Search results

Rising energy costs and potential scarcity are driving energy reduction initiatives in manufacturing companies. The reduction in energy use is complementary to the classic lean production philosophy and the lean and green literature implies that reducing energy waste supports lean objectives. The purpose of this paper is to examine this perceived positive correlation and identify the impact level of energy reduction of lean product flow.

To achieve this, published case studies and practices from interview were gathered and categorised against a waste management hierarchy.

Energy reduction activities implicitly reduce waste which is compatible with the lean waste objective, however, when applying the waste hierarchy principle to energy efficiency practice, lean product flow is progressively constrained or compromised towards the lower levels of the hierarchy.

The hierarchical classification seeks to communicate how reported energy efficiency improvements will/will not impact on flow. The research focuses on the modification of existing discrete part production facilities towards greater energy efficiency and neglects alternative production technologies and new build. The results suggest that as manufacturers seeking to be more energy efficient move away from preventative actions to more reduce and reuse actions then production flexibility could become restricted and the design of production facilities make re-think the fast, linear and short flow of product.

Examples of industrial practices are provided to show the implications of energy reduction practice on production flow.

Categorises the relationship between classic lean and industrial low-energy initiatives to provide insight to how higher energy cost could impact on production.

Pumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity.

In this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems.

The results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable.

In pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

Electricity plays an essential role in nations' economic development. However, coal and renewables currently play an important part in electricity production in major world economies. The current study aims to forecast the electricity production from coal and renewables in the USA, China and Japan.

Two intelligent grey forecasting models – optimized discrete grey forecasting model DGM (1,1,α), and optimized even grey forecasting model EGM (1,1,α,θ) – are used to forecast electricity production. Also, the accuracy of the forecasts is measured through the mean absolute percentage error (MAPE).

Coal-powered electricity production is decreasing, while renewable energy production is increasing in the major economies (MEs). China's coal-fired electricity production continues to grow. The forecasts generated by the two grey models are more accurate than that by the classical models EGM (1,1) and DGM (1,1) and the exponential triple smoothing (ETS).

The study confirms the reliability and validity of grey forecasting models to predict electricity production in the MEs.

The purpose of this study is to investigate whether news media as a form of social communication regarding pressing, important, and contemporary issues could be used as a leading indicator of technology adoption. For technology foresight, monitoring and analyzing energy technologies is in the spotlight due to their strategic importance to the agenda of competitive and sustainable economic growth.

The trends in renewable energy production and news media are determined and compared to draw inferences in foresight concerning the use of renewable energy technologies in energy production. Consequently, the data concern wind and solar energy production and their representation in news media in Germany and the UK. The analysis proceeds as a quasi-experiment treating each yearly observation of energy production as a function of news media data with lagged variables.

The study reveals consistent dynamics in the lag in the primary production of energy in related technologies compared to the media visibility of the respective technologies.

This study explores the prospects of using news media data in foresight analysis concerning renewable energy production and provides many fruitful avenues for foresight research in investigating relationships between technology adoption and media exposure.

This study aims to explore Taiwan's potential for bioenergy production using feedstocks grown on set-aside land and discusses the consequent effects on Taiwan's energy security plus benefits and greenhouse gas (GHG) emission.

The Modified Taiwan Agricultural Sector Model (Modified TASM), based on price endogenous mathematical programming, was used to simulate different agricultural policies related to bioenergy production. To do this simulation, the TASM model was extended to include additional bioenergy production possibilities and GHG accounting.

Taiwan's bioenergy production portfolio depends on prices of ethanol, electricity and GHG. When GHG prices go up, ethanol production decreases and electricity production increases because of the relatively stronger GHG offset power of biopower.

Taiwan is interested in producing bioenergy but only limited information is available. This study provides the information on potential bioethanol and bioelectricity production from various energy crops, GHG emission offset from bioenergy, and regional energy security.

This paper aims to use a lead market approach for each of 25 European Union member states (EU‐25) to assess the likelihood that locally preferred innovation designs in the Energy Production Sector will become successful in other countries. Based on the lead market analysis, it aims to outline implications for innovation management.

The paper identifies and operationalises indicators to measure and compare the lead market properties of the energy production sector at international level. The indicators used are taken from the Community Innovation Surveys, the Eurostat/OECD PPP and Expenditure Database, the UNCTAD FDI‐Database, the EU Business Demography Statistics, and the Eurostat Foreign Trade Database (Comext).

French energy production companies proved the most effective at orienting their product innovations towards the needs of customers in international markets. The companies in other countries within the EU trade on home markets that exhibit barriers to innovation in at least two of the lead market factors. Therefore, the lead market, France, should be the focal point for the development of global innovation designs. By focusing on innovation designs which respond to the preferences within the French lead market, the innovation management of a company can leverage the success experienced in the lead market for the product's global market launch.

Indicator values were not always available for lead market properties of the energy production sector in every member state. This was particularly true when it came to measuring market structure advantage and transfer advantage.

Market research on the lead market takes centre stage when product innovations are in the development phase. Companies in countries that do not have sufficient above‐average lead market attributes must target product innovations to fit the preferences of users in the lead market – in this case, the French clients of the energy production sector. The observation of the lead market can take on varying degrees of intensity. These range from simply making use of listening posts in the lead market to testing and/or launching new products there.

This paper is the first to apply the lead market approach to systematically investigate demand‐specific innovation drivers in the energy production sector. Its consideration of the demand side of innovation is of the utmost interest for the more recent strains of innovation research as well as for innovation management in the energy production sector itself.

Faults in the actual outdoor performance of Building Integrated Photovoltaic (BIPV) systems can go unnoticed for several months since the energy productions are subject to significant variations that could mask faulty behaviors. Even large BIPV energy deficits could be hard to detect. The purpose of this paper is to develop a cost-effective approach to automatically detect faults in the energy productions of BIPV systems using historical BIPV energy productions as the only source of information that is typically collected in all BIPV systems.

Energy productions of BIPV systems are time series in nature. Therefore, time series methods are used to automatically detect two categories of faults (outliers and structure changes) in the monthly energy productions of BIPV systems. The research methodology consists of the automatic detection of outliers in energy productions, and automatic detection of structure changes in energy productions.

The proposed approach is applied to detect faults in the monthly energy productions of 89 BIPV systems. The results confirm that outliers and structure changes can be automatically detected in the monthly energy productions of BIPV systems using time series methods in presence of short-term variations, monthly seasonality, and long-term degradation in performance.

Unlike existing methods, the proposed approach does not require performance ratio calculation, operating condition data, such as solar irradiation, or the output of neighboring BIPV systems. It only uses the historical information about the BIPV energy productions to distinguish between faults and other time series properties including seasonality, short-term variations, and degradation trends.

The purpose of this paper is to make a preliminary analysis of the potentials for the adoption of biofuels in Nigeria. This initial analysis aims to capture some of the possibilities in the adoption of biofuel and the promotion of the cultivation of energy crops and processing of biofuels in Nigeria. Taking a step towards biofuel adoption is crucial for Nigeria to remain an important player in the world energy market, as there is a shift in global fossil fuel consumption.

The study adopted a desk review of existing literatures on global biofuels production potentials. A synthesis of data from the Food and Agriculture Organization (FAO) secondary database on major energy crops production was also conducted, while the GIS map was generated from GIS data sourced from the International Institute of Tropical Agriculture, Ibadan, Nigeria.

Nigeria has immense potential for energy crops cultivation and the production of bioethanol and biodiesel. The existing database shows that Nigeria ranks very high in terms of production of the major energy crops such as soybean, palm oil, sesame and cassava. The rainfall distribution shows that most energy crops can be grown all over Nigeria. Nigeria has the capacity to be a leading exporter of biofuels. The adoption of biofuels can also ease the financial strain relating to the heavy burden of fossil fuel subsidy and also enhance local livelihoods within the production chains.

With the very high potential for biofuel production, the Government as well as private investors should take steps towards investing in agriculture for the production of energy crops and the establishment of biofuel‐processing plants in Nigeria.

The paper is a preliminary analysis of bio‐economic and environmental modeling of the adoption of biofuels in the energy sector in Nigeria. This analysis has opened up the focus of the bigger study, modeling the biological, economic, environmental and other impacts of biofuel adoption.

This study aims to investigate the interrelationships and elasticities between the production of renewable energy (RE) and three key variables: oil prices, gross domestic product (GDP) and carbon dioxide (CO₂) emissions.

The research uses panel data and time-series analyses for 10 developed and 16 emerging countries for the period 1976–2018, to identify panel and country-specific elasticity of RE production and dynamic causal relationships between these variables. The study uses an autoregressive distributed lag model to determine the long- and short-run dynamics between RE production and the three variables in each country.

Results show a long-run elasticity between RE and GDP, and short-run dynamics between RE and oil prices and CO₂ emissions in the developed countries. Whereas in the emerging countries category, there were long-run relationships between RE and GDP, CO₂ emissions and oil prices.

Results of this study are in fact crucial and can be applied in the drafting of resilience policies to tackle energy vulnerability as well as sustainable growth. The study results will inform and guide governments on the right policies to stimulate RE production in their own countries in the interests of both their national security and sustainable development globally.

This paper attempts to contribute to the literature in at least two ways. First, research on identifying common determining factors, including socioeconomic factors, in both emerging and advanced economies is considerably scarce. Most of the previous research in this field has focused only on the absolute value of RE production in a particular geographical area. Second, many studies have focused on RE consumption. This research differs from them by focusing on the production of RE. Thus, the main contribution of this study is to fill these gaps. The study also presents novel empirical evidence to determine RE production elasticity from 26 countries.