As power systems globally are transitioning from fossil fuels to renewable sources, integrating energy storage becomes imperative to balance variable renewable electricity generation. The core objective of this paper is to conduct a comprehensive cost assessment of selected energy storage technologies from 2023 to 2050, focusing on the Austrian electricity market. Our method combines techno-economic assessment with the technological learning method to integrate various storage technologies into a renewable electricity system, using scenarios that account for decarbonization goals. Results indicate that pumped storage hydro exhibits none or negative learning effects, while lithium-ion batteries demonstrate significant investment cost decreases. Despite investment cost reductions, underground hydrogen storage continues to incur high total costs per kWh discharged due to low roundtrip efficiency, suggesting its future outlook depends on seasonal storage needs in fossil-free power systems. An important finding of this analysis underscores the importance of optimizing the ratio of electricity demand, renewable generation expansion and storage deployment for cost-effectiveness. Excessive storage deployment leads to lower utilization and higher costs, emphasizing the necessity of at least 1500 full-load hours for profitable operation across all storage systems. Strategic planning for optimal storage deployment is emphasized to optimize utilization and minimize costs.
Reversible protonic solid oxide cell (P-SOC) operating at intermediate-temperature exhibits excellent potential as a power generation and green hydrogen production device in fuel cell and electrolysis cell modes because of the high conversion efficiency. However, the lack of efficient air electrodes is the main challenge to obtain P-SOC with remarkable performance. Typically, air electrodes should possess high proton, oxygen ion and electron conductivity, outstanding catalytic ability for oxygen reduction reaction and H2O splitting, and also long-term durability. Recently, high entropy oxides (HEO) have become popular due to their various potential applications in terms of outstanding properties, including catalysis ability, conductivity, thermal stability, etc. HEO air electrodes have been confirmed to show good electrochemical performance in P-SOC, but the complex compositions and structure make it difficult to study HEO by traditional experimental methods. Machine learning (ML) has been regarded as a powerful tool in materials research and can solve the drawbacks in the discovery of HEO in a traditional way. In this perspective, we not only discuss the current utilization of HEO in P-SOC but also provide a possible process to use ML to guide the development of HEO.
As wind energy becomes increasingly vital in global energy strategies, optimizing wind turbine design is essential. This research focuses on the development of a 100 kW single rotor horizontal axis wind turbine (HAWT) tailored to meet the energy needs of Jamshoro, Pakistan. The turbine design leverages SolidWorks for structural modeling and is validated through comprehensive simulations using ANSYS and Q-Blade. Operating at an optimal wind speed of 6.9 m/s, the turbine achieves maximum efficiency, as indicated by the highest power factor. This efficiency translates to an estimated power output of approximately 100 kW, suitable for common household consumption. The study integrates regional climatic data and wind conditions to enhance turbine performance and durability. The findings offer a sustainable energy solution for Jamshoro, contributing to Pakistan’s renewable energy infrastructure and addressing local energy demands effectively. The focus of this study will be Jamshoro, a region in Pakistan as a case study. The software simulations will consider a variety of elements, including as wind speeds, variable loads, and environmental factors unique to the chosen region (Jamshoro). This research proposes a sustainable solution for addressing the energy demands in Jamshoro by integrating accurate data based on software analysis with real-world concerns, adding to the larger goal of developing sustainable sources of energy in Pakistan.
This paper investigates the potential benefits of a bidirectional multi-port power electronic transformer (MPPET) to interface multiple microgrids with utility distribution networks in terms of power quality and stability. The main concept is based on the interaction between the utility grid, the connected microgrids, and the MPPET in controlling the disturbances that lead to grid instability and power quality issues. The proposed MPPET does not require any serious communication infrastructure for operation. In addition, the MPPET can respond to reverse power flow caused by excess power generation on the grid. Due to the intermittent nature of the renewable energy sources and the different stages involved in the design of the proposed MPPET, the system is liable to internal DC voltage fluctuation, causing grid instability; thus, an energy storage system (ESS) is incorporated to avert the challenges. The networks under investigation and the proposed MPPET are designed and simulated using MATLAB and Simulink software. The electrical isolation capability of the proposed bidirectional MPPET is verified through simulation. Several case studies have been carried out to evaluate the behavior of the system under different operating conditions and to check the feasibility of MPPET for power quality improvements. It was observed that the MPPET is proficient in regulating power quality issues, thus enhancing grid stability. It is also varied that the proposed MPPET prevents the escalation of the impact of faults or disturbances all over the grid. At the same time, it is verified that the proposed bidirectional energy storage systems enhance energy transfer between the utility grid and microgrids, which improves the system’s stability.
Oil-based drilling cuttings is a pollutive nearly-solid waste produced in oil exploitation that has to be treated for meeting clean production requirement of oil and gas exploration. A two-layer screw-driving spiral heat exchanger was thus proposed for this purpose. To investigate its effectiveness and performance, a 10-component n-decane one-step product proportional distribution chemical model was used to describe oil-based drilling cuttings pyrolysis process, and numerical simulations were carried out of forced convection inside the heat exchanger with a full consideration of pyrolysis and evaporation effects. The influences of rotation speed, screw pitch and cross-sectional shape of spiral tube on pyrolysis, flow, and heat mass transfer characteristics were studied. The results show that the heat absorbed needed for evaporation is much less than that for pyrolysis, and the heat transfer coefficient with consideration of evaporation and pyrolysis is almost two times greater than that without. The pyrolysis rate increases first, and then decreases once the temperature is higher than 838 K due to the coupled effects of temperature and reactant concentration change. The velocity, heat transfer coefficient and conversion ratio of oil-based drilling cuttings all increase with rotation speed, but the conversion ratio increase becomes slower and slower once the rotation speed exceeds 0.2 rad·s−1. The average vorticity and flow resistance of oil-based drilling cuttings both decrease with screw pitch monotonously, while heat transfer coefficient increases first and then decreases because of the opposite effects of centrifugal force and thermal entrance length. Reducing screw pitch can increase conversion ratio, but once screw pitch is smaller than 800 mm, the conversion ratio approaches to a constant. Cross-sectional shape of spiral tube also affects pyrolysis performance, and circular cross-sectional spiral tube seems to be the best.
Clean energy applications often involve systems with technological process monitoring. This supervision aims to optimize operation, in particular efficiency, performance and compatibility with dedicated criteria. Most of these energy systems involve complex procedures. A complex procedure is an arrangement of compound processes interacting in interdependent behaviors. The supervision of these complex procedures focuses on the interaction of compound processes, their digital coupling and the handling of uncertainties in their detection and digital tools. Real-virtual pairs, such as digital twins, could carry out such surveillance. This commentary aims to analyze and illustrate such supervision in clean electromagnetic energy systems based on a review of the literature. The notion of complexity and the interactions of the compound processes involved are first addressed and detailed. The modeling of these interactions is presented through the mathematical coupling of the electromagnetic equations with other equations of the phenomena involved. These phenomena are linked to the functional or environmental behaviors of the systems. Compound process monitoring in complex procedures is then analyzed taking into account threats, unsolicited external events and uncertainties related to the sensing and digital tools involved. This contribution illustrated several points relating to, the relationship between the complexities of a real energy procedure and its coupled virtual model, the dependence of the model reduction strategy on each specific application and the reduction of uncertainties through the matching of real-virtual pairs. The different analyses are supported by literature references permitting more information when necessary.
Seawater desalination plays a vital role in addressing the increasing global demand for freshwater. However, the energy-intensive nature of desalination processes and the generation of brine by-products pose environmental challenges. In Western Australia (WA), approximately 48% of freshwater is supplied by two seawater desalination plants employing the energy-intensive seawater reverse osmosis (SWRO) method. These plants are powered by a combination of renewable and conventional energy sources. Typically, the most efficient approach for desalination plants involves a blend of renewable energy sources. Salinity gradient energy (SGE) harnessed through the reverse electrodialysis (RED) system, which derives energy from mixing waters with varying salinities, has emerged as a potential solution. RED utilizes ion-exchange membranes to convert the chemical potential difference between two solutions into electric power. The net specific energy of SGE, calculated based on the Gibbs free energy associated with mixing seawater and wastewater, is estimated at approximately 0.14 kWh per cubic metre of brine for SWRO desalination plants. The combined SGE potential of WA’s two desalination facilities theoretically amounts to approximately 87.4 MWh of energy. However, due to the inherent limitations of the RED system’s current energy efficiency, only about 2.5% of the desalination plant’s energy requirements can be met through this technique. This paper addresses a significant gap in the literature by analyzing the technical and economic constraints of utilizing salinity gradient energy (SGE) through the reverse electrodialysis (RED) system for seawater desalination plants. This marks the first examination of its kind, shedding light on both the technical feasibility and economic challenges of SGE-RED application in this context. The scientific contribution lies in its innovative approach, integrating technical and economic perspectives to provide an understanding of SGE-RED technology’s potential drawbacks and opportunities. By identifying and tackling these challenges, this paper aims to pave the way for optimizing SGE-RED systems for practical implementation in seawater desalination plants.
Holistic decarbonisation requires collaborative efforts and substantial investments across diverse economic sectors. This study introduces an innovative national approach, blending technological insights and philosophical considerations to shape decarbonization policies and practices. Libya is the case study. The proposed framework involves submersible power stations with continuous-duty helium closed-cycle gas turbines to supply electricity demand and hydrogen. Extensive national data is analysed, incorporating factors such as sectoral consumption, sea temperature, and port locations. An analytical model is developed, providing a valuable foundation for realistic decarbonization scenarios. The model aims to maintain the benefits of current energy consumption, assuming a 2% growth rate, while assessing changes in a fully green economy. The results offer qualitative and quantitative insights on hydrogen use and an expected rise in electricity demand. Two scenarios are examined: self-sufficiency and replacing oil exports with hydrogen exports. This study provides a quantitative perspective on decarbonization, focusing on a submersible helium closed cycle gas turbine concept resistant to natural disasters and proliferation. Findings underscore the substantial changes and investments needed for this transition, identifying primary needs of 27 GW or 129 GW for self-sufficiency and exports, respectively. This foundational analysis marks the start of research, investment, and political agendas toward decarbonization.
Solar energy, as a clean source of energy, plays a relevant role in this much desired (r)evolution. When talking about photovoltaics, despite the multiple studies on parameters that affect the panels operation, concrete knowledge on this matter is still in an incipient stage and precise data remains dispersed, given the mutability of outer factors beyond technology-related properties, hence the difficulties associated with exploration. Wind is one of them. Wind loads can affect the temperature of photovoltaics, whose efficiency is reduced when higher temperatures are reached. The viability of wind as natural cooling mechanism for solar plants and its influence on their electrical energy production is studied in this research work. Some appropriate results were achieved: depending on the module temperature prediction model used and on the photovoltaic technology in question, solar panels are foreseen to be up to approximately 3% more productive for average wind speeds and up to almost 7% more productive for higher speeds. Taking into consideration that wind speed values were collected in the close vicinity of the modules, these results can be proven to be even higher. That being said, this article contributes with accurate insights about wind influence on electrical energy production of solar plants.
This paper focuses a novel non-isolated coupled inductor based DC-DC converter with excessive VG (voltage gain) is analyzed with a state-space modeling technique. It builds up of using three diodes, three capacitors, an inductor and CI (coupled inductor). The main switch S is turn on due to body diode and voltage stress is reduced at the switch S by using diode D1 and Capacitor C1. This paper focuses on design modelling, mathematical calculations and operation principle of DC-DC converter is discussed with state-space modelling technique. The performance has been presented for two different voltages for EV applications, i.e., 12 V, 48 V as input voltages with a high step-up outputs of 66 V and 831.7 V respectively. The converter stability is studied and determined the bode plot along with simulation performance results which are carried out using MATLAB R2022B.
