Research on Operation Optimization of Heating System Based on Electric Storage Coupled Solar Energy and Air Source Heat Pump

For heating systems based on electricity storage coupled with solar energy and an air source heat pump(ECSA),choosing the appropriate combination of heat sources according to local conditions is the key to improving economic efficiency.In this paper,four cities in three climatic regions in China were selected,namely Nanjing in the hot summer and cold winter region,Tianjin in the cold region,Shenyang and Harbin in the severe cold winter region.The levelized cost of heat(LCOH)was used as the economic evaluation index,and the energy consumption and emissions of different pollutants were analyzed.TRNSYS software was used to simulate and analyze the system performance.The Hooke-Jeeves optimization algorithm and GenOpt software were used to optimize the system parameters.The results showed that ECSA systemhad an excellent operation effect in cold region and hot summer and cold winter region.Compared with ECS system,the systemenergy consumption,and the emission of different pollutants of ECSA system can be reduced by a maximum of 1.37 times.In cold region,the initial investment in an air source heat pump is higher due to the lower ambient temperature,resulting in an increase in the LOCH value of ECSA system.After the LOCH value of ECSA system in each region was optimized,the heating cost of the system was reduced,but also resulted in an increase in energy consumption and the emission of different pollutant gases.

Heat and power load dispatching considering energy storage of district heating system and electric boilers

As one of promising clean and low-emission energy, wind power is being rapidly developed in China.However, it faces serious problem of wind curtailment,particularly in northeast China, where combined heat and power(CHP) units cover a large proportion of the district heat supply. Due to the inherent strong coupling between the power and the heat load, the operational flexibility of CHP units is severely restricted in winter to meet the heat supply demand, which imparts considerable stress on the wind power connection to the grid. To promote the integration of wind power and enhance the flexibility of CHP units, this paper presented a method of heat and power load dispatching by exploring the energy storage ability of electric heating boilers and district heating systems. The optimization results indicate that the proposed method can integrate additional wind power into the grid and reduce the coal consumption of CHP units over the optimized period. Furthermore, the thermal inertia of a district heating system is found to contribute more to the reduction of coal consumption, whereas the electric heating boilers contribute to lower wind curtailment.

Coordinated control strategy for wind power accommodation based on electric heat storage and pumped storage

To solve the severe problem of wind power curtailment in the winter heating period caused by ＂power determined by heat＂ operation constraint of cogeneration units, this paper analyzes thermoelectric load, wind power output distribution and fluctuation characteristics at different time scales, and finally proposes a two level coordinated control strategy based on electric heat storage and pumped storage. The optimization target of the first level coordinated control is the lowest operation cost and the largest wind power utilization rate. Based on prediction of thermoelectric load and wind power, the operation economy of the system and wind power accommodation level are improved with the cooperation of electric heat storage and pumped storage in regulation capacity. The second level coordinated control stabilizes wind power real time fluctuations by cooperating electric heat storage and pumped storage in control speed. The example results of actual wind farms in Jiuquan, Gansu verifies the feasibility and effectiveness of the proposed coordinated control strategy.

Intelligent Agent-Based Architecture for Demand Side Management Considering Space Heating and Electric Vehicle Load

Contraction of resilience on generation side due to the introduction of inflexible renewable energy sources is demanding more elasticity on consumption side. It requires more intelligent systems to be implemented to maintain power balance in the grid and to fulfill the consumer needs. This paper is concerned about the energy balance management of the system using intelligent agent-based architecture. The idea is to limit the peak power of each individual household for different defined time regions of the day according to power production during those time regions. Monte Carlo Simulation (MCS) has been employed to study the behavior of a particular number of households for maintaining the power balance based on proposed technique to limit the peak power for each household and even individual load level. Flexibility of two major loads i.e. heating load (heat storage tank) and electric vehicle load (battery) allows us to shift the peaks on demand side proportionally with the generation in real time. Different parameters related to heating and Electric Vehicle (EV) load e.g. State of Charge (SOC), storage capacities, charging power, daily usage, peak demand hours have been studied and a technique is proposed to mitigate the imbalance of power intelligently.

Research on Performance Optimization of Phase Change Thermal Storage Electric Heating Device

At present, the main heating method for reducing crude oil viscosity is electric heating, and the all-day electric heating method has the problems of high energy consumption and high cost. In order to meet the needs of environmental protection and industrial production, a new type of phase change thermal storage electric heating device was designed by combining the crude oil viscosity reduction heating method with valley price and phase change materials. The results indicate that as the inlet flow rate of the working fluid increases, the outlet temperature continuously decreases. And when the outlet temperature rises to 10?C, the inlet flow rate of the device can meet the flow range of 1.413 - 2.120 m3/h. At the same time, the addition of foam nickel makes the internal temperature of PCM more uniform, and the internal temperature of PCM decreases with the decrease of porosity of foam metal. By increasing the number of electric heating rods and reducing the power of individual electric heating rods, the structure of the device was optimized to significantly improve local high-temperature phenomena. The use of this device can maintain high heat exchange efficiency and reduce production costs.

Heating Characteristics and Economic Analysis of a Controllable On-Demand Heating System Based on Off-Peak Electricity Energy Storage

The working principle of a controllable on-demand heating system based on off-peak electricity energy storage(COHSBOEES) is as follows: the cheap off-peak electricity energy is converted into heat energy for storage in the evening, and the heat energy can be extracted on demand for heating during daytime peak or flat electricity periods. This technology can promote the smooth operation of the power grid, solve the problem of peak regulation for the electrical network, and promote renewable energy consumption. Based on the controllable on-demand heating strategy, a COHSBOEES for a heating area of 1000 m^2 was designed and built. Variations in the energy consumption and operating cost of the COHSBOEES in different heating situations were analyzed. The results showed that, off-peak electricity energy storage for heating was energy saving in comparison with central heating when the heating intensity of the COHSBOEES was 70 W/m^2 and the on-demand heating rate was less than 73.0%, and the off-peak electricity energy storage for heating was energy saving at any on-demand heating rate when the COHSBOEES had a heating intensity of 50 W/m^2. After the COHSBOEES has been running for three complete heating seasons, when the off-peak electricity price was 0.25 yuan/kW·h, the energy consumption cost of the COHSBOEES can be saved by 77.6% in comparison with central heating.

Electricity Storage With High Roundtrip Efficiency in a Reversible Solid Oxide Cell Stack

We theoretically investigate the electricity storage/generation in a reversible solid oxide cell stack. The system heat is for the first time tentatively stored in a phase-change metal when the stack is operated to generate electricity in a fuel cell mode and then reused to store electricity in an electrolysis mode. The state of charge （H2 frication in cathode） effectively enhances the open circuit voltages （OCVs） while the system gas pressure in electrodes also increases the OCVs. On the other hand, a higher system pressure facilitates the species diffusion in electrodes that therefore accordingly improve electrode polarizations. With the aid of recycled system heat, the roundtrip efficiency reaches as high as 92% for the repeated electricity storage and generation.

Integrated Heat and Power Dispatch Model for Wind-CHP System with Solid Heat Storage Device Based on Robust Stochastic Theory

This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.

储液式CCS耦合P2G的综合能源系统低碳经济调度

为应对电转气P2G(power-to-gas)和碳捕集系统CCS(carbon capture system)在可再生能源出力不足时耦合失效的问题,考虑对常规CCS引入CO_(2)储液罐以加强P2G和CCS的耦合。首先,构建储液式CCS和P2G的耦合模型,利用储液罐将CCS捕集的CO_(2)时移至可再生能源富足时段,供P2G再利用;其次,构建储液式CCS与P2G耦合的电热气综合能源系统日前优化调度模型;最后,以北方某工业园区为例进行仿真。结果证明所提模型可以充分利用CCS捕集的CO_(2),从而获得更好的经济和环境效益。

氢储能系统容量双层鲁棒随机优化配置方法

氢能作为一种清洁无污染、能量密度大的二次能源,是大规模消纳新能源的理想储能载体,耦合氢储能系统和可再生能源的电热氢综合能源系统为消纳新能源提供新的思路和方案。围绕电热氢综合能源系统中如何以经济合理的方式投入氢储能设备展开研究,解决氢储能设备容量的合理配置问题以及考虑源荷不确定性对电热氢综合能源系统运行的影响,提出了一种考虑季节性存储和源荷不确定性的电热氢综合能源系统中氢储能容量优化配置方法。首先针对风电功率预测误差较大,电热气负荷预测精度较高的特点,分别采用不确定集和抽样场景描述源和荷两侧的不确定性。然后建立了考虑源荷不确定性和季节性存储的氢储能容量配置双层鲁棒随机优化模型,其上层问题以年化投资成本和运行成本的总成本最小化为目标确定氢储能系统装置容量,下层问题采用两阶段鲁棒随机优化模型模拟电热氢综合能源系统典型日在风电出力最恶劣场景下的最优运行方案。由于该模型难以直接求解,提出基于粒子群优化算法和列与约束生成算法对该类复杂模型进行求解。最后,通过对某个电热氢综合能源系统算例进行分析,算例分析结果验证了所提方法的有效性,获得的氢储能系统容量优化配置方案能够促进风电消纳和提高系统运行的经济性。

考虑阶梯式碳交易与电热需求响应的综合能源系统经济调度

在能源安全新战略背景下,推动可再生能源发展、降低碳排放将是未来发展趋势。为了消纳大规模风电的弃风功率以提升电网的调峰能力,首先考虑阶梯式碳交易机制,采用碳交易市场,利用碳交易价格达到控制碳排放的目的;其次基于分时电价形成用户用电舒适度与用热舒适度,构建电热负荷需求响应模型,在掌握电锅炉、储热装置和热需求可时移特性的基础上,通过风电供给价格弹性系数描述风电出力与电锅炉协议电价之间的变化;最后通过综合满意度指标评估负荷响应能力,构建了考虑需求响应和阶梯式碳交易机制的含蓄热式电锅炉综合能源系统优化调度模型,实现系统经济运行,并采用CPLEX求解器对所构建模型进行求解。结果表明所提方法能够有效促进风电消纳,减少碳排放量且有效降低系统运行成本。

电阻式熔盐加热器内部传热特性研究

高温熔盐电加热器是储热系统中实现电热转换的核心设备,掌握内部温度分布特性是推动其结构优化的关键。文章建立了传统电阻式熔盐加热器计算模型,采用CFD软件,通过求解三维N-S方程和能量方程,研究了加热器内部温度分布特点,得到了电加热器内部温度分布在不同工况下的变化规律。结果表明:沿流动方向上熔盐和管壁温差逐渐增加,而多组串联布置能够有效降低传热温差,在加热器连接处二者温差可从27℃降低至2℃;同时,由于内部加热管密集程度不一致,横截面内中心位置熔盐、电阻丝、填充材料温度明显高于边缘位置,且伴随着负荷的增加温度梯度也逐渐增加,当平均热流密度从5.71 W/cm^(2)增加至28.57 W/cm^(2)时,截面熔盐温差从49℃升高至68℃,可以看出,合理分配电加热管排布是降低截面温差、减小热应力的关键。

考虑氢储能和需求响应的综合能源系统双层优化配置

在双碳目标下,为改善综合能源系统功率不平衡,提高能源运营商收益,降低用户购能成本,首先,结合氢储能可作为源-荷-储的优点以及电制热的能源转换特性,设计了考虑氢储能的综合能源系统双层框架。其次,根据两种不同时间尺度,提出了一种考虑负荷侧需求响应和含电制热设备用户群的综合能源系统氢储能双层优化配置模型,上层模型结合氢储能特性进行长时间尺度优化配置;下层模型利用需求响应和电制热设备对用户群负荷进行优化,以求解短时间尺度含氢储能综合能源系统优化运行问题。再次,采用KKT条件和Big-M法将模型转为单层线性问题。最后,结果显示,通过配置氢储能以及采用电制热设备和需求响应,可提高运营商收入和新能源消纳,降低用户群成本,减少功率失衡风险。

考虑变掺氧富氧燃烧与利用LNG冷能的LAES的综合能源系统低碳经济调度

为促进风电消纳,减少火电机组的碳排放,解决综合能源系统(Integrated Energy System,IES)低碳经济运行问题,文中引入变掺氧富氧燃烧技术对燃气机组进行改造,并结合利用液化天然气(Liquefied Natural Gas,LNG)冷能的液化空气储能(Liquid Air Energy Storage,LAES),提出了一种电热气冷IES低碳经济优化策略。首先,构建含变掺氧富氧燃烧燃气机组、利用LNG冷能的LAES、电转气(Power To Gas,P2G)设备、中央空调和溴化锂制冷机的IES架构,并建立各设备的数学模型;其次,引入阶梯式碳交易机制,建立了以系统运行成本最小为目标的电热气冷IES低碳经济调度模型;最后,采用MATLAB调用GUROBI求解器对多个场景进行求解,验证了文中提出的低碳经济优化调度策略可以提高系统的风电消纳、有效降低系统运行成本,实现碳减排。

适用于一次调频能力在线监测的锅炉蓄热系数计算方法

锅炉蓄热系数是衡量火电机组一次调频能力的重要参数,实际运行中随着机组工况变化,但目前仿真中多忽略变工况下的蓄热系数变化对调频能力的影响。为准确掌握机组运行中真实的一次调频能力,需要在线确定蓄热系数。基于IEEE标准模型的框架,提出适用于一次调频能力在线监测的锅炉蓄热系数计算方法。建立考虑工质流动与传热过程的锅炉热力系统动态模型。以某1000 MW超临界机组为算例,结果表明所提出的变工况锅炉蓄热系数算法能更准确地描述一次调频过程中热力参数的动态变化。一次调频60 s内积分电量相较于IEEE标准模型减小62.4%。且低负荷下蓄热系数大,蓄热释放速率慢。该方法能根据现场实时数据确定当前工况下的蓄热系数,可应用于一次调频能力在线监测。

基于水蓄热的热源厂蒸汽调峰技术

基于工业供汽负荷波动大、昼夜偏差显著的现状,将水蓄热技术与热源厂热力生产工艺相结合,提出采用蒸汽-除盐冷水的间接换热技术、环氧富锌漆防腐技术和硬质聚氨酯发泡保温技术,并对形状、容积和高径比等罐体结构优化设计,旨在开发一种适用于工业供热的蒸汽调峰技术。实践应用表明,基于水蓄热的热源厂蒸汽调峰技术具有稳定高效、简单易操和投资收益显著等优点。本技术还可应用于燃煤机组实现深度调峰、消纳新能源发电等场景,具有重要的现实意义。

中高温热化学储热材料研究进展

可再生能源在利用过程中存在瞬时性、不稳定性以及供应与需求不匹配等问题。热化学储热技术具有储能密度大、储热温度高等特点,能够实现高效长时储热,可以将不稳定的可再生能源转化为稳定的中高温热能,并满足用户侧的波动需求。针对工作温度范围为400~1 100℃的中高温热化学储热材料,阐述了其分类、基本原理和特点,系统总结了碳酸盐、氢氧化物、氧化物、金属氢化物、氨和甲烷等典型热化学储热材料及其储热性能,分析了其结构定向调控及改性方法,并对典型的工程应用进行了介绍;分析了固-气和气-气反应体系的反应器设计及系统集成的研究进展,并针对优质热化学储能材料在开发及工业应用方面存在的问题,指出了未来的发展方向。

基于Smith模糊PID控制的固体电蓄热供热温控系统研究

固体电蓄热供热的温控系统存在滞后性,导致系统响应缓慢,抗干扰能力和能源利用率大大降低。为了解决这一问题,以某高校的固体储能供热示范工程为基础,提出了采用基于Smith模糊PID控制的方法对温控系统进行控制。实验结果显示,该温控系统的控温精度可达到±0.8℃,调节时间缩短了5 min。分析结果表明,与传统的PID控制方法相比,这种控制方法能够更有效地减小控制过程中的扰动影响,显著缩短调节时间,使系统更快进入稳定状态,有效克服了传统大滞后系统对稳定性的不利影响,温控效果优于传统PID控制。

基于蓄热装置辅助的燃料电池电动车供暖系统动态仿真

为了辅助燃料电池车辆预热,提升燃料电池在低温下的冷启动速率以及降低电动车能耗,该文提出了一种基于热泵和蓄热装置联合的燃料电池电动车供暖方案,并开展了燃料电池车辆系统动态仿真研究,对比了有无蓄热装置辅助的系统对车辆运行过程的影响。结果表明:在寒冷运行环境下,蓄热装置可确保驾驶循环工况下循环冷却液热量来源的连续性,相较于无蓄热装置的热管理系统,热泵和蓄热联合供暖方案可使空调系统能耗下降26%;利用蓄热装置辅助的供暖系统能够改善燃料电池电动车的冬季冷启动特性,优化车辆电池系统的热管理。

基于风电场景概率的电热混合储能优化配置

为有效提高风电入网的经济性和可行性,文中提出一种考虑风电典型场景概率的电热混合储能优化配置方案。首先通过场景分析,利用K-means聚类法将大量风机历史出力数据简化为6个典型出力场景,确定各场景发生的概率,其中聚类数目由肘部曲线法和Dunn指数法综合确定;其次提出电热混合储能系统控制策略,建立适用于多场景的风储联合系统模型;最后,以经济性成本最低与弃风量最小为目标,建立包含电、热负荷综合响应的容量配置优化模型,并将场景概率以权值的形式加入到目标函数中,采用粒子群算法求解模型。通过仿真分析和与其他储能配置场景对比,发现所提配置策略能够提高风电利用率约16.12%,同时减少系统综合成本约43.76%,验证了所提策略的合理性和有效性。