An integrated approach for improving energy efficiency of manufacturing process chains

The rising energy prices and increasingly imposing regulations have drawn attention for improving the energy efficiency of manufacturing processes. Over the past decade, different approaches have been developed to target from individual unit processes to entire manufacturing systems. However, each model or approach has limitations in terms of the efficiency improvement. Thus, an integrated approach is proposed to overcome these limitations combining unit process energy consumption models with production system simulation. The outcome potentially leads to a more energy-efficient production and process planning, which considers the dynamics of individual processes as well as the entire system. Two case studies are presented to demonstrate the approach and its benefits.     

Rebound effect and its decomposition – an analysis based on energy types in China

Rebound effect derived from energy efficiency improvement has been widely invested. However, most of studies focus on the rebound effect of the energy composite level and neither distinguish nor compare different energy types. We compare the differences in energy saving and energy rebound between primary and secondary energy sources, and further decompose the rebound effect into production rebound part and final demand component. To do so, we add a module for rebound into a comparative state China-CGE model. We design and test two simulation scenarios using the model. In Scenario 1, all production sectors’ energy efficiency of using primary energy increases by 5%. In Scenario 2, all production sectors’ energy efficiency of using secondary energy increases by 5%. The results show that Scenario 2 leads to more GDP growth and more energy saving. Our scenarios show rebound effects range between 9.6% and 27.9%, and in general are higher when energy efficiency of using primary energy sources is improved. Our decomposition analysis shows that improving energy efficiency in production sectors would stimulates energy use of final demand. Indeed, the consumption side has significant contribution to rebound in secondary energy use, especially in crude oil and gas. This study reveals that improving efficiency of using secondary energy is better than improving that of primary energy, both in terms of economic impact and energy rebound. And complementary policies that prevent energy services prices from falling too much can be adopted to reduce rebound. Controlling residential energy use could also be effective in reducing rebound, this has particular implication to economies in which residential energy consumption are far from saturation.     

Industrial energy efficiency potentials: an assessment of three different robot concepts

The rise in energy consumption and the associated costs instigate financial concerns among industrial energy consumers. For industrial processes addressing heating and cooling as well as material transformation, a wide range of energy efficiency measures have been developed and successfully implemented. In contrast to that, most robot-based operations such as pick-and-place motions or assembly tasks still use inefficient standard concepts causing high-energy consumption and high-energy costs. Thanks to a rather low payload-to-weight ratio of new robot designs, such as parallel kinematic or hybrid robot manipulators, a high potential for energy savings is expected. This article identifies potentials for energy saving concerning industrial consumers by assessing three different robot concepts. Based on a literature review, two existing designs for robots – the conventional serial robot and the parallel kinematic robot are analysed and compared with respect to the energy utilised during a typical item placement task. Afterwards, the concept of PARAGRIP, a hybrid of the two presented robot designs is introduced and examined based on simulation regarding its energy consumption. The final results demonstrate significantly different energy consumptions between the robot concepts, identifying potential savings of about 40% in a selected industrial application scenario.     

Economic feasibility of autonomous hybrid wind–diesel power systems for residential loads in hot regions: a step to mitigate the implications of fossil fuel depletion

Today, energy occupies a pivotal position around which all socio-economic activities revolve. No energy means no life, and supply of energy in a cheap, plentiful, long-sustainable and environmentally safe form is a boon for everyone. In the light of rising cost of oil and fears of its exhaustion coupled with increased pollution, the governments worldwide are deliberating and making huge strides to promote renewable energy sources such as wind. Integration of wind machines with the diesel plants is pursued widely to reduce dependence on fossil-fuel-produced energy and to reduce the release of carbon gases that cause global climate change. The literature indicates that commercial/residential buildings in the Kingdom of Saudi Arabia (KSA) consume an estimated 10–40% of the total electric energy generated. The aim of this study is to analyse wind-speed data of Dhahran (East-Coast, KSA) to assess the economic feasibility of utilising autonomous hybrid wind–diesel power systems to meet the electrical load of 100 typical residential buildings (with annual electrical energy demand of 3512 MWh). The monthly average wind speeds range from 3.3 to 5.6 m/s. The hybrid systems simulated consist of different combinations of 600 kW commercial wind machines supplemented with diesel generators. The National Renewable Energy Laboratory's hybrid optimisation model for electric renewables software was employed to perform the techno-economic analysis.

The simulation results indicate that for a hybrid system comprising 600 kW wind capacity together with a 1.0 MW diesel system (two 500 kW units), the wind penetration (at 50 m hub-height, with 0% annual capacity shortage) is 26%. The cost of generating energy (COE, $/kWh) from this hybrid wind–diesel system was found to be 0.070 $/kWh (assuming diesel fuel price of 0.1 $/l). The study exhibits that for a given hybrid configuration, the number of operational hours of diesel generator sets (gensets) decreases with an increase in the wind-farm capacity. Concurrently, emphasis has also been placed on wind penetration, un-met load, effect of hub-height on energy production and COE, excess electricity generation, percentage fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost breakdown of wind–diesel systems, COE of different hybrid systems, etc.     

Feasibility analysis of renewable hybrid energy supply options for Masirah Island

In this paper, the assessment and modelling of alternative renewable energy systems for Masirah Island is considered. The hybrid system that is simulated comprises various combinations of wind turbines and/or photovoltaic (PV) supplemented with diesel generators and short-term battery storage. It was found from the analysis that the PV–wind–diesel hybrid system, with battery unit, has the lowest cost values as compared to solar-only or wind–diesel hybrid systems. Furthermore, the study illustrates that for a given hybrid system the presence of battery storage will reduce diesel consumption. The decrease in carbon emission, the percentage of fuel savings, the cost of energy production and the effect of wind and PV penetration are also addressed in this paper. The PV–wind–diesel hybrid option is techno-economically viable for the electrification of the Masirah Island.     

Pre-feasibility study of stand-alone hybrid energy systems for applications in eco-houses

In light of rising cost of fossil fuels and fears of its depletion, coupled with the increase in energy demand and the rise in pollution levels, governments worldwide have had to look at alternative energy resources. Combining renewable energy generation like solar power with superior storage and conversion technology such as hydrogen storage, fuel cells and batteries offers a potential solution for a stand-alone power system. The aim of this paper was to assess the techno-economic feasibility of using a hybrid energy system with hydrogen fuel cell for application in an eco-house that will be built in Sultan Qaboos University, Muscat, Oman. Actual load data for a typical Omani house of a similar size as the eco-house was considered as the stand-alone load with an average energy consumption of 40 kW/day and 5 kW peak power demand. The National Renewable Energy Laboratory's Hybrid Optimisation Model for Electric Renewable software was used as a sizing and optimisation tool for the system. It was found that the total annual electrical energy production is 42,255 kW and the cost of energy for this hybrid system is 0.582 $/kW. During daylight time, when the solar radiation is high, the photovoltaics (PV) panels supplied most of the load requirements. Moreover, during the evening time the fuel cell mainly serves the house with the help of the batteries. The proposed system is capable of providing the required energy to the eco-house during the whole year using only the solar irradiance as the primary source.     

Forecasting China’s primary energy demand based on an improved AI model

An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.     

基于能源类型的中国反弹效应测算及其分解

能源问题是实现可持续发展的重大战略问题。能效改进所引起的能耗反弹问题已成为能源经济学领域的一个重要议题。针对已有研究基于复合能源维度探讨反弹效应的不足,本文通过构建一个引入反弹效应测算模块的中国静态CGE模型,研究不同类型能源效率改进的节能效果和反弹差异,并将其在生产侧和消费侧进行分解。在分别提高所有生产部门一次能源使用效率和二次能源使用效率两种情景下,我们发现提高二次能源使用效率对经济的促进作用更大,带来的能源节约也更多。就反弹效应而言,两种情景的反弹效应在9.6%-27.9%范围间,但提高一次能源使用效率带来的反弹效应要普遍大于提高二次能源使用效率带来的反弹。这意味着,能效改进的能源类型选择将关系到政策的实施效果。对反弹效应在生产侧和消费侧的分解则显示,生产侧的能效改进会刺激消费侧能耗增加,而且来自消费侧的能耗增加在二次能源品种的反弹效应中扮演了重要角色,尤其是成品油和燃气。综上,我们认为不论从经济表现还是反弹效应来看,提高二次能源使用效率都是比较理想的能源类型选择,这是以往研究未曾注意到的。同时,由于反弹效应的存在确实降低了能效政策的有效性,因此政府在制定能效政策时可通过对冲能效改进带来的能源服务价格下降来减缓能耗反弹。引导和规范居民的用能观念和用能行为也是减缓反弹效应的一个重要途径,这一点对能源需求远未饱和的发展中国家尤其重要。     

Intelligent power supply management of an autonomous hybrid energy generator

ABSTRACT

This work deals with the optimization of an hybrid energy system used to supply an isolated site. The proposed system combines a wind turbine, a photovoltaic panel, a diesel generator and a battery bank to electrify atypical home. An energy cost-effectiveness approach is adopted in accordance with meteorological data, time profile of energy consumption, and the cost of different alternative systems. A variety of performances is obtained through simulations within the Homer Pro environment. The selection of an optimal combination is based on the maximum integration of renewable energy in the suggested system with a minimum of gas emission. According to the obtained results, the overall cost of the selected installation is about 72,900 €, with 0.415€ the unit cost of a kWh electric energy provided with a contribution of renewable energy of around 86%. Simulations show a technical and financial benefits of the different configurations obtained to supply the target site. To control the proposed hybrid energy system, a supervision algorithm is developed and implemented on TMS320F28027 DSP platform. The proposed energy system aims to take advantages of renewable energy sources and shift to conventional sources only when necessary in order to ensure source autonomy and service continuity.     

Energy consumption analysis of ABS plastic parts injected in a hybrid injection moulding machine

The energy analysis of injection moulding processes is influenced by complex interactions amongst the moulded part, its material, the injection machine, the process parameters and the environmental conditions. The availability of energy usage analyses that comprehend information on specific materials and machine kind is limited. This paper reports a study that estimates and analyses the power usage profile (PUP), the specific energy consumption (SEC), and the energy distribution at an operation level of two different injected parts made of acrylonitrile-butadiene-styrene and produced in a hybrid injection moulding machine. The methodology followed by the authors incorporates an experiment carried out in an industrial facility. A large sample size, and data-acquisition and data post-processing processes to obtain an accurate PUP and SEC are used. A breakdown of the energy consumed by the injection moulding process of the parts studied at an operation level using Sankey diagrams is discussed. The study results are used to identify strategies to reduce the energy consumed by the processes. The methodology employed, and the strategies reported could be used with other plastic parts regardless of the material and machine used. The results reported are new experimental data useful input for theoretical models.     

Stand-alone wind power system with battery/supercapacitor hybrid energy storage

This paper presents a stand-alone wind power system with battery/supercapacitor hybrid energy storage. A stand-alone wind power system mainly consists of a wind turbine, a permanent magnet synchronous generator, hybrid energy storage devices based on a vanadium redox flow battery and a supercapacitor, an AC/DC converter, two bidirectional DC/DC converters, a DC/AC converter and a variable load. Several control strategies for the stand-alone wind power system are involved such as a maximum power point tracking (MPPT) control, a vanadium redox flow battery charge/discharge control and a supercapacitor charge/discharge control. The proposed MPPT control combines a sliding mode control with an extreme search control to capture maximum wind energy. This strategy avoids the necessity of measuring wind velocity, obtaining models or parameters of the wind turbine and calculating the differentials of the power generated from the wind power system and from the speed of the generator. The battery charge/discharge control maintains a constant DC bus voltage. When the battery charging/discharging current reaches the setting threshold, the charge/discharge control of the supercapacitor is triggered to limit the charging/discharging current of the battery. The simulation results show that the proposed method can rapidly respond to variations in wind velocity and load power.     

新疆能源强度影响因素及其治理策略

在发展低碳经济的趋势下,新疆过高的能源强度成为其自身发展和全国节能工作的"短板",会给我国的节能减排工作造成越来越难以解决的障碍,因此新疆面临严峻的节能减排挑战。能源强度(单位GDP能耗)是一个地区能源综合利用效率指标,受到多方面因素的影响。本文编制了1992、1997、2002和2007年新疆30部门能源投入产出表,采用投入产出结构分解方法(SDA),全面并深入分析GDP变动、单位产出能耗(即直接能源消耗系数)、技术变动和最终需求(包括消费规模、消费结构、投资规模、投资结构和净出口)变动对新疆生产能源强度的影响效应,并基于节能降耗角度分析技术变动和最终需求对产业结构变动的影响效应。结果表明:1992-2007年技术变动、消费规模、消费结构、投资规模和投资结构均对新疆生产能源强度的降低起抑制作用,并推动了产业结构中低能耗部门比重的下降。最后结合测算结果与新疆资源经济的特殊性,从技术投入、投资与消费引导以及民生扶持等方面提出了新疆能源强度治理策略建议。     

Prediction of primary energy demand in China based on AGAEDE optimal model

In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and RD inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).     

中国三大经济区域全要素能源效率研究——基于超效率DEA模型和Malmquist指数

三大经济区域能源效率的高低直接决定我国总体能源利用水平.通过研究能源效率与全要素生产率变动的关系,可以较好分析能源效率提高的原因,从丽为全国节能工作提供有益的建议.本文将知识存量纳入生产函数,使用1995-2008三大经济区域的面板数据,选取超效率DEA模型和Malmquist指数法,测算出三大经济区域的能源效率和全要素生产率,并回归分析全要素生产率分解的各指标对能源效率的影响.结果显示:长三角和珠三角区域能源效率普遍要高于环渤海区域;2007年经济危机导致三大经济区域能源效率降低,同时却迫使产业转型,技术进步增长较快.另外,能源效率的改善依赖于全要素生产率的提高,技术进步和技术效率的增长都可导致能源效率的提高,但技术进步由于回弹效应使得影响值较小.据此,本文提出了在分解节能目标时要考虑地区差异、处理经济危机时须防止能源消费反弹等政策建议.     

System dynamics modelling of hybrid renewable energy systems and combined heating and power generator

The role of energy in the present world is critical in terms of both economical development and environmental impact. Renewable energy sources are considered essential in addressing these challenges. As a result, a growing number of organisations have been adopting hybrid renewable energy system (HRES) to reduce their environmental impact and sometimes take advantage of various incentives. When a HRES is being planned, the ability to model a HRES can provide an organisation with numerous benefits including the capability of optimising sub-systems, predicting performances and carrying out sensitivity analysis. In this paper, we present a comprehensive system dynamics model of HRES and combined heating and power (CHP) generator. Data from a manufacturing company using HRES and CHP generator are used to validate the model and discuss important findings. The results illustrate that the components of a HRES can have conflicting effects on cost and environmental benefits; thus, there is a need for an organisation to make trade-off decisions. The model can be a platform to further simulate and study the composition and operating strategies of organisations that are venturing to adopt new or additional HRESs.     

A holistic approach to achieving energy efficiency for interoperable machining systems

In the twenty-first century, the continuous demand in energy resource has put sustainability on the agenda of many businesses. This is particularly true for the manufacturing industry, where a large amount of energy is consumed to sustain daily operations. This paper studies energy-efficient computer numerical control machining systems. To achieve overall energy efficiency in machining systems, several activities are involved as in the proposed research framework of a global energy-efficient machining system (GEMS). These activities are described as modules, i.e. energy monitoring, energy analysis and optimisation, energy-based optimal control and energy-enriched database. In a GEMS, one critical issue is data interoperability. Seamless data sharing enables collaboration for improving energy efficiency. Using the EXPRESS language, energy data models are proposed for each module in the GEMS, and integrated with the existing STEP-NC (STandard for Exchange of Produce-compliant Numerical Control) standards. Two case studies are presented to demonstrate how the proposed data models may be used. One study updates an existing production file to include general energy information for auditing or reviewing purposes; the other study maintains machine tool energy profiles in a database. Many other energy-efficient activities, e.g. online energy optimisation, can be realised with the proposed data models. The present study proved that interoperable energy information can enhance the energy-efficient performance of a machining system.     

可再生能源发展情景设计及评价研究

通过对当前主要的情景设计及评价方法的研究,认为目前我国可再生能源发展迅速,但初期的部分基本工作尚未完成.尤其是可再生能源的供给潜力及其经济可开发性评价.基于此,提出一种基于动态成本曲线的可再生能源发展战略情景仿真模型.动态成本曲线生成的基本原理是在静态成本曲线基础上,考虑技术进步、可再生能源外部价值对静态成本曲线的影响,从而生成不同时期的可再生能源成本曲线,进而构成可再生能源动态成本曲线.考虑不同种类可再生能源技术进步水平、外部环境价值的变化,设计不同的可再生能源发展情景.基于可再生能源动态成本曲线,并对不同的可再生能源发展情景下的投资成本、能源效益、经济效益和社会效益进行了综合评价.最后通过一个案例,分四种情景,即不考虑技术进步,低环境方案情景;不考虑技术进步,高环境方案情景;考虑技术进步,低环境方案情景;考虑技术进步,高环境方案情景;分别给出了四种情景下的装机总量、投资总额、创造就业、污染物和温室气体减排量.     

A methodology for electricity monitoring and targeting (M&T) in an Irish precision engineering SME

Abstract

Energy management in small to medium enterprises (SMEs) remains undeveloped due to competing priorities and a lack of specialist knowledge. However considerable savings can be demonstrated where companies take the time to investigate their energy use. Savings of over 20% can be achieved through changes to operational and behavioural practice. Additional benefits, such as improved production tracking and improved maintenance, can been seen which add to the value in undertaking an energy monitoring and targeting (M&T) plan. The method described involves the application of a series of ‘virtuous’ cycles of engagement and energy savings that can be applied from the highest factory level right down to a specific machine. The analysis of overall energy use from utility bills and the visualisation of typical machine power profiles aid in understanding the drivers of energy consumption and in engaging management in energy efficiency. The monitoring of specific machines in production highlights the significant consumption of electricity during non-productive times. The development of energy performance indicators is described for product variations which can be useful in tendering for business and selecting optimum production pathways. The approach is illustrated with data from a case study of a precision engineering SME based in Limerick, Ireland.     

“后补贴”时代地方政府新能源汽车补贴策略研究

新能源汽车补贴是政府为了发展新能源汽车产业所采取的一项激励政策。现有文献虽在微观层面上研究了政府补贴对新能源汽车推广的影响,但多将补贴政策限定为固定额度的政府补贴,未考虑中国特殊的两级政府补贴政策尤其是地方政府补贴对新能源汽车推广的影响,且在补贴政策的设计上未与新能源汽车的实际推广目标相结合。基于"后补贴"时代的地方政府既要实现新能源汽车推广目标又要保证补贴政策合理退坡的双重现实要求。本文依据当前中央政府为新能源汽车提供固定补贴,地方政府提供配套比例补贴以及制定价格补贴比例上限的现实情形,综合考虑新能源汽车成本、充电桩建设情况、消费者初始效用、中央政府补贴等因素对地方新能源汽车推广的影响,构建了地方政府为实现既定新能源汽车推广目标的最优补贴策略模型。研究表明:(1)对于不同效用水平的消费者,地方政府价格补贴比例上限和配套比例补贴对新能源汽车零售价格所起的作用不同;(2)地方政府补贴政策只有在小于或等于其最优配套比例或价格补贴比例上限时才会对新能源汽车推广产生正向影响。最后,还结合北京新能源汽车推广的实际情况进行了数值模拟,给出了在不同新能源汽车成本、充电桩建设情况、消费者初始效用下北京市政府为实现新能源汽车推广目标的最优补贴策略。数值模拟结果表明,当前北京新能源汽车存在地方配套比例过高、价格补贴比例上限过高等问题。在后补贴时代,北京市政府可依据新能源汽车成本下降、充电设施逐步完善、消费者初始效用提升等因素变化,对补贴进行适当退坡。数值模拟表明,所构造的最优补贴策略模型对后补贴时代地方政府新能源汽车补贴政策的制定具有较高的参考价值。     

考虑能源、环境影响的住宅建筑节能CGE模型构建

中国承诺将于2030年左右使单位国内生产总值二氧化碳排放比2005年下降60%—65%,排放总量达到峰值并争取尽早实现。我国目前的碳排放主要来自工业、交通运输业和建筑业,其中建筑业碳排放约40%,所占比重最大,而高达550亿m2的存量住宅能耗和排放是建筑业碳排放的主力。住宅建筑节能是关系到我国建筑业节能减排目标能否顺利实现的重要因素,是我国节能减排工作的重要领域。构建一个可用于衡量住宅建筑节能对资源环境及经济发展影响的可计算模型是推动住宅建筑节能工作的重要基础。本文尝试以CGE标准模型为基础,依次对住宅建筑生产模块、污染排放模块、节能住宅建筑模块、动态模块和环境福利模块进行详细构建说明。在四方面对标准模型进行扩展:第一,将生产要素扩展为资本、劳动和能源要素束,能源要素束被深化分解为清洁能源与非清洁能源束,然后再予深化细化;第二,依据差异的贸易伙伴将进出口细化为差异的国家和地区;第三,将建筑污染排放作为一个特殊部门,建立建筑污染排放模块,纳入到CGE模型中,并将污染要素纳入到效应函数中;第四,依据资本增长模型,建立动态模块。通过将住宅建筑节能作为变量扩展到标准CGE模型的方法,构建了住宅建筑节能CGE扩展模型。借助该扩展模型,可以研究非节能建筑约束、外部节能建筑与经济增长之间的内在关系,进而破解非节能建筑约束、外部节能建筑与住宅建筑节能快速发展之间难以协调的矛盾。在本文研究成果的基础上,可进一步建立相应的社会核算矩阵(SAM),并对各种函数的参数估计和敏感性检验进行实证分析。