or with experimental results. A notional 135 MWe power plant employing particle thermal energy storage for grid-scale, electricity storage applications is conceived and simulated. The results show these systems can achieve greater than 50% annual round-trip efficiencies in a variety of durations, locations, dispatch schedules, and key design parameters. A 1.5% decrease in round-trip efficiency was observed when increasing storage duration from 10 to 100 h. Dispatch schedules can impact round-trip efficiency by greater than 0.5%. In regards to component design and performance, the insulation thickness of the silos and the heat exchanger approach temperature impacted performance the most. Particle-based thermal energy storage has the potential to assist in the decarbonization of not only electricity but industry and building sectors as well. This work enables the analysis of the performance of systems in these sectors and serves as a detailed technical model for design optimization in the future.

A multi-generation system with integrated solar energy, combining energy storage, cooling, heat, and hydrogen production functionalities: Mathematical model and thermo-economic analysis

Increasing the proportion of renewable energy is of paramount importance for all countries in the world. In this work, a novel multi-generation system is designed to fully utilize solar energy, which includes a photovoltaic/thermal subsystem (PV/T), an absorption refrigeration cycle (ARC), a proton-exchange membrane (PEM) electrolysis, and a promising pumped thermal electricity storage (PTES) energy storage subsystem, which can simultaneously achieve the purposes of refrigeration, hydrogen production, heat production, and energy storage. Meanwhile, the solar radiation data of Wuwei City, Gansu Province, China for the year 2022 are selected for the study. According to different seasons, the thermodynamic and thermo-economic performances of the combined power, heat and hydrogen production (CPHH) mode operated in spring, autumn, winter, and the combined power, cooling and hydrogen production (CPCH) mode operated in summer are investigated, and multi-objective optimization is conducted. The results indicate that the direct normal irradiance (DNI) of solar, the area of PV/T, the thermal storage temperature of the PTES subsystem, and the pinch point temperature difference significantly affect the total energy efficiency, total exergy efficiency, and total product unit cost of the system. The multi-objective optimization results show that the optimal solutions of total energy efficiency and total product unit cost of the system are 85.90 %, 24.25 $·GJ−1 and 86.97 %, 24.25 $·GJ−1 for the CPHH mode in spring and winter, respectively, and 88.26 % and 22.21 $·GJ−1 for the CPCH mode in summer. This work can provide a valuable reference for the research of multi-generation systems with integrated renewable energy sources.

Investigating Electricity Usage Profile for Residential Consumers in India

Electricity has become one of the essential needs in modern society. The demand and necessity for electricity have increased with population, trade, and industry, which has resulted in increased stress on the grid. As the development of an electricity storage system is costly, utilities are working on customer segmentation to classify the consumers according to their usage patterns to understand their demand and further develop resources accordingly. In this work, the K-Means clustering algorithm has been applied to a two-year monthly consumption data set (January 2019 to December 2020) of 100 residential consumers from Kutheda village Hamirpur (Himachal Pradesh, India) to visualize the diverse consumption behaviour. It resulted in four different clusters of consumers. It also showed that there is a group having a large number of consumers whose consumption is low and consumption pattern is very less flexible in different seasons. Another group of consumers with high consumption also shows high flexibility in consumption patterns, but their number is less. Also, the winter season shows the highest consumption of electricity and the monsoon season shows the lowest consumption of electricity in this particular region. This analysis will certainly help the electricity provider to make production planning for a different group of consumers in a specific season based on electricity consumption patterns.

Synthesis and characterization of Fe-doped CuO nanoparticles: Catalytic efficiency in crystal violet dye degradation and exploration of electrical properties

In recent times, environmental pollution has become a pressing issue. Different methods have been developed to detach hazardous materials from H2O bodies. Among these techniques, photo-catalysis has emerged as a low-cost and advanced method. However, finding a potent photocatalyst has been a topic of considerable research. Our study prepared CuO from copper acetate using hydrothermal treatment in an autoclave at 170 ºC for 14 hours. We introduced various quantities of Fe by adding FeSO4 mixture to Cu (CH3COO)2, following the identical method for preparing CuO. The resulting precipitate was cleaned with deionized H2O and dried at 100 °C. The prepared substance was then heated at 450 ºC in a muffle furnace for 60 minutes. We characterized the manufacture of photocatalysts utilizing various techniques such as Ultraviolet (UV), FT-IR, SEM, EDX, and XRD. Our Ultraviolet (UV) spectrum analysis helped us recognize the adsorption spectroscopic analysis of un-doped and doped CuO with various ratios of Fe. FTIR spectroscopic analysis helped us identify functional groups in CuO NPs. Our XRD study showed the monoclinic composition of copper oxide nanoparticles. The SEM picture suggested that NPs exist in a spherical shape. We studied the catalytic activity of synthesized NPs concerning crystal violet (CV) colorant degradation below a direct ray of light irradiation. Our results showed that the degradation productiveness, as compared to CV colorant, was about 93.52% in 180 min. This research is of great importance in the quest for effective and sustainable solutions to environmental problems. The examination of electrical properties highlighted the promising aspects of Fe-doped CuO, particularly at 6% doping. This variant demonstrated superior dielectric parameters, lower tangent loss, semiconductor-like impedance behavior, and enhanced electrical conductivity, emphasizing its potential for applications in electrical and energy storage domains.

A comparative well-to-wheel analysis of renewable energy pathways for hydrogen and battery electric vehicles

Renewable hydrogen and batteries are pivotal not only for promoting renewable energy adoption but also for serving as key components in electric vehicles. While multiple hydrogen-based and battery-based pathways exist for linking renewable energy to automotive powertrains, comprehensive evaluations of them are lacking, especially in the context of long-distance energy transmission in China. This study aims to fill this gap by offering an in-depth well-to-wheel (WTW) analysis of costs and CO2 emissions across various pathways. The pathways involve two energy storage mediums - hydrogen and battery, five transport options, and three automotive powertrains - Internal Combustion Engine Vehicle (ICEV), Fuel Cell Electric Vehicle (FCEV), and Battery Electric Vehicle (BEV). How the electricity price, storage duration, and transport distance influence these pathways is also examined. The results show that the battery-based pathway offers the lowest WTW cost and CO2 emissions in BEV applications. Hydrogen-based pathways are not economically feasible for ICEVs. Importantly, the indirect use of hydrogen in BEVs - H2 for power generation - outperforms its direct use in FCEVs and ICEVs in both cost and emissions. The battery-based pathway is significantly affected by storage duration and becomes less feasible for durations exceeding one day. The most cost-efficient hydrogen transport methods are identified for different transport distances and electricity prices. This research may provide valuable insights for the planning of the hydrogen industry, automotive decarbonization and renewable energy development in China.

Magnesium Transfer between Atomic Force Microscopy Probes and Metal Electrodes in Aqueous Alginate Electrolytes.

The upcoming energy transition requires not only renewable energy sources but also novel electricity storage systems such as batteries. Despite Li-ion batteries being the main storage systems, other batteries have been proposed to fulfil the requirements on safety, costs, and resource availability. Moving away from lithium, materials such as sodium, magnesium, zinc, and calcium are being considered. Water-based electrolytes are known for their improved safety, environmentally friendliness, and affordability. The key, however, is how to utilize the negative metal electrode, as using water-based electrolytes with these metals becomes an issue with respect to oxidation and/or dendrite formation. This work studied magnesium, where we aimed to determine if it can be electrochemically deposited in aqueous solutions with alginate-based additives to protect the magnesium. In order to do so, atomic force microscopy was used to research the morphological structure of magnesium deposition at the local scale by using a probe-the tip of a cantilever-as the active electrode, during charging and discharging. The second goal of using the AFM probe technology for magnesium deposition and stripping was an extension of our previous study in which we investigated, for lithium, whether it is possible to measure ion current and perform nonfaradaic impedance measurements at the local scale. The work presented here shows that this is possible in a relatively simple way because, with magnesium, no dendrite formation occurs, which hinders the stripping process.

Мodelling of Passive Coupling of Battery Units of Hybrid Energy Storage System

Due to the development of electric transport and the growth of “green” energy, electric energy storage systems (ESS) are increasingly being used in the world. The growth of the battery market in the last decade has been 20-30%. One of the ways to increase the efficiency of an electric power storage device is its hybridization, i.e. the use of heterogeneous battery units. The paper examines the features of passive coupling of lead-acid and lithium-ion batteries in a hybrid storage device. A model is presented for calculating the electrical characteristics of these units during operation. The possibility of choosing a hybrid drive structure that provides a comparable operating voltage range of the units (operation without voltage converters) is demonstrated. The modes of operation of a hybrid energy storage system are modeled both for simple parallel connection and for switching blocks according to a threshold algorithm. It is demonstrated that in order to equalize the discharge rate of the main and additional units, it is necessary to coordinate the capacity of the ESS, the degree of hybridization, the type of load and the electrical parameters of the batteries, which is impossible without modeling the system. When the threshold switching of the blocks takes place, additional control parameters, making it possible to change the discharge rate of the additional block and increase the economic efficiency of the hybrid ESS. Estimates of the economic efficiency of hybrid ESSs have been made for different values of the threshold switching voltage of the lithium-ion unit, as well as for three characteristic loads: an electric forklift truck, a 30-apartment apartment building and a 300-apartment residential complex. The results demonstrate the features and technical and economic potential of passive hybridization, can be used for the design of hybrid ESSs for small power systems with solar and wind power plants, in the calculation and design of generator – storage – consumer systems.

Development of the Polish Power Sector towards Energy Neutrality—The Scenario Approach

This article discusses three scenarios for the transformation of the Polish power system leading to the achievement of climate neutrality through investment in renewable energy sources. The scenarios differ in terms of the role played by the selected energy technologies. The scenarios were developed using the balancing tool, the Simulator Polish Power System, which analyzed the development of the national power system in terms of optimal costs of achieving climate neutrality and the lowest possible price of electricity generation. The research shows that under Polish climatic conditions, 100% RES energy can be achieved in the balance, but ensuring the continuity of energy supply, which in future will be generated mainly from this type of source, requires the participation of controllable sources such as gas-fired power plants powered by biomethane and energy storage facilities. The scenarios assume balancing RES sources with 15–25 GW of available gas sources and 40 GWh in electricity storage. The article also discusses factors limiting the suggested scenarios, such as the availability of sustainable biomethane in Poland or limitations associated with the possibility of building onshore and offshore wind turbines.

Optimization of residential energy system configurations considering the bidirectional power supply of electric vehicles and electricity interchange between two residences

Electric vehicles (EVs) combined with bidirectional home chargers (vehicle-to-home (V2H) units) and electricity interchange between residences are promising options for the self-consumption of rooftop photovoltaics (PVs) in residences. Furthermore, considering that EVs have large storage capacities, one EV + V2H might support neighborhood-scale electricity storage by electricity interchange between residences, resulting in more cost-efficient self-consumption systems. Therefore, this paper investigates how permitting electricity interchange between residences affects the economically optimal design of distributed energy systems, such as PVs, EVs and V2H units. For this purpose, a mixed-integer linear programming model is developed to optimize the configurations and operation strategies of distributed energy resources (DERs) considering electricity interchange in neighborhoods. V2H units, which supply electricity from EVs to residences, are considered DER options independent of EVs. Furthermore, the optimization results are compared under two scenarios wherein electricity interchange is and is not permitted between two residences. The results indicate that permitting electricity interchange improves the self-consumption rate of PV power while reducing investment in storage facilities. The one influencing factor is sharing one EV + V2H between two residences and effectively utilizing the available storage capacity.