Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Analysis on Carbon Emissions from Energy Consumption in Agriculture and Reduction Measures in Guangdong Province

[Objective] The aim was to study CO2 emissions from energy consumption in agricultural production in Guangdong Province and put forward feasible reduction measures.[Method] Based on the data from China Energy Statistical Yearbook and Guangdong Statistical Yearbook,CO2 emissions from agricultural energy use in Guangdong Province from 2000 to 2009 was estimated by using the formula of carbon emissions recommended by Intergovernmental Panel on Climate Change (IPCC),and corresponding reduction measures were put forward.[Result] With the rapid increase of agricultural output and energy consumption,CO2 emissions from energy consumption in agricultural production in Guangdong Province showed increasing trend from 2000 to 2009,that is to say,increasing from 423.63×104 t C million tons in 2000 to 605.99×104 t C in 2009,with annual growth rate of 4.1%.Meanwhile,carbon emissions intensity during energy consumption in agriculture went down in recent ten years,in other words,decreasing from 0.424 t C/×104 yuan in 2000 to 0.301 t C/×104 yuan in 2009,and its annual decreasing rate was 3.7%.The variation of CO2 emissions from energy consumption in agriculture mainly resulted from the increase of agricultural output,improvement of energy utilization efficiency,high carbonization in agricultural energy consumption structure and so forth.Therefore,in order to reduce CO2 emissions from energy consumption in agriculture,it is necessary to vigorously develop rural renewable energy,develop and popularize advanced technology for energy utilization,advance the energy conservation of agricultural machines,establish and improve the macroeconomic control mechanism for carbon emissions from the energy consumption in agricultural production in the further.[Conclusion] The study could provide references for the establishment of policy about reducing carbon emissions from agricultural energy consumption in Guangdong Province.

Impacts of Total Energy Consumption Control and Energy Quota Allocation on China′s Regional Economy Based on A 30-region Computable General Equilibrium Analysis

This paper examined the impacts of the total energy consumption control policy and energy quota allocation plans on China′s regional economy. This research analyzed the influences of different energy quota allocation plans with various weights of equity and efficiency, using a dynamic computable general equilibrium(CGE) model for 30 province-level administrative regions. The results show that the efficiency-first allocation plan costs the least but widens regional income gap, whereas the outcomes of equity-first allocation plan and intensity target-based allocation plan are similar and are both opposite to the efficiency-first allocation plan′ outcome. The plan featuring a balance between efficiency and equity is more feasible, which can bring regional economic losses evenly and prevent massive interregional migration of energy-related industries. Furthermore, the effects of possible induced energy technology improvements in different energy quota allocation plans were studied. Induced energy technology improvements can add more feasibility to all allocation plans under the total energy consumption control policy. In the long term, if the policy of the total energy consumption control continues and more market-based tools are implemented to allocate energy quotas, the positive consequences of induced energy technology improvements will become much more obvious.

Based on the water source heat pump system operation control and energy consumption optimization

The contradiction between the increasing material demand and resource,is the country has faced problems,to better solve the material demand and the contradiction between the environment and resources,is applied to the development of new energy,new energy,not only can alleviate people and resources,environment and resources,the contradiction between people and the environment,also can promote the sustainable development of world economy,HVAC technology has emerged a new generation of energysaving technology,HVAC has the characteristics of low consumption,low pollution,is a development of technology,to be promoted for environmentfriendly,resource-conserving society has an important role in promoting.This paper focuses on the HVAC technology,water source heat pump system operation control and energy consumption optimization,for the relevant personnel reference.

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

Optimized model-based control of main mine ventilation air flows with minimized energy consumption

In early 2018,the Boliden Garpenberg operation implemented an optimized control strategy as an addition to the existing ventilation on demand system.The purpose of the strategy is to further minimize energy use for main and booster fans,whilst also fulfilling airflow setpoints without violating constraints such as min/max differential pressure over fans and interaction of air between areas in mines.Using air flow measurements and a dynamical model of the ventilation system,a mine-wide coordination control of fans can be carried out.The numerical model is data driven and derived from historical operational data or step changes experiments.This makes both initial deployment and lifetime model maintenance,as the mine evolves,a comparably easy operation.The control has been proven to operate in a stable manner over long periods without having to re-calibrate the model.Results prove a 40%decrease in energy use for the fans involved and a greater controllability of air flow.Moreover,a 15%decrease of the total air flow into the mine will give additional proportional heating savings during winter periods.All in all,the multivariable controller shows a correlation between production in the mine and the ventilation system performance superior to all of its predecessors.

Spatial and temporal variation of energy carbon emissions in Yantai from 2001 to 2011

In order to understand the characteristics of spatial and temporal variation,as well as provide effective ideas on carbon emissions and regulatory policy in Yantai,this article analyzed spatial and temporal variation of carbon emissions in Yantai based on energy consumption statistics for a variety of energy sorts together with industrial sectors from 2001 to 2011.The results were as following:First of all,Yantai's carbon emissions grew by an average of 5.5%per year during the last 10 years,and there was a peak of 10.48 million carbon in the year of 2011.Second,compared with the gross domestic product(GDP) growth rate,the figures for energy carbon emissions growth rate were smaller;however the problem of carbon emissions were still more obvious.Furthermore,carbon emissions in Yantai increased rapidly before 2008;while after 2008,it increased more slowly and gradually become stable.Third,the energy consumption was different among regions in Yantai.For instance,the energy consumption in Longkou city was the largest,which occupied 50%of the total carbon emissions in Yantai;and the energy consumption in Chang Island was generally less than 1%of the Longkou consumption.Finally,there were relative close relationships among the spatial difference of carbon emissions,regional resources endowment,economic development,industrial structure,and energy efficiency.

Heavy Industry Share Increase Is Causing Higher Energy Consumptioni

The"11th Five-Year"plan sets the objective of reducing energy consumption per unit of GDP by 20% in five years.Readjusting industrial structure is one of the possible means to reach this goal.As for energy consumption reduction through industrial readjustment,however,present research only explores the effects of industry structural change in the six sectors such as agriculture,industry,construction,transportation and commerce,yet without considering the ramifications of sub-sector two-digit code industry structure.In this paper,we have calculated the effects of structural change in light- heavy industries on energy consumption and energy intensity from 1993 to 2005 using the factor decomposition method.As a result,we found for each percentage point gain in favour of heavy industry in the light-heavy industry mix,China’s energy consumption increases by nearly 9 million metric tons of coal equivalent.However the overall effects of structural change in light-heavy industry are less than those of sub-sector intensity factors on industrial energy intensity and energy consumption per unit of GDP.The heavy industry share gain has over recent years exerted a significant impact on industrial energy intensity.For example,78% of the abnormal increase in industrial energy intensity in 2003 could be attributed to this factor.Finally,an analytical framework for energy intensity based on this study is presented.

Low energy consumption depth control method of self-sustaining intelligent buoy

Aiming at the contradiction between the depth control accuracy and the energy consumption of the self-sustaining intelligent buoy,a low energy consumption depth control method based on historical array for real-time geostrophic oceanography(Argo)data is proposed.As known from the buoy kinematic model,the volume of the external oil sac only depends on the density and temperature of seawater at hovering depth.Hence,we use historical Argo data to extract the fitting curves of density and temperature,and obtain the relationship between the hovering depth and the volume of the external oil sac.Genetic algorithm is used to carry out the optimal energy consumption motion planning for the depth control process,and the specific motion strategy of depth control process is obtained.Compared with dual closed-loop fuzzy PID control method and radial basis function(RBF)-PID method,the proposed method reduces energy consumption to 1/50 with the same accuracy.Finally,a hardware-in-the-loop simulation system was used to verify this method.When the error caused by fitting curves is not considered,the average error is 2.62 m,the energy consumption is 3.214×10^(4)J,and the error of energy consumption is only 0.65%.It shows the effectiveness and reliability of the method as well as the advantages of comprehensively considering the accuracy and energy consumption.

Reducing Electrical Consumption in Stationary Long-Haul Trucks

On average, long-haul trucks in the U.S. use approximately 667 million gallons of fuel each year just for idling. This idling primarily facilitates climate control operations during driver rest periods. To mitigate this, our study explored ways to diminish the electrical consumption of climate control systems in class 8 trucks through innovative load reduction technologies. We utilized the CoolCalc software, developed by the National Renewable Energy Laboratory (NREL), which integrates heat transfer principles with extensive weather data from across the U.S. to mimic the environmental conditions trucks face year-round. The analysis of the CoolCalc simulations was performed using MATLAB. We assessed the impact of various technologies, including white paint, advanced curtains, and Thinsulate insulation on reducing electrical demand compared to standard conditions. Our findings indicate that trucks operating in the eastern U.S. could see electrical load reductions of up to 40%, while those in the western regions could achieve reductions as high as 55%. Such significant decreases in energy consumption mean that a 10 kWh battery system could sufficiently manage the HVAC needs of these trucks throughout the year without idling. Given that many long-haul trucks are equipped with battery systems of around 800 Ah (9.6 kWh), implementing these advanced technologies could substantially curtail the necessity for idling to power air conditioning systems.

Trend of Final Energy Intensity Changes in Lao PDR

While being developed, Lao society and economy have gradually shifted from agricultural-based to service-industrial oriented one. As a result, final energy consumption has rapidly changed. This paper studied a trend of changes in final energy intensity by looking at sector-wide energy demand and shares in gross domestic products. It was found that intensity of total final energy consumption in Lao PDR （People＇s Democratic Republic） gradually decreased during the last decades. This was resulted of high stable economic growth and comparatively slow growth in energy demand. Furthermore, Lao economy still relays mainly on less-energy intensive economic sectors, such as services and traditional agriculture. Although energy intensities of the industry, transportation and services sectors continuously decreased, but have slowed down in recent years. Moreover, energy intensity of agricultural sector continues increasing. All these facts give a ground for thinking that in the future, when socio-economic development of the country will reach higher level, there will be more energy consuming activities, then energy demand will increase while economic growth will slow down, and therefore, energy intensity is to increase. Knowledge on trend of energy consumption changes would be useful for predicting energy demand and securing energy supply in the future.

Impact of COVID-19 on the energy consumption of commercial buildings:A case study in Singapore

Numerous studies have demonstrated that commercial activities have significantly reduced during COVID-19,while there are few studies disclosing the consequent impacts on the energy consumption of commercial build-ings.This study explores the changes in energy consumption of different types of commercial buildings in Sin-gapore under the impact of the pandemic,using commercial building energy performance data from 2017 to 2020(n=540).The sampled buildings include 93 hotel buildings,303 office buildings,106 retail buildings,and 38 mixed developments.The analysis mainly used linear regression and paired sample t-test.The results showed that relative to 2019,the mean energy use intensity(EUI)of sampled commercial buildings decreased by 56.77 kWh/m^(2)in the pandemic year(2020),a plunge of 19.9%.The extent to which the EUI of each type of commercial building is affected by the pandemic is found as:mixed development>retail>office>hotel.The study also identi-fied the factors that significantly influenced the EUI of commercial buildings before and during the pandemic.The results of the study complement existing knowledge about the factors influencing energy consumption in com-mercial buildings by considering the impact of the pandemic and furthermore contribute to the improvement of energy management in commercial buildings by providing directions for building energy efficiency approaches.

Train energy simulation with locomotive adhesion model

Railway train energy simulation is an important and popular research topic.Locomotive traction force simulations are a fundamental part of such research.Conventional energy calculation models are not able to consider locomotive wheel-rail adhesions,traction adhesion control,and locomotive dynamics.This paper has developed two models to fill this research gap.The first model uses a 2D locomotive model with 27 degrees of freedom and a simplified wheel-rail contact model.The second model uses a 3D locomotive model with 54 degrees of freedom and a fully detailed wheel-rail contact model.Both models were integrated into a longitudinal train dynamics model with the consideration of locomotive adhesion control.Energy consumption simulations using a conventional model(1D model)and the two new models(2D and 3D models)were conducted and compared.The results show that,due to the consideration of wheel-rail adhesion model and traction control in the 3D model,it reports less energy consumption than the 1D model.The maximum difference in energy consumption rate between the 3D model and the 1D model was 12.5%.Due to the consideration of multiple wheel-rail contact points in the 3D model,it reports higher energy consumption than the 2D model.An 8.6%maximum difference in energy consumption rate between the 3D model and the 1D model was reported during curve negotiation.

Prospect of energy management system for large steel enterprise

The energy management system(EMS),which acts as the heart of the energy management center of a steel enterprise,is a large computer system focused on the concentrative monitor and control of the production and utilization of energy.Although Chinese steel industry was well developed in the latest decade, so far the levels of the comprehensive energy consumption per ton steel among Chinese steel enterprises are remarkably distinct,and the average value of the comprehensive energy consumption per ton steel of them has still been much higher than the value of those in developed countries.This bad situation,in the opinion of the author,partially results from the poor ability for most Chinese steel enterprises to manage the production and utilization of energy.National policies associated to energy-saving and ejection-decreasing call for steel enterprises to build the EMS;and more and more steel enterprises themselves also desire to achieve EMS projects so that they can optimize their energy production and utilization.Baosteel,the largest and most advanced steel enterprise in China,has got plenty of experience in the EMS due to its incessant practice for more than 30 years in the design,construction,application,and revampment of its EMS.In the present article,the features of an advanced EMS is described and discussed based on the design practice of the EMS of Baosteel Zhanjiang Project.An advanced EMS should be an optimized and integrated system,which possesses of the characteristic of high managing efficiency,enough openness in expansion,friendly interfaces, and simple structure.Furthermore,it could support many-sided applications,e.g.,energy related data mineing,energy network combination and co-supply,application of geographic information technology,and other technical researched on energy-saving aspects.It is known that some energy-related indexes of Baosteel have stood on a high level better than those of some worldwide famous steel enterprises.Moreover,it goes without saying that the indexes of Baosteel Zhanjiang will be better than those of present Baosteel.Therefore, one can easily expect that the new EMS of Baosteel Zhanjiang will be much more advanced,which will be more helpful to fulfil systematiclly saving of energy,to elevate the efficiency of energy utilization,to lower the comprehensive energy consumption per ton steel.

Presence Aware Power Saving Mode (PA-PSM) Enhancement for IoT Devices for Energy Conservation

The Internet of Things has brought a vision to turn the digital object into smart devices by adding an intelligence system and thereafter connecting them to the internet world. These smart devices accumulate environmental information with the help of sensors and act consequently without human intervention. The Internet of Thing is a rapidly growing industry with expected 50 - 200 billion smart devices to connect to the internet. Multi-billions of smart devices will produce a substantial amount of data to provide services to human society, although, it will lead to increase energy consumption at the highest level and drive to high energy bills. Moreover, the flood of IoT devices may also lead to energy scarcity. IoT is nowadays mainly focused on the IT industry and researchers believe the next wave of IoT may connect 1 trillion sensors by 2025. Even if these sensors would have 10 years of battery life, it will still require 275 million batteries to be replaced every day. Therefore, it is a necessity to reduce energy consumption in smart devices. “Presence Aware Power Saving Mode (PA-PSM) Enhancement for IoT Devices for Energy Conservation”, a proposed novel approach in this research paper by the help of a proposed algorithm in this research paper to reduce power consumption by individual devices within smart homes. In the proposed approach, a centralized automation controller keeps the less priority smart devices into deep sleep mode to save energy and experiments suggest the proposed system may help to reduce 25.81% of the energy consumed by smart devices within the smart home.

Energy-Efficiency Improvement in Mine-Railway Operation Using AI

The mining industry consumes an enormous amount of energy globally,the main part of which is conservable.Diesel is a key source of energy in mining operations,and mine locomotives have significant diesel consumption.Train speed has been recognized as the primary parameter affecting locomotive fuel consumption.In this study,an artificial intelligence(AI)look-forward control is developed as an online method for energy-efficiency improvement in mine-railway operation.An AI controller will modify the desired train-speed profile by accounting for the grade resistance and speed limits of the route ahead.Travel-time increment is applied as an improvement constraint.Recent models for mine-train-movement simulation have estimated locomotive fuel burn using an indirect index.An AI-developed algorithm for mine-train-movement simulation can correctly predict locomotive diesel consumption based on the considered values of the transfer parameters in this paper.This algorithm finds the mine-locomotive subsystems,and satisfies the practical diesel-consumption data specified in the locomotive’s manufacturer catalog.The model developed in this study has two main sections designed to estimate locomotive fuel consumption in different situations by using an artificial neural network(ANN),and an optimization section that applies a genetic algorithm(GA)to optimize train speed for the purpose of minimizing locomotive diesel consumption.The AI model proposed in this paper is learned and validated using real datasets collected from a mine-railway route in Western Australia.The simulation of a mine train with a commonly used locomotive in Australia GeneralMotors SD40-2(GM SD40-2)on a local railway track illustrates a significant reduction in diesel consumption along with a satisfactory travel-time increment.The simulation results also demonstrate that the AI look-forward controller has faster calculations than control systems based that use dynamic programming.

能耗双控转向碳排放双控的理论逻辑与实践路径

能耗双控向碳排放双控转变是推进碳达峰碳中和的制度保障,系统分析能耗双控转向碳排放双控的理论逻辑及实践路径,对促进企业适应国内国际市场、降低碳排放,保障中国“双碳”目标的实现有重要现实意义。能耗双控通过需求效应、技术效应和要素替代效应影响节能降碳,碳排放双控主要通过技术创新效应、技术溢出效应和产业结构升级效应的综合作用促进节能降碳,碳排放双控节能降碳的作用机制更加完善,更加注重碳排放控制,更能够精准控碳。能耗双控转向碳排放双控有利于企业能源转型、绿电消费的增加,对于“双碳”目标的实现、国际竞争力的提高具有深远的影响。能耗双控转向碳排放双控背景下,中国面临能耗双控转向碳排放双控的识别阶段、分阶段、落实阶段难题,碳市场建设不足,碳排放监管和执法体系不完善的挑战;为顺利推动能耗双控转向碳排放双控,本文提出统筹推进分阶段、差异化考核工作,通过加大碳市场覆盖范围、完善碳交易机制、优化用能权交易市场等加强碳市场建设,加强碳排放监管和法治体系建设等关键举措和推动路径。中国实现绿色低碳发展须注重能耗双控向碳排放双控转变,准确把握能耗双控转向碳排放双控,促进“双碳”目标实现。

三轴分级循环加卸载下爆破损伤顶板砂岩能量耗散试验研究

为探究不同围压环境爆破荷载损伤砂岩在循环加卸载作用下能量耗散演化规律,利用三轴试验加载装置系统对三种不同损伤度的砂岩试件开展不同围压下的分级循环加卸载试验,并结合电子数码显微镜获取不同损伤度试件细观结构,分析爆破荷载损伤、围压及加载级数对试件能量耗散及破裂破碎形态的影响规律。结果表明:(1)爆破荷载作用会对岩体造成损伤,单轴压缩荷载下振动损伤、爆破损伤试件峰值强度降幅分别为5.53%、18.87%,单轴分级循环加卸载作用对未损伤、振动损伤试件产生劣化,对爆破损伤试件产生强化作用;(2)爆源近端岩体损伤程度较高,在外荷载作用下率先发生破坏,围压的存在显著降低试件的破裂破碎程度,试件呈剪切、拉伸及压碎破坏多种模式共存;(3)循环加卸载过程中第1次循环加载试件所获取总能量及塑性变形能最大,循环次数的增加使试件塑性变形能及耗散能整体均呈现减小趋势,围压及循环加载级数的增大使试件在循环加载过程中各能量均随之增加;(4)分级循环加卸载过程中Ⅱ级循环加卸载试件耗能比要低于Ⅰ级与Ⅲ级,爆破损伤、振动损伤及未损伤试件在Ⅰ级、Ⅱ级、Ⅲ级循环加卸载过程中耗能比均值分别为15.73%、12.47%、13.95%,13.49%、12.44%、13.46%,12.07%、8.69%、11.56%,爆破荷载损伤改变岩体内部结构使得试件在循环加卸载作用下耗能占比更加显著。

MPS型磨煤机制粉系统动态模型与瞬态运行优化控制研究

为提升MPS型磨煤机制粉系统变出力过程关键参数的控制精度,该文建立并验证制粉系统动态模型,开展控制策略优化研究。在原逻辑基础上,提出考虑煤质水分信息的前馈磨煤机入口一次风温控制回路,以优化控制策略。开展煤质水分增加、给煤速率增加、磨煤机变出力等瞬态过程模拟研究,获得制粉系统关键参数瞬态特征和能耗特性,验证所提出策略的优越性。结果表明:采用优化的控制逻辑后,系统在应对煤质水分突变、煤量突变等扰动时的响应速率增加、磨煤机出口风粉温度波动范围减小50%以上、瞬态能耗下降2.4%。磨煤机在变出力过程中,稳态能耗可降低100 kW以上,制粉过程能耗降低6.82%,瞬态过程中磨煤机出口风温的波动幅度下降50%、响应时间缩短10%以上、可实现瞬态节能5.43%,保障制粉系统的运行安全并降低能耗。在燃煤发电机组中应用提出的制粉系统优化控制逻辑,可降低燃煤发电机组变负荷瞬态过程中负荷率、主汽压力等关键参数的运行偏差,提高机组的运行灵活性。

冬季不同最小通风量模式对肉种鸡育雏育成期生长性能及环控能耗的影响

为研究冬季不同最小通风量模式对肉种鸡育雏育成期舍内环境、生长性能以及环控能耗的影响,试验测试了间歇式通风和连续式通风两种不同的最小通风量通风控制模式,分别比较了两种模式下鸡舍内主要环境质量参数、环控能耗、体重均匀度和抗体效价。结果显示:第一周,连续通风温度高于间歇通风(P>0.05),相对湿度显著低于间歇通风(P<0.05),二氧化碳浓度显著高于间歇通风模式(P<0.05),第2~10周,连续通风温度极显著高于间歇通风(P<0.01),相对湿度极显著低于间歇通风(P<0.01),二氧化碳浓度极显著高于间歇通风模式(P<0.01),同时连续通风鸡舍内环境参数波动度小于间歇通风;试验期间连续通风环控总能耗(7036.01 kW·h)低于间歇通风(7633.02 kW·h),并且连续通风种鸡体重均匀度优于间歇通风;H5N1亚型禽流感病毒抗体效价显著高于间歇通风(P<0.05),H7N9亚型禽流感病毒抗体效价极显著高于间歇通风(P<0.01)。研究表明,冬季肉种鸡育雏育成期采用连续通风的最小通风量模式对比间歇通风的最小通风量模式,可以获得更加稳定的舍内环境,雏鸡生长性能以及免疫效果更优,且能源消耗更少。