Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The aim of this paper is to introduce a newly developed multi-criteria analysis for the comparison of two grid expansion alternatives, conventional and voltage-regulated distribution transformer. The case study comprises environmental, economic, technical and social aspects. Design/methodology/approach The newly developed method decision condition Preference Ranking Organization METHod for Enrichment Evaluation (DC-PROMETHEE) combines scenario planning with the multi-attribute decision-making method PROMETHEE. DC-PROMETHEE supports the decision-maker to evaluate the total potential of an alternative considering a large number of decision conditions. The calculated performance indicator supports the decision-maker to select the best alternative. Findings The voltage-regulated distribution transformer shows a high overall potential in the present case study. This leads to the recommendation to the investigated distribution system operator to include the voltage-regulated distribution transformers as a grid expansion measure. Practical implications The DC-PROMETHEE can be applied to other distribution system operators by considering their individual grid topology and preferences. Other fields of application are infrastructure investments in the service area, in which expansion alternatives are evaluated in a large number of decision conditions. Examples include telecommunication, gas supply, water supply, sewage and rail networks. Originality/value This paper develops the DC-PROMETHEE approach. The DC-PROMETHEE enables the multi-criteria evaluation of a few alternatives in a large number of decision conditions. Citation: International Journal of Energy Sector Management PubDate: 2017-09-19T09:28:56Z DOI: 10.1108/IJESM-08-2015-0004
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This study aims to explore the relationship among energy consumption, real income, financial development and oil prices in Italy over the period 1960-2014. Design/methodology/approach Different econometric techniques – such as the General Methods of Moment (GMM) or the AutoRegressive Distributed Lags (ARDL) bounds test – are usually used in the empirical analysis. Moreover, both the Toda and Yamamoto causality tests and the Granger causality tests are applied to the data. Findings The results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1). The ARDL bounds F-test reveals an evidence of a long-run relationship among the four variables at 1% significance level. Moreover, an increase in real GDP and oil prices has a significant effect on energy consumption in the long run. The coefficients of estimated error correction term are also negative and statistically significant. In addition, the paper explores the causal relationship between the variables by using a VAR framework, with Toda and Yamamoto but also Granger causality tests, within both multivariate and bivariate systems. The findings indicate that energy consumption is affected by real GDP. Originality/value The study also filled the literature gap of applying ARDL technique to examine this relevant issue for Italy. Citation: International Journal of Energy Sector Management PubDate: 2017-09-14T08:30:08Z DOI: 10.1108/IJESM-01-2017-0004
First page: 522 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This work aims to determine the best linear model using an artificial neural network (ANN) with the imperialist competitive algorithm (ICA-ANN) and ANN to predict the energy consumption for land leveling. Design/methodology/approach Using ANN, integrating artificial neural network and imperialist competitive algorithm (ICA-ANN) and sensitivity analysis (SA) can lead to a noticeable improvement in the environment. In this research, effects of various soil properties such as embankment volume, soil compressibility factor, specific gravity, moisture content, slope, sand per cent and soil swelling index on energy consumption were investigated. Findings According to the results, 10-8-3-1, 10-8-2-5-1, 10-5-8-10-1 and 10-6-4-1 multilayer perceptron network structures were chosen as the best arrangements and were trained using the Levenberg–Marquardt method as the network training function. Sensitivity analysis revealed that only three variables, namely, density, soil compressibility factor and cut-fill volume (V), had the highest sensitivity on the output parameters, including labor energy, fuel energy, total machinery cost and total machinery energy. Based on the results, ICA-ANN had a better performance in the prediction of output parameters in comparison with conventional methods such as ANN or particle swarm optimization (PSO)-ANN. Statistical factors of root mean square error (RMSE) and correlation coefficient (R2) illustrate the superiority of ICA-ANN over other methods by values of about 0.02 and 0.99, respectively. Originality/value A limited number of research studies related to energy consumption in land leveling have been done on energy as a function of volume of excavation and embankment. However, in this research, energy and cost of land leveling are shown to be functions of all the properties of the land, including the slope, coefficient of swelling, density of the soil, soil moisture and special weight dirt. Therefore, the authors believe that this paper contains new and significant information adequate for justifying publication in an international journal. Citation: International Journal of Energy Sector Management PubDate: 2017-09-06T12:56:43Z DOI: 10.1108/IJESM-01-2017-0003
First page: 541 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to analyze the internal relationships and tendency of residential energy consumption, income and carbon emissions. Design/methodology/approach Taking 30 provinces of China as the analysis unit and dividing them into two types of urban and rural consumer groups, the panel data model was built. In addition, panel unit root test, panel cointegration test and panel Granger causality test were also used. Findings The results showed that there are long-run equilibrium relationships between the three variables, which show the regular tendency in the spatial process. The elasticity coefficients of residential energy consumption and CO2 emissions vary across the three regions and decline continuously from the western to central and eastern regions. In addition, geographic location is also an important factor on the energy consumption and CO2 emissions in residential sector. Originality/value This paper provides some points for policies on cutting energy use and pollution in residential sector. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T12:45:40Z DOI: 10.1108/IJESM-01-2016-0004
First page: 557 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Since the liberalization of electricity markets in the European Union, prices are subject to market dynamics. Hence, understanding the short-term drivers of electricity prices is of major interest to electricity companies and policymakers. Accordingly, this paper aims to study movements of prices in the combined German and Austrian electricity market. Design/methodology/approach This paper estimates an autoregressive model with exogenous variables (ARX) in a two-step procedure. In the first step, both time series, which inherently feature seasonality, are de-seasonalized, and in the second step, the influence of all model variables on the two dependent variables, i.e. the day-ahead and intraday European Power Energy Exchange prices, is measured. Findings The results reveal that the short-term market is largely driven by seasonality, consumer demand and short-term feed-ins from renewable energy sources. As a contribution to the existing body of literature, this paper specifically compares the price movements in day-ahead and intraday markets. In intraday markets, the influences of renewable energies are much stronger than in day-ahead markets, i.e. by 24.12 per cent for wind and 116.82 per cent for solar infeeds. Originality/value Knowledge on the price setting mechanism in the intraday market is particularly scarce. This paper contributes to existing research on this topic by deriving drivers in the intraday market and then contrasting them to the day-ahead market. A more thorough understanding is especially crucial for all stakeholders, who can use this knowledge to optimize their bidding strategies. Furthermore, the findings suggest policy implications for a more stable and efficient electricity market. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T01:00:40Z DOI: 10.1108/IJESM-05-2016-0009
First page: 574 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to analyse how the political, relational and institutional contexts of the offshore wind industry affect supply-network-enabled innovation (SNEI) and to identify significant possibilities for obtaining the overall target of reducing the cost of producing energy based on the offshore wind industry. Design/methodology/approach Through an embedded single-case study, the contextual conditions of SNEI within the relatively immature offshore wind energy industry are investigated. Findings The national system of innovation only affects product innovation within the industry. Process innovation, which is needed to make the industry grow and mature, seems lesser supported. Different levels of maturity exist among the actors within the industry, which creates barriers for SNEI. To help the offshore wind industry grow, the educational and research system can promote integration of companies by helping the actors to design best practices and manage their business processes according to some generic goals and practices. Additionally, the political system must provide clearer intentions for a sustainable future. Practical implications This paper provides insights into how SNEI can be applied within the Danish offshore wind industry to foster competitive advantages against energy recovered based on fossil fuels. Originality/value The paper contributes to the rather immature field of research on SNEI with empirical data from a network of companies. Furthermore, it adds to the emerging research area of political-initiated development of renewable energy sources. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T01:04:22Z DOI: 10.1108/IJESM-09-2016-0003
First page: 595 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The aim of this paper is to review the current situation and existing problem, establish investment benefits evaluation indicator system and introduce synthetic approach degree containing Hamming approach degree, Euclid approach degree and gray correlation degree to improve the shortage of Euclidean distance in traditional TOPSIS method, and the evaluation result is strengthened by multiplication rule. This paper aims to solve the distribution network investment decision-making problem and construct a comprehensive distribution network investment benefit indicator system, which is more suitable for China distribution network characteristics. Design/methodology/approach This study develops improved TOPSIS methods for decision maker in the power distribution network market and uses an example to prove its effectiveness and superiority in practice which can realize the combination of theory and practice. Findings The research shows that the investment evaluation indicator system built in present paper covers more investment benefit influencing factors (such as qualified rate of trunk cross-section, pass rate of N-1 lines), and the evaluation result obtained by improved TOPSIS method is more efficient and persuasive. Originality/value The study can help investors evaluate distribution network project more efficient, and make contribution to the choice of distribution cases with similar investment benefits. Citation: International Journal of Energy Sector Management PubDate: 2017-09-12T01:58:48Z DOI: 10.1108/IJESM-05-2017-0005
First page: 609 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose In recent years, fast urban expansion in China has stimulated rapid energy consumption growth and increased environmental pollution. Therefore, it is important to utilize clean and renewable energy in district heating for the sustainable urban development. This study aimed to investigate the environmental and economic impacts of one hot dry rock (HDR) geothermal energy-based heating system in a life cycle framework. Design/methodology/approach By using the input–output-based life cycle analysis model, the energy consumption, CO2 emission and other pollutants of the HDR-based heating system were evaluated and then compared with those of other four heating systems based on burning coal or natural gas. The life cycle costs of the HDR-based heating system were also analyzed. Findings The results showed that using HDR geothermal energy for heating can significantly reduce fossil fuel consumption, CO2 emission as well as environmental pollution, and its life cycle costs are also competitive. Originality/value This study not only evaluated the environmental and economic impacts of the HDR-based heating system in a life cycle framework but also provided a methodological life cycle assessment framework that can estimate both economic and environmental benefits, which can be used in policy making for China’s urban development. Citation: International Journal of Energy Sector Management PubDate: 2017-09-14T08:34:47Z DOI: 10.1108/IJESM-04-2016-0008
First page: 626 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This research aims to analyse cognitive factors, innovation attributes and their influence on adoption of solar renewable energy technologies (RETs) for urban households in Mexico. It expands existing cognitive frameworks by including variables from diffusion of innovation theory. Design/methodology/approach On the basis of the data of 291 urban consumers and through the use of partial least squares (PLS), the proposed model was empirically tested. Finite mixture PLS method helped identify two market segments. Findings Findings suggest that beliefs about consequences of adopting RETs have significant influence in shaping consumer’s attitudes towards RETs which were found to be an accurate predictor of the behavioural intention to adopt these technologies. Regarding innovation attributes, the results show that for a solar heater to be adopted, it should be compatible with the social values of the consumer. Triability and relative advantage show little influence on attitude formation. Two market segments found differ on the basis of beliefs and attitudes. Research limitations/implications The study was limited to analyse consumer responses to solar energy in residential urban settings. Practical implications Organizations wanting to increase their consumer base need to develop sound technological innovations with high levels of compatibility a low complexity. Originality/value The study combines diffusion of innovation theory with cognitive frameworks and finds that innovation attributes become strong predictors of intentions to adopt RETs. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T12:53:01Z DOI: 10.1108/IJESM-02-2017-0001
First page: 650 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this study is to select the most accurate and the most efficient method in estimating Weibull parameters at Agadir region in Morocco. Design/methodology/approach In this paper, Weibull distribution is used to model the wind speed in hourly time series format. Since several methods are used to adjust the Weibull distribution to the measured data, in reporting and analyzing the easiest and the most effective method, seven methods have been investigated, namely, the graphical method (GM), the maximum likelihood method (MLM), the empirical method of Justus (EMJ), the empirical method of Lysen (EML), the energy pattern factor method (EPFM), Mabchour’s method (MMab) and the method of moments (MM). Findings According to the statistical analysis tools (the coefficient of determination, root mean square error and chi-square test), it was found that for five months, the MLM presents more efficiency, and for four months, EMJ is ranked first and it is ranked second for February. To select only one method, the selected methods (MLM and EMJ) were compared by calculating the error in estimating the power density using Weibull distribution adjusted by those methods. The average error was found to be −0.51 and −4.56 per cent for MLM and EMJ, respectively. Originality/value This investigation is the first of its kind for the studied region. To estimate the available wind power at Agadir in Morocco, investors can directly use MLM to determine the Weibull parameters at this site. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T12:56:43Z DOI: 10.1108/IJESM-06-2017-0002
First page: 664 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to reveal how larger enterprises and small and medium-sized enterprises (SMEs) can enable innovation collaboration for enhanced competitiveness of the offshore wind energy sector. Design/methodology/approach The research is based on a longitudinal qualitative study starting in 2011 with a project-based network learning course with 15 SME wind farm suppliers and follow-up interviews with 10 SMEs and continued with interviews conducted with 20 individual enterprises within operation and maintenance conducted in 2014-2015. Findings The findings reveal challenges as well as opportunities for innovation collaboration between larger enterprises and SMEs to contribute to the innovation and competitiveness of the offshore wind farm sector. A glass ceiling is revealed for demand-driven positions if the SME does not possess rare and specific valuable knowledge. There are opportunities revealed in general for supplier-driven positions if SME suppliers can collaborate and develop interesting solutions for larger enterprises. If SMEs succeed in either of these aims, the SMEs have an opportunity to attain partner-driven collaboration. However, challenges are present according to the understanding of the different organisational approaches in SMEs and larger enterprises and in the different business approaches. Research limitations/implications The research is limited to the offshore wind energy sector. Further research is needed for verification of the findings in other energy sectors. Originality/value A fourfold contribution is made to enhance the understanding of innovation collaboration and to enable competitiveness for the offshore wind energy sector. SMEs, larger enterprises, academic researchers and policy bodies are provided with a model for action within the four positions for innovation collaboration. Citation: International Journal of Energy Sector Management PubDate: 2017-09-05T01:07:35Z DOI: 10.1108/IJESM-04-2016-0005
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