Cold Thermal Storage and Peak Load Reduction for Office Buildings in Saudi Arabia

This paper the chilled water and involves the investigations of ice cold thermal storage technologies along with the associated operating strategies for the air conditioning （AC） systems of the typical office buildings in Saudi Arabia, so as to reduce the electricity energy consumption during the peak load periods. In Saudi Arabia, the extensive use of AC for indoor cooling in offices composes a large proportion of the annual peak electricity demand. The very high temperatures over long summer periods, extending tYom May to October, and the low cost of energy are the key factors in the wide and extensive use of air conditioners in the kingdom. This intense cooling load adds up to the requirement increase in the capacity of power plants, which makes them under utilized during the oil：peak periods. Thermal energy storage techniques are one of the effective demand-side energy management methods. Systems with cold storage shifts all or part of the electricity requirement from peak hours to off-peak hours to reduce demand charges and/or take advantage of off-peak rates. The investigations reveal that the cold thermal energy storage techniques are effective from both technical and economic perspectives in the reduction of energy consumption in the buildings during peak periods.

Optimization of Minimum Power Output for Combined Heat and Power Units Considering Peak Load Regulation Ability

Northern China has rich wind power and photovoltaic renewable resources. Combined Heat and Power (CHP) Units to meet the load demand and limit its peaking capacity in winter, to a certain extent, it results in structural problems of wind-solar power and thermoelectric. To solve these problems, this paper proposes a plurality of units together to ensure supply of heat load on the premise, by building a thermoelectric power peaking considering thermal load unit group dynamic scheduling model, to achieve the potential of different thermoelectric properties peaking units of the excavation. Simulation examples show, if the unit group exists obvious relationship thermoelectric individual differences, the thermal load dynamic scheduling can be more significantly improved overall performance peaking unit group, effectively increase clean energy consumptive.

Management of Peak Loads in an Emerging Electricity Market

An electricity market is a trading platform provided by the actors in the electricity sector to sell and buy electricity while maintaining the stability of the transmission network and minimizing energy losses.The management of electrical energy for rational use consists of all the operations that the consumers can carry out in order to minimize their electricity bill,while the producers optimize their benefits and the transmission infrastructure.The reduction of active and reactive power consumption and the smoothing of daily and yearly load profiles are the main objectives in this work.Many developed countries already have properly functioning electricity markets,but developing countries are still in their infancy of deregulated electricity markets.The major tools used in smoothing the load profiles include decentralized generation,energy storage and demand response.A load power smoothing control strategy is proposed to smooth the load power fluctuations of the distribution network.The required power change is determined by evaluating the power fluctuation rate of the load,and then the required power change is allocated to some generators or to some stored reserves.Otherwise,the consumers are made to curtail their power consumption.The ideas proposed in this work provide important opportunities for energy policy makers and regulators.These ideas would only be feasible if there exists real-time communication among the actors in the electricity market.The results indicate that as much as 1100 Megawatt-hours of energy can be stored for smoothing the load profile,when applied to the Southern Interconnected Grid of the Cameroon power system;and that Time of Use(TOU)pricing could be used instead of rotating blackouts in case of energy shortage.

Potential of Rooftop PV Systems on Weekly Peak Load Shaving in Saudi Arabia

In recent years, high annual increasing load demand in Saudi Arabia has led to large investments in the construction of conventional power plants, which use oil or gas as the main fuel. The government is considering a large deployment of renewable energy for its 2030 vision plan. The Kingdom of Saudi Arabia is one of the best potential candidates for harvesting solar energy because of the country’s geographical location, clear sky, and vast land area. A recent energy policy announced by the government involves harvesting solar photovoltaic (PV) energy to reduce the country’s reliance on fossil fuel and greenhouse gas emissions. Using rooftop PV systems can help to shave the peak load and lead to a significant savings in the power sector through the reduction of annual installation of conventional power plants and standby generators. Employing solar PV at the end user level helps to reduce the overloading of transmission and distribution lines as well as decreases power losses. This paper will provide ratings for different rooftop PV systems that are being considered for installation for customers with various needs. The distribution of PV installation among the customers is as follows: 5% residential, 10% commercial, and 20% government. The effect of PV output power on weekly peak demand has been evaluated. The paper has also investigated the impact of the temperature on PV output power, especially during the summer. The PV power contribution is analyzed based on the assumption that weekly peak power production of solar PV coincides with weekly peak load demand. The PV model is implemented in Matlab to simulate and analyze the PV power.

Peak Load Modeling for Kingdom of Bahrain

Deriving some models to estimate the electrical demand for future for the Kingdom of Bahrain is carried out in the present study. The ambient temperature is taken into the account as well as the time factor (Year). The model was developed in away describing the electric power demand during a summer period. The estimated values of the maximum electrical load is obtained and evaluated on actual peak load data of the Kingdom of Bahrain.

Optimal Management of Energy Storage Systems for Peak Shaving in a Smart Grid

In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the energy storage is taken into consideration,then,the charge-discharge strategy for this equipment is determined.Here,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)are used to calculate the minimum and maximum load in the network with the presence of energy storage systems.The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach.Ultimately,the battery charge-discharge is managed at any time during the day,considering the load consumption at each hour.The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes.This shows the significance of such matters in terms of economy and technicality.

面向季节性短时高峰负荷的虚拟配电馈线功能架构及协同配置

传统线路增容方式面对季节性短时高峰负荷时存在线路整体利用率低、紧急功率支撑能力差等问题。因此,文中以功能虚拟化为核心,研究了传统配电馈线与储能元件融合的虚拟配电馈线功能架构,利用双端储能元件搭建虚拟电能传输通道,以应对季节性短时高峰负荷、延缓传统线路增容改造工程,并在非高峰时期提供紧急功率支撑和辅助服务功能,提高储能元件整体利用率。为充分挖掘虚拟配电馈线的灵活传输和紧急功率支撑潜力,提出了配电网线路增容优化配置模型,在保证经济性和满足高峰负荷需求的前提下,优化虚拟配电馈线储能配置。算例研究表明,虚拟配电馈线能够有效延缓传统线路增容改造工程、应对季节性短时高峰负荷;对于线路负荷增长较稳定、线路长度较长和设计延缓增容年限较短的配电区域,虚拟配电馈线的优势更加凸显。

300 MW供热机组低压缸零出力热力性能、调峰性能和经济性能分析

供热机组低压缸零出力运行可有效提升机组供热能力和调峰深度。该文基于Ebsilon软件,建立300 MW供热机组抽凝工况和低压缸零出力工况的数学模型,从热力性能、调峰性能和经济性能三个维度对常规抽凝模式和低压缸零出力模式进行分析。结果表明,低压缸零出力模式能够有效增加机组的供热能力,并降低发电标准煤耗率,当主蒸汽量为957.6 t/h时,供热量比常规抽凝供热模式提高16.25%,发电标准煤耗率下降27.2 g/kWh。低压缸零出力模式下,虽然供热机组的电负荷不具备调节能力,但其最小电负荷低于常规抽凝供热模式,适宜参与电网的深度调峰。从净收益最大化的角度,当热负荷在162~310 MW时,应采用低压缸零出力模式进行供热;当热负荷在310~375 MW时,应采用抽凝模式进行供热。

一种采用记忆神经网络和曲线形状修正的负荷预测方法

针对分布式电源和新型负荷容量累积造成负荷影响因素多元化和不确定性特性增强的问题,文中提出一种采用记忆神经网络和曲线形状修正的负荷预测方法。在负荷峰值预测中,采用最大信息系数计算负荷峰值与影响因素的非线性相关性,实现对输入特征的筛选;综合考虑负荷峰值序列的长短期自相关性和输入特征与负荷峰值的不同程度相关性,结合Attention机制和双向长短时记忆(bidirectional long short-term memory,BiLSTM)神经网络建立负荷峰值预测模型。在负荷标幺曲线预测中,通过误差倒数法组合相似日和相邻日,建立负荷标幺曲线预测模型;针对预测偏差的非平稳特征,利用自适应噪声的完全集成经验模态分解和BiLSTM网络建立误差预测模型,对曲线形状进行修正。应用中国北方某城市的区域电网负荷数据为算例,验证了所提模型的有效性。

峰前峰后循环加卸载对砂岩动力特性的影响

为深入分析砂岩峰前和峰后不同阶段的动力特性规律,开展单轴分级循环加卸载试验,综合分析下限应力对砂岩峰前峰后不同加卸载阶段的表观弹性模量、滞回圈面积、阻尼比、阻尼系数及动弹性模量等相关动力参数的影响。研究结果表明:①岩样在峰后因内部损伤加深和累积,相同下限应力下滞回曲线位于峰前右侧,且应变量增幅和最大应变增幅均随下限应力的增加而逐渐减小,说明峰后岩样虽然强度已达到极限状态,但只要岩石未完全破坏失稳,其致密性仍可以在高应力条件下的循环加卸载中得到增强。②砂岩在峰前峰后循环加卸载下的变化过程,可以通过表观弹性模量曲线斜率a值的变化得以体现,低下限应力循环加卸载试验中,致密性增强系数a_(1)>致密性劣化系数a_(2),斜率a均为正值,轴向应力对岩石整体的压密作用明显强于劣化损伤作用;随着下限应力升高,a_(2)的降低速率高于a_(1)的升高速率,a值逐渐减小甚至变为负值,说明轴向应力对岩石整体的压密作用逐渐弱于劣化损伤作用。③4组不同下限应力条件下,岩样峰后的滞回圈面积、阻尼比、阻尼系数均高于峰前状态,而动弹性模量低于峰前状态,说明岩样在峰后循环加卸载过程中内部劣化损伤程度高于峰前。

夏季尖峰电价启动条件优化研究

分时电价是电力系统开展需求响应、削减夏季空调负荷所造成负荷尖峰的重要手段。为协调各方利益、达成削峰填谷和压减电网尖峰负荷的目的,需要挖掘分析用户用电数据,优化分时电价的实施方案。提出基于余弦相似度的用户需求响应参与度的峰段负荷转移系数指标。应用该指标分行业地进行某省会电网峰段负荷转移评估,发现除充换电等行业响应积极外,大量行业用户因行业和负荷特性等原因难以参与需求响应。针对在整个夏季启动尖峰电价将会增大实体企业用电成本的问题,结合历史气象和负荷数据进行夏季尖峰电价日启动条件设置分析,发现将气温在35℃及以上的工作日设置为尖峰电价日,可在精准削减尖峰负荷的同时明显降低用户用能成本。

一种考虑峰荷-电量分摊机制和风电关键场景的输-配电网协同调度策略

风电功率的不确定性问题严重制约其消纳,因此,激发输-配电网积极性并提出合理的风电协同消纳方法具有重要意义。在建立改进峰荷-电量责任模型的基础上,提出一种基于场景法的输-配电网多目标协同调度模型。首先,将传统输-配电网峰荷责任模型、电量责任模型相结合,同时计入风电消纳、需求响应的影响并引入输配电成本分摊机制,建立改进输-配电网峰荷-电量责任模型。其次,针对输-配电网集中式和分布式风电出力的不确定性问题,基于风电功率日前基础预测场景和奇、偶时刻的极限爬坡场景构建关键风电场景集,并在此基础上提出输-配电网柔性资源协同调度策略。然后,将输-配电网改进峰荷-电量责任模型和柔性资源协同调度策略相结合,建立输-配多目标协同优化模型。最后,基于典型T6D2系统进行案例仿真,采用目标级联分析法对所提模型进行求解。结果表明,所提模型有利于支撑并促进输-配电网提升风电消纳水平,而峰荷-电量责任的边际效应有助于输-配电网有序制定对应责任权重,从而实现经济效益、风电消纳和社会效益的合理均衡。

基于BOXGBoost的配变日峰值负荷预测及重过载预警方法

为解决配变负荷日峰值预测精度不高、重过载预警误差大的问题,提出一种配变日峰值负荷预测及重过载预警方法。首先,基于时间卷积网络对配变日负荷进行预测;然后,通过贝叶斯优化极限梯度提升模型对配变日负荷峰值出现时刻及峰值区间幅值进行独立预测;最后,使用峰值预测补正日负荷预测结果并转化为预警等级,实现配变重过载预警。采用湖南某地区配电台区数据实例验证,结果表明,所提方法可实现配变日峰值负荷精确预测及准确预警重过载运行风险。

深度调峰背景下火电机组热电解耦技术路径对比分析

新能源发电在出力和发电负荷上具有波动大、不稳定的特点,为解决新能源机组上网后带来的上述问题,利用多种热电解耦方式对火电机组进行改造,并对不同技术路径进行对比分析,探究火电机组解耦潜力与调峰能力。采用EBSILON Professional软件进行模拟仿真,对不同热电解耦方案下调峰负荷空间进行评估和对比分析。计算结果表明,低压缸零出力热电解耦改造方案可以使机组的调峰能力得到最大的改善。在原最大供热负荷304.60 MW下,最小发电量下降172.21 MW,最低电负荷率下降32.70%。火电机组经过热电解耦改造可显著提高热电机组与新能源机组的协调调峰能力,提高发电单元整体发电的稳定性。

填充墙分布对RC框架结构抗连续倒塌承载力的影响

为研究填充墙分布对钢筋混凝土(reinforced concrete,RC)框架结构抗连续倒塌承载力的影响,基于ABAQUS软件建立了RC填充墙框架结构抗连续倒塌的整体式有限元模型,并与已有的试验研究结果进行对比,验证了建模方法和本构关系选取的合理性。在此基础上,对比分析了不同填充墙数量及分布形式下RC框架结构抗连续倒塌的全过程荷载-位移关系、节点水平位移与中柱竖向位移关系、塑性铰分布和峰值承载力。结果表明:位于失效柱跨的填充墙可显著提高框架结构的抗连续倒塌承载力;填充墙分布会改变框架结构塑性铰的位置,塑性铰分布越不均匀,结构的抗倒塌性能越弱;建筑设计中应避免填充墙水平不对称分布及填充墙仅在楼层两端分布的情况。

多目标优化的高渗透率电动汽车有序充电策略

电动汽车作为一种新型负载,其大量无序充电行为给电网造成了压力,影响了电网的稳定和经济性,因此提出了一种基于分时电价的电动汽车有序充电策略。以电动汽车为研究主体,分析充电模式因素对电动汽车充电负荷的影响,并引用蒙特卡洛法对预测充电负荷进行计算。在此基础上,结合分时电价建立一个以负荷峰谷差最小和用户充电费用最低为目标的多目标模型,采用改进非支配排序遗传(NSGA-Ⅱ)算法对目标函数进行求解,对比不同渗透率下的优化结果。结果表明,该控制策略降低了充电成本、减小了峰谷差,实现了负荷曲线的“削峰填谷”,且随渗透率的增加,优化效果更为显著。

电能型-功率型混合储能日前-日内协同滚动调度策略

混合储能可以利用不同类型储能在电量和功率上的不同优势。然而,在滚动优化调度中,电能型储能资源(如电池储能)容易因较短的日内滚动时间窗而限制其削峰填谷的能力;而功率型储能资源(如超级电容)又容易因较长的日前时间窗而影响其平抑风电波动的效果。针对以上两种问题,文中提出一种同时考虑电能型和功率型储能资源的日前-日内协同滚动调度策略。首先,针对电能型储能削峰填谷能力受限的问题,将日内滚动周期扩展到一天中的剩余时间,并将调度范围划分为时间分辨率不同的两个部分,从而使该部分储能资源尽可能参与削峰填谷,同时提升模型的求解效率。然后,针对功率型储能平抑波动能力受限的问题,通过对波动量的极值点统计分析,提出有限时间窗电量约束策略,从而避免该部分储能资源因过度参与削峰填谷而导致能量不足。算例表明,提出的调度策略能够发挥不同储能资源的调度潜力,在削峰填谷的同时平抑风电波动,提升风电消纳能力。