Optimization and analysis of an integrated energy system based on wind power utilization and on-site hydrogen refueling station

An integrated energy system coupled with wind turbines and an on-site hydrogen refueling station is proposed to simulate the future scenario, which can meet the demands of cooling, heating, power and hydrogen. The system was modeled to calculate the capacity and annual operation of each equipment with the total annual cost as the optimization objective. This study evaluates the performance of the system based on the results. When the system is configured with 0–10 wind turbines, the economics, energy consumption and carbon emissions improve as the scale of wind turbines increases. Energy utilization and wind power utilization are above 66.79% and 99.73%, respectively. The on-off coefficient of the power generation unit can affect energy efficiency. When the system contains 5 turbines, 91% of the hydrogen can be self-produced with the minimum amount of energy redundancy.     

Multi-objective optimized operation of integrated energy system with hydrogen storage

In this paper, an integrated energy system (IES) consisting of wind turbine unit, photovoltaic cell unit, electrolytic hydrogen unit, fuel cell unit, and hydrogen storage unit is proposed, and the construction of multi objectives for day-ahead power dispatching of the IES considering both operation and environment cost is discussed. By adopting piecewise linearization method, the optimization variables are divided into 24 periods, and the day-ahead power dispatching optimization problem is transformed into a 24-h piecewise optimization problem. On the basis, a complete non-linear mixed integer dynamic scheduling optimization model is established. An improved non-dominated sorting genetic algorithm (NSGA-II) is applied to solving the model. In optimization process, an interactive strategy is adopted to solve the coordination between discretization of variables and restriction of switching times of electrolyzer. Optimization results show that, compared with the single objective of minimizing operating costs, the multi-objective optimization scheme can reduce carbon emissions by 3.5% with 2.8% increase of operating cost. Compared with the single objective of minimizing environmental, the multi-objective optimization scheme can reduce operating cost carbon by 5.12% with 2.6% increase of environmental cost.     

Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system

This paper presents and evaluates three energy management systems (EMSs) based on Particle Swarm Optimization (PSO) for long-term operation optimization of a grid-connected hybrid system. It is composed of wind turbine (WT) and photovoltaic (PV) panels as primary energy sources, and hydrogen system (fuel cell –FC–, electrolyzer and hydrogen storage tank) and battery as energy storage system (ESS). The EMSs are responsible for making the hybrid system produce the demanded power, deciding on the energy dispatch among the ESS devices. The first PSO-based EMS tries to minimize the ESS utilization costs, the second one to maximize the ESS efficiency, and the third one to optimize the lifetime of the ESS devices. Long-term simulations of 25 years (expected lifetime of the hybrid system) are shown in order to demonstrate the right performance of the three EMSs and their differences. The simulations show that: 1) each EMS outperforms the others in the designed target; and 2) the third EMS is considered the best EMS, because it needs the least ESS devices, and presents the lowest total acquisition cost of hybrid system, whereas the rest of parameters are similar to the best values obtained by the other EMSs.     

Decoupling optimization of integrated energy system based on energy quality character

Connections among multi-energy systems become increasingly closer with the extensive application of various energy equipment such as gas-fired power plants and electricity-driven gas compressor. Therefore, the integrated energy system has attracted much attention. This paper establishes a gas-electricity joint operation model, proposes a system evaluation index based on the energy quality character after considering the grade difference of the energy loss of the subsystem, and finds an optimal scheduling method for integrated energy systems. Besides, according to the typical load characteristics of commercial and residential users, the optimal scheduling analysis is applied to the integrated energy system composed of an IEEE 39 nodes power system and a 10 nodes natural gas system. The results prove the feasibility and effectiveness of the proposed method.     

Multi-objective optimal droop control of solid oxide fuel cell based integrated energy system

Solid oxide fuel cell (SOFC) based integrated energy system (IES) is promising in the future low-carbon power generation market, due to the high efficiency and flexibility. However, it is challenging for the dynamic control design in dealing with the conflicting objectives in terms of fast power tracking and overall efficiency during the transient process of load response. To this end, this paper develops a multi-objective optimal droop control strategy for the real-time power dispatch of the IES. Firstly, a nonlinear implicit dynamic model consisting of SOFC, lithium-ion battery, photovoltaic array and DC-DC converter is developed. Then, a multi-objective optimization is formulated to balance the power tracking performance and transient efficiency. Non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to search the optimal parameters for droop controller. Simulation results demonstrates that the electricity loss of the proposed method can be reduced by 96.26% with a slight compromise in power tracking performance.     

Multi-objective optimization of wind-hydrogen integrated energy system with aging factor

Large-scale hydrogen production with wind power generation has been gaining increasing attention and applications. Achieving a good balance between the capacity and cost of wind power generation however remains as a critical challenge restricting the development of wind-hydrogen integrated energy systems (WHIES). In addition, the aging factor may come in over time, making negative impacts on the efficiency and cost of WHIES. In this work, a method is proposed to seek a good balance between the capacity and cost of WHIES. Specifically, by comparing operational data and equipment condition, we evaluate the aging status of the wind power generation system and the hydrogen production system, then the aging economic model of WHIES is proposed. By taking into account the actual operating conditions in constructing the WHIES objective function with the aging factor, the proposed model allows striving to maximize the production capacity with the minimum cost. An improved multi-objective gray wolf optimizer algorithm is developed to solve the WHIES cost optimization problem. Finally, case studies are carried out via MATLAB based on the configuration and experimental data for a specific wind farm located in Ningxia, China. Our results help achieve a balance between maximizing capacity and minimizing cost under various conditions.     

大规模储能电站参与电力系统自动发电控制的协调控制策略优化研究

文章提出了一种双层结构的储能电站参与电网二次调频的优化控制策略。首先,综合对比分析了常规机组与储能电站参与电网二次调频的技术特性,并在调度层面对储能电站与常规机组的功率进行解耦;然后研究了储能电站辅助火电机组调频的协调控制框架,以实现不同调频资源的合理分配;在储能电站主控层面,建立了表征储能实时调频能力的评估模型,并采用改进遗传算法对模型进行求解,以对储能各单元出力进行精细化协调管理;最后,基于仿真模型验证了所提控制策略的有效性。     

Synergistic planning of an integrated energy system containing hydrogen storage with the coupled use of electric-thermal energy

Regional integrated energy systems (RIES) can economically and efficiently use regional renewable energy resources, of which energy storage is an important means to solve the uncertainty of renewable energy output, but traditional electrochemical energy storage is only single electrical energy storage, and the energy efficiency level is low. Hydrogen energy storage has the advantages of large energy storage capacity, long storage time, clean and pollution-free, and can realize the synergistic and efficient utilization of electricity and thermal power. Based on this, this paper proposes a synergistic planning method for an integrated energy system with hydrogen storage taking into account the coupled use of electric-thermal energy, which effectively reduces the system carbon emission and improves the comprehensive energy efficiency level. Firstly, this paper constructs an electric-thermal coupling model of the hydrogen energy storage unit and proposes an optimization strategy for the integrated energy system containing hydrogen storage taking into account the utilization of electricity and thermal power. Secondly, a planning optimization model with the lowest economy and carbon emission and the highest comprehensive energy efficiency was constructed. Third, the CSPO-GE optimization algorithm is proposed for solving the problem, which significantly improves the solution efficiency. Finally, a planning optimization simulation of RIES for a residential community W in northern China verifies the effectiveness of the model and method proposed in this paper. The comparative analysis of the three schemes shows that compared with the integrated energy system with conventional electrochemical energy storage and heat storage tank as the main form of energy storage and the integrated energy system with only hydrogen storage, the integrated energy system with hydrogen storage and heat storage tank can reduce carbon emissions by 43.8% and 7.61%, respectively, and improve the integrated energy efficiency level by 337.14% and 14.44%.     

Operation optimization for gas-electric integrated energy system with hydrogen storage module

Hydrogen is gradually becoming one of the important carriers of global energy transformation and development. To analyze the influence of the hydrogen storage module (HSM) on the operation of the gas-electricity integrated energy system, a comprehensive energy system model consisting of wind turbines, gas turbines, power-to-hydrogen (P2H) unit, and HSM is proposed in this paper. The model couples the natural gas network and power grid bidirectionally, and establishes a mixed integer nonlinear programming problem considering HSM. The linearization model of the natural gas pipeline flow equation and the generator set equation is constructed by piecewise linearization method to improve the efficiency of solving the model. And the energy flow distribution in the gas-electricity integrated energy system is finally solved. In Model 1, compared with not considering the installation of P2H units, when the hydrogen doping ratio is 10%, the operating cost can be reduced by 6.63%, and the wind curtailment cost can be reduced by 17.54%, and the carbon emission can be reduced by 298.7 tons. The optimization results of Model 2 reveal that compared with no HSM, the system operating cost is reduced by 5.96%, the hydrogen content level in the natural gas pipeline network is increased by 42.12%, and the carbon emission of the system is reduced by 117.6 tons, and the fluctuation of wind power is suppressed. This study demonstrates the feasibility of large-scale absorption of renewable energy through HSM.     

风光-氢储微电网系统多目标容量优化配置

为实现“双碳目标”,减少“限电”带来的不利影响,提出了风光-氢储能的微电网方案,介绍了系统容量配置原理,并建立数学模型。采用Homer Pro软件和改进BAS GA算法创建多目标风光-氢储能容量优化配置模型。在离网运行状态下,对风光-氢储能系统容量优化配置模型进行实例验证。结果表明：相较于风储、光储、风光储、风光柴储系统,风光-氢储能系统的净现值及度电成本分别降低为1 425.036 8万元和1.529 元/（kW〖DK〗•h）;可再生能源利用率提升至98.7%,负荷缺失率降低至5.50%。     

Multi-objective optimization of a hydrogen production through the HyS process powered by solar energy in different scenarios

Thermochemical or hybrid cycles powered by concentrated solar energy are a very promising way to produce an effective clean hydrogen through the water splitting, in terms of greenhouse gas (GHG) emissions and power production sustainability. SOL2HY2 is an European project focused on this goal. It deepens the so-called HyS process in a closed or partially open version using a proper SO₂ depolarized electrolyser, and moreover, it investigates key materials and process solutions, along the entire production chain. However, the identification of the best solution to obtain a suitable hydrogen in terms of cost, efficiency, availability of energy and material, sharing of renewable energy source, continuity of operation in different locations and plant sizes, poses many challenges in terms of flexibility and complexity of the system. In fact, it involves various chemical equipment, different solar and thermal storage technologies, and variable operative conditions with different reaction temperatures and mixture concentrations. Hence it arises the importance to have a tool for the investigation of this system.In this paper, data analysis and multi-objective techniques are used to study and optimize the process under consideration. Several mathematical methods have been exploited to make the best use of the available data, such as Design of Experiments techniques, meta-modeling strategies and genetic algorithms. All these methods have been implemented in the open source environments Scilab and R.     

Hydrogen energy storage integrated battery and supercapacitor based hybrid power system: A statistical analysis towards future research directions

Environmentally friendly and pollution-free hydrogen cell, battery and supercapacitor hybrid power system has taken the attention of scientists in recent years. Several notable advancements in energy storage mechanisms with hybrid power systems have been made during the last decade, influencing innovation, research, and the possible direction for improving energy storage technologies. This paper represents a quantitative analysis of all knowledge carriers with mathematical and statistical methods of hydrogen energy storage to establish a hybrid power system. For selecting the top cited papers in this topic, related articles on energy storage mechanisms for hybrid power systems were searched in the Scopus database under specified predetermined parameters. The selection technique of the most cited paper was based on filtered keywords in the hybrid hydrogen energy storage-based hybrid power system and related research during 2008–2021. About 48% of all articles have been published between 2016 and 2019; 21% will have originated from China; and 29% of the papers have used batteries as a form of energy storage in the application of electric vehicles. Most of the articles contain experimental work (25.11%) followed by simulation analysis (25%) and systematic and nonsystematic review (18.75%). Related publications with the most citations were published in 35 different impactful journals from different publishers and nations. This research found that integrating hydrogen energy storage with battery and supercapacitor to establish a hybrid power system has provided valuable insights into the field's progress and development. Moreover, it is a thriving and expanding subject of study. Bibliometric analysis was used to identify the most significant research publications on the subject of hybrid energy storage, mapping the multidisciplinary character, illustrating nature and trends, and outlining areas for further research. The process of collecting, selecting, and analyzing the most cited articles is expected to contribute to a methodical foundation for future developments of hydrogen energy storage systems and provide viable research paths toward attaining a hybrid power system.     

中国核电站节能减排问题研究

介绍核电发展现状及其节能减排意义,提出核电节能减排应坚持“引进、利用、改造、创新和安全”的“十字”原则,通过费用投入与节约、燃料节约、节电、节水、系统设备节能、三废处理等途径来实现。明确核电节能减排的意义和必要性,把握核电节能减排的原则,按照核电节能的正确途径实施,才能安全、合理地发展核能事业。     

Exergoeconomic analysis and multi objective optimization of a solar based integrated energy system for hydrogen production

In the current study, an integrated renewable based energy system consisting of a solar flat plate collector is employed to generate electricity while providing cooling load and hydrogen. A parametric study is carried out in order to determine the main design parameters and their effects on the objective functions of the system. The outlet temperature of generator, inlet temperature to organic Rankine cycle turbine, solar irradiation intensity $\left(I\right)$, collector mass flow rate $\left({\dot{m}}_{col}\right)$ and flat plate collector area $\left(A_P\right)$ are considered as five decision variables. The results of parametric study show that the variation of collector mass flow rate between 3 kg/s and 8 kg/s has different effects on exergy efficiency and total cost rate of the system. In addition, the result shows that increment of inlet temperature to the ORC evaporator has a negative effect on cooling capacity of the system. It can lead to a decrease the cooling capacity from 44.29 kW to 22.6 kW, while the electricity generation and hydrogen production rate of the system increase. Therefore, a multi objective optimization is performed in order to introduce the optimal design conditions based on an evolutionary genetic algorithm. Optimization results show that exergy efficiency of the system can be enhanced from 1.72% to 3.2% and simultaneously the cost of the system can increase from 19.59 $/h to 22.28 $/h in optimal states.     

Multi-objective optimization of the airfoil shape of Wells turbine used for wave energy conversion

Wells turbine is one of the technical systems allowing an efficient use of the power contained in oceans’ and seas’ waves with a relatively low investment level. It converts the pneumatic power of the air stream induced by an Oscillating Water Column into mechanical energy. The standard Wells turbines show several well-known disadvantages: low tangential force, leading to low power output from the turbine; high undesired axial force; usually a low aerodynamic efficiency and a limited range of operation due to stall. In the present work an optimization process is employed in order to increase the tangential force induced by a monoplane Wells turbine using symmetric airfoil blades. The automatic optimization procedure is carried out by coupling an in-house optimization library (OPAL (OPtimization ALgorithms)) with an industrial CFD (Computational Fluid Dynamics) code (ANSYS-Fluent). This multi-objective optimization relying on Evolutionary Algorithms takes into account both tangential force coefficient and turbine efficiency. Detailed comparisons are finally presented between the optimal design and the classical Wells turbine using symmetric airfoils, demonstrating the superiority of the proposed solution. The optimization of the airfoil shape leads to a considerably increased power output (average relative gain of +11.3%) and simultaneously to an increase of efficiency (+1%) throughout the full operating range.     

Multi-objective design optimization of a natural gas-combined cycle with carbon dioxide capture in a life cycle perspective

The use of multi-objective optimization techniques is attractive to incorporate environmental objectives into the design of energy conversion systems. A method to locally optimize a given process while considering its global environmental impact by using life cycle assessment (LCA) to account for avoidable and unavoidable off-site emissions for each independent material input is presented. It is applied to study the integration of a CO₂-capture process using monoethanolamine in a natural gas-combined cycle power plant, simultaneously optimizing column dimensions, heat exchange, and absorbent flow configuration with respect to two objectives: the levelized cost of electricity and its life cycle global-warming potential. The model combines a process flow-sheeting model and a separate process-integration model. After optimization using an evolutionary algorithm, the results showed that widening the absorber and generating near-atmospheric pressure steam are cost-effective options but that increasing stripper complexity is less so. With $7.80/GJ natural gas and $20/ton CO₂ handling, the minimum on-site CO₂ abatement cost reaches $62.43/ton on a life cycle basis, achieved with a capture rate of over 90%. Of this, $2.13/ton is related to off-site emissions – a specific advantage of LCA that could help industries and governments anticipate the actual future costs of CO₂ capture.     

Review on combined wind power generation and energy storage systems

储能系统由于能够实现电能的时空平移,具有响应速度快,规模化等优点,是改善风电波动性,提高其并网能力的有效手段,构建风储联合发电系统成为目前研究重点.简单介绍了风电并网对电力系统的影响及不同类型电池储能技术的发展现状,给出了部分国内外风储联合发电系统的示范工程,并分析了平滑风电功率波动,跟踪计划出力曲线和削峰填谷3种主要运行方式,重点阐述了目前风储联合发电系统控制策略和储能容量配置研究现状,对进一步开展风储联合发电系统的研究进行了展望,指出经济性仍然是制约储能技术应用的关键问题之一,提高包含储能单元的风储联合发电系统的经济性是今后的研究重点.     

Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects

Along with the continuing global warming, the environmental constraints are expected to play more and more important role in the operation of distributed energy resource (DER) systems, besides the economic objective. In this study, a multi-objective optimization model is developed to analyze the optimal operating strategy of a DER system while combining the minimization of energy cost with the minimization of environmental impact which is assessed in terms of CO₂ emissions. The trade-off curve is obtained by using the compromise programming method. As an illustrative example, the DER system installed in an eco-campus in Japan has been selected for case study. The distributed technologies under consideration include photovoltaics (PV), fuel cell and gas engine for providing electrical and thermal demands. The obtained results demonstrate that increasing the satisfaction degree of economic objective leads to increased CO₂ emissions. The operation of the DER system is more sensitive when environmental objective is paid more attention. Moreover, according to the sensitivity analysis, the consideration of electricity buy-back, carbon tax, as well as fuel switching to biogas, has more or less effect on the operation of DER systems.     

Distributed optimization of electricity-Gas-Heat integrated energy system with multi-agent deep reinforcement learning

The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES) has the characteristics of strong coupling, non-convexity, and nonlinearity. The centralized optimization method has a high cost of communication and complex modeling. Meanwhile, the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency, which is difficult to apply online. For the coordinated optimization problem of the electricity-gasheat IES in this study, we c...     

Optimal dispatch of HCNG penetrated integrated energy system based on modelling of HCNG process

Hydrogen is injected into the existing natural gas network to form hydrogen-rich compressed natural gas (HCNG), effectively addressing the high cost of hydrogen transmission. However, the traditional IES model cannot be used due to the hydrogen injection's effect on gas properties and the vague characteristics of the transport and separation processes. Therefore, this paper proposes an HCNG penetrated integrated energy system (HPIES) optimal dispatching method by comprehensively modelling the injection, transmission, and separation processes of HCNG. An HCNG mass flow rate model considering variable mixing ratio and unknown beginning flow direction is developed to describe the effect of hydrogen injection. Furthermore, the hydrogen separation model is established by introducing a combined membrane and pressure swing adsorption separation process. The tightening McCormick algorithm is proposed to solve quickly HPIES optimal dispatch problem with an acceptable feasibility check. Finally, case studies on the HPIES consisting of IEEE 39-bus power system and 20-node natural gas system validate the effectiveness of the algorithm and model. The results show that the average error is 0.031% for the bilinear term constraint.