Search Results (21)

Energy storage facilities serve as flexible resources that comprehensively support grid operations; they are also essential, especially when the thermal power plants that previously served as regulators run out. Electricity is becoming the dominant carrier through which the bulk of consumers’ energy needs are met. The efficiency of long-distance transmission and the ease of conversion to other forms of energy in Poland are attributed to the national grid. Thanks to the development of new technologies and distribution channels, energy is changing its supply network system. The purpose of this article is to discuss the economic viability of energy storage systems and their strategic role in the energy transition. The research methods used are data analysis, and the dependence on capital expenditures ($CAPEX$) and operating costs ($OPEX$) of energy storage in distribution channels. Energy storage facilities operated by grid companies account for 90% of the installed capacity, but there is a noticeable increase in the number of prosumer installations, with an energy storage of up to 50 KWh at microinstallations. Full article

The growing scale of offshore wind farms and increasing transmission distances has driven the demand for optimized offshore substation (OSS) configurations. This study proposes a comprehensive techno-economic framework to minimize the total lifecycle cost (LCC) of an OSS by determining the optimal number of OSSs and transformers considering wind farm capacity and transmission distance. The methodology incorporates three cost models: capital expenditure (CAPEX), operational expenditure (OPEX), and expected energy not supplied (EENS). CAPEX considers transformer costs, topside structural mass effects, and nonlinear installation costs. OPEX accounts for substation maintenance and vessel operating expenses, and EENS is calculated using transformer failure probability models and redundancy configurations. The optimization is performed through scenario-based simulations and a net present value (NPV)-based comparative analysis to determine the cost-effective configurations. The quantitative analysis demonstrates that for small- to medium-scale wind farms (500–1000 MW), configurations using 1–2 substations and 3–4 transformers achieve minimal LCC regardless of the transmission distance. In contrast, large-scale wind farms (≥1500 MW) require additional substations to mitigate transmission losses and disruption risks, particularly over long distances. These results demonstrate that OSS design should holistically balance initial investment costs, operational reliability, and supply security, providing practical insights for cost-effective planning of next-generation offshore wind projects. Full article

The increasing concern over greenhouse gas emissions, particularly CO₂, has emphasized the urgency for practical solutions to mitigate the environmental impacts of climate change. This study assessed the technical, economic, and environmental feasibility of producing dimethyl carbonate (DMC) through an integrated route using methanol derived from biomass gasification in sugarcane-based industries. Unlike previous studies that analyzed isolated aspects of DMC production, this research was conducted through process modeling and simulation in Aspen Plus^® V12.1, evaluating key performance indicators such as conversion rates, product purity, capital and operating expenses, and CO₂ emissions. A DMC conversion rate of 78.06% and a purity level of 96.80% were achieved. However, the integration of methanol production increased both CAPEX and OPEX, leading to a net present value (NPV) of R$ 36.7 million over 10 years, lower than alternative routes using commercially available methanol. Additionally, the process resulted in a net CO₂ emission of 3.41 kg CO₂ per kg of DMC, exceeding conventional methods. These findings suggest that under the evaluated conditions, process integration did not offer economic advantages, despite many environmental advantages over commercially available methanol. Full article

Energy efficiency constitutes a pivotal performance indicator for 5G New Radio (NR) networks and beyond, and achieving optimal efficiency necessitates the meticulous consideration of trade-offs against other performance parameters, including latency, throughput, connection densities, and reliability. Energy efficiency assumes it is of paramount importance for both User Equipment (UE) to achieve battery prologue and base stations to achieve savings in power and operation cost. This paper presents an exhaustive review of power-saving research conducted for 5G and beyond 5G networks in recent years, elucidating the advantages, disadvantages, and key characteristics of each technique. Reinforcement learning, heuristic algorithms, genetic algorithms, Markov Decision Processes, and the hybridization of various standard algorithms inherent to 5G and 5G NR represent a subset of the available solutions that shall undergo scrutiny. In the final chapters, this work identifies key limitations, namely, computational expense, deployment complexity, and scalability constraints, and proposes a future research direction by theoretically exploring online learning, the clustering of the network base station, and hard HO to lower the consumption of networks like 2G or 4G. In lowering carbon emissions and lowering OPEX, these three additional features could help mobile network operators achieve their targets. Full article

As natural gas-fired combined cycle (NGCC) power plants continue to constitute a crucial part of the global energy landscape, their carbon dioxide (CO₂) emissions pose a significant challenge to climate goals. This paper evaluates the feasibility of implementing post-combustion carbon capture, storage, and utilization (CCSU) technologies in NGCC power plants for end-of-pipe decarbonization in Uzbekistan. This study simulates and models a 450 MW NGCC power plant block, a first-generation, technically proven solvent—MEA-based CO₂ absorption plant—and CO₂ compression and pipeline transportation to nearby oil reservoirs to evaluate the technical, economic, and environmental aspects of CCSU integration. Parametric sensitivity analysis is employed to minimize energy consumption in the regeneration process. The economic analysis evaluates the levelized cost of electricity (LCOE) on the basis of capital expenses (CAPEX) and operational expenses (OPEX). The results indicate that CCSU integration can significantly reduce CO₂ emissions by more than 1.05 million tonnes annually at a 90% capture rate, although it impacts plant efficiency, which decreases from 55.8% to 46.8% because of the significant amount of low-pressure steam extraction for solvent regeneration at 3.97 GJ/tonne CO₂ and multi-stage CO₂ compression for pipeline transportation and subsequent storage. Moreover, the CO₂ capture, compression, and transportation costs are almost 61 USD per tonne, with an equivalent LCOE increase of approximately 45% from the base case. This paper concludes that while CCSU integration offers a promising path for the decarbonization of NGCC plants in Uzbekistan in the near- and mid-term, its implementation requires massive investments due to the large scale of these plants. Full article

In this study, real voyage data and ship specifications of a general cargo ship are employed, and it is assumed that diesel generators are replaced with hydrogen proton exchange membrane fuel cells. The effect of the replacement on CO₂, NO_X, SO_X, and PM emissions and the CII value is calculated. Emission calculations show that there is a significant reduction in emissions when hydrogen fuel cells are used instead of diesel generators on the case ship. By using hydrogen fuel cells, there is a 37.4% reduction in CO₂ emissions, 32.5% in NO_X emissions, 37.3% in SO_X emissions, and 37.4% in PM emissions. If hydrogen fuel cells are not used instead of diesel generators, the ship will receive an A rating between 2023 and 2026, a B rating in 2027, a C rating in 2028–2029, and an E rating in 2030. On the other hand, if hydrogen fuel cells are used, the ship will always remain at an A rating between 2023 and 2030. The capital expenditure (CAPEX) and operational expenditure (OPEX) of the fuel cell system are USD 1,305,720 and USD 2,470,320, respectively, for a 15-year lifetime, and the hydrogen fuel expenses are competitive at USD 260,981, while marine diesel oil (MDO) fuel expenses are USD 206,435. Full article

This paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impacting operating expenses (OPEX). An approach of BS sleep mode has been studied to reduce energy consumption, but there has been insufficient consideration for the periodic uplink transmission of industrial Internet of Things (IIoT) devices. Additionally, 5G New Reno’s synchronization signal interval limits the effectiveness of the deepest sleep mode in reducing BS energy consumption. By addressing this issue, the aim of this paper is to propose an energy-efficient multi-level sleep mode control for periodic uplink transmission to improve the energy efficiency of BSs. In advance, we develop an energy-efficient model that considers the trade-off between throughput impairment caused by increased latency and energy saving by sleep mode operation for IIoT’s periodic uplink transmission. Then, we propose an approach based on proximal policy optimization (PPO) to determine the deep sleep mode of BSs, considering throughput impairment and energy efficiency. Our simulation results verify the proposed MSC-PUT algorithm’s effectiveness in terms of throughput, energy saving, and energy efficiency. Specifically, we verify that our proposed MSC-PUT enhances energy efficiency by nearly $27.5\%$ when compared to conventional multi-level sleep operation and consumes less energy at $75.21\%$ of the energy consumed by the conventional method while incurring a throughput impairment of nearly $4.2\%$. Numerical results show that the proposed algorithm can significantly reduce the energy consumption of BSs accounting for periodic uplink transmission of IIoT devices. Full article

This work evaluates the sustainability of small-scale biorefineries as a potential enterprise alternative to be introduced in rural areas based on experimental and simulation data. Four scenarios were evaluated: the first scenario involves the production of guacamole, the second involves the production of animal feed, and the third and fourth scenarios involve the extraction of bioactive compounds and the production of avocado oil or animal feed, respectively. In addition, all scenarios produce biogas and fertilizer. Each of the scenarios were evaluated considering the technical, economic, environmental, and social aspects. As a main result, the first scenario showed the lowest operating and investment costs, as well as the lowest economic profitability (profit margin 35%). On the other hand, the third and fourth scenarios present the highest investment and operating expenses (OpEx USD 6.2 million per year and CapEx USD 1.0 million), but their profit margins are in the 60–70% range. Furthermore, a life-cycle assessment (LCA) was carried out and allows inferring that the transformer link presents the highest environmental impact of the entire value chain and that the carbon footprint for all scenarios ranges between 1.01–2.41 kg $\mathrm{C}{\mathrm{O}}_2$ eq per kg avocado. Similarly, the social impact methodology shows that the proposed scenarios do not present any social risk. Thus, the biorefinery for animal feed, bioactive compounds, biogas, and fertilizer was selected as the best option to be implemented in Caldas. Full article

In this study, we present a pre-feasibility analysis that examines the viability of implementing autonomous green hydrogen production plants in two strategic regions of Chile. With abundant renewable energy resources and growing interest in decarbonization in Chile, this study aims to provide a comprehensive financial analysis from the perspective of project initiators. The assessment includes determining the optimal sizing of an alkaline electrolyzer stack, seawater desalination system, and solar and wind renewable energy farms and the focus is on conducting a comprehensive financial analysis from the perspective of project initiators to assess project profitability using key economic indicators such as net present value (NPV). The analyses involve determining appropriate sizing of an alkaline electrolyzer stack, a seawater desalination system, and solar and wind renewable energy farms. Assuming a base case production of 1 kiloton per year of hydrogen, the capital expenditures (CAPEX) and operating expenses (OPEX) are determined. Then, the manufacturing and production costs per kilogram of green hydrogen are calculated, resulting in values of USD 3.53 kg⁻¹ (utilizing wind energy) and USD 5.29 kg⁻¹ (utilizing photovoltaic solar energy). Cash flows are established by adjusting the sale price of hydrogen to achieve a minimum expected return on investment of 4% per year, yielding minimum prices of USD 7.84 kg⁻¹ (with wind energy) and USD 11.10 kg⁻¹ (with photovoltaic solar energy). Additionally, a sensitivity analysis is conducted to assess the impact of variations in investment and operational costs. This research provides valuable insights into the financial feasibility of green hydrogen production in Chile, contributing to understanding renewable energy-based hydrogen projects and their potential economic benefits. These results can provide a reference for future investment decisions and the global development of green hydrogen production plants. Full article

During recent years, gasification technology has gained a high potential and attractiveness to convert biomass and other solid wastes into a valuable syngas for energy production or synthesis of new biofuels. The implementation of real gasification facilities implies a good insight of all expenses that are involved, namely investments required in equipment during the project and construction phases (capital expenditures, CapEx) and costs linked to the operation of the plant, or periodic maintenance interventions (operational expenditures, OpEx) or costs related to operations required for an efficient and sustainable performance of a gasification plant (e.g., feedstock pre-treatment and management of by-products). Knowledge of these economic parameters and their corresponding trends over time may help decision-makers to make adequate choices regarding the eligible technologies and to perform comparisons with other conventional scenarios. The present work aims to provide an overview on CapEx associated with gasification technologies devoted to convert biomass or solid waste sources, with a view of reducing the carbon footprint during energy generation or production of new energy carriers. In addition, an analysis of technology cost trends over time using regression methods is also presented, as well as an evaluation of specific capital investments according to the amount of output products generated for different gasification facilities. The novelty of this work is focused on an analysis of CapEx of existing gasification technologies to obtain distinct products (energy and fuels), and to determine mathematical correlations relating technology costs with time and product output. For these purposes, a survey of data and categorization of gasification plants based on the final products was made, and mathematical regression methods were used to obtain the correlations, with a statistical analysis (coefficient of determination) for validation. Specific investments on liquid biofuel production plants exhibited the highest decreasing trend over time, while electricity production became the least attractive solution. Linear correlations of specific investment versus time fitted better for electricity production plants (R² = 0.67), while those relating the product output were better for liquid biofuel plants through exponential regressions (R² = 0.65). Full article

With the limited Internet bandwidth in a given area, unlimited data plans can create congestion because there is no retribution for transmitting many packets. The real-time pricing mechanism can inform users of their Internet consumption to limit congestion during peak hours. However, implementing real-time pricing is opex-heavy from the network provider side and requires high-integrity operations to gain consumer trust. This paper aims to leverage the software-defined network to solve the opex issues and blockchain technology to solve trust issues. First, the network congestion level in a given area is analyzed. Then, the price is adjusted accordingly. Devices that send a lot of traffic during congestion will be charged more expensive bills than if transmitting traffic during an off-peak period. To prevent over-charging, the consumers can pre-configure a customized Internet profile stating how many data bytes they are willing to send during congestion. The software-defined controller also authenticates consumers and checks whether they have enough token deposits in the blockchain as Internet usage fees. We implement our work using Ethereum and POX controllers. The experiment results show that the proposed real-time pricing can be performed seamlessly, and the network provider can reap up to 72.91% more profits than existing approaches, such as usage-based pricing or time-dependent pricing. The fairness and trustability of real-time pricing is also guaranteed through the proof-of-usage mechanism and the transparency of the blockchain. Full article

Wind-waves exhibit variations both in shape and steepness, and their asymmetrical nature is a well-known feature. One of the important characteristics of the sea surface is the front-back asymmetry of wind-wave crests. The wind-wave conditions on the surface of the sea constitute a sea state, which is listed as an essential climate variable by the Global Climate Observing System and is considered a critical factor for structural safety and optimal operations of offshore oil and gas platforms. Methods such as statistical representations of sensor-based wave parameters observations and numerical modeling are used to classify sea states. However, for offshore structures such as oil and gas platforms, these methods induce high capital expenditures (CAPEX) and operating expenses (OPEX), along with extensive computational power and time requirements. To address this issue, in this paper, we propose a novel, low-cost deep learning-based sea state classification model using visual-range sea images. Firstly, a novel visual-range sea state image dataset was designed and developed for this purpose. The dataset consists of 100,800 images covering four sea states. The dataset was then benchmarked on state-of-the-art deep learning image classification models. The highest classification accuracy of 81.8% was yielded by NASNet-Mobile. Secondly, a novel sea state classification model was proposed. The model took design inspiration from GoogLeNet, which was identified as the optimal reference model for sea state classification. Systematic changes in GoogLeNet’s inception block were proposed, which resulted in an 8.5% overall classification accuracy improvement in comparison with NASNet-Mobile and a 7% improvement from the reference model (i.e., GoogLeNet). Additionally, the proposed model took 26% less training time, and its per-image classification time remains competitive. Full article

SARS-COVID-19 vaccine supply for the total worldwide population has a bottleneck in manufacturing capacity. Assessment of existing messenger ribonucleic acid (mRNA) vaccine processing shows a need for digital twins enabled by process analytical technology approaches in order to improve process transfer for manufacturing capacity multiplication, a reduction in out-of-specification batch failures, qualified personal training for faster validation and efficient operation, optimal utilization of scarce buffers and chemicals and speed-up of product release by continuous manufacturing. In this work, three manufacturing concepts for mRNA-based vaccines are evaluated: Batch, full-continuous and semi-continuous. Technical transfer from batch single-use to semi-continuous stainless-steel, i.e., plasmid deoxyribonucleic acid (pDNA) in batch and mRNA in continuous operation mode, is recommended, in order to gain: faster plant commissioning and start-up times of about 8–12 months and a rise in dose number by a factor of about 30 per year, with almost identical efforts in capital expenditures (CAPEX) and personnel resources, which are the dominant bottlenecks at the moment, at about 25% lower operating expenses (OPEX). Consumables are also reduceable by a factor of 6 as outcome of this study. Further optimization potential is seen at consequent digital twin and PAT (Process Analytical Technology) concept integration as key-enabling technologies towards autonomous operation including real-time release-testing. Full article

Demand for nickel and cobalt sulfate is expected to increase due to the rapidly growing Li-battery industry needed for the electrification of automobiles. This has led to an increase in the production of sodium sulfate as a waste effluent that needs to be processed to meet discharge guidelines. Using bipolar membrane electrodialysis (BPED), acids and bases can be effectively produced from corresponding salts found in these waste effluents. However, the efficiency and environmental sustainability of the overall BPED process depends upon several factors, including the properties of the ion exchange membranes employed, effluent type, and temperature which affects the viscosity and conductivity of feed effluent, and the overpotentials. This work focuses on the recycling of Na₂SO₄ rich waste effluent, through a feed and bleed BPED process. A high ion-exchange capacity and ionic conductivity with excellent stability up to 41 °C is observed during the proposed BPED process, with this temperature increase also leading to improved current efficiency. Five and ten repeating units were tested to determine the effect on BPED stack performance, as well as the effect of temperature and current density on the stack voltage and current efficiency. Furthermore, the concentration and maximum purity (>96.5%) of the products were determined. Using the experimental data, both the capital expense (CAPEX) and operating expense (OPEX) for a theoretical plant capacity of 100 m³ h⁻¹ of Na₂SO₄ at 110 g L⁻¹ was calculated, yielding CAPEX values of 20 M EUR, and OPEX at 14.2 M EUR/year with a payback time of 11 years, however, the payback time is sensitive to chemical and electricity prices. Full article

Hydrogen and biocarbon are important materials for the future fossil-free metallurgical industries in Sweden; thus, it is interesting to investigate the process that can simultaneously produce both. Process simulations of biomass pyrolysis coupled with steam reforming and water-gas-shift to produce H₂, biocarbon, and bio-oil are investigated in this work. The process simulation is performed based on a biomass pyrolysis plant currently operating in Sweden. Two co-production schemes are proposed: (1) production of biocarbon and H₂, and (2) production of biocarbon, H₂, and bio-oil. Sensitivity analysis is also performed to investigate the performance of the production schemes under different operating parameters. The results indicated that there are no notable differences in terms of the thermal efficiency for both cases. Varying the bio-oil condenser temperature only slightly changes the system’s thermal efficiency by less than 2%. On the other hand, an increase in biomass moisture content from 7 to 14 wt.% can decrease the system’s efficiency from 79.0% to 72.6%. Operating expenses are evaluated to elucidate the economics of 3 different cases: (1) no bio-oil production, (2) bio-oil production with the condenser at 50 °C, and (3) bio-oil production with the condenser at 130 °C. Based on operation expenses (OPEX) and revenue alone, it is found that producing more bio-oil helps improving the economics of the process. However, capital costs and the cost for post-processing of bio-oil should also be considered in the future. The estimated minimum selling price for biocarbon based on OPEX alone is approx. 10 SEK, which is within the range of the current commercial price of charcoal and coke. Full article