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.

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.

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.

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 Dispatch for Battery Energy Storage Station in Distribution Network Considering Voltage Distribution Improvement and Peak Load Shifting

Distribution networks are commonly used to demonstrate low-voltage problems.A new method to improve voltage quality is using battery energy storage stations(BESSs),which has a four-quadrant regulating capacity.In this paper,an optimal dispatching model of a distributed BESS considering peak load shifting is proposed to improve the voltage distribution in a distribution network.The objective function is to minimize the power exchange cost between the distribution network and the transmission network and the penalty cost of the voltage deviation.In the process,various constraints are considered,including the node power balance,single/two-way power flow,peak load shifting,line capacity,voltage deviation,photovoltaic station operation,main transformer capacity,and power factor of the distribution network.The big M method is used to linearize the nonlinear variables in the objective function and constraints,and the model is transformed into a mixed-integer linear programming problem,which significantly improves the model accuracy.Simulations are performed using the modified IEEE 33-node system.A typical time period is selected to analyze the node voltage variation,and the results show that the maximum voltage deviation can be reduced from 14.06%to 4.54%.The maximum peak-valley difference of the system can be reduced from 8.83 to 4.23 MW,and the voltage qualification rate can be significantly improved.Moreover,the validity of the proposed model is verified through simulations.

Demand response:a strategy to address residential air-conditioning peak load in Australia

Rapid growth in electricity network peak demand is increasing pressure for new investment which may be used for only a few hours a year.Residential airconditioning is widely believed to be the prime cause of the rise in peak demand but,in the absence of detailed residential demand research,there is no bottom-up empirical evidence to support this supposition or to estimate its impact.This paper first examines the developments in network peak demand,at a national,network distribution,and local distribution feeder level to show recent trends in peak demand.Secondly,this paper applies analytics to the half-hourly consumption data of a sample of Ausgrid’s interval metered customers,combined with local weather data,to develop an algorithm which can recognize air-conditioner use and can identify consumption patterns and peak load.This estimate is then compared to system peaks to determine residential airconditioning’s impact on overall demand.Finally,this paper considers the future impacts of air-conditioning load on peak demand as penetration rates reaches saturation levels and new minimum energy performance standards take effect reducing new units peak impacts.

Improved peak load management control technique for nonlinear and dynamic residential energy consumption pattern

Advancements in computational technologies for residential energy management have become widespread due to increased energy usage and peak demand in households.Controlled switching of appliances during peak periods for energy reduction is one of such solutions.However,this technique may constrict the consumer’s flexibility to utilize desired appliances to fulfil their needs.This study proposes a peak load control technique based on an end-use appliance prioritization and event detection algorithm.A noteworthy feature of the technique is the users’preferred appliance(UPA),which provides the occupants with the flexibility to use any electric load to fulfill their needs at any time whether peak demand control has been initiated or not.Furthermore,to address the challenging issue around the uncertain and varying nature of the users’energy usage pattern,an empirical bottom-up approach is adopted to characterize the consumers’diverse end-use behavior.The results obtained show good performance in terms of peak demand and energy consumption reduction,with 3%to 20%and at least 14.05%in demand reduction for time of use(ToU)periods and energy savings,respectively.These offer a further perspective on demand side management,affording load users a new cost-saving energy usage pattern.

Hybrid Control Strategy for Air-conditioning Loads Participating in Peak Load Reduction Through Wide-range Transport Model

This paper proposes a hybrid control strategy of air-conditioning loads(ACLs)for participating in peak load reduction.The hybrid control strategy combines the temperature setpoint adjustment(TSA)control and on/off control together to make full use of response potentials of ACLs.The primary free transport model of ACLs has been established in literature at or near a fixed temperature setpoint.In this paper,a wide-range transport(WRT)model suitable for larger value of TSA is proposed.The WRT model can be constructed easily through the parameter of devices and indoor and outdoor temperature.To modulate the aggregate response characteristics of ACLs more friendly to the power grid,the safe protocol(SP)is adopted and integrated into the WRT model,which achieves a good unification of oscillation suppression and efficient modeling.Moreover,the hybrid control strategy is implemented based on the WRT model,and the model predictive control(MPC)controller is designed considering the tracking error and control switch cost.At last,the superiority of the hybrid control strategy is verified and the performance of ACLs for peak load reduction under this controller is simulated.The simulation results show that the hybrid control strategy could exploit the load reduction potential of ACLs fully than the TSA mode and track the reference signal more accurately.

Impact of climate change on outdoor design conditions and implications to peak loads

This study exams the impact of climate change on outdoor design conditions and peak loads of five Chinese cities over the five major climate zones for the winter and summer conditions.The design dry-bulb temperature(DDBT)and the coincident wet-bulb temperature(CWBT)for two 30-year periods;1971–2000 and 1984–2013 were analysed.It was found that the DDBT of the period 1984–2013 was higher than that of the period 1971–2000,whereas the CWBT and the corresponding outdoor enthalpy of the period 1984–2013 was lower than that of 1971–2000 at the various cumulative frequencies.This trend implies that the increment in conductive heat gain through the building envelope due to the rising temperature can be lower than the reduction in fresh air load due to the lower outdoor air enthalpy.In this case,the peak cooling loads may reduce in all five cities under study,and this is different from the widely held view that global warming will lead to more stringent outdoor design conditions,higher peak cooling loads and larger heating,ventilation and air conditioning(HVAC)plants than the current or historical status.The implications to the“free-cooling”of HVAC systems with enthalpy control are discussed as well.

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.

Long-term forecasting of annual peak load considering effects of demand-side programs

The main purpose of this research paper is to investigate the long-term effects of the proposed demandside program,and its impact on annual peak load forecasting important for strategic network planning.The program comprises a particular set of demand-side measures aimed at reducing the annual peak load.The paper also presents the program simulations for the case study of the Electricity Distribution Company of Belgrade(EDB).According to the methodology used,the first step is to determine the available controllable load of the distribution utility/area under consideration.The controllable load is presumed constant over the analyzed time horizon,and the smart grid(SG)infrastructure available.The saturation of positive effects during intense program application is also taken into account.Technical and economic input data are taken from the real projects.The conducted calculations indicate that demand-side programs can bring about the same results as the energy storage in the grids with a strong impact of distributed generation from variable renewable sources(V-RES).In conclusion,the proposed demand-side program is a good alternative to building new power facilities,which can postpone investment costs for a considerable period of time.

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。

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。

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。