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.

National Electricity Generation,Electricity Consumption and Peak Load by Grid (March 2006)

Statistics on electricity generation and time of frequency over-limit;Statistics on electricity consumption and peak load.

National Electricity Generation,Electricity Consumption and Peak Load by Grid (April 2006)

Statistics on electricity generation and time of frequency over-limit;Statistics on electricity consumption and peak load.

Peak Load Evaluation Based on the Accumulated Annual Energy

This paper presents a nonlinear approach to estimate the consumed energy in electric power distribution feeders. The proposed method uses the statistical solution algorithm to analyze the active energy monthly consumption, which enables one to estimate the energy consumption during any period of the year. The energy readings and the normalized accumulated energy profile are used to estimate the hourly consumed active power, which can be used for future planning and sizing the equipment of the electrical system. The effectiveness of the proposed method is demonstrated by comparing the simulated results with that of real measured data.

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.

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.

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.

PROPOSED LEED CREDIT FOR ELECTRICAL LOAD SHEDDING

The cost of energy is a signifi cant percentage of the operating expense for most buildings.Energy used within buildings is supplied primarily by electricity.Demand for electricity used in industrial and agricultural applications is frequently leveled by shifting portions of peak loads to non-peak periods.Leveling electrical loads reduces the utility’s carbon footprint and the cost of generating power.Resulting savings are commonly shared with customers through economic incentives.Similar techniques can be applied to control the energy demand of buildings,with benefi ts for both the electrical utility and electricity users.This paper provides an overview of electrical load-shedding techniques,outlines some of the benefi ts and problems associated with each,and discusses how some of these techniques are currently being applied to reduce the total electrical load for buildings.The paper also proposes a LEED credit which provides an incentive for owners and tenants to incorporate one or more load-shedding systems into LEED certifi ed buildings to lower peak electrical demand.

Energy-Efficient Operation of Water Systems through Optimization of Load Power Reduction in Electricity Markets

Demand response(DR) is gaining more and more importance in the architecture of power systems in a context of flexible loads and high share of intermittent generation. Changes in electricity markets regulation in several countries have recently enabled an effective integration of DR mechanisms in power systems. Through its flexible components(pumps, tanks), drinking water systems are suitable candidates for energy-efficient DR mechanisms. However, these systems are often managed independently of power system operation for both economic and operational reasons. Indeed, a sufficient level of economic viability and water demands risk management are necessary for water utilities to integrate their flexibilities to power system operation. In this paper,we proposed a mathematical model for optimizing pump schedules in water systems while trading DR blocs in a spot power market during peak times. Uncertainties about water demands were considered in the mathematical model allowing to propose power reductions covering the potential risk of real-time water demand forecasting inaccuracy.Numerical results were discussed on a real water system in France, demonstrating both economic and ecological benefits.

Long-Term Load Forecasting of Southern Governorates of Jordan Distribution Electric System

Load forecasting is vitally important for electric industry in the deregulated economy. This paper aims to face the power crisis and to achieve energy security in Jordan. Our participation is localized in the southern parts of Jordan including, Ma’an, Karak and Aqaba. The available statistical data about the load of southern part of Jordan are supplied by electricity Distribution Company. Mathematical and statistical methods attempted to forecast future demand by determining trends of past results and use the trends to extrapolate the curve demand in the future.

Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression

Medium-term forecasting is an important category of electric load forecasting that covers a time span of up to one year ahead. It suits outage and maintenance planning, as well as load switching operation. We propose a new methodol-ogy that uses hourly daily loads to predict the next year hourly loads, and hence predict the peak loads expected to be reached in the next coming year. The technique is based on implementing multivariable regression on previous year's hourly loads. Three regression models are investigated in this research: the linear, the polynomial, and the exponential power. The proposed models are applied to real loads of the Jordanian power system. Results obtained using the pro-posed methods showed that their performance is close and they outperform results obtained using the widely used ex-ponential regression technique. Moreover, peak load prediction has about 90% accuracy using the proposed method-ology. The methods are generic and simple and can be implemented to hourly loads of any power system. No extra in-formation other than the hourly loads is required.

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。