Dynamic and Power Generation Features of A Wind-Wave Hybrid System Consisting of A Spar-Type Wind Turbine and An Annular Wave Energy Converter in Irregular Waves

Combining wave energy converters(WECs)with floating offshore wind turbines proves a potential strategy to achieve better use of marine renewable energy.The full coupling investigation on the dynamic and power generation features of the hybrid systems under operational sea states is necessary but limited by numerical simulation tools.Here an aero-hydro-servo-elastic coupling numerical tool is developed and applied to investigate the motion,mooring tension,and energy conversion performance of a hybrid system consisting of a spar-type floating wind turbine and an annular wave energy converter.Results show that the addition of the WEC has no significant negative effect on the dynamic performance of the platform and even enhances the rotational stability of the platform.For surge and pitch motion,the peak of the spectra is originated from the dominating wave component,whereas for the heave motion,the peak of the spectrum is the superposed effect of the dominating wave component and the resonance of the system.The addition of the annular WEC can slightly improve the wind power by making the rotor to be in a better position to face the incoming wind and provide considerable wave energy production,which can compensate for the downtime of the offshore wind.

Short-term power generation scheduling rules for cascade hydropower stations based on hybrid algorithm

Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm （POA） in combination with the genetic algorithm （GA）. After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.

Solving open vehicle problem with time window by hybrid column generation algorithm

This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.

Allocation of Hybrid Distributed Generations and Energy Management in Radial Electrical Systems

This paper presents a method for optimal sizing of a Micro grid connected to a hybrid source to ensure the continuity and quality of energy in a locality with a stochastically changing population. The hybrid system is composed of a solar photovoltaic system, a wind turbine, and an energy storage system. The reliability of the system is evaluated based on the voltage level regulation on IEEE 33-bus and IEEE 69-bus standards. Power factor correction is performed, despite some reliability and robustness constraints. This work focuses on energy management in a hybrid system considering climatic disturbances on the one hand, and on the other hand, this work evaluates the energy quality and the cost of energy. A combination of genetic algorithms of particle swarm optimization (CGAPSO) shows high convergence speed, which illustrates the robustness of the proposed system. The study of this system shows its feasibility and compliance with standards. The results obtained show a significant reduction in the total cost of production of this proposed system.

Hybrid PV/Wind/Diesel Based Distributed Generation for an Off-Grid Rural Village in Afghanistan

Afghanistan has a tremendous resource potential of renewable energy especially solar and the wind. Therefore, utilization of these resources has a special rule for the remote areas where access to the electrical grid or secure power supply is a dream for most of the people. This paper presents a feasibility and usefulness of hybrid power generation based on PV/wind/diesel generator for an off-grid rural village that feeds the load at a rate of average 7.9 kWh/day with 1.32 kW peak load. GsT （geospatial toolkit） is used to obtain the solar and wind data of the site. Windographer software is used to analyze the wind resource data of the site. HOMER Pro software package is used to select the suitable and reliable hybrid generation system and calculate the optimal capacities and costs of the components. Through the study, it is found that this state of the art adaptation could provide vast opportunities for off-grid rural communities such as in Afghanistan where enough high penetration of renewable energy is available.

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Pure Jatropha Oil for Power Generation on Floreana IslandlGalapagos： Four Years Experience on Engine Operation and Fuel Quality

In the small country of Ecuador, all environmental risks of the production and consumption of fossil fuels can be observed by damages through oil exploration in the amazonite rainforest and two tank ship accidents close by Galapagos Islands causing death of 10,000 marine iguanas and other species. Now Ecuador plans to replace all environmentally dangerous diesel generators from all four inhabited Galapagos Islands by a hybrid system using 100% renewable energy for electricity production. Since 2010 a hybrid system of two Jatropha oil generators with an electrical power of 69 kW （kWel） and a photovoltaic plant with an electrical peak power of 21 kW （kWpeak） is successfully providing electricity from renewable energy for inhabitants and tourists of Floreana Island. After more than 15.000 engine operation hours of each engine there is no engine defect. For fuel supply, the so-called ＂Living Fence＂ concept collecting Jatropha seeds by farmers and families from already existing 6,000 km hedges on Ecuadorian mainland was chosen to comply with highest biofuel sustainability standards. The Jatropha oil is produced in a decentralized so-called CompacTropha oil mill container following the ambitious German fuel quality standard DIN51605. Since 2010 Floreana project successfully demonstrates that it is possible to replace diesel gen sets by generators fueled with pure Jatropha oil from decentralized sustainable production.

Simulation of large-scale numerical substructure in real-time dynamic hybrid testing

A solution scheme is proposed in this paper for an existing RTDHT system to simulate large-scale finite element （FE） numerical substructures. The analysis of the FE numerical substructure is split into response analysis and signal generation tasks, and executed in two different target computers in real-time. One target computer implements the response analysis task, wherein a large time-step is used to solve the FE substructure, and another target computer implements the signal generation task, wherein an interpolation program is used to generate control signals in a small time-step to meet the input demand of the controller. By using this strategy, the scale of the FE numerical substructure simulation may be increased significantly. The proposed scheme is initially verified by two FE numerical substructure models with 98 and 1240 degrees of freedom （DOFs）. Thereafter, RTDHTs of a single frame-foundation structure are implemented where the foundation, considered as the numerical substructure, is simulated by the FE model with 1240 DOFs. Good agreements between the results of the RTDHT and those from the FE analysis in ABAQUS are obtained.

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

To reduce the comprehensive costs of the construction and operation of microgrids and to minimize the power fluctuations caused by randomness and intermittency in distributed generation,a double-layer optimizing configuration method of hybrid energy storage microgrid based on improved grey wolf optimization(IGWO)is proposed.Firstly,building a microgrid system containing a wind-solar power station and electric-hydrogen coupling hybrid energy storage system.Secondly,the minimum comprehensive cost of the construction and operation of the microgrid is taken as the outer objective function,and the minimum peak-to-valley of the microgrid’s daily output is taken as the inner objective function.By iterating through the outer and inner layers,the system improves operational stability while achieving economic configuration.Then,using the energy-self-smoothness of the microgrid as the evaluation index,a double-layer optimizing configuration method of the microgrid is constructed.Finally,to improve the disadvantages of grey wolf optimization(GWO),such as slow convergence in the later period and easy falling into local optima,by introducing the convergence factor nonlinear adjustment strategy and Cauchy mutation operator,an IGWO with excellent global performance is proposed.After testing with the typical test functions,the superiority of IGWO is verified.Next,using IGWO to solve the double-layer model.The case analysis shows that compared to GWO and particle swarm optimization(PSO),the IGWO reduced the comprehensive cost by 15.6%and 18.8%,respectively.Therefore,the proposed double-layer optimizationmethod of capacity configuration ofmicrogrid with wind-solar-hybrid energy storage based on IGWO could effectively improve the independence and stability of the microgrid and significantly reduce the comprehensive cost.

Second Law Analysis of Magneto Radiative GO-MoS_(2)/H_(2)O–(CH_(2)OH)_(2) Hybrid Nanofluid

Entropy Generation Optimization(EGO)attained huge interest of scientists and researchers due to its numerous applications comprised in mechanical engineering,air conditioners,heat engines,thermal machines,heat exchange,refrigerators,heat pumps and substance mixing etc.Therefore,the study of radiative hybrid nanofluid(GO-MoS_(2)/C_(2)H_(6)O_(2)–H_(2)O)and the conventional nanofluid(MoS_(2)/C_(2)H_(6)O_(2)–H_(2)O)is conducted in the presence of Lorentz forces.The flow configuration is modeled between the parallel rotating plates in which the lower plate is permeable.The models which govern the flow in rotating system are solved numerically over the domain of interest and furnished the results for the temperature,entropy generation and thermophysical characteristics of the hybrid as well as conventional nanofluids,respectively.It is examined that the thermal profile intensifies against stronger thermal radiations and magnetic field.The surface of the plate is heated due to the imposed thermal radiations and magnetic field which cause the increment in the temperature.It is also observed that the temperature declines against more rotating plates.Further,the entropy production increases for more dissipative effects and declines against more magnetized fluid.Thermal conductivities of the hybrid nanofluid enhances promptly in comparison with regular liquid therefore,under consideration hybrid nanofluid is reliable for the heat transfer.Moreover,dominating thermal transport is perceived for the hybrid nanofluid which showed that hybrid suspension GO-MoS_(2)/C_(2)H_(6)O_(2)–H_(2)O is better for industrial,engineering and technological uses.

Figure of Merit Analysis of a Hybrid Solar-geothermal Power Plant

Figure of merit analysis is a general methodology used to evaluate whether a hybrid power plant could produce more power than two stand-alone power plants. In this paper, the assessment methodology using figure of merit analysis was re-examined for a hybrid solar-geothermal power plant. A new definition of the figure of merit was introduced specifically for a solar boosted geothermal plant to include both the technical and economic factors. The new definition was then applied in a case study of a hypothetical demonstration hybrid solar-geothermal power plant in Australia. The power plant was considered to have a typical net power output of 2.2 MW with a solar energy fraction of 27%. The analysis was performed to compare the power output and capital cost of the hybrid plant with the state-of-the-art (SoA) and existing stand-alone solar and geothermal plants. Based on the new definition, the hybrid plant was found to generally outperform the two existing stand-alone plants. Moreover, at an ambient temperature of 5 °C, the hybrid plant was found to outperform the SoA stand-alone plants when the geothermal temperature was greater than 150 °C. For geothermal temperature of 180 °C on the other hand, the hybrid plant outperformed the SoA stand-alone plants at ambient temperatures lower than 33 °C.

Magnetohydrodynamics hemodynamics hybrid nanofluid flow through inclined stenotic artery

The present study aims to perform computational simulations of twodimensional(2D)hemodynamics of unsteady blood flow via an inclined overlapping stenosed artery employing the Casson fluid model to discuss the hemorheological properties in the arterial region.A uniform magnetic field is applied to the blood flow in the radial direction as the magneto-hemodynamics effect is considered.The entropy generation is discussed using the second law of thermodynamics.The influence of different shape parameters is explored,which are assumed to have varied shapes(spherical,brick,cylindrical,platelet,and blade).The Crank-Nicolson scheme solves the equations and boundary conditions governing the flow.For a given critical height of the stenosis,the key hemodynamic variables such as velocity,wall shear stress(WSS),temperature,flow rate,and heat transfer coefficient are computed.

Enabling Hybrid Projects through Appropriate Market Design

Large-scale hybrid power plants, composed of two or more generation sources and with the participation of energy storage systems, have driven important electricity Market Design regulation discussions worldwide. Regulatory framework ought to be adapted to support technical particularities of these new generation arranges. This paper presents an assessment of the main requirements to be met by Market Design to enable hybrid power plants by means of assertive market incentives. Assessing regulatory adjustments promoted in Australia, United States, India, China, and Brazil, emphasizing the latter one, the authors presents a case study by applying specific computational simulation and optimization model to a hybrid Hydro-Solar plant, that supports the findings for the necessary evolution needed in the national regulatory framework in order to enable hybrid projects. The evaluation of international experiences indicates that the insertion of hybrid projects is associated with the design of the market they belong to and demand regulatory adjustments so that their attributes can be properly valued for the benefit of all stakeholders, especially for the electricity consumer.

General Automatic Solution Generation for Social Problems

Given the escalating intricacy and multifaceted nature of contemporary social systems,manually generating solutions to address pertinent social issues has become a formidable task.In response to this challenge,the rapid development of artificial intelligence has spurred the exploration of computational methodologies aimed at automatically generating solutions.However,current methods for the auto-generation of solutions mainly concentrate on local social regulations that pertain to specific scenarios.Here,we report an automatic social operating system(ASOS)designed for general social solution generation built upon agent-based models that enables both global and local analyses and regulations of social problems across spatial and temporal dimensions.ASOS adopts a hypergraph with extensible social semantics for a comprehensive and structured representation of social dynamics.It also incorporates a generalized protocol for standardized hypergraph operations and a symbolic hybrid framework that delivers interpretable solutions,yielding a balance between regulatory efficacy and functional viability.To demonstrate the effectiveness of the ASOS,we apply it to the domain of averting extreme events within international oil futures markets.By generating a new trading role supplemented by new mechanisms,ASOS can adeptly discern precarious market conditions and make front-running interventions for nonprofit purposes.This study demonstrated that ASOS provides an efficient and systematic approach for generating solutions for enhancing our society.

A 3D hybrid grid generation technique and a multigrid/parallel algorithm based on anisotropic agglomeration approach

A hybrid grid generation technique and a multigrid/parallel algorithm are presented in this paper for turbulence flow simulations over three-dimensional （3D） complex geometries. The hybrid grid generation technique is based on an agglomeration method of anisotropic tetrahedrons. Firstly, the complex computational domain is covered by pure tetrahedral grids, in which anisotropic tetrahedrons are adopted to discrete the boundary layer and isotropic tetrahedrons in the outer field. Then, the anisotropic tetrahedrons in the boundary layer are agglomerated to generate prismatic grids. The agglomeration method can improve the grid quality in boundary layer and reduce the grid quantity to enhance the numerical accuracy and efficiency. In order to accelerate the convergence history, a multigrid/parallel algorithm is developed also based on anisotropic agglomeration approach. The numerical results demonstrate the excellent accelerating capability of this multigrid method.

Integrated generation-transmission expansion planning for offshore oilfield power systems based on genetic Tabu hybrid algorithm

To address the planning issue of offshore oil-field power systems, an integrated generation-transmission expansion planning model is proposed. The outage cost is considered and the genetic Tabu hybrid algorithm(GTHA)is developed to find the optimal solution. With the proposed integrated model, the planning of generators and transmission lines can be worked out simultaneously,which outweighs the disadvantages of separate planning,for instance, unable to consider the influence of power grid during the planning of generation, or insufficient to plan the transmission system without enough information of generation. The integrated planning model takes into account both the outage cost and the shipping cost, which makes the model more practical for offshore oilfield power systems. The planning problem formulated based on the proposed model is a mixed integer nonlinear programming problem of very high computational complexity, which is difficult to solve by regular mathematical methods. A comprehensive optimization method based on GTHA is also developed to search the best solution efficiently.Finally, a case study on the planning of a 50-bus offshore oilfield power system is conducted, and the obtained results fully demonstrate the effectiveness of the presented model and method.

Control strategy of hybrid fuel cell/battery distributed generation system for grid-connected operation

This paper presents a control strategy of a hybrid fuel cell/battery distributed generation (HDG) system in distribution systems. The overall structure of the HDG system is given, dynamic models for the solid oxide fuel cell (SOFC) power plant, battery bank and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units and fuel cell to control the power flow from the hybrid power plant to the utility grid are presented. To distribute the power between the fuel cell power plant and the battery energy storage, a neuro-fuzzy controller has been developed. Also, for controlling the active and reactive power independently in distribution systems, the current control strategy based on two fuzzy logic controllers has been presented. A Matlab/Simulink simulation model is developed for the HDG system by combining the individual component models and their controllers. Simulation results show the overall system performance including load-following and power management of the HDG system.

Chiral induction and Sb3+doping in indium halides to trigger second harmonic generation and circularly polarized luminescence

Recently,organic-inorganic hybrid metal halides(HMHs)have attracted extensive attention as promis-ing multifunctional materials by virtue of their structural diversity and tunable photophysical properties.However,it remains a challenge to design HMHs with specific functions on demand.Herein,by introduc-ing R/S-methylbenzylamine(R/S-MBA)and doping Sb^(3+),we have achieved both second harmonic gen-eration(SHG)and circularly polarized luminescence(CPL)properties in lead-free indium halides.The introduction of chiral organic cations can break the symmetry and induce the indium halides to crys-tallize in the chiral space group.The Sb^(3+)with ns2 electronic configuration can serve as the dopants to promote the formation of self-trapped excitons,so as to activate highly efficient luminescence.As a re-sult,the as-prepared Sb3+doped(R/S-MBA)3 InCl6 show not only SHG responses but also CPL signals with luminescence dissymmetry factor of−5.3×10^(−3) and 4.7×10^(−3).This work provides a new inspiration for the exploitation of chiral multifunctional materials.

Cascade utilization of full spectrum solar energy for achieving simultaneous hydrogen production and all-day thermoelectric conversion

Solar-driven photocatalytic water/seawater splitting holds great potential for green hydrogen production.However,the practical application is hindered by the relatively low conversion efficiency resulting from the inadequate utilization of solar spectrum with significant waste in the form of heat.Moreover,current equipment struggles to maintain all-day operation subjected to the lack of light during nighttime.Herein,a novel hybrid system integrating photothermal catalytic(PTC)reactor,thermoelectric generator(TEG),and phase change materials(PCM)was proposed and designed(named as PTC-TEG-PCM)to address these challenges and enable simultaneous overall seawater splitting and 24-hour power generation.The PTC system effectively maintains in an optimal temperature range to maximize photothermal-assisted photocatalytic hydrogen production.The TEG component recycles the low-grade waste heat for power generation,complementing the shortcoming of photocatalytic conversion and achieving cascade utilization of full-spectrum solar energy.Furthermore,exceptional thermal storage capability of PCM allow for the conversion of released heat into electricity during nighttime,contributing significantly to the overall power output and enabling PTC-TEG-PCM to operate for more than 12 h under the actual condition.Compared to traditional PTC system,the overall energy conversion efficiency of the PTC-TEG-PCM system can be increased by∼500%,while maintaining the solar-to-hydrogen efficiency.The advancement of this novel system demonstrated that recycling waste heat from the PTC system and utilizing heat absorption/release capability of PCM for thermoelectric application are effective strategies to improve solar energy conversion.With flexible parameter designing,PTC-TEG-PCM can be applied in various scenarios,offering high efficiency,stability,and sustainability.

Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission

To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day.To mitigate this challenge,an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system(HBESS)operating within a microgrid is proposed,with a focus on efficient state-of-charge(SoC)planning to minimize microgrid expenses.The SoC ranges of the battery energy storage(BES)are determined in the day-ahead stage.Concurrently,the power generated by fuel cells and consumed by electrolysis device are optimized.This is followed by the intraday stage,where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized.To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage,we proposed an outer-inner column-and-constraint generation algorithm(outer-inner-CCG).Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.