Energy Utilization Rate Research Articles

Control parameter optimization of underwater gliders with uncertainty using hierarchical optimization method and interval analysis theory

This article attempts to solve the engineering optimization problem for control parameter configuration of underwater gliders with parameter uncertainty. The optimization objectives are maximizing the glider energy utilization rate and average voyage velocity; design variables include the net buoyancy adjustment amount and movable mass block translation amount; and uncertain parameters include the glider control parameter errors, manufacturing errors and sensor measurement errors. First, a dynamic simulation-based performance evaluation model of the glider is established, and interval number order theory is used to quantify the uncertainty. Then, surrogate models of the performance evaluation model are established, and the Sobol’ method-based sensitivity analysis is executed to identify the key uncertain parameters. Thus, a hierarchical optimization framework is introduced, and its system level and sub-level are used for determining optimal control parameter values and performance evaluation parameter intervals, respectively. Finally, optimization calculation is executed under different parameter configurations, and some rules are summarized.

Optimal scheduling of a township integrated-energy system using the adjustable heat-electricity ratio model

With the expansion and implementation of rural revitalization strategies, there is a constant need for new energy sources for the construction of new townships. Consequently, integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly. Biomass energy, a renewable green energy source with low pollution and wide distribution, has significant application potential in integrated energy systems. Considering the application of biomass energy in townships, this study established an integrated biomass energy system and proposed a model to optimize its operation. Lowest economic cost and highest clean energy utilization rate were considered as the objective functions. In addition, a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass. Finally, a simulation analysis conducted for a town in China was discussed, demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate. Moreover, by adjusting the heat-electricity ratio, the economic cost was further reduced by 6.70%, whereas the clean energy utilization rate was increased by 5.14%.

Energy flow optimization of an electric-gas-heat integrated energy system based on the energy circuit theory

The energy flow optimization of the integrated energy system (IES) can not only decrease the operating cost of the IES but also maximize the utilization rate of renewable energy. To deal with the problem that the optimization results fall into the local optimal solution due to the over-limit of IES state variables, based on the IES energy circuit theory, this paper established an energy flow optimization model of the electric-gas-heat integrated energy system by taking the weighted sum of the operating cost, state variables over-limit penalty cost, and wind and light abandonment penalty cost as the optimization objective. The growth optimizer (GO) algorithm can avoid the local convergence of the optimization results and accelerate the solving speed of the model. Therefore, the effectiveness and feasibility of the model and the optimization method are confirmed by the simulation example.

Optimal operation of electric-heat-gas-hydrogen integrated energy system considering source-load uncertainty

Faced with the threat of global climate change crisis, increasing the use of hydrogen-enriched compressed natural gas (HCNG) and the utilization rate of renewable energy can both reduce the carbon emissions of the integrated energy system (IES). This paper establishes an electric-heat-gas-hydrogen integrated energy system (EHGH-IES) framework considering source-load uncertainty, and the natural gas pipe network in the traditional IES is transformed into a HCNG pipe network with a certain hydrogen blending ratio. An optimal operation model of the EHGH-IES considering source-load uncertainty is proposed in this paper. The chance constrained programming method is adopted to deal with source-load uncertainty. We pay attention to comparing different confidence coefficient and hydrogen blending ratio in terms of the changes in the cost of the IES. The results show that the total cost of the EHGH-IES will increase by considering source-load uncertainty and using HCNG pipeline, but will bring some stability and environmental benefits to the IES by them.

An energy‐efficient timetable optimization method for express/local train with on‐board passenger number considered

AbstractWith the expansion of the metropolitan area, the application of express/local mode is gradually increasing. In contrast to the normal mode, the express/local mode has advantages in reducing energy consumption and saving total travel time by having express trains skipping some stops. This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy‐efficient timetable. As the consumed energy of a train is highly dependent on the rolling stock weight and the on‐board passengers’ weight. An integer programming model is proposed with on‐board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. An improved grey wolf algorithm is designed by improving convergence factor and incorporating differential evolution to solve the proposed problem. The real data on Guangzhou Metro Line 18 is adopted for numerical studies. The results show that the optimized timetable increases the regenerative energy utilization rate by 21.37% and reduces the total energy consumption by 5.02% compared to the operational timetable.

Effect of Freeze-Thaw Cycle and Moisture Content on Compressive and Energy Properties of Alkali Slag Ceramsite Concrete

Freeze-thaw cycle and moisture content are important factors for structural strength degradation in cold areas. Using coal gangue and slag to prepare alkali slag ceramsite concrete (ASCC) can implement the reuse of solid waste of coal gangue and slag. To study the influence of ceramsite content and moisture content on compressive strength and energy characteristics under freeze-thaw cycles (FTCs), uniaxial compression tests were conducted for ASCC with different moisture contents (dry, 4%, 5%, and 6%) and ceramsite contents (0%, 25%, 50%, 75%, and 100%) after 20 FTCs. The results show that the stress-strain curves of ASCC with different moisture contents and ceramsite contents all undergo four stages under FTCs, namely initial compaction, elastic deformation, crack development, and post-peak failure. The addition of coal gangue ceramsite makes concrete failure show certain ductility characteristics. Both compressive strength and ultrasonic pulse velocity decrease with the moisture content, and elastic energy utilization rate of wet ASCC is better than that of dry ASCC. The compressive strength, ultrasonic pulse velocity, and energy characteristics all decrease with the increase of ceramsite content.

Strategy and capacity optimization of renewable hybrid combined cooling, heating and power system with multiple energy storage

Combined cooling, heating, and power systems offer significant potential for integration with renewable energy sources, such as solar and geothermal energy, alongside energy storage devices. However, the effectiveness and feasibility of these systems depend crucially on the operational strategies and capacity planning for each component. Therefore, an innovative hourly dynamic simulation model that integrates solar energy, geothermal energy, and multiple energy storage devices is established. Using the multi-objective comprehensive evaluation method that combines Technique for Order Preference by Similarity to Ideal Solution methods and non-dominated sorting genetic algorithm-II including elite strategy, establish five dimensions of multi-objective optimization model, including energy-saving, economy, environmental protection, system independence and renewable energy utilization scale. Meanwhile, the system and reference system in a community in Beijing are used as models to analyze the equipment capacity under the three operating strategies. The findings reveal that, compared to the reference system, the new system attains optimal performance when following the electrical load strategy. Its comprehensive index reaches 69%, surpassing the thermal load and hybrid load strategies by 8% and 11%, respectively. When the target is set as “independence-renewable energy-cost,” the utilization rate of solar energy and geothermal energy reaches an impressive 79%, showcasing excellent renewable energy utilization. The presented model holds substantial significance for advancing research in the realms of operating strategies and equipment capacity planning within such systems.

A Novel Reinforcement Learning Balance Control Strategy for Electric Vehicle Energy Storage Battery Pack

Abstract Energy imbalance in electric vehicle energy storage battery packs poses a challenge due to design and usage variations. Traditional balancing control algorithms struggle to cope with large-scale battery data and complex nonlinear relationship modeling, which jeopardizes the stability of energy storage systems. To overcome this issue, we propose a reinforcement learning (RL)-based strategy for battery pack balancing control. Our approach begins with adaptive battery pack modeling followed by the employment of an active balancing control strategy to determine the duration of the balancing charge state and rank the balancing strength of individual battery pack cells. Subsequently, a RL network is employed to learn dynamic parameters that capture battery pack variations, enabling subsequent automatic learning and prediction of effective balancing strategies while simultaneously selecting the optimal control policy. Our simulation experiments demonstrate that our approach ensures an orderly charge and discharge process of battery pack cells, achieving an impressive balance efficiency of 91% when compared to other similar balancing control methods. Furthermore, the optimization of RL methods results in significant improvements in battery pack energy efficiency, stability, and operational costs. Notably, our method also outperforms other similar control methods in terms of energy utilization rates, establishing its superiority in this category.

Numerical simulation on dynamic compression properties of sandstone under axial static preload

In this study, through a series of static mechanical tests and split Hopkinson pressure bar (SHPB) dynamic impact tests, the static and dynamic mechanical parameters of yellow sandstone are determined, and the Holmquist–Johnson–Cook model parameters of the rock are determined by the test data and theoretical calculation. The feasibility of a numerical model is verified, based on which the SHPB impact process under different axial pressure is subjected to numerical analysis. The results show that with increasing impact load, the degree of rock breakage increases, and the dynamic compressive strength and dynamic elastic modulus increase continuously. With the application and increase of axial pressure, the dynamic compressive strength and dynamic elastic modulus of the rock decrease gradually under the same impact load, and the maximum cumulative strain keeps increasing, indicating that under the influence of axial pressure, micro-cracks in the rock have initially developed and expanded. With increasing axial pressure, the rock is more vulnerable to breakage, and its weakening degree keeps increasing. The energy utilization rate of one-dimensional dynamic and static combined loading is affected by the axial compression ratio and impact load. At low axial compression ratio, the rock has high impact resistance but high energy utilization rate; at high axial compression ratio, the rock has low impact resistance but low energy utilization rate. Therefore, the combination of axial compression ratio and impact velocity can improve the crushing effect and energy utilization rate on the premise of clear crushing form requirements.

Numerical Simulation of Liquid Film Characteristics during Atomization of Aluminum Alloy Powder

The process of atomizing aluminum alloy powder using a rotating disk was studied by numerical simulation and experimental verification. The motion characteristics of the molten metal thin liquid film and the evolution law of atomization into droplets were systematically studied with different disk shapes and speeds. The results showed that the slippage of the liquid film on the surface of the spherical disk was smaller, the liquid film spread more evenly, and the velocity distribution was more uniform. Under the same working condition, the boundary diameter of the continuous liquid film on the spherical disk was 21–29% larger, and the maximum liquid film velocity increased by approximately 19%. In other words, the liquid film obtained more energy at the same rotational speed, the energy utilization rate was higher, and the liquid filaments produced by the splitting region of the disk surface were finer and greater in number. The data showed that the average thickness of the liquid film on the surfaces of different disk shapes was more affected by the speed of the flat disk, and the thickness on the spherical disk was relatively stable and uniform, but the difference in thickness between the two disk shapes decreased from 4.2 μm to 0.3 μm when the speed increased from 10,000 rpm to 60,000 rpm. In particular, the influence of the disk shape on the liquid film thickness became smaller when the speed increased to a certain range. At the same time, the characteristics of the liquid film during the spreading movement of molten metal on the disk and the mechanisms of the primary and secondary breakage of the liquid film were obtained through this simulation study.

Optimal Energy Configuration of Integrated Energy Community Considering Carbon Emission

An integrated energy community with a distributed utilization of renewable energy and complementary electricity–gas–cold–heat integrated energy will play an important role in energy conservation and emission reduction. In addition, compared with traditional thermoelectric power equipment, solid oxide fuel cells have many advantages, such as a high energy utilization rate, good waste heat quality, and low carbon emissions. Therefore, the SOFC-based multi-energy and energy storage sharing operation model of an integrated energy community with an electricity–gas–cooling–heat integrated energy system is constructed, and a bi-objective optimal configuration model considering the carbon emission index is established. Considering the economic objective of the smallest annual total operating cost as the most important objective in optimizing the planning model, the ε-constraint method is used to transform the environmental objective function with the smallest annual total carbon emission into a constraint condition under the decision making of an economic single objective function, and then the planning model is linearized and solved by using the Big-M method and the McCormick relaxation method. By calculating and analyzing the energy allocation results in five scenarios, the effectiveness and rationality of the model built in this article are verified. At the same time, the calculation example analysis results show that as the ε value decreases, the energy configuration of the integrated energy community will shift from natural gas to clean energy. From this perspective, the energy equipment configuration and operating costs will increase. However, the heat storage system and power storage system sharing can effectively reduce the energy allocation capacity and costs.

Dynamic response characteristics and economic analyses of two solar-assisted multi-generation systems

Efficient use of solar energy can alleviate the depletion of fossil energy and global warming. In this paper, two solar-aided combined cooling, heating and power systems are proposed and dynamically modeled. The main difference between the two systems is whether the solar energy is stored. A rotor speed-temperature-fuel control system is established, which is suitable for both systems. A control system for solar heat collection process is developed. Energy, exergy and techno-economic analyses are carried out to evaluate the thermodynamic and economic performances. The dynamic responses under direct normal irradiation perturbation and load perturbation are also investigated. The result shows that compared with the system without energy storage, the system with energy storage has higher primary energy utilization rate, exergy efficiency and fuel saving rate, but the economic performance is poorer. The rotor speed-temperature-fuel control system can guarantee a short equilibrium time and a small overshoot for power generation process. When electrical load disturbance occurs, the stabilization times of the output power, cooling energy supply and thermal energy supply are 30 s, 675 s and 770 s, respectively. Under the regulation of the solar heat collection control system, the maximum overshoot of the outlet thermal oil temperature of the parabolic trough solar collector is 2.6 % with a stabilization time of 83 s when the direct normal irradiation step disturbance occurs.

Research on the calculation method of the reasonable utilization rate of renewable energy considering generation–grid–load–storage coordinated planning

The continuous advancement of the dual carbon goal will lead to fundamental changes in China’s energy structure, with renewable energy emerging as the dominant force in the power supply system. As the proportion of installed capacity for renewable energy continues to increase, the absorption capacity and reasonable utilization rate of renewable energy will become a concern for all sectors of society. At present, the degree of utilization of renewable energy has emerged as a significant factor limiting the development of renewable energy sources. Due to variations in the power structure, load characteristics, and flexible adjustment resources across different regions, blindly pursuing full absorption or higher utilization of renewable energy as a goal can result in increased reserve costs for the system and limited economic benefits, and hinder the development of renewable energy. Therefore, the present study develops a generation–grid–load–storage collaborative planning model aimed at achieving economic optimization by setting different renewable energy utilization rates and obtains the installed capacity of renewable energy and storage under different conditions in the planned year of Gansu Province. The economic analysis indicates that the optimal utilization rate of renewable energy in Gansu Province is projected to decrease from 100% during the period of 2024–2028 to approximately 90% from 2040 to 2060. It serves as a valuable tool for informing the planning and economic development of renewable energy and storage initiatives in Gansu Province, facilitating the achievement of its dual-carbon objectives.

Distributed resilient fault-tolerant cooperative automatic generation control and multi-event triggering mechanism co-design for wind energy conversion power system

In wind energy conversion power system, some sensor and actuator fall into abnormal condition which may lead to lower wind energy utilization rate and poor system performance or even system collapse. Meanwhile, with the increasing complexity of wind energy conversion power system, more device nodes compete for limited network communication resources, there are time-delays and packets dropout in data transmission, and these may reduce the efficiency of wind energy conversion. Accordingtoaboveconsideration, the multi-event triggering mechanism based distributed resilient fault-tolerant cooperative control scheme for wind energy conversion power system is put forward. A novel model of the wind energy conversion power system is established when the sensor and actuator faults simultaneously. According to Lyapunov stability theory, the sufficient condition for system exponential mean-square stable is obtained. Different from previous fault-tolerant control method, the proposed control strategy considered the wind energy conversion power system with data transmission management under simultaneous stochastic sensor and actuator faults. The simulation demonstrates that the method proposed in this paper is effective and the multi-event triggering mechanism based distributed resilient fault-tolerant controller provides stronger reliability and higher wind energy utilization efficiency.

Evaluation and Power Grid Investment Efficiency under High Quality Development

In the context of the reform of transmission and distribution prices, how to improve the investment efficiency of power networks is a noteworthy issue. This article constructs a transmission and distribution price system under the electricity market price system from the perspective of efficiency, and evaluates the effectiveness of each indicator based on the upper limit, benchmark, and profit criteria of transmission and distribution prices. It establishes evaluation methods for investment efficiency of power grids in various regions and provides the optimal solution based on gross profit margin. Through example analysis, the relationship between transmission coefficient, asset return rate, and investment and energy utilization rate was obtained, which is an important basis for making safe and reliable investment decisions. The experiment shows that the accuracy of the three stage DEA method based on the dataset is higher than 89%, which is higher than other algorithms.

Electron heating mode in magnetic field diffusion region of microwave discharge ion thruster

In magnetic field design principle of microwave discharge ion thruster, it is universally received that enlarging the magnetic mirror region can confine more electrons to acquire better energy utilization rate, while reducing the magnetic field diffusion region can prevent electrons from losing at wall to reduce the discharge loss. However, recently the integrated simulation proposes a hypothesis that electrons can also be heated in the magnetic field diffusion region when the Child-Langmuir sheath is considered as a constraint condition for electrons. Therefore, herein a magnetic field structure for the magnet array microwave discharge ion thruster is designed to verify the hypothesis, in which the magnetic field diffusion region is located near the screen grid. Then, an integrated simulation is conducted for studying the initial discharge and ion beam extraction stages of the thruster. The simulation results show that in the magnetic field diffusion region, the electron temperature is 4–8 eV when the grid system voltage is not applied, while the electron temperature is 4–12 eV when the the grid system voltage is applied. And the plasma density in the latter case has one order of magnitude higher than that in the former case. It means that electrons are obviously heated in the magnetic field diffusion region when they are confined among the Child-Langmuir sheath, the plasma sheath at antenna surface, and magnetic mirror. This electron heating mode produces more high-energy electrons outside the magnetic mirror region to generate plasma in front of the grid system, which can significantly increase the plasma density and ion beam current density. The result shows that under the conditions of 0.3 sccm (1 sccm = 1 mL/min) xenon gas flow, 1 W input microwave power, 300 V screen grid voltage and –50 V acceleration grid voltage, the ion beam current and its density are 0.47 mA and 0.60 mA/cm<sup>2</sup> for the magnet array microwave discharge ion thruster, while the ion beam current and its density are 1.2 mA and 0.38 mA/cm<sup>2</sup> for the 2-cm microwave discharge ion thruster. The ion beam current density increases by 57.9%. Through the integrated simulation, a new electron heating mode in the magnetic field diffusion region is proved theoretically, which provides a theoretical basis for the magnetic field structure optimization of microwave discharge ion thruster.

Preparation of P-coupled g-C3N4/TiO2 photoanode and its photoelectrocatalytic degradation of sulfadiazine

In order to solve the problems of TiO2 bandgap width and low utilization rate of light energy, red phosphorus which can absorb visible light is introduced, which is complementary to the characteristics of TiO2 which mainly absorb ultraviolet light. The introduction of red phosphorus is expected to broaden the light response range of the photoelectrode to the visible region, thereby improving the efficiency of sunlight utilization. TiO2 was modified by red phosphorus sublimation precipitation. The joint introduction of P and g-C3N4 not only broadened the photoresponse range of TiO2, extended the visible light absorption range to 460nm, improved the light absorption efficiency, but also promoted the effective separation and transmission of charge, thus greatly improving the degradation efficiency of SD up to 90.28%. ꞏOH, h+ and ꞏO2- were the main active species of SD degradation, in which ꞏOH played a key role.

Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid

To aggregate rural biomass energy, distributed power supply, flexibility load, and other resources, a novel structure of the rural Biomass-derived Fuel -based new energy microgrid (BDF-NEM) is proposed. It includes the Biomass Waste Conversion System (BWS), Distributed Renewable Energy (DRE), and Flexible Load Cluster (FLC). The two-stage scheduling optimization framework is designed for the BDF-NEM, minimizing operating costs in the Day-ahead phase and system deviation costs in the Intra-day phase. Uncertainty analysis of wind power plant (WPP) and photovoltaic generators (PV) is conducted using Latin hypercube sampling and the Kantorovich distance approach. To guarantee the equitable allocation of benefits, a benefit allocation mechanism grounded in the enhanced Sharp value approach takes into account operational risks. The analysis of a rural area in northern China demonstrates: (1) After BDF - NEM joined the tiered carbon trading mechanism, although it increased carbon trading costs by 31.27 %, wind power and photovoltaic output increased by 36.08 %, improving new energy consumption; (2) The two-stage scheduling optimization model with daily plan and daily correction can effectively alleviate the deviation caused by wind and solar uncertainty. Although the adjustment cost is 3966.41 yuan, it can avoid the penalty of load loss; (3) The improved benefit allocation based on the Shapley value method reflects the marginal contribution of each system module at the risk level, and when the system modules cooperate with each other, the return is 18.17 % higher than when operating alone, effectively stimulating the enthusiasm to participate in transactions. In summary, the BDF NEM proposed in this article can improve the utilization rate of wind and solar energy, promote the low-carbon development of rural power plants, and achieve local resource allocation in rural areas.

Optimal Scheduling of Regional Integrated Energy System Considering the Integration of Electric Vehicles and the Life Cycle Assessment Method

With the increasing scale of renewable energy and electric vehicles (EVs), the optimization scheduling of the regional integrated energy system (RIES) is facing new challenges due to the integration of EVs and new energy into the system. To realize the low-carbon economic operation of the RIES, a bi-level optimization scheduling strategy for low-carbon economic operation of the RIES is proposed, which considers EVs' participation and lifecycle carbon emissions, and integrates the electricity market and carbon trading market. Firstly, there are many factors affecting the carbon emissions of EVs and the difficulties in prediction. From the indirect carbon emissions during the use of EVs, the relationship between the carbon emissions of EVs and the charging mode and carbon emission sources is comprehensively analyzed. A carbon emission model of EVs based on the Life Cycle Assessment (LCA) is established in this paper. Secondly, the charging model of EVs based on demand response is combined with the electricity market; The carbon emission model of EVs based on the LCA is combined with the carbon trading market, and a bi-level scheduling strategy based on the flexible interaction between carbon and electricity is proposed. Then the strategy is solved to minimize system economic costs and carbon transaction costs. Finally, simulation example analysis is conducted to demonstrate that the proposed strategy can effectively reduce the total charging costs of electric vehicle users, improve the utilization rate of renewable energy, and reduce carbon dioxide emissions, with good economic and environmental benefits.

A durable hydrophobic photothermal membrane based on a honeycomb structure MXene for stable and efficient solar desalination.

Solar powered water evaporation is a green and environmentally friendly water treatment technology, which is a hot research topic for water purification at present. Advanced structural design and hydrophilic photothermal materials have achieved efficient solar evaporation of pure water, but the long-term stability of high salinity desalination has become a problem that cannot be ignored in practical applications. In order to solve this problem, a hydrophobic honeycomb structure MXene/AuNFs composite membrane was proposed in this paper, which used the three-dimensional highly porous microstructure of MXene and multibranched structure of gold nanoflowers particles to improve the light absorption and photothermal conversion efficiency of MXene/AuNFs. At the same time, the surface of the composite membrane was modified with hydrophobic fluorosilane 1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFTE). The hydrophobic layer can prevent the accumulation of salt particles on the surface of the membrane, so that the composite film can continue to produce water vapor in a high salt environment. With high utilization rate of light energy, multiple-level geometrical structures of MXene for rapid water transport on the filter membrane and salt barrier on the membrane good stability, the hydrophobic MXene/AuNFs achieves solar evaporation rate of 1.59 kg m-2 h-1 and solar conversion efficiency is 97.8%, and stable operation under simulated sea water conditions under one sun irradiation over more than 10 cycles. The hydrophobic MXene/AuNFs membrane proved to be an efficient and stable photothermal material for solar desalination.