At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in p...At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in power systems to reduce peak demands for deferring or avoiding augmentation in the network and power generation.As the battery cost is still very high at present,a comprehensive assessment is necessary to determine the optimum ESS capacity so that the maximum financial gain is achievable at the end of the batteries’lifespan.Therefore,an effective life-cycle assessment is proposed in this paper to show how the optimum ESS capacity can be determined such that the maximum net financial gain is achievable at the end of the batteries’lifespan when ESS is used to perform peak demand reductions for the customer or utility companies.The findings reveal the positive financial viability of ESS on the power grid,otherwise the projection of the financial viability is often seemingly poor due to the high battery cost with a short battery lifespan.An improved battery degradation model is used in this assessment,which can simulate the battery degradation accurately in a situation whereby the charging current,discharging current,and temperature of the batteries are intermittent on a site during peak demand reductions.This assessment is crucial to determine the maximum financial benefits brought by ESS.展开更多
The effect of two nighttime ventilation strategies on cooling and heating energy use is investigated for a prototype office building in several northern America climates, using hourly building energy simulation softwa...The effect of two nighttime ventilation strategies on cooling and heating energy use is investigated for a prototype office building in several northern America climates, using hourly building energy simulation software （DOE2.1E）. The strategies include： scheduled-driven nighttime ventilation and a predictive method for nighttime ventilation. The maximum possible energy savings and peak demand reduction in each climate is analyzed as a function of ventilation rate, indoor-outdoor temperature difference, and building thermal mass. The results show that nighttime ventilation could save up to 32% cooling energy in an office building, while the total energy and peak demand savings for the fan and cooling is about 13% and 10%, respectively. Consequently, finding the optimal control parameters for the nighttime ventilation strategies is very important. The performance of the two strategies varies in different climates. The predictive nighttime ventilation worked better in weather conditions with fairly smooth transition from heating to cooling season.展开更多
To reduce peak electricity demand and hence reduce capacity costs due to added investment of generating additional power to meet short intervals of peak demand, can enhance energy efficiency. Where it is possible to a...To reduce peak electricity demand and hence reduce capacity costs due to added investment of generating additional power to meet short intervals of peak demand, can enhance energy efficiency. Where it is possible to adjust timing and the quantity of electricity consumption and at the same time achieve the same useful effect, the value of the energy service itself remains unchanged. Peak demand management is viewed as the balance between demand and generation of energy hence an important requirement for stabilized operation of power system. Therefore, the purpose of this study was to establish the correlation between peak electricity demand management strategies and energy efficiency among large steel manufacturing firms in Nairobi, Kenya. The strategies investigated were demand scheduling, Peak shrinking and Peak shaving. Demand scheduling involves shifting predetermined loads to low peak periods thereby flattening the demand curve. Peak shrinking on the other hand involves installation of energy efficient equipment thereby shifting the overall demand curve downwards. Peak shaving is the deployment of secondary generation on site to temporarily power some loads during peak hours thereby reducing demand during the peak periods of the plant. The specific objectives were to test the relationship between demand scheduling and energy efficiency among large steel manufacturing firms in Nairobi Region;to test the correlation between peak shrinking and energy efficiency among large steel manufacturing firms in Nairobi Region;and to test the association between peak shaving and energy efficiency among large steel manufacturing firms in Nairobi Region. The study adopted a descriptive research design to determine the relationship between each independent variable namely demand scheduling, peak shrinking, peak shaving and the dependent variable, the energy efficiency. The target population was large steel manufacturing firms in Nairobi Region, Kenya. The study used both primary and secondary data. The primary data was from structured questionnaires while secondary data was from historical electricity consumption data for the firms under study. The results revealed that both peak shrinking and peak shaving were statistically significant in influencing energy efficiency among the steel manufacturing firms in Nairobi Region, each with Pearson correlation coefficient of 0.903, thus a strong linear relationship between the investigated strategy and the dependent variable, energy efficiency. The obtained results are significant at probability value of 0.005 (p 0.05). The conclusion is that peak shrinking and peak shaving have an impact on energy efficiency in the population under study, and if properly implemented, may lead to efficient utilization of the available energy. The study further recommended that peak demand management practices need to be implemented efficiently as a way of improving the overall plant load factor and energy efficiency.展开更多
Modelling of intraday increases in peak electricity demand using an autoregressive moving average-exponential generalized autoregressive conditional heteroskedastic-generalized single Pareto (ARMA-EGARCH-GSP) approach...Modelling of intraday increases in peak electricity demand using an autoregressive moving average-exponential generalized autoregressive conditional heteroskedastic-generalized single Pareto (ARMA-EGARCH-GSP) approach is discussed in this paper. The developed model is then used for extreme tail quantile estimation using daily peak electricity demand data from South Africa for the period, years 2000 to 2011. The advantage of this modelling approach lies in its ability to capture conditional heteroskedasticity in the data through the EGARCH framework, while at the same time estimating the extreme tail quantiles through the GSP modelling framework. Empirical results show that the ARMA-EGARCH-GSP model produces more accurate estimates of extreme tails than a pure ARMA-EGARCH model.展开更多
Energy planning must anticipate the development and strengthening of power grids, power plants construction times, and the provision of energy resources with the aim of increasing security of supply and its quality. T...Energy planning must anticipate the development and strengthening of power grids, power plants construction times, and the provision of energy resources with the aim of increasing security of supply and its quality. This work presents a methodology for predicting power peaks in mainland Spain’s system in the decade 2011-2020. Forecasts of total electricity demand of Spanish energy authorities set the boundary conditions. The accuracy of the results has successfully been compared with records of demand (2000-2010) and with various predictions published. Three patterns have been observed: 1) efficiency in the winter peak;2) increasing trend in the summer peak;3) increasing trend in the annual valley of demand. By 2020, 58.1 GW and 53.0 GW are expected, respectively, as winter and summer peaks in a business-as-usual scenario. If the observed tendencies continue, former values can go down to 55.5 GW in winter and go up to 54.7 GW in summer. The annual minimum valley of demand will raise 5.5 GW, up to 23.4 GW. These detailed predictions can be very useful to identify the types of power plants needed to have an optimum structure in the electricity industry.展开更多
This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand...This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md ...https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.展开更多
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 buildi...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.展开更多
When typical meteorological year (TMY) data are used as an input to simulate the energy used in a building, it is not clear which hours in the weather data file might correspond to an electric or natural gas utility’...When typical meteorological year (TMY) data are used as an input to simulate the energy used in a building, it is not clear which hours in the weather data file might correspond to an electric or natural gas utility’s peak demand. Yet, the determination of peak demand impacts is important in utility resource planning exercises and in determining the value of demand-side management (DSM) actions. We propose a formal probability-based method to estimate the summer and winter peak demand reduction from an energy efficiency measure when TMY data and model simulations are used to estimate peak impacts. In the estimation of winter peak demand impacts from some example energy efficiency measures in Texas, our proposed method performs far better than two alternatives. In the estimation of summer peak demand impacts, our proposed method provides very reasonable results which are very similar to those obtained from the Heat Wave approach adopted in California.展开更多
为了实现“双碳”目标、促进多能源互补,构建以新能源为主体的新型电力系统,文中建立了电转气-碳捕集利用与封存装置(power to gas and carbon capture utilization and storage,P2G-CCUS)耦合系统下含光热发电(concentrating solar pow...为了实现“双碳”目标、促进多能源互补,构建以新能源为主体的新型电力系统,文中建立了电转气-碳捕集利用与封存装置(power to gas and carbon capture utilization and storage,P2G-CCUS)耦合系统下含光热发电(concentrating solar power,CSP)站的虚拟电厂(virtual power plant,VPP)优化调度模型,考虑需求响应(demand response,DR)参与调峰市场(peak shaving market,PSM)制定分时电价为系统带来收益,从而进一步降低系统运行成本,并引入短期风功率预测及熵值权重法协助后期调度求解。在多能源互补层面,针对风能特点建立风电与CSP联合运行系统。在低碳化方面,建立P2G-CCUS耦合系统,其中包含两段式电转气、燃气轮机(gas turbine,GT)和碳捕集利用与封存系统的数学模型,提出以运行成本最低、碳排放量最小为目标的优化调度策略。采用MATLAB调用CPLEX进行求解,通过设置不同的场景进行对比,结果表明文中所提的优化调度策略可充分实现碳循环利用,极大限度地减少碳排放,具有显著的经济及社会效益。展开更多
Increasing consumption, changing nature of loads and the need to reduce carbon emission are some of the factors threatening electricity grid stability and reliability. Demand side management programs mainly work by sh...Increasing consumption, changing nature of loads and the need to reduce carbon emission are some of the factors threatening electricity grid stability and reliability. Demand side management programs mainly work by shifting consumption from peak to off-peak period, which inconveniences some consumers and possibly creates a new peak (Reverse Peak) in off-peak hours. Growing use of Photovoltaic solar power in residences provides an opportunity to manage grid reliability and stability in a more flexible manner, and mitigates reverse peaks. We propose a community based scheduling algorithm that guarantees access to shared power capacity and integrates residences’ solar power into the grid. Results indicate peak demand can be reduced by up to 32.1%, while energy costs can be reduced by up to 14.0%. Furthermore, coordinated discharging can mitigate reverse peaks by up to 23.4%. Encouraging and integrating green energy generation and storage in the consumer side is crucial to grid stability and reliability.展开更多
文摘At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in power systems to reduce peak demands for deferring or avoiding augmentation in the network and power generation.As the battery cost is still very high at present,a comprehensive assessment is necessary to determine the optimum ESS capacity so that the maximum financial gain is achievable at the end of the batteries’lifespan.Therefore,an effective life-cycle assessment is proposed in this paper to show how the optimum ESS capacity can be determined such that the maximum net financial gain is achievable at the end of the batteries’lifespan when ESS is used to perform peak demand reductions for the customer or utility companies.The findings reveal the positive financial viability of ESS on the power grid,otherwise the projection of the financial viability is often seemingly poor due to the high battery cost with a short battery lifespan.An improved battery degradation model is used in this assessment,which can simulate the battery degradation accurately in a situation whereby the charging current,discharging current,and temperature of the batteries are intermittent on a site during peak demand reductions.This assessment is crucial to determine the maximum financial benefits brought by ESS.
文摘The effect of two nighttime ventilation strategies on cooling and heating energy use is investigated for a prototype office building in several northern America climates, using hourly building energy simulation software （DOE2.1E）. The strategies include： scheduled-driven nighttime ventilation and a predictive method for nighttime ventilation. The maximum possible energy savings and peak demand reduction in each climate is analyzed as a function of ventilation rate, indoor-outdoor temperature difference, and building thermal mass. The results show that nighttime ventilation could save up to 32% cooling energy in an office building, while the total energy and peak demand savings for the fan and cooling is about 13% and 10%, respectively. Consequently, finding the optimal control parameters for the nighttime ventilation strategies is very important. The performance of the two strategies varies in different climates. The predictive nighttime ventilation worked better in weather conditions with fairly smooth transition from heating to cooling season.
文摘To reduce peak electricity demand and hence reduce capacity costs due to added investment of generating additional power to meet short intervals of peak demand, can enhance energy efficiency. Where it is possible to adjust timing and the quantity of electricity consumption and at the same time achieve the same useful effect, the value of the energy service itself remains unchanged. Peak demand management is viewed as the balance between demand and generation of energy hence an important requirement for stabilized operation of power system. Therefore, the purpose of this study was to establish the correlation between peak electricity demand management strategies and energy efficiency among large steel manufacturing firms in Nairobi, Kenya. The strategies investigated were demand scheduling, Peak shrinking and Peak shaving. Demand scheduling involves shifting predetermined loads to low peak periods thereby flattening the demand curve. Peak shrinking on the other hand involves installation of energy efficient equipment thereby shifting the overall demand curve downwards. Peak shaving is the deployment of secondary generation on site to temporarily power some loads during peak hours thereby reducing demand during the peak periods of the plant. The specific objectives were to test the relationship between demand scheduling and energy efficiency among large steel manufacturing firms in Nairobi Region;to test the correlation between peak shrinking and energy efficiency among large steel manufacturing firms in Nairobi Region;and to test the association between peak shaving and energy efficiency among large steel manufacturing firms in Nairobi Region. The study adopted a descriptive research design to determine the relationship between each independent variable namely demand scheduling, peak shrinking, peak shaving and the dependent variable, the energy efficiency. The target population was large steel manufacturing firms in Nairobi Region, Kenya. The study used both primary and secondary data. The primary data was from structured questionnaires while secondary data was from historical electricity consumption data for the firms under study. The results revealed that both peak shrinking and peak shaving were statistically significant in influencing energy efficiency among the steel manufacturing firms in Nairobi Region, each with Pearson correlation coefficient of 0.903, thus a strong linear relationship between the investigated strategy and the dependent variable, energy efficiency. The obtained results are significant at probability value of 0.005 (p 0.05). The conclusion is that peak shrinking and peak shaving have an impact on energy efficiency in the population under study, and if properly implemented, may lead to efficient utilization of the available energy. The study further recommended that peak demand management practices need to be implemented efficiently as a way of improving the overall plant load factor and energy efficiency.
文摘Modelling of intraday increases in peak electricity demand using an autoregressive moving average-exponential generalized autoregressive conditional heteroskedastic-generalized single Pareto (ARMA-EGARCH-GSP) approach is discussed in this paper. The developed model is then used for extreme tail quantile estimation using daily peak electricity demand data from South Africa for the period, years 2000 to 2011. The advantage of this modelling approach lies in its ability to capture conditional heteroskedasticity in the data through the EGARCH framework, while at the same time estimating the extreme tail quantiles through the GSP modelling framework. Empirical results show that the ARMA-EGARCH-GSP model produces more accurate estimates of extreme tails than a pure ARMA-EGARCH model.
文摘Energy planning must anticipate the development and strengthening of power grids, power plants construction times, and the provision of energy resources with the aim of increasing security of supply and its quality. This work presents a methodology for predicting power peaks in mainland Spain’s system in the decade 2011-2020. Forecasts of total electricity demand of Spanish energy authorities set the boundary conditions. The accuracy of the results has successfully been compared with records of demand (2000-2010) and with various predictions published. Three patterns have been observed: 1) efficiency in the winter peak;2) increasing trend in the summer peak;3) increasing trend in the annual valley of demand. By 2020, 58.1 GW and 53.0 GW are expected, respectively, as winter and summer peaks in a business-as-usual scenario. If the observed tendencies continue, former values can go down to 55.5 GW in winter and go up to 54.7 GW in summer. The annual minimum valley of demand will raise 5.5 GW, up to 23.4 GW. These detailed predictions can be very useful to identify the types of power plants needed to have an optimum structure in the electricity industry.
文摘This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.
文摘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.
文摘When typical meteorological year (TMY) data are used as an input to simulate the energy used in a building, it is not clear which hours in the weather data file might correspond to an electric or natural gas utility’s peak demand. Yet, the determination of peak demand impacts is important in utility resource planning exercises and in determining the value of demand-side management (DSM) actions. We propose a formal probability-based method to estimate the summer and winter peak demand reduction from an energy efficiency measure when TMY data and model simulations are used to estimate peak impacts. In the estimation of winter peak demand impacts from some example energy efficiency measures in Texas, our proposed method performs far better than two alternatives. In the estimation of summer peak demand impacts, our proposed method provides very reasonable results which are very similar to those obtained from the Heat Wave approach adopted in California.
文摘为了实现“双碳”目标、促进多能源互补,构建以新能源为主体的新型电力系统,文中建立了电转气-碳捕集利用与封存装置(power to gas and carbon capture utilization and storage,P2G-CCUS)耦合系统下含光热发电(concentrating solar power,CSP)站的虚拟电厂(virtual power plant,VPP)优化调度模型,考虑需求响应(demand response,DR)参与调峰市场(peak shaving market,PSM)制定分时电价为系统带来收益,从而进一步降低系统运行成本,并引入短期风功率预测及熵值权重法协助后期调度求解。在多能源互补层面,针对风能特点建立风电与CSP联合运行系统。在低碳化方面,建立P2G-CCUS耦合系统,其中包含两段式电转气、燃气轮机(gas turbine,GT)和碳捕集利用与封存系统的数学模型,提出以运行成本最低、碳排放量最小为目标的优化调度策略。采用MATLAB调用CPLEX进行求解,通过设置不同的场景进行对比,结果表明文中所提的优化调度策略可充分实现碳循环利用,极大限度地减少碳排放,具有显著的经济及社会效益。
文摘Increasing consumption, changing nature of loads and the need to reduce carbon emission are some of the factors threatening electricity grid stability and reliability. Demand side management programs mainly work by shifting consumption from peak to off-peak period, which inconveniences some consumers and possibly creates a new peak (Reverse Peak) in off-peak hours. Growing use of Photovoltaic solar power in residences provides an opportunity to manage grid reliability and stability in a more flexible manner, and mitigates reverse peaks. We propose a community based scheduling algorithm that guarantees access to shared power capacity and integrates residences’ solar power into the grid. Results indicate peak demand can be reduced by up to 32.1%, while energy costs can be reduced by up to 14.0%. Furthermore, coordinated discharging can mitigate reverse peaks by up to 23.4%. Encouraging and integrating green energy generation and storage in the consumer side is crucial to grid stability and reliability.
