Search Results (2,115)

With increasing global pressure to decarbonize electricity systems, particularly in regions outside international carbon trading frameworks, it is essential to develop adaptive optimization tools that account for regulatory policies and system-level uncertainty. An emission-constrained power dispatch strategy based on an Adaptive Grouped Fish Migration Optimization (AGFMO) algorithm is proposed. The algorithm incorporates dynamic population grouping, a perturbation-assisted escape strategy from local optima, and a performance-feedback-driven position update rule. These enhancements improve the algorithm’s convergence reliability and global search capacity in complex constrained environments. The proposed method is implemented in Taiwan’s 345 kV transmission system, covering a decadal planning horizon (2023–2033) with scenarios involving varying load demands, wind power integration levels, and carbon tax schemes. Simulation results show that the AGFMO approach achieves greater reductions in total dispatch cost and CO₂ emissions compared with conventional swarm-based techniques, including PSO, GACO, and FMO. Embedding policy parameters directly into the optimization framework enables robustness in real-world grid settings and flexibility for future carbon taxation regimes. The model serves as decision-support tool for emission-sensitive operational planning in power markets with limited access to global carbon trading, contributing to the advanced modeling of control and optimization processes in low-carbon energy systems. Full article

To meet the demands for weight reduction and cost efficiency, the design of interior permanent magnet synchronous motors (IPMSMs) for electric vehicles is inevitably evolving toward high-speed operation, compactness, and improved efficiency. This paper proposes and analyzes a novel hybrid winding design that combines hair-pin coils and litz wire coils. The objective of this hybrid approach is to leverage the high-fill-factor advantage of hair-pin windings while mitigating the increased high-frequency copper losses caused by skin effect—an area where litz wire excels. Finite element analysis (FEA) is used to evaluate and compare the performance of the proposed hybrid stator design against conventional winding configurations, including round wire windings and pure rectangular windings. Key factors such as fill factor and skin effect are thoroughly considered in the analysis. Additionally, a system-level evaluation is conducted based on assumed electric vehicle parameters, providing a comprehensive assessment of efficiency and energy losses under real-world operating conditions. Full article

Energy storage will play an important role in the new power system with a high penetration of renewable energy due to its flexibility. Large-scale energy storage can participate in electricity market clearing, and knowing how to make more profits through bidding strategies in various types of electricity markets is crucial for encouraging its market participation. This paper considers differentiated bidding parameters for energy storage in a two-stage market with wind power integration, and transforms the market clearing process, which is represented by a two-stage bi-level model, into a single-level model using Karush–Kuhn–Tucker conditions. Nonlinear terms are addressed using binary expansion and the big-M method to facilitate the model solution. Numerical verification is conducted on the modified IEEE RTS-24 and 118-bus systems. The results show that compared to bidding as a price-taker and with marginal cost, the proposed mothod can bring a 16.73% and 13.02% increase in total market revenue, respectively. The case studies of systems with different scales verify the effectiveness and scalability of the proposed method. Full article

This study investigates the exergoeconomic performance of a milk pasteurization system powered by geothermal energy, operating across geothermal source temperatures (GSTs) ranging from 80 °C to 110 °C. The system uses geothermal heat as its primary energy source, while the cooling process is supported by a vapor compression refrigeration cycle driven by electricity generated through an Organic Rankine Cycle (ORC). The analysis was carried out in three stages: determining system parameters for each GST level, conducting detailed energy and exergy analyses, and performing an exergoeconomic evaluation using the specific exergy costing (SPECO) method. The results show that both energy and exergy efficiencies decline as GST increases. Energy efficiency varies between 88.30% and 78.53%, while exergy efficiency ranges from 72.86% to 58.02%. In parallel, unit-specific manufacturing costs increase with higher GST. Electricity production costs range from 610 to 900 USD·MWh⁻¹, and the cost of pasteurized milk varies between 3.76 and 6.53 USD·ton⁻¹. These findings offer practical insights into how geothermal source temperature affects the thermodynamic and economic performance of such systems, contributing to the broader understanding of sustainable dairy processing technologies. Full article

Blue hydrogen is a promising low-carbon alternative to conventional fossil fuels. This technology has been garnering increasing attention with many technological advances in recent years, with a particular focus on the deployed materials and process configurations aimed at minimising the cost and CO₂ emissions intensity of the process as well as maximising efficiency. However, less attention is given to the practical aspects of large-scale deployment, with the cooling requirements often being overlooked, especially across multiple locations. In particular, the literature tends to focus on CO₂ emissions intensity of blue hydrogen production processes, with other environmental impacts such as water and electrical consumption mostly considered an afterthought. Notably, there is a gap to understand the impact of cooling methods on such environmental metrics, especially with technologies at a lower technology readiness level. Herein, two cooling methods (namely, air-cooling versus water-cooling) have been assessed and cross-compared in terms of their energy impact alongside techno-economics, considering deployment across two specific locations (United Kingdom and Saudi Arabia). A sorption-enhanced steam-methane reforming (SE-SMR) coupled with chemical-looping combustion (CLC) was used as the base process. Deployment of this process in the UK yielded a levelised cost of hydrogen (LCOH) of GBP 2.94/kg H₂ with no significant difference between the prices when using air-cooling and water-cooling, despite the air-cooling approach having a higher electricity consumption. In Saudi Arabia, this process achieved a LCOH of GBP 0.70 and GBP 0.72 /kg H₂ when using air- and water-cooling, respectively, highlighting that in particularly arid regions, air-cooling is a viable approach despite its increased electrical consumption. Furthermore, based on the economic and process performance of the SE-SMR-CLC process, the policy mechanisms and financial incentives that can be implemented have been discussed to further highlight what is required from key stakeholders to ensure effective deployment of blue hydrogen production. Full article

With the rapid growth in the scale of high-percentage new energy generation, the structure of the new power system is changing. Influenced by the uncertainty and zero marginal cost characteristics of new energy, the security cost required by the power system under the high proportion of new energy access has increased dramatically. How to accurately measure the cost of the power system and assess the trend of the system cost changes and the impact on its end-user price has become critical. Accordingly, this paper creatively proposes a levelized cost of electricity (LCOE) prediction and end-user price deduction model for power systems with high renewable energy penetration. Firstly, the power system factor cost prediction model is constructed from the three dimensions of power-side, grid-side, and system operation cost. Secondly, a levelized cost of electricity prediction model is constructed based on the above model. Again, based on the analysis of the end-user price composition, the end-user price deduction model is proposed. Finally, the data of Gansu Province is selected for example analysis, and the results show that, in 2060, the power LCOE will be 0.064 USD/kWh, the system LCOE will be 0.103 USD/kWh, and the end-user price will rise to 0.1 USD/kWh. Full article

To address the increasing need for clean energy and efficient resource utilization, this paper aims to provide a cooperative framework and a fair profit allocation mechanism for integrated photovoltaic (PV) and energy storage systems that are shared among different types of users within a regional alliance, including industrial, commercial, and residential users. A cooperative game model is proposed and formulated by a two-level optimization problem: the upper level determines the optimal PV and storage capacities to maximize the alliance’s net profit, while the lower level allocates profits using an improved Nash bargaining approach based on Shapley value. The model simultaneously incorporates different real-world factors such as time-of-use electricity pricing, system life cycle cost, and load diversity. The results demonstrate that coordination between energy storage systems and PV systems can avoid 18% of solar curtailment losses. Compared to independent deployment by individual users, the cooperative sharing model increases the net present value by 8.41%, highlighting improvements in cost-effectiveness, renewable resource utilization, and operational flexibility. Users with higher demand or better load–generation matching gain greater economic returns, which can provide decision-making guidance for the government in formulating differentiated subsidy policies. Full article

Against the backdrop of global low-carbon transition, the integrated development of electricity and carbon markets demands higher efficiency in the optimal operation of virtual power plants (VPPs) and distribution networks, yet conventional trading mechanisms face limitations such as inadequate recognition of differentiated contributions and inequitable benefit allocation. To address these challenges, this paper proposes a collaborative optimal trading mechanism for VPP clusters and distribution networks in an electricity–carbon coupled market environment by first establishing a joint operation framework to systematically coordinate multi-agent interactions, then developing a bi-level optimization model where the upper level formulates peer-to-peer (P2P) trading plans for electrical energy and carbon allowances through cooperative gaming among VPPs while the lower level optimizes distribution network power flow and feeds back the electro-carbon comprehensive price (EACP). By introducing an asymmetric Nash bargaining model for fair benefit distribution and employing the Alternating Direction Method of Multipliers (ADMM) for efficient computation, case studies demonstrate that the proposed method overcomes traditional models’ shortcomings in contribution evaluation and profit allocation, achieving 2794.8 units in cost savings for VPP clusters while enhancing cooperation stability and ensuring secure, economical distribution network operation, thereby providing a universal technical pathway for the synergistic advancement of global electricity and carbon markets. Full article

This paper introduces a novel strategy for the diagnosis and fault-tolerant control (FTC) of inter-turn short-circuit (ITSC) faults in the stator windings of Doubly Fed Induction Generator (DFIG)-based wind turbines. ITSC faults are among the most common electrical issues in rotating machines: early detection is therefore essential to reduce maintenance costs and prevent severe damage to the wind turbine system. To address this, a Fault Detection and Diagnosis (FDD) approach is proposed to identify and assess the severity of ITSC faults in the stator windings. A state-space model of the DFIG under ITSC fault conditions is first developed in the (d,q) reference frame. Based on this model, an Unknown Input Observer (UIO) structured using Takagi–Sugeno (T-S) fuzzy models is designed to estimate the fault level. To mitigate the impact of the fault and ensure continued operation under degraded conditions, a T-S fuzzy fault-tolerant controller is synthesized. This controller enables natural decoupling and optimal power extraction across a wide range of rotor speed variations. Since the effectiveness of the FTC relies on accurate fault information, a Proportional-Integral Observer (PIO) is employed to estimate the ITSC fault level. The proposed diagnosis and compensation strategy is validated through simulations performed on a 3 kW wind turbine system, demonstrating its efficiency and robustness. Full article

Electric vehicle (EV) charging stations play a pivotal role in the widespread adoption and integration of electric vehicles into mainstream transportation systems. While the effects of climate change and greenhouse gases are increasing worldwide, the transition to electric vehicles is of high importance in terms of both ecological and sustainability. EV charging stations serve as the backbone of this transition, providing essential infrastructure to support the charging needs of EV owners and facilitate the transition to electric vehicles. In this study, a MINLP mathematical model is developed for the multi-objective optimization of EVCS. For implementation, Istanbul’s European side and a large-scale synthetic case are addressed considering both current demand and estimations for low, medium, and high EV numbers by the Energy Market Regulatory Authority (EMRA) for 2030 and 2035. The primary aim is to minimize station numbers, capacity, waiting time, and station idle time while meeting the demand. During the solvation of the mathematical model, both present demand and future EV usage forecasts are taken into consideration. This involves simulating different scenarios using EMRA’s 2030 and 2035 estimates and determining the optimal locations and capacities for charging stations for each demand level. Efficiencies in different scenarios were evaluated and the created mathematical model provides to optimize EV charging stations in multiple ways, there will be savings in total cost and labor force. The findings of the study will provide a valuable guide to the EV charging station infrastructure planning of the highways, regions, and urban areas to be selected in possible studies. The multi-directional optimization model addressed in this study will support decision-makers and industry experts in making informed decisions towards the sustainable and efficient development of EV charging infrastructure. Full article

The instability of the energy supply, growing demand and the need to reduce carbon emissions are priority challenges in developing countries such as Ecuador, where power outages affect productivity and generate economic losses. Therefore, solar energy is positioned as a sustainable alternative. The objective of this study is to evaluate a pilot photovoltaic (PV) system for residential housing in coastal areas in the Santa Elena province, Ecuador. The methodology included the following: (i) criteria for the selection of three representative residential housings; (ii) design of a distributed generation system using PVsyst software; and (iii) proposal of strategic guidelines for the design of PV systems. This proposed system proved to be environmentally friendly, achieving reductions of between 16.4 and 32 tonnes of CO₂ in the first 10 years. A return on investment (ROI) of 16 years was achieved for the low-demand (L) scenario, with 4 years for the medium-demand (M) scenario and 2 years for the high-demand (H) scenario. The sensitivity analysis showed that the Levelized Cost of Energy (LCOE) is more variable in the L scenario, requiring more efficient designs. It is proposed to diversify the Ecuadorian energy matrix through self-supply PV systems, which would reduce electricity costs by 6% of consumption (L scenario), 30% (M scenario), and 100% (H scenario). Although generation is concentrated during the day, the net metering scheme enables compensation for nighttime consumption without the need for batteries, thereby improving the system’s profitability. The high solar potential and high tariffs make the adoption of sustainable energy solutions a justifiable choice. Full article

This paper seeks to provide a cost benefit analysis of the implementation of a vehicle-to-grid (V2G) charging strategy relative to a smart charging (V1G) strategy from the perspective of an individual electric vehicle (EV) owner with and without solar photovoltaics (PV) located on their roof. This work utilizes a novel AC optimized power flow model (ACOPF) to produce distributed location marginal prices (DLMP) on a modified IEEE-33 node network and uses a complete set of real-world costs and benefits to perform this analysis. Costs, in the form of the addition of a bi-directional charger and the increased vehicle depreciation incurred by a V2G strategy, are calculated using modern reference sources. This produces a more true-to-life comparison of the V1G and V2G strategies from the frame of reference of EV owners, rather than system operators, with parameterization of EV penetration levels performed to look at how the choice of strategy may change over time. Counter to much of the existing literature, when the analysis is performed in this manner it is found that the benefits of implementing a V2G strategy in the U.S.—given current compensation schemes—do not outweigh the incurred costs to the vehicle owner. This result helps explain the gap in findings between the existing literature—which typically finds that a V2G strategy should be favored—and the real world, where V2G is rarely employed by EV owners. Full article

The volatility of renewable energy outputs is a well-known obstacle that has hindered the integration of more renewables in the UK’s energy mix, as the current network was not designed to handle such swings. Microgrids (MGs) may function as an effective means of integrating more renewables, particularly if they can effectively control the volatility of renewables at a smaller scale (the MG level) through a collaborative operational strategy. This paper focuses on the management of renewable energy fluctuations in MGs, proposing a pre-contract order update (COU) strategy based on the lean balancing (Heijunka) concept. The study compares the performance of collaborative and selfish MGs in terms of levelized cost of electricity (LCOE), order volatility, and carbon emissions. Two simulations models for the collaborative and selfish MGs were implemented, while considering two distinct backup generation scenarios within the MG system. The findings indicate a two-dimensional trade-off between the collaborative MG models, which are 61% more sustainable and reduce order volatility to the utility grid by 55%, and the selfish MGs, which incur lower energy consumption costs reduced by only 19%. These findings highlight the potential of collaborative MGs in enhancing grid stability and supporting broader renewable energy integration goals. Full article

This research introduces a two-stage, low-carbon industrial heating process, leveraging advanced waste heat recovery (WHR) technologies and exploiting waste heat (WH) to drive decentralised hydrogen production. This study is supported by a data-driven analysis of individual technologies, followed by 0D modelling of the integrated system for technical and feasibility assessment. Within 10 years, the EU industry will be supported by two main strategies to transition to low-carbon energy: (a) shifting from grid-mix electricity towards fully renewable sources, and (b) expanding low-carbon hydrogen infrastructure within industrial clusters. On the demand side, process heating in the industrial sector accounts for 70% of total energy consumption in industry. Almost one-fifth of the energy consumed to fulfil the process heat demand is lost as waste. The proposed heating solution is tailored for process heat in industry and stands apart from the dual-mode residential heating system (i.e., heat pump and gas boiler), as it is based on integrated and simultaneous operation to meet industry-level reliability at higher temperatures, focusing on WHR and low-carbon hydrogen. The solution uses a cascaded heating approach. Low- and medium-temperature WH are exploited to drive high-temperature heat pumps (HTHPs), followed by hydrogen burners fuelled by hydrogen generated on-site by electrolysers, which are powered by advanced WHR technologies. The results revealed that the deployment of the solution at scale could fulfil ~14% of the process heat demand in EU/UK industries by 2035. Moreover, with further availability of renewable energy sources and clean hydrogen, it could have a higher contribution to the total process heat demand as a low-carbon solution. The economic analysis estimates that adopting the combined heating solution—benefiting from the full capacity of WHR for the HTHP and on-site hydrogen production—would result in a levelised cost of heat of ~EUR 84/MWh, which is lower than that of full electrification of industrial heating in 2035. Full article

With the deepening electrification of transportation, hydrogen fuel cell electric vehicles (FCEVs) are emerging as a vital component of clean and electrified transportation systems. Nonetheless, renewable-based hydrogen production–refueling stations (HPRSs) for FCEVs still need solid models for accurate simulations and a practical capacity optimization method for cost reduction. To address this gap, this study leverages real operation data from China’s largest HPRS to establish and validate a comprehensive model integrating hydrogen production, storage, renewables, FCEVs, and the power grid. Building on this validated model, a novel capacity optimization framework is proposed, incorporating an improved Jellyfish Search Algorithm (JSA) to minimize the initial investment cost, operating cost, and levelized cost of hydrogen (LCOH). The results demonstrate the framework’s significant innovations and effectiveness: It achieves the maximum reductions of 29.31% in the initial investment, 100% in the annual operational cost, and 44.19% in LCOH while meeting FCEV demand. Simultaneously, it reduces peak grid load by up to 43.80% and enables renewable energy to cover up to 89.30% of transportation hydrogen demand. This study contributes to enhancing economic performance and optimizing the design and planning of HPRS for FCEVs, as well as promoting sustainable transportation electrification. Full article