Search

Abstract With the revolution of the traditional economic and social pattern based on centralized fossil energy consumption, the regional integrated energy system (RIES) has gained rapid development in recent years for achieving higher energy efficiency. This paper expands the Demand Response (DR) concept to the RIES and presents an optimal operation model of RIES considering the DR mechanism on the energy price. In this paper, a comprehensive DR strategy combining energy price and different loads is firstly developed to exploit the demand flexibility of RIES in the DR model established. Based on the DR modeling of the RIES, an operation optimization model with environmental, economic benefits and energy supply reliability as objective functions has been firstly established in detail. Secondly, a complete scheduling scheme is built based on the energy consumption characteristics and system operation characteristic of the integrated energy system. The model presented could reduce the cost of system without causing a significant amount of environmental pollution, and improve the energy efficiency of the RIES efficiently. Besides, the scheduling strategy proposed could also provide support for the operation strategy of integrated energy system under the energy development. Hopefully, this paper will provide reference for future research and engineering projects on DR programs in the RIES. Highlights • The typical structure of the RIES is introduced. • A DR model suitable for the RIES considering different loads is established. • An optimal operation model of the RIES based on DR is established. • The load in the RIES is affected not only by energy price but also by other loads. [ABSTRACT FROM AUTHOR]

Industry poses one of the biggest challenges in the renewable energy transition. In this paper, fossil fuels in the European industrial sector are replaced by renewable energy using a novel tool, IndustryPLAN, a planning tool for the assessment of national industrial sectors. In a bottom-up approach, each industry sub-sector is addressed with energy efficiency and fossil fuel replacement measures based on best available and innovative technologies, and in a top-down approach, the fuel and electricity consumption per country is analysed and decarbonised. The results indicate that: 1. Known technologies can decarbonise most of the industrial sector; 2. Costs and efficiencies are improved by energy savings and electrification; 3. Limiting bioenergy consumption is a critical challenge, emphasising the key role of energy savings and electrification, and the alternative of using hydrogen or hydrogen-based electrofuels will make the transition more expensive and induce energy losses. A full transition to renewable energy and a decarbonised industry sector may be possible before 2050, however, this requires that all investments are sustainable from 2030 onwards and that grid electricity is fully decarbonised. This paper presents several pathways toward 100% renewable energy supply in the European industrial sector and discusses the implications of the outlined scenarios. • Four tangible 100% renewable energy scenarios for industry in EU27 + UK are established. • 100% renewable energy in industry is feasible before 2050. • Energy efficiency improvements are essential to limit biomass consumption. • Industry energy transition needs to be prioritised in short- and long-term planning. [ABSTRACT FROM AUTHOR]

Energy efficiency is a critical issue in data centre management, which is the foundation for cloud computing. The VM placement has a considerable impact on a data centre's energy efficiency and resource utilisation. The assignment of VMs to PMs is an NP-hard problem without an easy way to find an optimal solution, particularly in large-scale data centres. In this study, the VM placement problem is formulated as a constrained optimisation problem. The Genetic Algorithm (GA) is a suitable method for solving this problem in terms of the quality of the solution. However, GA is time-consuming to obtain an optimal solution in the large scale optimisation problem. Therefore, this paper focuses on accelerated GA for energy-efficient VM placement. As the most time-consuming element of the GA is the calculation of its fitness function, this paper simplifies this calculation through a new fitness function in GA. Simulation results of small-, medium-, and large-scale data centres demonstrate that our accelerated GA is faster than the standard GA and gives better quality of solution than the First Fit Decreasing (FFD) algorithm, respectively. The findings of our GA with the new fitness function reveal an 8% energy saving for our GA compared to FFD and a 66% reduction in our GA execution time compared to the standard GA with standard energy formula as a fitness function. The number of generations in our GA is reduced by about 50% in comparison with the standard GA. Moreover, we started with 3000 PMs in the large-scale dataset, and only 1086 PMs were actually used after running our GA. Therefore, we may switch off far more PMs for energy savings from our GA results than those from the standard GA. • Virtual machine placement problem formulated as a constrained optimisation problem. •It focuses on accelerated genetic algorithm for virtual machine placement. •Our algorithm can minimise residual resources using Taylor extension. •Our solution quality is better than FFD and standard genetic algorithm. •It reduces execution time and energy in large scale data centres. [ABSTRACT FROM AUTHOR]

The deployment of electric vehicles (EVs) is rapidly progressing worldwide, and energy efficiency is an important indicator for both the economy and the environment. It is necessary to verify whether EVs are more energy efficient than internal combustion engine (ICE) vehicles. However, studies have yet to evaluate the energy efficiency of EVs using the data envelopment analysis (DEA) approach. To fill this research gap, this paper evaluated the energy efficiency of EVs for road passenger transportation using a slacks-based measure (SBM) approach in six European countries from 2012 to 2018. EVs have been separated from the entire transport sector and compared to ICE vehicles. In the case of EVs that use electricity as fuel, the primary energy supply must be used as energy input to reflect conversion loss during power generation. The primary energy supply was calculated by applying the power generation efficiency of each country for use as an energy input to reflect conversion loss. EVs were more energy efficient than ICE vehicles in four out of six countries but less energy efficient in two countries. Based on the measured slack results, the potential energy savings were quantified, and the main factors in reducing energy efficiency were identified. • The energy efficiency of EVs for road passenger transportation was analyzed. • A SBM model based on DEA was used for this analysis for the first time. • Primary energy supply was used as an input to reflect the energy conversion loss. • EVs were more efficient than ICE vehicles in Belgium, Germany, Norway, and the UK. • Large labor force (Greece) and energy consumption (Italy) led to low EV efficiency. [ABSTRACT FROM AUTHOR]

High energy efficiency for low operating cost of desalination can be obtained from operational optimizations as well as component-wise innovations. This paper is concerned with an energy-efficient operation for reverse osmosis (RO) desalination process involving a joint control of multiple modules. Energy resource considered for desalination is of two types: intermittent solar energy and steady grid energy. With solar energy, the energy efficiency is measured by total permeate production obtained while the solar energy is available. With grid energy, the energy efficiency is measured by the power consumed to get unit permeate production rate. Achieving maximum energy efficiency is equivalent to solving constrained optimization. For the constrained optimization, obligatory constraints are given by the permissible ranges of trans-membrane pressure on RO membrane and total dissolved solids of permeate, and optional constraint is given by the permissible range of permeate production rate. Constraints as well as the objective function are modeled by the empirical second order equations in terms of control variables of multiple modules. Jointly optimal values of the control variables are found by the sequential quadratic programming. Experimental results obtained by the jointly optimal control demonstrate superior performances as compared to those acquired by marginally optimal control schemes. [ABSTRACT FROM AUTHOR]

The fast growing Revenue Passenger Kilometers and the relatively lagged energy supply of aviation industry impels the airlines to improve energy efficiency. In this paper, we focus on evaluating and analyzing influencing factors for airline energy efficiency. Number of employees and aviation kerosene are chosen as the inputs. Revenue Ton Kilometers, Revenue Passenger Kilometers and total business income are the outputs. Capital stock is selected as the dynamic factor. A new model, Virtual Frontier Dynamic Slacks Based Measure, is proposed to calculate the energy efficiencies of 21 airlines from 2008 to 2012. We verify two important properties to manifest the advantages of the new model. Then a regression is run to analyze the influencing factors of airline energy efficiency. The main findings are: 1. The overall energy efficiency of Malaysia Airlines is the highest during 2008–2012.2. Per capita Gross Domestic Product, the average service age of fleet size and average haul distance have significant impacts on the efficiency score. 3. The difference between full-service carriers and low-cost carriers has no significant effects on airline energy efficiency. [ABSTRACT FROM AUTHOR]

Energy efficiency in industries is one of the dominating challenges of the 21st century. Since the release of the eco-design directive 2005/32/EC in 2005, great research effort has been spent on the energy efficiency assessment for energy using products. The ISO (International Organization for Standardization) standardization body (ISO/TC 39 WG 12) currently works on the ISO 14955 series in order to enable the assessment of energy efficient design of machine tools. A missing piece for completion of the ISO 14955 series is a metric to quantify the design of machine tools regarding energy efficiency based on the respective assembly of components. The metric needs to take into account each machine tool components' efficiency and the need-oriented utilization in combination with the other components while referring to efficiency limits. However, a state of the art review reveals that none of the existing metrics is feasible to adequately match this goal. This paper presents a metric that matches all these criteria to promote the development of the ISO 14955 series. The applicability of the metric is proven in a practical case study on a turning machine. [ABSTRACT FROM AUTHOR]

Utilizing the global DEA (data envelopment analysis), this paper analyzes China's energy efficiency from both static and dynamic perspectives based on China's provincial panel data for the period of 2001–2010. We present the evolution of energy efficiency in China from 2001 to 2010, and identify the key factors influencing the energy efficiency from the aspects of technical progress, productive scale and management level. The results show that there was an overall declining trend for China's energy efficiency from 2001 to 2005, and technical regress and the decrease in scale efficiency were the main reasons for this decline. Then an overall rising trend appeared during 2005–2010, and technical progress was the most important motivation for this increase. Moreover, among the three main regions in China, the eastern China was leading in the energy efficiency during the sample period, while the energy efficiency in western China fell far behind since the beginning. And the energy efficiency in central China was in the middle. This indicates that west region may be China's promising growth engine of energy efficiency in the future, and further technical progress is thought to be the key motivation for this improvement. [ABSTRACT FROM AUTHOR]

Energy systems are in a state of transition due to national energy and climate policies. The Finnish Government has declared a national target of achieving carbon neutrality by 2035. This will require further reductions in carbon intensity of the Finnish energy generation mix. Some of the energy related emission reductions could simultaneously be achieved through effective energy efficiency measures in the buildings sector. In this paper, the effectiveness of these measures is studied in alternative long-term energy system scenarios with varying CO 2 reduction targets for the energy supply sector until 2050. The results show that initial carbon intensity of energy mix has a significant effect on the achievable CO 2 emission reductions of demand-side measures. Moreover, assigned system boundaries can significantly affect the results, especially in a low-carbon energy system, where energy savings mostly reduce the use of wood-based biomass in the energy production. Furthermore, long-term perspective for identifying the environmental effects of an energy efficiency measure is recommended, since they often have a long economic lifetime and due to structural changes in the energy system, the marginal energy production unit changes over its lifetime. Consequently, the CO 2 emission reduction potential of an energy efficiency measure can vary over its lifetime. • Building sector demand-side measures are analysed in broader energy system context. • CO 2 emission reduction potential depends on the carbon intensity of marginal unit. • Marginal emission factor can change during the lifetime of demand-side measure. • System boundaries can significantly affect the results in a low carbon energy system. [ABSTRACT FROM AUTHOR]

The use of thermal energy storage (TES) allows to cleverly exploit clean energy resources, decrease the energy consumption, and increase the efficiency of energy systems. In the past twenty years, TES has continuously attracted researchers generating an extensive scientific production growing year by year. Despite the large number of publications, there are some aspects of TES that need to be further investigated in order to assess its complete feasibility. This paper gives a perspective on the state-of-the-art of TES, highlighting the research trends and the research gaps of different TES technologies. Using bibliometric analyses techniques, the main research gaps identified were related to economic, environmental, and social aspects. • A bibliometric analysis on thermal energy storage was carried out. • The state-of-the-art, research trend and research gaps of TES are discussed. • The main research gaps are related to economic, environmental and social aspects. [ABSTRACT FROM AUTHOR]

There remain major concerns over the increasing use and waste of materials and energy resources in multiple manufacturing sectors. To address these concerns, some manufacturers have begun to align their R&D efforts with the circular economy principles: Reduce, Reuse, Recycle and Replace (RRRR). Focusing on advanced composites manufacturing sector, this paper presents an innovative approach for process design and analysis of a new waste heat recovery system for carbon fiber manufacturing. Namely, the stabilization process is known to be one of the most critical steps in the production of carbon fibers, as it consumes the most energy, has the largest factory footprint, is a complex system composed of many components, and is the largest capital investment within the factory line. The heat recovery system in this step of the manufacturing can notably reduce energy consumption, emission, cost, and conversion time, while aiming to maintain the mechanical properties of the final product. Here, via an actual industry-scale fibre production setting, the energy consumption factors were obtained and used to model the total energy and its balance in the thermal stabilization step. Two machine learning approaches with limited data, Artificial Neural Network and Non-Linear Regression were then constructed to predict the energy consumption. Results suggested that using the recovery system by means of a heat exchanger, can yield over 62.7 kW recovery, corresponding to 64% of total exhausted energy from the entire process. The electric energy consumption was reduced from 73.3 kW to 10.2 kW, which corresponded to an 86% improvement in the total energy efficiency. The model also confirmed that, by preheating the make-up air with the recovered energy, the energy performance index of the thermal stabilization can be increased from 0.08 to 0.44, along with a reduction in the process carbon footprint by 28.5 t/y. This is especially crucial as we are turning on smart digitalisation in manufacturing inspired by industry 4.0 concept with limited data. Waste heat recovery system for stabilization process of carbon fiber manufacturing. [Display omitted] • Measurement of key factors in energy and resource flows in the carbon fiber stabilization process. • Development of two machine learning models for prediction of the stabilization energy consumption. • Reducing the energy consumption of stabilization process through a heat recovery system. • The electric energy consumption can be improved up to 86% in the total energy efficiency. • The ANN model confirmed that the energy performance index can be increased from 0.08 to 0.44. [ABSTRACT FROM AUTHOR]

Maximising energy efficiency is essential for an energy system based on renewable or non-renewable energy sources to minimise fuel demand. Process Integration methodologies for specific energy types (thermal and power) have been well developed in recent years for enhancing energy efficiency. However, the interaction between different types of energy (thermal and power) within a single system could be more deeply studied to achieve the ultimate goal of maximising energy and exergy efficiency. This research work extends the previously developed Locally Integrated Energy Sector (LIES) concept, which integrates the energy systems (thermal and power) of industrial, commercial and residential buildings with thermal energy storage and batteries. The LIES concept aims to reduce overall energy consumption and to enhance overall energy efficiency and power cogeneration. In the present paper, a comprehensive targeting framework is introduced for designing and optimising a combined energy system using a Process Integration (i.e. Pinch Analysis) approach. Steam turbines connect the thermal and power systems, which, in this case, the turbines generate power from waste heat. The on-grid and off-grid power supply options are also considered in this framework. The case study concludes that the lowest energy cost system requires a heat storage systems with let-down in between, power cogeneration from waste heat (i.e. surplus heat below the TS Pinch), Power Pinch Analysis, battery storage and on-grid power supply. The results for the case study show that the overall energy cost of the optimised system is 52% lower than the base case without integration. In this energy system, however, it has been found that the increment of energy efficiency for the steam (thermal energy) system might lead to lower overall energy efficiency and higher total operating cost. This situation happens when there is a lower amount of waste heat available. • A new framework to optimise the heat and power systems of a LIES. • Cogeneration system satisfies the excess and deficit in thermal and power systems. • Cumulative effects of Heat Integration, Power Integration, storages & cogeneration. • On-grid and the off-grid power supply system for heat and power integrated LIES. [ABSTRACT FROM AUTHOR]