Optimization of fire tube heat recovery steam generators for cogeneration plants through genetic algorithm

In the present paper, a small cogeneration system including a gas microturbine and a fire tube heat recovery steam generator (HRSG) is considered. The HRSG system is optimized considering two different objective functions. Sum of the exergy losses resulting from the gases leaving the stack and the exergy destruction due to the internal irreversibility is considered as the first objective function while the second objective function is considered to be the sum of annualized values of the capital cost and the cost of the energy loss. The cost of energy loss includes the cost of the loss by hot gases leaving the stack and the cost of the reduction in the power production in the microturbine as the result of the pressure drop in the HRSG. Finally multi-objective optimization method via genetic algorithm is employed to find the optimum values of the design parameters. A decision making process based on finding the closest point to the ideal point is used. Results of different optimum points on the Pareto front are compared and discussed. The results show that the thermodynamic optimization doesn’t lead to major improvement of the total cost of the HRSG although the thermoeconomic and multi-objective methods improve the total cost of the system due decrease in the cost of energy loss due to decrease in the pinch point.     

Active-reactive power scheduling of integrated electricity-gas network with multi-microgrids

Advances in natural gas-fired technologies have deepened the coupling between electricity and gas networks, promoting the development of the integrated electricity-gas network (IEGN) and strengthening the interaction between the active-reactive power flow in the power distribution network (PDN) and the natural gas flow in the gas distribution network (GDN). This paper proposes a day-ahead active-reactive power scheduling model for the IEGN with multi-microgrids (MMGs) to minimize the total operating cost. Through the tight coupling relationship between the subsystems of the IEGN, the potentialities of the IEGN with MMGs toward multi-energy cooperative interaction is optimized. Important component models are elaborated in the PDN, GDN, and coupled MMGs. Besides, motivated by the non-negligible impact of the reactive power, optimal inverter dispatch (OID) is considered to optimize the active and reactive power capabilities of the inverters of distributed generators. Further, a second-order cone (SOC) relaxation technology is utilized to transform the proposed active-reactive power scheduling model into a convex optimization problem that the commercial solver can directly solve. A test system consisting of an IEEE-33 test system and a 7-node natural gas network is adopted to verify the effectiveness of the proposed scheduling method. The results show that the proposed scheduling method can effectively reduce the power losses of the PDN in the IEGN by 9.86%, increase the flexibility of the joint operation of the subsystems of the IEGN, reduce the total operation costs by $32.20, and effectively enhance the operation economy of the IEGN.     

气电联合系统的协同规划方法及应用

鉴于传统规划方法分析单一能源系统存在的不足,提出了一种气电联合系统的协同规划方法,其考虑了天然气系统和电力系统的安全运行约束,以总投资成本、运行成本及碳排放成本最小为目标,建立了气电联合系统的协同规划模型,并采用改进的粒子群算法进行求解,最后对IEEE39节点系统和12节点天然气系统构建的算例进行分析。结果表明,与独立规划相比,气电联合系统协同规划所得规划方案总成本更低,碳排放量也更小。     

多时间尺度滚动优化在冷热电联供系统中的优化调度研究

为解决可再生能源和用户负荷波动所造成的能量供需不平衡问题,该文提出多时间尺度优化运行方法。该方法建立“日前-日内滚动-实时调整”的三阶段优化模型来逐级优化机组出力,日前阶段考虑环境成本,日前优化以日运行成本最低为目标,日内滚动优化以滚动控制时域内购能成本和机组出力变化惩罚成本最低为目标,实时调整优化以设备功率总调整率最小为目标,最终得到设备的实时平滑出力计划。日前阶段比较不同的系统结构对CCHP系统日运行成本的影响,并确定了最佳的系统结构。仿真结果验证了所提策略的准确性,优化结果显示：多元储能模式能降低CCHP系统的运行成本;多时间尺度滚动优化不但能提高CCHP系统的运行经济性,而且能减小设备的功率波动,减小设备运行损耗。     

计及天然气压力能的微电网储荷协调优化调度

为解决天然气输送过程中压力能的浪费问题,提高天然气能源利用率,提出将天然气压力能发电系统引入至微电网整体调度方案中。针对天然气压力能发电系统中前后端口的补热需要,将微电网中的风冷热泵补热系统与压力能发电系统进行耦合。考虑到由天然气管网中流量波动和环境因素造成的压力能出力波动问题,提出微电网储荷一体化协调优化方案,以确保系统高效稳定运行。基于上述内容,构建考虑可控电源出力成本、储能调度成本、微电网与配电网的交互成本和负荷调度成本的微电网优化调度模型,并采用Yalmip工具包编写优化调度程序。最后,通过对西南地区某调压站数据进行仿真,验证该方案的可行性与经济性。     

含分布式能源的配电网双层优化运行策略

为响应“碳达峰、碳中和”的号召,兼顾分布式能源（DG）参与下配电网运行的经济性和环保性,该文构建一种含DG的配电网双层优化模型。该模型以DG投资运行成本及环境效益为上层目标对DG进行优化配置,并以网损和电压偏移度成本为下层目标对配电网进行无功优化。针对模型特点,提出改进麻雀算法进行模型求解,增加Tent混沌映射初始化种群,引入萤火虫扰动机制改进操作算子并优化越界处理机制维持种群多样性。仿真结果表明,该模型能有效提高配电网运行的经济环保性,并验证了改进麻雀算法在求解复杂非线性非凸含离散变量的复杂组合优化问题上的优势。     

一种计及无功补偿的分布式电源优化配置方法

可再生能源以分布式电源的形式接入配电网是消纳可再生能源的重要手段,为进一步提高可再生能源的利用率,本文在分布式电源优化配置过程中考虑无功补偿设备以及储能系统的配置,建立了分布式电源、储能系统、无功补偿设备建设成本最小,系统网络损耗最小,系统电压稳定指标最优的多目标优化模型,并提出基于概率分布策略的改进遗传算法用于优化模型的求解。最后,以IEEE-33节点配电网系统为例,表明本文提出的配置方法可以改善分布式电源的波动性对配电网的不利影响,在保证系统稳定的前提下,进一步提高可再生能源利用率。     

面向碳中和的多源异质全可再生能源系统优化规划方法研究

为有效应对气候变化与能源危机,早日实现碳达峰与碳中和目标,提出多源异质全可再生能源热电气储耦合系统,在供能侧实现100%全可再生能源。首先,构建了全可再生能源系统的物理架构,并对系统内典型设备进行建模;然后,以系统年总经济成本最小为目标函数,构建了可实现系统结构、设备配置与运行策略协同优化的混合整数线性规划模型;最后,通过具体算例分析,验证了所提优化模型的正确性和可行性,确立了所提出的多源异质全可再生能源热电气储耦合系统在降低碳排放、实现全额消纳可再生能源等方面的有效性。     

Multi-objective optimization of large-scale grid-connected photovoltaic-hydrogen-natural gas integrated energy power station based on carbon emission priority

Establishing integrated energy systems is conducive for improving renewable energy utilization and promoting decarbonization. In this study, a grid-connected photovoltaic-hydrogen-natural gas integrated energy system is established to explore the effects of the configuration of the integrated energy system on its environment and economy. A multi-objective hierarchical optimization allocation model is developed, and an optimization strategy with carbon emission superior to total cost is established for the first time. Additionally, the economy, environment, and energy efficiency of the system are analyzed. A comparative study is performed using a strategy considering that the total cost is superior to carbon emission. A case study reveals that the levelized cost of electricity increases by 62.24%, levelized carbon emission of power decreases by 74.19%, and energy efficiency increases by 8.51%, as compared with those of the comparison strategy. Thus, the carbon emission of the system is reduced considerably, and the energy efficiency is improved. Although the cost of the system optimized by the proposed strategy is higher, it is economically feasible. Further analyses indicate that extending the grid-connected period would be infeasible, as it might increase the total cost and carbon emission of the system. Moreover, sensitivity analyses show that increasing the natural gas price or carbon tax base price will not reduce the carbon emission of the system.     

Robust optimization of hydrogen network

Process integration is an effective way to reduce hydrogen utility consumption in refineries. A number of graphical and mathematical programming approaches have been proposed to synthesis the optimal network. However, as the operation of refineries encounters uncertainty with the rapidly changing market and deteriorating crude oil, existing approaches are inadequate to achieve robust hydrogen network distribution due to the uncertain factors. In this paper, robust optimization is introduced as a framework to optimize hydrogen network of refineries under uncertainty. In this framework, a number of scenarios representing possible future environments are considered. Both model robust and solution robust are explicitly incorporated into the objective function. A possible optimal network distribution which is less sensitive to the change of scenarios and has the minimum total annual cost is achieved by the tradeoff between the total annual cost and the expected error. Case studies indicate that this method is effective in dealing with hydrogen network design and planning under uncertainty in comparison to the deterministic approach and the stochastic programming method.     

Standalone hybrid system energy management optimization for remote village considering methane production from livestock manure

Recently, many efforts have been done to overcome increasing fuel consumption. One of the vital solutions is utilization of standalone renewable energy resources hybrid systems. This paper attempts to develop a cost-effective methodology to ascertain optimal design and energy management for a remote village. Different energy resources such as wind and solar, fuel cell, and energy storage systems are employed to satisfy total demands including agriculture, residential, school, and health center. Different hydrogen production methods are proposed to verify the efficiency of the developed methodology. In the proposed village, different waste types such as rice husk, maize straw, livestock, and residential wastes are used to generate the required hydrogen for fuel cells to generate electricity. The main objective of the proposed methodology is minimizing the total cost of the village including total costs of each Distributed Generation (DG), cost of natural gas consumption, penalty for interruption the demands, and cost of CO₂ emission. A Particle Swarm Optimization (PSO) algorithm is employed to solve the optimization problem by minimizing the total system costs while the customers required Loss of Power Supply Probability (LPSP) is satisfied. The suggested hybrid system not only increases the renewable energy penetration but also decreases the natural gas consumption. The results achieved in the course of the present study depict that utilization of energy produced from different types of wastes plays a significant role in conserving fossil fuels and overcoming the fossil fuels depletion. It is concluded from the results that there is about a 17.46% reduction in natural gas consumption when all available waste is utilized. In addition, considering 100% availability for the animal manure reduces the natural gas consumption by reformer from 2.373 to 1.605 million liters which means reduction of the natural gas consumption is 32.35%. The results conclude that H₂ produced by livestock waste is dominating among available wastes. However, there is about 18% reduction in the Cost of Energy (COE), when 100% availability is considered for this type of waste.     

Comparative exergoeconomic analyses of the integration of biomass gasification and a gas turbine power plant with and without fogging inlet cooling

Inlet cooling is effective for mitigating the decrease in gas turbine performance during hot and humid summer periods when electrical power demands peak, and steam injection, using steam raised from the turbine exhaust gases in a heat recovery steam generator, is an effective technique for utilizing the hot turbine exhaust gases. Biomass gasification can be integrated with a gas turbine cycle to provide efficient, clean power generation. In the present paper, a gas turbine cycle with fog cooling and steam injection, and integrated with biomass gasification, is proposed and analyzed with energy, exergy and exergoeconomic analyses. The thermodynamic analyses show that increasing the compressor pressure ratio and the gas turbine inlet temperature raises the energy and exergy efficiencies. On the component level, the gas turbine is determined to have the highest exergy efficiency and the combustor the lowest. The exergoeconomic analysis reveals that the proposed cycle has a lower total unit product cost than a similar plant fired by natural gas. However, the relative cost difference and exergoeconomic factor is higher for the proposed cycle than the natural gas fired plant, indicating that the proposed cycle is more costly for producing electricity despite its lower product cost and environmental impact.     

Optimal centralized integrated energy station site approach based on energy transmission loss analysis

Centralized integrated energy station, which combines electrical power, gas, and heat supplying source together, is emerging with the development of an integrated energy system. In the previous works, the site optimization approaches of energy stations were developed for electrical power and gas sources. In these approaches, the candidate sites only include user nodes. However, with the development of the integrated energy system, the previous approach cannot be applied effectively for the system containing heating networks with high energy transmission loss. The energy transmission loss must be calculated accurately in the optimization approach rather than valued by the simple linear model. This paper aims to propose an optimal site approach of a centralized integrated energy station, in which all possible candidates of energy station sites are considered. The candidates can be any point in the whole energy supplying area. The analysis of energy transmission losses, based on nodal energy flow models, in pipelines and feeders, are incorporated. The simultaneous optimization of the station site and energy distribution networks is conducted. It is found that the energy transmission loss is significant in heating networks; therefore, network optimization should be carried out considering exact energy transmission loss. The optimal station site obtained in the present work has reduced 2.3% of the life cycle cost much more than that obtained from the previous method selecting a site from the user node. A noticeable reduction in life cycle cost, 2.6%, can also be achieved when using the proposed approach for a single energy source station. Moreover, for integrated energy systems, it is found that the adoption of the centralized integrated energy stations is more competitive comparing with the adoption of the single energy source station.     

含电转气的电—气综合能源系统低碳经济调度策略

为优化用能效率和发展低碳电力,采用综合能源系统(IES)模式耦合电力网络和天然气网络,通过电转气(P2G)技术形成电—气—电能量闭环流动,提升电力与天然气网络间的强耦合性和IES整体供能稳定性。兼顾电—气综合能源系统的经济性与低碳性,引入碳排放机制构建IES低碳经济调度模型,首先详细阐述了IES模型架构、电转气技术、碳排放交易机制等基本理论,并对天然气网络进行建模,然后采用多场景法考虑风电出力波动,以经济成本和碳交易成本最小为优化目标,构建综合能源系统新型低碳经济优化调度模型,最后通过算例对比分析了4种不同调度方案,验证了所提模型的有效性和合理性。     

换热网络模型预测控制中的滚动优化策略

针对换热网络具有非线性、滞后性、约束性等特性,提出将模型预测控制算法应用到换热网络的控制中,并对其滚动优化策略进行深入研究。首先,建立以综合费用最少的换热网络模型及目标函数,然后引入最速下降法对换热网络进行优化,以获得下一步的最优旁路开度,实时计算,实现换热网络模型预测控制中的滚动优化策略。通过算例证明:采用滚动优化策略能够快速、准确地计算出每一步的最优旁路开度,在保证出口温度达到目标值的同时使系统经济效益有所提升。     

Economic optimization of shell and tube heat exchanger based on constructal theory

In this paper, the new approach of constructal theory has been employed to design shell and tube heat exchangers. Constructal theory is a new method for optimal design in engineering applications. The purpose of this paper is optimization of shell and tube heat exchangers by reduction of total cost of the exchanger using the constructal theory. The total cost of the heat exchanger is the sum of operational costs and capital costs. The overall heat transfer coefficient of the shell and tube heat exchanger is increased by the use of constructal theory. Therefore, the capital cost required for making the heat transfer surface is reduced. Moreover, the operational energy costs involving pumping in order to overcome frictional pressure loss are minimized in this method. Genetic algorithm is used to optimize the objective function which is a mathematical model for the cost of the shell and tube heat exchanger and is based on constructal theory. The results of this research represent more than 50% reduction in costs of the heat exchanger.     

An optimal P2P energy trading model for smart homes in the smart grid

This research addresses a demand side management (DSM) system coordinated with Peer-to-Peer (P2P) energy trading among the households in the smart grid. It considers the components which have significant impact on cost optimization, e.g., storage, renewables, and microgrid. The model utilizes load and source scheduling, and energy trading strategies for cost optimization. It also addresses the inconvenience created to the users by delaying certain tasks. The contributions of the research are threefold. First, to our knowledge, this is the first optimal model which integrates DSM with P2P energy trading. The solutions of the proposed model determine optimal microgrid energy and price for P2P trading, which was not considered previously. Second, P2P energy trading in the microgrid potentially results in an unfair cost distribution among the participating households. We address this unfair cost distribution problem by employing Pareto optimality, ensuring that no households will be worse off to improve the cost of others. Third, our proposed trading strategy considers total cost optimization in a microgrid. The model utilizes all available energy to minimize energy cost. Therefore, there is a very low risk of energy waste, which is typically neglected in other energy trading strategies.     

基于排污权交易的石化企业蒸汽动力系统运行优化研究

针对以往石化企业蒸汽动力系统的节能减排仅局限于企业自身,提出基于排污权交易的蒸汽动力系统多周期运行优化模型。以操作、减排和排污权交易总费用为目标函数,增加排污总量约束,并采用线性变化参数的粒子群优化算法求解,通过企业与企业之间排污权的交易,来达到减排降耗的目的。工程实例研究结果表明,该企业的排污量超过允许排污额度277.86t,如将减排效率提高至91.8%以上,则可将排污权卖出。该模型的提出为企业管理者提供了全新的理论依据。     

An optimized control method for a high utilization ratio and fast filling speed in hydrogen refueling stations

A well-designed control system with a high utilization ratio of hydrogen and a fast filling speed are two critical objectives to ensure the reduction of cost and time required in the refueling process. In this paper, the popular three-stage refueling process is modeled with the aim to address both objectives. Using the real gas law of hydrogen, the utilization ratio of hydrogen filling is analyzed and the filling flowrate and time of each stage are evaluated. A multi-objective iterative optimization model is established and an optimization algorithm for the filling process is proposed to achieve both fast refueling and high utilization. Numerical results can be applied to the optimization of an actual hydrogen filling process. Besides, the tests show that an optimized control method can significantly improve the utilization ratio and allow refueling in a widely acceptable time.     

Multiobjective optimization for exergoeconomic analysis of an integrated cogeneration system

In this paper, a novel cogeneration system integrating Kalina cycle, CO₂ chemical absorption, process, and flash‐binary cycle is proposed to remove acid gases in the exhaust gas of solid oxide fuel cell (SOFC) system, improve the waste heat utilization, and reduce the cold energy consumed during CO₂ capture. In the CO₂ chemical absorption process, the methyldiethanolamine (MDEA) aqueous solution is utilized as a solvent, and feed temperature and absorber pressure are optimized via Aspen Plus software. The single‐objective and multiobjective optimization are carried out for the flash‐binary cycle subsystem. Results show that when the multiobjective optimization is applied to identify the exergoeconomic condition, the cogeneration system can simultaneously satisfy the high thermodynamic cycle efficiency and also the low product unit cost. The optimal results of the exergy efficiency, product unit cost, and normalized CO₂ emissions obtained by Pareto chart were 75.84%, 3.248 $/GJ, and 13.14 kg/MWhr, respectively.