Search Results (155)

To fully accommodate renewable and derivative energy sources in mine energy systems under supply and demand uncertainties, this paper proposes an optimized electricity–heat scheduling method for mining areas that incorporates Power-to-Gas (P2G) technology and Conditional Value-at-Risk (CVaR). First, to address uncertainties on both the supply and demand sides, a P2G unit is introduced, and a Latin hypercube sampling technique based on Cholesky decomposition is employed to generate wind–solar-load sample matrices that capture source–load correlations, which are subsequently used to construct representative scenarios. Second, a stochastic optimization scheduling model is developed for the mine electricity–heat energy system, aiming to minimize the total scheduling cost comprising day-ahead scheduling cost, expected reserve adjustment cost, and CVaR. Finally, a case study on a typical mine electricity–heat energy system is conducted to validate the effectiveness of the proposed method in terms of operational cost reduction and system reliability. The results demonstrate a 1.4% reduction in the total operating cost, achieving a balance between economic efficiency and system security. Full article

In the context of achieving low-carbon goals, building low-carbon energy systems is a crucial development direction and implementation pathway. Renewable energy is favored because of its clean characteristics, but the access may have an impact on the power grid. Microgrid technology provides an effective solution to this problem. Uncertainty exists in single microgrids, so multiple microgrids are introduced to improve system stability and robustness. Electric carbon trading and profit redistribution among multiple microgrids have been challenges. To promote energy commensurability among microgrids, expand the types of energy interactions, and improve the utilization rate of renewable energy, this paper proposes a cooperative operation optimization model of multi-microgrids based on the green certificate and carbon trading mechanism to promote local energy consumption and a low carbon economy. First, this paper introduces a carbon capture system (CCS) and power-to-gas (P2G) device in the microgrid and constructs a cogeneration operation model coupled with a power-to-gas carbon capture system. On this basis, a low-carbon operation model for multi-energy microgrids is proposed by combining the local carbon trading market, the stepped carbon trading mechanism, and the green certificate trading mechanism. Secondly, this paper establishes a cooperative game model for multiple microgrid electricity carbon trading based on the Nash negotiation theory after constructing the single microgrid model. Finally, the ADMM method and the asymmetric energy mapping contribution function are used for the solution. The case study uses a typical 24 h period as an example for the calculation. Case study analysis shows that, compared with the independent operation mode of microgrids, the total benefits of the entire system increased by 38,296.1 yuan and carbon emissions were reduced by 30,535 kg through the coordinated operation of electricity–carbon coupling. The arithmetic example verifies that the method proposed in this paper can effectively improve the economic benefits of each microgrid and reduce carbon emissions. Full article

Intermediate-band photovoltaics promise single-junction efficiencies that exceed the Shockley and Queisser limit, yet viable material platforms and device geometries remain under debate. Here, we perform comprehensive two-dimensional device-scale simulations using Silvaco Atlas TCAD to analyze p-i-n In_0.20Ga_0.80N solar cells in which the intermediate band is supplied by In_0.35Ga_0.65N quantum dots located inside the intrinsic layer. Quantum-dot diameters from 1 nm to 10 nm and areal densities up to 116 dots per period are evaluated under AM 1.5G, one-sun illumination at 300 K. The baseline pn junction achieves a simulated power-conversion efficiency of 33.9%. The incorporation of a single 1 nm quantum-dot layer dramatically increases efficiency to 48.1%, driven by a 35% enhancement in short-circuit current density while maintaining open-circuit voltage stability. Further increases in dot density continue to boost current but with diminishing benefit; the highest efficiency recorded, 49.4% at 116 dots, is only 1.4 percentage points above the 40-dot configuration. The improvements originate from two-step sub-band-gap absorption mediated by the quantum dots and from enhanced carrier collection in a widened depletion region. These results define a practical design window centred on approximately 1 nm dots and about 40 dots per period, balancing substantial efficiency gains with manageable structural complexity and providing concrete targets for epitaxial implementation. Full article

In the context of the dual-carbon goals, this study proposes a cooperative game-theoretic optimization strategy to enhance the energy utilization efficiency, operational efficiency, and cost-effectiveness of integrated energy systems (IESs) while simultaneously reducing carbon emissions, improving operational flexibility, and mitigating renewable energy variability. To achieve these goals, an IES framework integrating power-to-gas (P2G) technology and carbon capture and storage (CCS) facilities is established to regulate carbon emissions. The system incorporates P2G conversion units and thermal components—specifically, hydrogen fuel cells, electrolyzers, reactors, and electric boilers—aiming to maximize energy conversion efficiency and asset utilization. A cooperative game-theoretic optimization model is developed to facilitate collaboration among multiple stakeholders within the coalition, which employs the Shapley value method to ensure equitable distribution of the cooperative surplus, thereby maximizing collective benefits. The model is solved using an improved gray wolf optimizer (IGWO). The simulation results demonstrate that the proposed strategy effectively coordinates multi-IES scheduling, significantly reduces carbon emissions, facilitates the efficient allocation of cooperation gains, and maximizes overall system utility. Full article

To reduce carbon emission levels and improve the low-carbon performance and economic efficiency of Integrated Energy Systems (IESs), this paper introduces oxy-fuel combustion technology to transform traditional units and proposes a low-carbon economic dispatch method. Considering the stepwise carbon trading mechanism, it provides new ideas for promoting energy conservation, emission reduction, and economic operation of integrated energy systems from both technical and policy perspectives. Firstly, the basic principles and energy flow characteristics of oxy-fuel combustion technology are studied, and a model including an air separation unit, an oxygen storage tank, and carbon capture equipment is constructed. Secondly, a two-stage power-to-gas (P2G) model is established to build a joint operation framework for oxy-fuel combustion and P2G. On this basis, a stepwise carbon trading mechanism is introduced to further constrain the carbon emissions of the system, and a low-carbon economic dispatch model with the objective of minimizing the total system operation cost is established. Finally, multiple scenarios are set up for simulation analysis, which verifies that the proposed low-carbon economic optimal dispatch strategy can effectively reduce the system operation cost by approximately 21.4% and improve the system’s carbon emission level with a total carbon emission reduction of about 38.3%. Meanwhile, the introduction of the stepwise carbon trading mechanism reduces the total cost by 12.3% and carbon emissions by 2010.19 tons, increasing the carbon trading revenue. Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article

To investigate the effect of ultrasound on the quality of pumpkin juice fermented by yeast, ultrasound (power range 0–400 W, duration 10 min) was used to assist the yeast fermentation of pumpkin juice. The effects of ultrasound-assisted fermentation at different powers on the quality characteristics of pumpkin juice, such as the color, aroma components, carotenoid content, and antioxidant activity, were studied. The optimal combination of fermentation process parameters was determined as follows: a pumpkin juice content of 20 mL, fermentation temperature of 30 °C, fermentation time of 1 day, and inoculation amount of 3% (the mass-to-volume ratio of yeast to water). The results showed that after ultrasound treatment, the physicochemical properties of pumpkin juice, including the Vitamin C (VC) content, carotenoid content, and antioxidant activity, did not change significantly (p > 0.05), while the total acid content decreased significantly, indicating that ultrasound treatment was beneficial for improving the sensory properties of pumpkin juice after yeast fermentation. Notably, when the ultrasound power was 100 W, the flavonoid content in pumpkin juice reached the highest level (1.27 mg/100 g). A total of 127 volatile substances were identified via gas chromatography, among which 14 were characteristic aroma profiles of pumpkin juice, suggesting that ultrasound (US) treatment had little impact on the natural flavor of pumpkin juice. Cavitation caused cell rupture in pumpkin juice, and ultrasound treatment significantly improved the sterilization rate of yeast-fermented pumpkin juice and was extremely effective in maintaining its color. This study provides a theoretical basis for the development of high-quality and nutrient-rich fermented pumpkin juice. Full article

Multi-energy systems (MESs) are designed to convert, store, and distribute energy to diverse end-users, including those in the industrial, commercial, residential, and agricultural sectors. This study proposes an integrated optimal planning optimization model for the techno-economic assessment of an MES integrated with power-to-gas (P2G) to meet electricity, heating, and cooling requirements while enabling sustainable energy solutions. The goal of the system optimal planning is to appropriately size the MES components to minimize the total planning costs. This includes not only the investment and operation costs but also the emissions cost and the cost of energy not supplied (ENS). The study implements P2G, electricity demand response (E-DRP), and thermal demand response (T-DRP), with four distinct operational scenarios considered for optimal planning, to evaluate the benefits of adopting MESs. A comprehensive validation study is presented based on a case study farm in Nigeria, with an MES investment model developed to assess feasibility. The results show that the integration of P2G with E-DRP and T-DRP gives the best operational scenario and planning cost for this farming application integration, leading to potential savings of up to USD 2.77 million annually from the proposed MES adoption. Full article

This study proposes an improved multi-objective black-winged kite algorithm (MOBKA-QL) integrating Q-learning with adaptive mutation strategies for optimizing multi-objective scheduling in integrated energy systems (IES). The algorithm dynamically selects mutation strategies through Q-learning to enhance solution diversity and accelerate convergence. First, an optimal scheduling model is established, incorporating a carbon capture system (CCS), power-to-gas (P2G), solar thermal, wind power, and energy storage to minimize economic costs and carbon emissions while maximizing energy efficiency. Second, the heat-to-power ratio of the cogeneration system is dynamically adjusted according to load demand, enabling flexible control of combined heat and power (CHP) output. The integration of CCS+P2G further reduces carbon emissions and wind curtailment, with the produced methane utilized in boilers and cogeneration systems. Hydrogen fuel cells (HFCs) are employed to mitigate cascading energy losses. Using forecasted load and renewable energy data from a specific region, dispatch experiments demonstrate that the proposed system reduces economic costs and CO₂ emissions by 14.63% and 13.9%, respectively, while improving energy efficiency by 28.84%. Additionally, the adjustable heat-to-power ratio of CHP yields synergistic economic, energy, and environmental benefits. Full article

This paper presents a highly linear two-stage InGaP/GaAs power amplifier integrated circuit (PAIC) using a dynamic predistorter for 5G small-cell applications. The proposed predistorter, based on a diode-connected transistor, utilizes a supply voltage to accurately control the linearization characteristics by adjusting its dc current. It is connected in parallel with an inter-stage of the two-stage PAIC through a series configuration of a resistor and an inductor, and features a shunt capacitor at the base of the transistor. These passive components have been optimized to enhance the linearization performance by managing the RF signal’s coupling to the diode. Using these optimized components, the AM−AM and AM−PM nonlinearities arising from the nonlinear resistance and capacitance in the diode can be effectively used to significantly flatten the AM−AM and AM−PM characteristics of the PAIC. The proposed predistorter was applied to the 2.6 GHz two-stage InGaP/GaAs HBT PAIC. The IC was tested using a 5 × 5 mm² module package based on a four-layer laminate. The load network was implemented off-chip on the laminate. By employing a continuous-wave (CW) signal, the AM−AM and AM−PM characteristics at 2.55–2.65 GHz were improved by approximately 0.05 dB and 3°, respectively. When utilizing the new radio (NR) signal, based on OFDM cyclic prefix (CP) with a signal bandwidth of 100 MHz and a peak-to-average power ratio (PAPR) of 9.7 dB, the power-added efficiency (PAE) reached at least 11.8%, and the average output power was no less than 24 dBm, achieving an adjacent channel leakage power ratio (ACLR) of −40.0 dBc. Full article

Waste-to-energy (WTE) is considered the most promising method for municipal solid waste treatment. An integrated energy system (IES) with carbon capture systems (CCS) and power-to-gas (P2G) can reduce carbon emissions. The incorporation of a “green-carbon” offset mechanism further enhances renewable energy consumption. Therefore, this study constructs a WTE-IES hybrid system, which conducts multi-dimensional integration of IES-WTP, CCS-P2G, photovoltaic (PV), wind turbine (WT), multiple energy storage technologies, and the “green-carbon” offset mechanism. It breaks through the limitations of traditional single-technology optimization and achieves the coordinated improvement of energy, environmental, and economic triple benefits. First, waste incineration power generation is coupled into the IES. A mathematical model is then established for the waste incineration and CCS-P2G IES. The CO₂ produced by waste incineration is absorbed and reused. Finally, the “green-carbon” offset mechanism is introduced to convert tradable green certificates (TGCs) into carbon emission rights. This approach ensures energy demand satisfaction while minimizing carbon emissions. Economic incentives are also provided for the carbon capture and conversion processes. A case study of an industrial park is conducted for validation. The industrial park has achieved a reduction in carbon emissions of approximately 72.1% and a reduction in the total cost of approximately 33.5%. The results demonstrate that the proposed method significantly reduces carbon emissions. The energy utilization efficiency and system economic performance are also improved. This study provides theoretical and technical support for the low-carbon development of future IES. Full article

The cooperative interconnection of multi-microgrid systems offers significant advantages in enhancing energy utilization efficiency and economic performance, providing innovative pathways for promoting sustainable development. To establish a fair energy trading mechanism for electricity–hydrogen sharing within multi-energy multi-microgrid (MEMG) systems, this study first analyzes the operational architecture of MEMG energy sharing and establishes a multi-energy coordinated single-microgrid model integrating electricity, heat, natural gas, and hydrogen. To achieve low-carbon operation, carbon capture systems (CCSs) and power-to-gas (P2G) units are incorporated into conventional combined heat and power (CHP) systems. Subsequently, an asymmetric Nash bargaining-based optimization framework is proposed to coordinate the MEMG network, which decomposes the problem into two subproblems: (1) minimizing the total operational cost of MEMG networks, and (2) maximizing payment benefits through fair benefit allocation. Notably, Subproblem 2 employs the energy trading volume of individual microgrids as bargaining power to ensure equitable profit distribution. The improved alternating direction multiplier method (ADMM) is adopted for distributed problem-solving. Experimental results demonstrate that the cost of each MG decreased by 5894.14, 3672.44, and 2806.64 CNY, while the total cost of the MEMG network decreased by 12,431.22 CNY. Additionally, the carbon emission reduction ratios were 2.84%, 2.77%, and 5.51% for each MG and 11.12% for the MEMG network. Full article

To further investigate the complementary characteristics among subsystems of the combined electricity–gas–heat system (CEGHS) and to enhance the renewable energy accommodation capability, this study proposes a comprehensive optimization scheduling framework. First, an optimization model is developed with the objective of minimizing the total system cost, incorporating key coupling components such as combined heat and power units, gas turbines, and power-to-gas (P2G) facilities. Second, to address the limitations of traditional robust optimization in managing wind power uncertainty, a distributionally robust optimization scheduling model based on Hausdorff distance is constructed, employing a data-driven uncertainty set to accurately characterize wind power fluctuations. Furthermore, to tackle the computational challenges posed by complex nonlinear equations within the model, various linearization techniques are applied, and a two-stage distributionally robust optimization approach is introduced to enhance solution efficiency. Simulation studies on an improved CEGHS system validate the feasibility and effectiveness of the proposed model, demonstrating significant improvements in both economic performance and system robustness compared to conventional methods. Full article

To improve the quality and functional properties of yogurts, a multi-starters co-fermentation system was used during yogurt preparation. In this work, Weissella cibaria G232 (added at 0%, 3%, 5%, and 7%) was involved as a co-fermenter with a traditional starter (Lactobacillus delbrueckii subsp. bulgaricus G119 and Streptococcus thermophilus Q019). The results showed that W. cibaria G232 co-fermentation could shorten the fermentation time and significantly enhance the viable counts of yogurt (p < 0.05). Moreover, the incorporation of W. cibaria G232 improved the water holding ability, viscosity, and texture of yogurt. Notably, the highest levels of firmness, consistency, and cohesiveness of yogurt were observed at the 5% addition level of W. cibaria G232. Furthermore, co-fermentation with W. cibaria G232 significantly enhanced the antioxidant activity of yogurt, as evidenced by increased free radical scavenging capacity and ferric ion reducing antioxidant power (FRAP) value. The intelligent sensory technology and Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) indicated that co-fermentation with W. cibaria G232 and a traditional starter notably altered the accumulation of aldehydes, ketones, and alcohols in yogurt. These findings suggest that co-fermentation of W. cibaria G232 with a traditional starter present the potential for the quality and functionality improvement of yogurt and also lay the foundation for the application of W. cibaria G232. Full article

This study develops a polymorphic energy coordination strategy for virtual power plants (VPPs) to enhance energy efficiency, operational flexibility, and carbon emission reduction. The proposed framework integrates three core components: (1) a tiered carbon trading mechanism enabling precise emission management through dynamic cost optimization; (2) an advanced two-stage power-to-gas (P2G) system combining electrolysis, methanation, and hydrogen fuel cell operations; (3) a mixed-integer linear programming (MILP) model optimized via CPLEX solver for cost-effective decision-making. Case studies demonstrate the strategy’s effectiveness in balancing economic and environmental objectives across multiple operational scenarios, with experimental validation confirming its practical advantages over conventional approaches. The findings offer critical insights for policymakers and energy enterprises pursuing low-carbon transitions. Full article