Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The global energy market has been facing lower prices of crude oil in recent years. Lower fuel price leads to lower transport cost and cheaper agricultural inputs (such as pesticides and chemical fertilizer), resulting in lower prices of agricultural commodities in the international markets. On the other hand, lower global oil price reduces the oil revenues of oil exporting countries, resulting in a decrease in government expenditures. Therefore, the purpose of this study is to examine the impacts of lower global oil and agricultural commodity prices and government expenditure on the entire economy and poverty level of Malaysia. Design/methodology/approach This study used a computable general equilibrium model (CGE) to investigate four simulation scenarios based on the latest Malaysia’s input-output table belonging to 2010. The first scenario is a 30 per cent fall in the export and import prices of agricultural commodity prices, while the second is a 50 per cent decline in the export and import prices of crude oil, and the third combines them. In the fourth scenario, government operating expenditure declines by 4 per cent because of the fall in government’s oil revenues as a result of the decline in global oil prices. Findings The simulation results suggest that lower international oil price decreases real gross domestic product (GDP) and investment in Malaysia and influences positively the output and employment of some agriculture sectors. However, lower agricultural commodity price increases real GDP and investment in the country and negatively influences the output, employment and exports of all agriculture sectors. The decline in government expenditures also increases the output and the employment in the economy, whereas it decreases household consumption. In conclusion, results show that the agriculture sector losses from the current decline in international agricultural commodity prices, while it benefits from lower oil and government expenditure. Originality/value The main contribution of this study is comparing the impacts of recent falls in global oil and agricultural prices on the entire economy and agriculture sector of Malaysia. Investigating the impacts of these issues on the poverty level of Malaysian households is another contribution to the study. Another contribution is analyzing the impact of a reduction in government expenditures because of the decline in global oil price on the economy and welfare of Malaysia. Therefore, this study makes a useful contribution to the small literature of the topic. Citation: International Journal of Energy Sector Management PubDate: 2018-12-10T11:54:20Z DOI: 10.1108/IJESM-06-2017-0006
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This study aims to investigate the challenges facing the implementation of the natural gas policy in Tanzania. Design/methodology/approach A structured questionnaire was used to collect data, while the principal component analysis and statistical tests were used to explore the relationship between the opinions on the influential factors for the natural gas policy implementation and the demographic information. Findings The findings showed that over 50 per cent of the respondents regarded poor community participation and transparency and accountability as the major policy implementation challenges. Most of the demographic information showed the statistically significant effects of the policy implementation influential factors. Originality/value This paper provides the current challenges facing the implementation of the national natural gas policy in Tanzania. Citation: International Journal of Energy Sector Management PubDate: 2018-12-05T02:06:17Z DOI: 10.1108/IJESM-08-2018-0005
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to focus on data analytic tools and integrated data analyzing approaches used on smart energy meters (SEMs). Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency. Design/methodology/approach A few research strategies have been accounted for analyzing the raw data, yet at the same time, a considerable measure of work should be done in making these commercially reasonable. Data analytic tools and integrated data analyzing approaches are used on SEMs. Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency. Advantages of SEM's are additionally discussed for inspiring consumers, utilities and their respective partners. Findings Consumers, utilities and researchers can also take benefit of the recommended framework by planning their routine activities and enjoying rewards offered by gamification approach. Through gamification, consumers’ commitment enhances, and it changes their less manageable conduct on an intentional premise. The practical implementation of such approaches showed the improved energy efficiency as a consequence. Citation: International Journal of Energy Sector Management PubDate: 2018-11-21T01:33:49Z DOI: 10.1108/IJESM-11-2017-0006
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Technological development has not only helped in effective integration of renewable sources but also made it possible for consumers to participate in system operation. Different market players are coming up in the electricity market, microgrid being one of them. Thus, this paper aims to investigate consumers’ role in the dispatch of a microgrid system that has a hybrid market structure under varied system conditions. Design/methodology/approach The mathematical model developed has been solved by the CONOPT solver in the GAMS optimization tool. GAMS-MATLAB interfacing is done to obtain solutions. Findings The problem formulated shows the effect of consumers in dispatch and overall operational cost. Consumers’ participation has been proposed through a quadratic cost function. The system operation under pool and bilateral contracts has been investigated. It shows that proper incentives to the consumers can help in reduction and effective management of the demand, carbon emission and overall system operational cost. Originality/value This paper considers the hybrid market structure to find the load dispatch in a microgrid system. The participation of consumers in the microgrid system has been implemented considering variations in wind power, solar power and load. The power exchange between the grid and microgrid system has been modeled showing the contribution of the consumers in system operation. Citation: International Journal of Energy Sector Management PubDate: 2018-11-21T01:31:29Z DOI: 10.1108/IJESM-12-2017-0008
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This study aims to consider a five-factor model to evaluate the service quality of solar product companies in the context of rural Punjab (India) and validate the proposed model. In addition, the study considered the factors which affect the service quality of solar product companies. Design/methodology/approach A five-factor model of service quality has been tested for reliability and validity by confirmatory factor analysis. For determining satisfaction of the solar product users, SERVQUAL model/gap analysis has been applied. Five dimensions, namely tangibility, reliability, responsiveness, assurance and empathy have been considered to assess the overall satisfaction level. A modified scale of Parasuraman incorporated in 1985 has been used as a survey instrument for research. A sample size of 345 solar submersible pump users was selected. Findings The study concluded that dimensions such as reliability, responsiveness, assurance and empathy have lesser gap. The major gap has been found in the tangibility dimension which includes variables like modern design of solar energy products, facilities and attractiveness, variety of solar products and performance of solar products, etc. Research limitations/implications As primary data are concerned, the biasness of the respondents may affect the results of the study. The survey has been conducted in the Punjab region, and a sample size is 345 only which may not reflect the broader picture. Practical implications Solar energy has huge benefits in the Indian agriculture sector. The erratic state of power supply in India casts important costs on agriculture productivity. One such segment concerns systems, an important input for agriculture production. The study has implications for solar energy product manufacturers, as it makes them aware about customer perception toward services of solar product companies. Social implications To decrease pollution and to save the environment, solar energy technologies have a good potential energy source and to meet the global energy demand, as it is the most promising and reliable energy source. Originality/value The existing studies in the context of service quality of solar product companies in Punjab have been majorly confined to proposing key drivers toward adoption of renewable energy sources. By providing an insight into the satisfaction level of farmers for solar submersible pumps, the proposed study attempts to fill the gap. As the study relates to solar product users in rural Punjab, the findings will be of additional value to solar product companies which are manufacturing solar products. Therefore, it is expected that this research will fill the gap in literature by studying empirically the service quality of solar product companies. Citation: International Journal of Energy Sector Management PubDate: 2018-11-15T01:31:45Z DOI: 10.1108/IJESM-07-2017-0007
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The degradation of the natural habitat at the expense of economic development is a harmful growth that warrants environmental policy actions. For instance, the economic impacts of environmental pollution are quite visible in developed and developing economies, where human health is compromised by rapid economic growth and energy induced pollution. Therefore, the purpose of this study is to investigate the impact of CO2 emissions on economic development. Design/methodology/approach This paper investigates the correlation between pollutant emissions and key economic variables within the economic community of West African states (ECOWAS) region by applying fixed effects model to unbalanced time-series panel data for the period 1980-2014. This paper examines the full ECOWAS panel and sub-panels with export-and-import-dependent countries. Findings The authors argue that energy consumption (EC) and real output exert causal influences on CO2 emissions for the full ECOWAS panel and the sub-panels with export-and-import-dependent countries. Practical implications The results imply that increase in EC is the main factor that promotes economic growth in the region. Additionally, growth in EC and real output stimulates CO2 emissions growth. Originality/value Therefore, it is argued that technological innovations that increase energy efficiency through new carbon-free technologies that minimize CO2 emissions growth without impairing economic growth and development must be introduced in the region. Citation: International Journal of Energy Sector Management PubDate: 2018-11-15T01:30:27Z DOI: 10.1108/IJESM-09-2017-0001
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of the paper is to provide to a better scientific understanding of Indonesia’s domestic gas allocation policy and its effects on the national economy and to answer the question of what best priorities can be set in allocating the natural gas for the domestic market to maximize the benefits for the national economy. Design/methodology/approach The authors apply a Computabled General Equilibrium (CGE). The Social Accounting Matrix 2008 is used to calibrate the CGE Model. There are two scenarios proposed, each is simulated with certain percentage of gas supply curtailment (50 MMSCFD, Scenario A), (100 MMSCFD, Scenario B). Findings It is confirmed that government’s current policy to give priority to oil production is not the optimum way to maximize added value of natural gas to Indonesian economy. While oil production generates state revenue, it is industry and petrochemical sector that induces high economic impacts because of strong backward and forward linkages. Research limitations/implications Due to the limited data availability, it is assumed that the data on the SAM 2008 are valid for describing the structure of Indonesian economy. Practical implications The paper provides recommendation to the government to revise gas allocation policy by changing the rank of consumers’ priority. Originality/value This paper provides instruments to measure the impact of Indonesia’s domestic gas allocation policy. Finding the best hierarchy of consumer priorities is essential for maximizing added value of natural gas for the national economy. Citation: International Journal of Energy Sector Management PubDate: 2018-11-13T02:54:28Z DOI: 10.1108/IJESM-05-2018-0003
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to analyze the role of industrial self-supply in the transition process from centralized energy generation based on fossil fuels and nuclear power to decentralized supply based on renewable energies in the Bavarian electricity system. Design/methodology/approach To quantify effects on system and price stability, a model of the Bavarian electricity grid is created and used to simulate electricity system behavior during a 1-year period for scenarios that are characterized by parameter variations in industrial self-supply, nuclear power capacity, renewable power generation and the capacity of electricity imports. Findings The simulations show that industrial self-supply can reduce instances of maximum grid utilization by 23 per cent and, based on the merit-order effect, decrease electricity market prices by 1.90 and 5.03 €/MWh in the scenarios with and without nuclear power, respectively; these values represent 5.7 and 15.0 per cent of average market prices from 2014. Research limitations/implications The analysis shows that industrial self-supply can contribute to transforming the electricity system in a secure, sustainable and affordable manner. However, merit-order-based price effects have a limitation concerning the future applicability of results as quantified effects may not be permanent when the electricity system adapts. Originality/value This paper connects industrial self-supply and the merit-order effect within a nodal energy model. It provides insights into the relevant interdependencies and reciprocal effects by means of a simulation. Citation: International Journal of Energy Sector Management PubDate: 2018-11-09T12:57:46Z DOI: 10.1108/IJESM-11-2017-0009
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to examine empirically if the encouragement by government policy of merger and acquisition activity involving municipal and provincially owned electricity distribution utilities (LDCs) in the Province of Ontario has had positive effects in terms of value creation, operating performance and economies of scale. Design/methodology/approach It was anticipated that with LDC consolidation, there will be increased operational efficiency and improvement in the cost-effectiveness of the merged electrical utility. Using matched pairs dependent t-testing and Wilcoxon signed-rank testing, the authors compared data for three years before and after the merger or acquisition of 16 municipal utilities (616 total observations) to determine if there were any statistically significant changes (positive or negative) in measures of financial, operational and service efficiency. Findings The findings indicate statistically significant increases in debt as a percentage of shareholder equity in post-merger/acquisition utilities and consequently leveraged higher returns on equity. However, there were no statistically significant changes in financial, operational or service efficiency measures (with the exception of decreased efficiency in telephone response). Research limitations/implications A total of 16 mergers or acquisitions were reviewed involving 32 of 79 LDCs, with the research implications pointing to a need for existing policy to be reviewed to determine whether a more detailed examination is required by the provincial energy regulator, including a closer examination of managerial motives, before approving mergers between municipal electricity distributors. This research involves only a quantitative approach and further research would examine these transactions using qualitative measures for a deeper examination as to managerial motives. Practical implications The results suggest that the mergers or acquisitions to date have served only to increase shareholder risk without improvement in other financial, operational or service efficiencies, a contradiction to the rationale behind the Province’s merger policy. Social implications The consolidation policy for Ontario LDCs has not resulted in any statistically significant improvement in electricity rates or service for consumers. Originality/value This paper is the first examination of the effects of Ontario’s LDC consolidation policy in terms of specific financial, operational and service efficiency measures. Citation: International Journal of Energy Sector Management PubDate: 2018-11-09T12:56:05Z DOI: 10.1108/IJESM-07-2018-0017
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose An electrical power distribution network is expected to deliver uninterrupted power supply to the customers. The disruption in power supply occurs whenever there is a fault in the system. Therefore, fast fault detection and its precise location are necessary to restore the power supply. Several techniques are proposed in the past for fault location in distribution network but they have limitations as their fault location accuracy depends on system conditions. The purpose of this paper is to present a travelling wave-based fault location method, which is fast, accurate and independent of system conditions. Design/methodology/approach This paper proposes an effective method for fault detection, classification and location using wavelet analysis of travelling waves for a multilateral distribution network embedded with distributed generation (DG) and electric vehicle (EV) charging load. The wavelet energy entropy (WEE) is used for fault detection and classification purpose, and wavelet modulus maxima (WMM) of aerial mode component is used for faulted lateral identification and exact fault location. Findings The proposed method effectively detects and classifies the faults, and accurately determines the exact fault location in a multilateral distribution network. It is also found that the proposed method is robust and its accuracy is not affected by the presence of distributed generation and electric vehicle charging load in the system. Originality/value Travelling wave based method for fault location is implemented for a multilateral distribution network containing distributed generation and electric vehicle load. For the first time, a fault location method is tested in the presence of EV charging load in distribution network. Citation: International Journal of Energy Sector Management PubDate: 2018-11-06T10:42:52Z DOI: 10.1108/IJESM-07-2018-0007
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every home with upcoming technology. So, it is becoming difficult for the energy suppliers to predict the power consumption for households at the appliance level. Power consumption in households depends on various factors such as building types, demographics, weather conditions and behavioral aspect. An uncertainty related to the usage of appliances in homes makes the prediction of power difficult. Hence, there is a need to study the usage patterns of the households appliances for predicting the power effectively. Design/methodology/approach Principal component analysis was performed for dimensionality reduction and for finding the hidden patterns to provide data in clusters. Then, these clusters were further being integrated with climate variables such as temperature, visibility and humidity. Finally, power has been predicted according to climate using regression-based machine learning models. Findings Power prediction was done based on different climatic conditions for electronic appliances in the residential sector. Different machine learning algorithms were implemented, and the result was compared with the existing work. Social implications This will benefit the society as a whole as it will help to reduce the power consumption and the electricity bills of the house. It will also be helpful in the reduction of the greenhouse gas emission. Originality/value The proposed work has been compared with the existing work to validate the current work. The work will be useful to energy suppliers as it will help them to predict the next day power supply to the households. It will be useful for the occupants of the households to complete their daily activities without any hindrance. Citation: International Journal of Energy Sector Management PubDate: 2018-11-06T10:42:12Z DOI: 10.1108/IJESM-04-2018-0012
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to model the relationship between oil price and six major agricultural commodity prices using monthly data from January 1997 to December 2016. Design/methodology/approach The authors use both the linear autoregressive distributed lag by Pesaran et al. (2001) and the nonlinear autoregressive distributed lag by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models. Findings These findings are discernible from the authors’ analyses. First, the linear analysis indicates a significant positive effect of oil prices on the agricultural commodity prices, which supports evidence on the non-neutrality hypothesis. Second, oil price asymmetries seem to matter more when dealing with agricultural commodity prices, except for groundnut. Third, it may be necessary to pre-test for structural breaks when modelling the relationship between oil price and agricultural prices regardless of the commodity being analysed. Fourth, the asymmetric effect for the agricultural commodity prices is non-neutral to oil prices, except for rice in the case of structural breaks. Originality/value This paper contributes to the on-going debate on the oil–agricultural commodity nexus using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and agricultural commodity prices. Citation: International Journal of Energy Sector Management PubDate: 2018-11-06T10:41:13Z DOI: 10.1108/IJESM-07-2018-0004
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to identify factors affecting consumers’ purchasing intentions of energy-efficient products (energy awareness, perceived benefits, perceived price and consumers’ attitudes). Also, it examines the effect of consumers’ attitudes on purchasing intentions of energy-efficient products (EEP) from households’ perspectives in Jordan. Design/methodology/approach A self-administered survey was hand-delivered to the targeted sample of households in Amman, Jordan. A total of 516 questionnaires were delivered to households from which 474 were valid for the analysis. Exploratory and confirmatory factor analyses were performed to assess the research constructs dimensions, unidimensionality, validity and composite reliability. Structural path analysis was also used to test the hypothesised relationships of the proposed research model. Findings Energy awareness positively and significantly affects purchasing intentions, perceived benefits and consumer attitudes. Energy awareness negatively but non-significantly affects perceived price. Perceived benefits positively and significantly affect consumer attitudes and purchasing intentions. Further, perceived price negatively and significantly affects perceived benefits and consumers attitudes. Also, consumers’ attitudes positively and significantly affect purchasing intentions. Consumers’ attitudes exerted the strongest effect on purchasing intentions of EEP; meanwhile, consumers’ attitudes are a function of perceived benefits and energy awareness. Finally, the results show that 50 per cent of variation in purchasing intentions of EEP was caused by perceived benefits–consumers’ attitudes–energy awareness path. Research limitations Future research needs to investigate other factors that may affect households’ intentions of purchasing EEP such as perceived brand and image of EEP, perceived risk, word-of-mouth, subjective norms and households’ cost-saving experience. Investigating and identifying types of perceived benefits of purchasing EEP from households’ perspectives is also important. Comparative studies between Jordanian and non-Jordanian consumers/households are potential areas of future research. Methodologically, future research can conduct comparative analysis between households and energy industry engineers and managers perceptions’ with regard to determinants of perceived benefits and purchasing intentions. Practical implications This paper highlights the crucial role of perceived benefits and energy awareness in formulating households’ attitudes towards EEP and the vital role of such attitudes on purchasing intentions. Marketing directors and CEOs of the energy industry should recognised that perceived benefits, attitudes and energy awareness are vital building blocks in formulating and implementing marketing strategies to operate in this industry. Also, purchase intentions are a function of positive attitudes of household toward EEP and are at the heart of EEP marketing communications campaigns. Originality/value This is the first paper in the energy industry of Jordan devoted to develop and test a model of determinants of purchasing intentions of EEP that focuses on energy consumption behaviour. CEOs, international manufacturers and marketing managers of EEP can benefit from the study’s empirical findings concerning the drivers of EEP purchasing intentions and behaviour decisions of households in Jordan as an emerging market in the Middle East. Citation: International Journal of Energy Sector Management PubDate: 2018-10-31T01:40:51Z DOI: 10.1108/IJESM-05-2018-0009
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The international energy agency states that the world’s primary energy needs are expected to grow to 55 per cent until 2030. Therefore, oil and gas industry as the main energy source will be more crucial where building or advancing new capacities is required. Because the reports highlight the delay as a recurring problem, thereby, more in-depth investigation to find out the main contributing causes is needed. Design/methodology/approach Root cause analysis (RCA) was applied to identify, rank, analysis and categorize the main sources of this problem. Findings Based on RCA procedure; Pareto analysis showed that 84.7 per cent of the delay is because: the radar chart indicated no difference in perception of the participants regarding the importance of the root causes, correlation analysis suggested strong relationship among the participants and the cause-and-effect diagram emphasized more on operational, human and equipment categories, which in total account for 51.86 per cent of the delay. Originality/value The risk planners of large-scale projects can consider these root causes as the main items to analysis, monitor and control, as they are vitally important for project success. Citation: International Journal of Energy Sector Management PubDate: 2018-10-30T02:45:10Z DOI: 10.1108/IJESM-04-2018-0014
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to investigate whether improvement in human capital can foster energy conservation by reducing the energy consumption in India using annual data from 1980 to 2014. Further, this study examines the relationship between human capital and various forms of energy consumption such as electricity, coal, natural gas, hydrocarbon gas and petroleum consumption. Design/methodology/approach To attain the objective, the study investigates this relation through the auto-regressive distributed lag model (ARDL) technique to find a long-run and short-run relationship. Second, to check the robustness of the results, the authors use alternative econometric methods such as dynamic ordinary least squares and fully modified dynamic ordinary least squares. Findings The results reveal a negative relationship between human capital and energy consumption, which implies that improvement in human capital lowers the energy consumption and various forms energy consumption, except for petroleum consumption. The results derived from ARDL show that there exists a long-run and short-run association between human capital and energy consumption. The results are consistent across the econometric techniques. Practical implications Because G20 countries including India aim at reducing carbon emission to a certain level, this study provides an insight that by emphasizing on human capital, India can reduce energy consumption, which would foster energy conservation. Originality/value To the best of the authors’ knowledge, this the first study in India which attempts to examine the effect of human capital on energy consumption and its various forms. Citation: International Journal of Energy Sector Management PubDate: 2018-10-30T02:43:49Z DOI: 10.1108/IJESM-07-2018-0009
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to optimally plan distributed generation (DG) and capacitor in distribution network by optimizing multiple conflicting operational objectives simultaneously so as to achieve enhanced operation of distribution system. The multi-objective optimization problem comprises three important objective functions such as minimization of total active power loss (Plosstotal), reduction of voltage deviation and balancing of current through feeder sections. Design/methodology/approach In this study, a hybrid configuration of weight improved particle swarm optimization (WIPSO) and gravitational search algorithm (GSA) called hybrid WIPSO-GSA algorithm is proposed in multi-objective problem domain. To solve multi-objective optimization problem, the proposed hybrid WIPSO-GSA algorithm is integrated with two components. The first component is fixed-sized archive that is responsible for storing a set of non-dominated pareto optimal solutions and the second component is a leader selection strategy that helps to update and identify the best compromised solution from the archive. Findings The proposed methodology is tested on standard 33-bus and Indian 85-bus distribution systems. The results attained using proposed multi-objective hybrid WIPSO-GSA algorithm provides potential technical and economic benefits and its best compromised solution outperforms other commonly used multi-objective techniques, thereby making it highly suitable for solving multi-objective problems. Originality/value A novel multi-objective hybrid WIPSO-GSA algorithm is proposed for optimal DG and capacitor planning in radial distribution network. The results demonstrate the usefulness of the proposed technique in improved distribution system planning and operation and also in achieving better optimized results than other existing multi-objective optimization techniques. Citation: International Journal of Energy Sector Management PubDate: 2018-10-30T02:42:50Z DOI: 10.1108/IJESM-01-2018-0007
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The main aim of this study was to examine whether any relationship exists between energy consumption and value added of the agricultural and industrial sector as well as the overall growth rate of the Nigerian economy. Design/methodology/approach The study used annualized time series data from 1971 to 2014 drawn from the World Bank Development Indicators, adopting an autoregressive distributed lag technique in the data analyses as well as the bound test and error correction representation. Findings There is a very strong evidence of the existence of a long-run relationship between energy consumption and indicators of economic growth. There are very strong proofs that economic growth and agricultural value added adjust to the shocks and dynamics of the studied energy-consumption-related variables while manufacturing value added proved otherwise. Originality value No study to the best of our knowledge has brought together aggregate growth, agricultural value added and manufacturing value added in the investigation of the energy consumption and economic growth nexus in one study using the Nigerian stylized economic environment. This represents the value added of this study and shows its originality. Citation: International Journal of Energy Sector Management PubDate: 2018-10-24T03:04:22Z DOI: 10.1108/IJESM-02-2018-0007
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Load forecasting is important to any electrical grid, but for the developing and third-world countries with power shortages, load forecasting is essential. When planed load shedding programs are implemented to face power shortage, a noticeable distortion to the load curves will happen, and this will make the load forecasting more difficult. Design/methodology/approach In this paper, a new load forecasting model is developed that can detect the effect of planned load shedding on the power consumption and estimate the load curve behavior without the shedding and with different shedding programs. A neuro-Fuzzy technique is used for the model, which is trained and tested with real data taken from one of the 11 KV feeders in Najaf city in Iraq to forecast the load for two days ahead for the four seasons. Load, temperature, time of the day and load shedding schedule for one month before are the input parameters for the training, and the load forecasting data for two days are estimated by the model. Findings To verify the model, the load is forecasted without shedding by the proposed model and compared to real data without shedding and the difference is acceptable. Originality/value The proposed model provides acceptable forecasting with the load shedding effect available and better than other models. The proposed model provides expected behavior of load with different shedding programs an issue helps to select the appropriate shedding program. The proposed model is useful to estimate the real demands by assuming load shedding hours to be zero and forecast the load. This is important in places suffer from grid problems and cannot supply full loads to calculate the peak demands as the case in Iraq. Citation: International Journal of Energy Sector Management PubDate: 2018-10-24T02:58:20Z DOI: 10.1108/IJESM-03-2018-0008
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose One of the key drivers behind the recent growth in the global solar energy market is the decline in solar module prices. Many empirical analyses have been carried out to identify the mechanism behind this price reduction. However, studies on the price reduction mechanism of solar modules over the years have focused purely on the technological aspect of manufacturing. The purpose of this study is to consider the influence of economic and monetary factors such as the interest rate and exchange rate on solar module pricing in addition to other factors that considered in earlier studies including technology, wage rate and other energy prices. Design/methodology/approach In this paper, an oligopolistic model and econometric method are used to determine the economic factors that have an influence on solar module prices. The paper constructs a solar module pricing model and conducts a fully modified ordinary least squares analysis to estimate the influence of each factor. Analysis is conducted for the top five solar module producing countries in the world from 1997 to 2015. The five countries are the People’s Republic of China, Germany, Japan, the Republic of Korea and the USA. Findings Empirical analysis provides several findings concerning the solar module pricing mechanism. These vary for each country. However, generally the interest rate has a positive correlation with solar module prices, while the exchange rate, knowledge stock and oil price have a negative correlation with solar module prices. Practical implications First, the government must expand channels for renewable energy funding. As renewable industries are high-tech, the influence that capital cost has on technology price is significant. Government efforts to provide industries with low-interest finance will accelerate renewable business. There have been many attempts to lower interest rates for renewable energy technology to accelerate growth in the green technology market. Second, the government must expand research and development (R&D) expenditures focused on renewable energy technology. The technological advancements acquired through R&D enhance module performance efficiency, thereby reducing costs. Therefore, government policies aimed at increasing targeted R&D expenditure will be an effective means of expanding the installation of renewable energies. Originality/value Studies on the price reduction mechanism of solar modules over the years have focused purely on the technological aspect of the manufacturing. This is the first research to bring economic, monetary and technological factors of solar module pricing together. Citation: International Journal of Energy Sector Management PubDate: 2018-10-24T02:52:40Z DOI: 10.1108/IJESM-05-2018-0005
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Analysis of relationship between energy and growth offers the sustainable energy pathway for a country’s sustainable economic development. This study aims to focus on the evaluation of the Pakistan’s energy system using long-run energy alternative planning (LEAP) modeling framework through different growth scenarios. Design/methodology/approach Principal component analysis has been adopted for indicators index formation. Study period of 1980 to 2030 is covered by forward and backward simulations in LEAP software. Findings The study reveals that current energy policy does not have the potential to lead the country toward a desired goal of economic sustainability. Research limitations/implications In falling off scenario, negative growth rate (-5 per cent) assumption is also debatable; LEAP shows an error in the analysis and takes the last positive available value for any further analysis as a default. This case could have been simply omitted from results but for research contribution, the computations for this case are also reported. Practical implications Long-range energy alternative planning model has been applied to answer the corresponding question for simulation period of 1980 to 2030 to better compare the past trend and future expectations. Critical analysis of four selected scenarios (BAU, moderate, advanced and falling off) indicate that energy policy of Pakistan is poorly managed to maintain energy system’s effectiveness. Social implications As far as statistical difference is concerned, early years have more fluctuation; however, from 2009, curve flattens for energy consumption and energy demand. The increasing demand of energy impacts the society and hence disturbs all sectors. Originality/value Policymakers have been so dragged off from the main route to sustainability, despite all odds there is a huge unexplored potential in the country for use to move in step with the world for a better tomorrow. The study educates the policymakers to comprehend the future energy scenarios and make rational decisions based on the study outcomes. Citation: International Journal of Energy Sector Management PubDate: 2018-10-18T12:55:22Z DOI: 10.1108/IJESM-04-2018-0006
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Spain has one of the greatest photovoltaic potentials in Europe. The boom suffered in the photovoltaic sector during the years 2007 and 2008 led to instability in the electrical system, prompting the legislator to develop a large number of legislative changes trying to control the electric system tariff deficit. These measures profoundly affected plant owners creating a non-transparent secondary market, which are not covered by the current exchange platforms. The purpose of this paper is to analyze the current situation of the photovoltaic market in Spain, try to understand it based on its historical sequence and propose efficiency improvement measures, based on the implementation of best practices and market mechanisms. Design/methodology/approach This paper studies the legislative evolution in the photovoltaic sector in Spain and its effect on owners and investors. The authors propose an intermediation system that improves the efficiency of the secondary market. Findings The authors propose an intermediation system that improves the efficiency of the secondary market. Originality/value The authors have not found any other paper that proposes the creation of a market for photovoltaic facilities to increase efficiency. Citation: International Journal of Energy Sector Management PubDate: 2018-10-18T02:18:57Z DOI: 10.1108/IJESM-07-2018-0005
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to explore the effect of oil price shocks on the US Consumer Price Index over the monthly period from 1876:01 to 2014:04. Design/methodology/approach The author uses the Bai and Perron (2003) structural break test to split the data sample into sub-periods delimited by the computed break dates. Afterwards, the author uses the quantile treatment effects over the full sample and then, by including sub-periods dummies to accommodate the selected structural breaks that drive the relationship between inflation and oil price growth. Findings The findings include a decreased transmission effect of oil price changes on inflation in recent years; a varied elasticity of inflation to the growth rate of oil prices across the distribution; and, finally, evidence of asymmetry in the relationship between the growth rate of oil prices and inflation, with a higher transmission mechanism for decreasing rather than increasing oil prices. Practical implications Policymakers should remain alert to monitoring potential inflation increases and should take precautionary measures to anchor inflation expectations, because inflation reacts differently to positive and negative oil price shocks. Moreover, authorities should consider the asymmetric reaction of inflation to oil price shocks to adopt an appropriate monetary policy strategy to achieve the price stability target. Originality/value The paper used a quantile regression model with structural breaks, which has not yet been used in the literature. Citation: International Journal of Energy Sector Management PubDate: 2018-10-16T02:01:01Z DOI: 10.1108/IJESM-05-2018-0002
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to uncover the importance of several variables centered around partnership in renewable energy (RE) projects. The concept developed earlier is applied to the project environment to identify interrelations between external and internal drivers, project partnership, resources and project success. A framework consisting of logical chain to project success is proposed. Design/methodology/approach The study derived the concepts and variables of RE projects’ partnership from the academic literature. The methodology of the case study was used to gain insights in relation to the variables in the logical chain of the proposed framework, suggesting that certain external/internal drivers direct diverse stakeholders to a partnership. Findings RE technologies are not commodities and require involvement of different stakeholders, who directly or indirectly are impacted by implementation of the RE projects. For the project to be a success, it is critical to involve the stakeholders early in the process and induce partnership synergy, through which dynamic capabilities and implementation mechanisms are capitalized upon as resources to achieve project success. Originality/value There appears to be no specific framework directly linking partnership synergy and project success; their relationships are only indirectly inferred. Focusing on project-level activities of public and private stakeholders the paper proposes a framework that conceptualizes relationships among external/internal drivers, partnership, resources and project success/performance. This could be a promising future research direction, helping technology project stakeholders maximize their returns by realizing full advantage of collaboration and partnership Citation: International Journal of Energy Sector Management PubDate: 2018-10-16T01:58:21Z DOI: 10.1108/IJESM-04-2018-0001
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose There are thousands of areas excluded from using electrical energy in China. It is mainly because that these places, which are away from towns, have the characteristics of scattered living and low-power consumption and are difficult to construct the power grid. The utilization of energy in remote areas could improve the level of education and quality of life for people living in there, which has great social significance. However, how to choose the optimal power generation model quantitatively according to local energy advantages is a difficult problem. Design/methodology/approach To carry out a better assessment of the energy benefits of Chinese rural areas to assist the decision-making of energy utilization project, this paper takes Sunan Yugu Autonomous County in Gansu Province as an example. Four feasible energy utilization scenarios are proposed by analyzing its geographical conditions and re-source advantage, respectively, are photovoltaic power generation, biomass power generation, wind power generation and power grid extension. Based on the above scenarios, the evaluation index system of comprehensive utilization of energy in remote areas is constructed, and the comprehensive benefit of each model is evaluated by adopting entropy-based fuzzy comprehensive evaluation model. Findings Evaluation results show that the comprehensive benefits of photovoltaic power generation is the best, followed by power grid extension. Thus, preference should be given to the two models in the energy utilization in Sunan County. This evaluation model can provide a scientific reference for the selection decision-making of energy utilization project, which is helpful to provide the feasibility and efficiency of the construction of energy utilization project. Originality/value The authors construct the comprehensive benefit evaluation index system and evaluate the comprehensive benefits of different scenarios are by using entropy - fuzzy comprehensive evaluation model. Then the qualitative problem can be analyzed quantitatively. The purpose of this study is to support the decision-making of energy investment. Simultaneously, the paper also has some practical significance in improving the credibility of the government and the quality of local people’s life. Citation: International Journal of Energy Sector Management PubDate: 2018-10-11T02:41:32Z DOI: 10.1108/IJESM-12-2017-0001
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Offshore renewable energy technologies provide many new opportunities for coastal regions around the world, and although the energy policy literature has documented the success stories of many “first mover” regions, there is little guidance for “second mover” or “follower” regions. This paper aims to investigate the strategic challenges faced by coastal regions in the Channel area that are not first movers. Design/methodology/approach The authors use a multiple case study approach to analyse the behaviour of regional stakeholders when planning and assessing their participation in the renewable energy sector. Findings The paper reveals the tendency of regional planners to idealise investments in renewable energy. The negative consequences of idealisation are inadequate strategic visions. Research limitations/implications The findings are only relevant in the context of the regions that are part of the case study. Practical implications The paper illustrates how idealisation of technology or strategy is created and how it impacts strategic decision-making. It also discusses how to address idealisation. Social implications Although much of the energy policy literature discusses the challenge of social acceptance, this paper documents an opposite phenomenon, idealisation. There is a need in the energy sector to find a middle ground between these two extremes. Originality/value The paper provides evidence and a theoretical analysis of a decision-making bias, idealisation, which is not discussed in the literature. Citation: International Journal of Energy Sector Management PubDate: 2018-10-01T02:20:44Z DOI: 10.1108/IJESM-02-2017-0011
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to examine the compatibility of Giffen behaviour with residential demand for kerosene and cooking gas. Design/methodology/approach In total, 600 questionnaires were administered on selected households in Ondo State while 485 were retrieved. Both ordinary least square and instrumental variables (IVs) were estimated, while, the IV estimated result was preferred. Findings The result showed that Giffen behaviour is compatible with the demand for kerosene in Ondo State, but not for cooking gas. As regard to other factors, prices of the alternatives to kerosene and cooking gas have positive but insignificant impact on the demand for the respective products. Age of the household has a positive significant impact on the demand for kerosene and cooking gas. Household in which the heads has tertiary education demand for kerosene and cooking gas more than those without any form of education. Larger households consume more of both commodities than smaller households. Research limitations/implications Based on these findings, the authors recommend that government should continue to subsidize either the production or consumption of household kerosene. Practical implications Consumers should not mind the initial expenditure in purchasing cylinder for cooking gas as subsequent expenditure would be lower than that of kerosene. Social implications Regulators should brace to ensure that kerosene and cooking gas be made available at government-regulated prices, particularly by checkmating the activities of the “black-marketers.” Originality/value Two outstanding knowledge gaps that this paper filled are in the novelty of this paper regarding the application of Giffen behaviour to kerosene and cooking gas. Second, previous studies did not account for the potential endogeneity problem that is inherent in the joint demand for kerosene and cooking gas. This paper took care of this by estimating the model using IVs. Citation: International Journal of Energy Sector Management PubDate: 2018-10-01T02:19:02Z DOI: 10.1108/IJESM-04-2016-0007
Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to determine the factors affecting the capital structure of companies engaged in the Indian energy sector. Design/methodology/approach Capital structure theories and empirical literature have been reviewed to formulate propositions concerning the factors/variables determining the capital structure of Indian energy companies. The examination is done using panel data techniques for the sample 141 companies operating in the Indian energy sector. Findings The results show firms’ age, asset turnover ratio, liquidity and firms’ size to be significant determinants of capital structure for the Indian energy companies, while profitability, debt service capacity, sales growth, non-debt tax shield and tangibility ratio to be insignificant determinants. Historically, profitability has shared a significantly negative relationship with debt ratio; however, the relation here is not significant. Research limitations/implications The focus of the current study is on Indian energy sector, the results obtained will not be applicable for other sectors. Originality/value The current research gives an insight into the determinants of capital structure of the companies engaged in the Indian energy sector, which are mostly overlooked due to the laws, policies and regulations governing the sector as a whole. Citation: International Journal of Energy Sector Management PubDate: 2018-09-24T06:53:08Z DOI: 10.1108/IJESM-03-2018-0001
First page: 470 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The development of the Marcellus Shale Play has altered the geography of production in the USA, particularly in the Northeast natural gas market. The purpose of this paper is to examine its impact on an already integrated industry. Design/methodology/approach The authors utilize the methodology of co-integration and focus on the geographic reach of the Marcellus region to examine movements of prices across the upstream, midstream and downstream segments of the industry. Findings The results of this paper indicate that prices across segments remain strongly co-integrated with the boom in production. The short-run dynamics, however, reveal a slower adjustment to the long-run equilibrium following the boom, particularly for wellhead to city-gate and wellhead to residential prices. Originality/value The growth in delivery infrastructure has not kept up with the boom in production creating bottlenecks. The supply shock brought about by the boom in production has not altered previously established co-integrating relationships but has altered the speeds of adjustment towards the long-run equilibrium. Citation: International Journal of Energy Sector Management PubDate: 2018-07-10T02:46:38Z DOI: 10.1108/IJESM-08-2017-0006
First page: 484 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to develop three methods including artificial bee colony algorithm (ABC-ANN), regression and adaptive neural fuzzy inference system (ANFIS) to predict the environmental indicators for land leveling and to analysis the sensitivity of these parameters. Design/methodology/approach This paper develops three methods including artificial bee colony algorithm (ABC-ANN), regression and adaptive neural fuzzy inference system (ANFIS) to predict the environmental indicators for land leveling and to analysis the sensitivity of these parameters. So, several soil properties such as soil, cut/fill volume, soil compressibility factor, specific gravity, moisture content, slope, sand per cent and soil swelling index in energy consumption were investigated. A total of 90 samples were collected from three land areas with the selected grid size of (20 m × 20 m). Acquired data were used to develop accurate models for labor, energy (LE), fuel energy (FE), total machinery cost (TMC) and total machinery energy (TM). Findings By applying the three mentioned analyzing methods, the results of regression showed that, only three parameters of sand per cent, slope and soil, cut/fill volume had significant effects on energy consumption. All developed models (Regression, ANFIS and ABC-ANN) had satisfactory performance in predicting aforementioned parameters in various field conditions. The adaptive neural fuzzy inference system (ANFIS) has the most capability in prediction according to least RMSE and the highest R2 value of 0.0143, 0.9990 for LE. The ABC-ANN has the most capability in prediction of the environmental and energy parameters with the least RMSE and the highest R2 with the related values for TMC, FE and TME (0.0248, 0.9972), (0.0322, 0.9987) and (0.0161, 0.9994), respectively. Originality/value As land leveling with machines requires considerable amount of energy, optimizing energy consumption in land leveling operation is of a great importance. So, three approaches comprising: ABC-ANN, ANFIS as powerful and intensive methods and regression as a fast and simplex model have been tested and surveyed to predict the environmental indicators for land leveling and determine the best method. Hitherto, only a limited number of studies associated with energy consumption in land leveling have been done. In mentioned studies, energy was a function of the volume of excavation (cut/fill volume). Therefore, in this research, energy and cost of land leveling are functions of all the properties of the land including slope, coefficient of swelling, density of the soil, soil moisture, special weight and swelling index which will be thoroughly mentioned and discussed. In fact, predicting minimum cost of land leveling for field irrigation according to the field properties is the main goal of this research which is in direct relation with environment and weather pollution. Citation: International Journal of Energy Sector Management PubDate: 2018-07-31T10:57:20Z DOI: 10.1108/IJESM-02-2017-0003
First page: 507 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Net energy importing countries (NEICs) pursue strategic policies to reduce the consumption of energy from conventional sources and increase that of renewable energy to attain energy security and sustainable development. However, net energy exporting countries (NEECs) rely substantially on the proceeds realised from oil and gas exports to mainly NEICs to finance government activities. This paper aims to investigate the effect of increased consumption of renewable energy in developed NEICs on the Nigeria’s oil and gas exports. Design/methodology/approach The study was undertaken by analysing macro-economic annual time-series data set (1980-2014) using autoregressive distributed lag (ARDL) bounds testing approach. Findings Both the short-run and the long-run results of the ARDL modelling reveal that renewable energy consumption in developed NEICs is affecting Nigeria’s oil and gas exports negatively, thereby causing significant decrease in the amounts of revenue being generated therefrom. Research Limitations/implications Like most empirical studies, the conduct of this research has encountered some challenges. Thus, the use of rather small sample in terms of period covered (1980-2014), annual frequency of data and focus on one NEEC (Nigeria) are the key limitations of this paper. While the first two challenges were dealt with by using ARDL, future research can focus on other NEECs to extend the study. Practical Implications The findings have several policy implications, including the need for Nigeria to focus on developing internal market trajectories to increase domestic utilisation of its conventional energy rather than depending on external markets. The results also suggest the need for public policymakers to develop a strategic plan that will effectively address the external economic threat arising from the influence of global energy transition. Originality/value To the best of the authors’ knowledge, this paper represents the first effort to empirically examine the effect of renewable energy consumption by developed NEICs on the Nigeria’s oil and gas exports. The paper contributes to the literature by providing insight into and documenting evidence that the world is taking transitioning to cleaner energy sources very seriously. Citation: International Journal of Energy Sector Management PubDate: 2018-07-31T01:42:35Z DOI: 10.1108/IJESM-11-2017-0010
First page: 525 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Energy scenarios have long been successfully used to inform decision-making in energy systems planning, with a wide range of different methodological approaches for developing and evaluating them. The purpose of this study is to analyze the existing approaches and classify them with a morphological box. Design/methodology/approach This paper builds upon the methodological literature on developing and evaluating energy scenarios and presents a morphological box, which comprises parameters describing the scenario properties, (energy system) model properties, scientific practice and institutional settings of energy scenarios. The newly developed morphological box is applied to four selected energy scenarios of the German energy transition. Findings The morphological box is a suitable tool to classify current energy scenarios. The exemplary application also points toward four challenges in the current practice of energy scenario development and evaluation: increasing complexity of decision problems, transparency of the scenario development process, transparency of the decision support process and communication of uncertainty. Originality/value The morphological box of energy scenarios helps researchers soundly document and present their methodological approaches for energy scenario development and evaluation. It also facilitates the work of analysts who want to classify, interpret and compare energy scenarios from a methodological perspective. Finally, it supports the identification of gaps between current practice and the methodological literature on energy scenarios, leading to the development of new types of energy scenarios. Citation: International Journal of Energy Sector Management PubDate: 2018-08-10T08:40:52Z DOI: 10.1108/IJESM-09-2017-0003
First page: 547 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to measure the state-level energy efficiency in Indian paper industry and simultaneously explain inter-state variation in efficiency by inefficiency effect model. Three variables, labor productivity, capital intensity and structure of paper industry, are included in inefficiency effect model to assess the likely impact on energy efficiency. Design/methodology/approach Sub-vector input distance function is derived through neo-classical production function which provides measures to estimate energy efficiency. Assuming a translog production function specification, energy efficiency is estimated by using Battese and Coelli (1995) stochastic frontier analysis (SFA). The authors also estimated four other SFA models, and energy efficiency from all the models is compared for robustness checking. Findings The results show the existence of a vast potential to improve energy efficiency. Inefficiency effect model reported a positive impact of structure of the industry and capital intensity on energy efficiency performance, while labor productivity does not have any significant impact on energy efficiency. There exists considerable energy efficiency variation among states. Uttarakhand, Punjab and Orissa are the best performing states while Rajasthan, Jharkhand and Goa have worst energy efficiency performance based on average efficiency. The ranks assigned to states according to inefficiency effects model are found contrary to the simple measure of energy efficiency, i.e. energy intensity. Thus, energy intensity may not always be a good proxy for underlying energy efficiency and need to be compared with a comprehensive possible measure. Originality/value To the best of the authors’ knowledge, this is the first study which measures energy efficiency of Indian paper industry through stochastic frontier model using region-level data. Instead of relying on traditional energy efficiency indicators (energy-output ratio), total-factor energy efficiency approach is used to conduct the empirical exercise. Deviations from the frontier because of factors beyond the scope of producers are also incorporated into analysis to portray the magnitude of random factors in influencing the efficiency performance. Citation: International Journal of Energy Sector Management PubDate: 2018-07-31T01:47:36Z DOI: 10.1108/IJESM-05-2017-0008
First page: 566 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to investigate the production of sugar cane ethanol in Brazil for the time period 1983-2016, separating the data by geographical location. Design/methodology/approach For this purpose, the authors use techniques based on the concept of fractional integration. Findings The authors show that the data corresponding to the total production is highly persistent, with an integration order smaller than 1 but close to it. In fact, the unit root hypothesis cannot be rejected implying that shocks have a permanent nature, and thus requiring policy measures to recover the level from exogenous shocks. Separating the data into two sub-regions, namely, North–Northeast and Central–South, higher levels of persistence are detected in the latter, while the former presents some evidence of mean reverting behavior, implying that shocks will disappear by themselves in the long run in the former regions. These results are obtained from all the different methods used. Originality/value The originality is based on the time series techniques used in the paper that departs from the classical methods based on unit roots and integer degrees of differentiation. Citation: International Journal of Energy Sector Management PubDate: 2018-08-24T11:58:26Z DOI: 10.1108/IJESM-05-2017-0004
First page: 581 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to investigate the drivers and inhibitors of the adoption of renewable energy by residential users. Based on the theoretical framework of consumer decision-making behaviour, an empirical study of the adoption of renewable energy in Malaysia was conducted. Design/methodology/approach A total of 501 residential users from the Klang Valley participated in this study. The data were analysed using partial least square (PLS) with Smart PLS 3.0 software. Findings The results indicated that the perceived utility of new technology, perceived utility of renewable energy and the perceived benefit of new technology were seen as the drivers of the adoption of renewable energy. At the same time, two inhibitor constructs, namely, perceived risk and perceived no need, were not seen to create a negative connection relating to the adoption of renewable energy. By contrast, as hypothesized, the perceived expense was the only factor that negatively correlated with the intentions to adopt renewable energy. To foster the intention to adopt renewable energy by residential users, more effort should be expended on capitalizing on the constructs of perceived benefits of new technology and the perceived utility of this new technology. Originality/value The current study contributes to the use of renewable energy in the country and indirectly to global renewable energy strategies. Citation: International Journal of Energy Sector Management PubDate: 2018-09-24T01:55:50Z DOI: 10.1108/IJESM-02-2017-0004
First page: 601 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. Design/methodology/approach This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented. Findings The results suggest that the amount of CO2 emissions related to fixed asset investments increased during the entire period. The social and economic effect played a major role in promoting carbon emissions, followed by the fixed asset effect. Therefore, the activity factor was the dominant positive factor, followed by the construction factor. The negative element was the energy effect, in which the energy intensity factor played an important role in reducing emissions, followed by the structural factor. Moreover, the carbon intensity factor might be a potential inhibitory force in reducing carbon emissions. Research/limitations/implications A steady financial policy, relaxed family planning, sustainable urbanization, strategy of innovation-driven development, reform of scientific and technological structures, development of science and technology and exploration of new energy sources are proposed to mitigate carbon emissions from fixed asset investments. The conclusion also provides a reference for developing countries in similar situations. Originality/value This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented. Citation: International Journal of Energy Sector Management PubDate: 2018-09-17T01:02:49Z DOI: 10.1108/IJESM-10-2017-0015
First page: 617 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Study conditions of empirical publications on time series modeling and forecasting of electricity prices vary widely, making it difficult to generalize results. The key purpose of the present study is to offer a comparison of different model types and modeling conditions regarding their forecasting performance. Design/methodology/approach The authors analyze the forecasting performance of AR (autoregressive), MA (moving average), ARMA (autoregressive moving average) and GARCH (generalized autoregressive moving average) models with and without the explanatory variables, that is, power consumption and power generation from wind and solar. Additionally, the authors vary the detailed model specifications (choice of lag-terms) and transformations (using differenced time series or log-prices) of data and, thereby, obtain individual results from various perspectives. All analyses are conducted on rolling calibrating and testing time horizons between 2010 and 2014 on the German/Austrian electricity spot market. Findings The main result is that the best forecasts are generated by ARMAX models after spike preprocessing and differencing the data. Originality/value The present study extends the existing literature on electricity price forecasting by conducting a comprehensive analysis of the forecasting performance of different time series models under varying market conditions. The results of this study, in general, support the decision-making of electricity spot price modelers or forecasting tools regarding the choice of data transformation, segmentation and the specific model selection. Citation: International Journal of Energy Sector Management PubDate: 2018-10-01T02:17:23Z DOI: 10.1108/IJESM-12-2017-0006
First page: 641 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose This paper aims to analyze the impact of the relations between the US oil prices, carbon emissions and GDP through the analysis of data between 1983 and 2013. Design/methodology/approach ARIMA, VAR and VEC models are used to establish synthesis integration model. Furthermore, the stability test, cointegration test and Granger causality test of the model were carried out. Findings The results indicate that, in both short and long term, change in oil prices is the reason for change in carbon emissions, while GDP is not the reason for the growth of carbon emissions. Originality/value Increase of oil prices would have a negative impact on carbon emissions, and GDP growth does not lead to an increase in carbon emissions. Citation: International Journal of Energy Sector Management PubDate: 2018-09-06T12:43:07Z DOI: 10.1108/IJESM-10-2017-0013
First page: 656 Abstract: International Journal of Energy Sector Management, Ahead of Print. PurposeThis study reviews present trends, barriers and outlooks for the future as seen by actors in the energy advice services market in Germany. As Germany is one of Europe’s leading markets for energy services, this review aims to highlight energy sector management issues that exist throughout Europe. Design/methodology/approachThis study combines qualitative and quantitative research approaches, using seven qualitative stakeholder interviews and a semi-structured survey covering over 500 energy advisors. Based on the present market, this study seeks to identify barriers against further market development, regulatory measures that can promote market development and business models for energy services likely to emerge in the future. FindingsSignificant barriers persist, despite a strong government commitment to support development of the energy services markets. The barriers encourage market actors to maintain the status quo rather than use innovate new service models. To support innovative business models, action is needed by both industry associations and the government to create a stronger demand pull for advice services. Originality/valueThis paper provides a new sectoral overview of Europe’s biggest energy service market as seen from a market actor perspective. It focuses on the analysis of barriers and business models to derive needs for further capacity building within the sector and for political governance to trigger further market dynamics. Citation: International Journal of Energy Sector Management PubDate: 2018-10-10T02:01:14Z DOI: 10.1108/IJESM-04-2018-0002
First page: 675 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Generation scheduling (GS) is the most prominent and hard-hitting problem in the electrical power industry especially in an integrated power system. Countless techniques have been used so far to solve this GS problem for proper functioning of the units in the power system to dispatch the load economically to consumers at once. Therefore, this work aims to study for the best possible function of integrated power plants to obtain the most favourable solution to the GS problem. Design/methodology/approach An appropriate method works in a proper way and assures to give the best solution to the GS problem. The finest function of incorporated power plants should be mathematically devised as a problem and via that the aim of the GS problem to minimize the total fuel cost subject to different constraints will be achieved. In this research work, the latest meta-heuristic and swarm intelligence-based technique called grey wolf optimization (GWO) technique is used as an optimization tool that will work along with the formulated problem for correct scheduling of generating units and thus achieve the objective function. Findings The recommended GWO technique provides the best feasible solution which is optimal in its performance for different test cases in the GS problem of integrated power plant. It is further found that the obtained solutions using GWO method are better than the former reports of other traditional methods in terms of solution excellence. The GWO method is found to be unique in its performance and having superior computational efficiency. Practical implications Decision making is significant for effective operation of integrated power plants in an electrical power system. The recommended tactic implements a modern meta-heuristic procedure that is applied to diverse test systems. The method that is proposed is efficient in providing the best solutions of solving GS problems. The suggested method surpasses the early techniques by offering the most excellent feasible solutions. Thus, it is obvious that the proposed method may be the appropriate substitute to attain the optimal operation of GS problem. Social implications Renewable energy sources are discontinuous and infrequent in nature, and it is tough to predict them in general. Further, integrating renewable energy source-based plants with the conventional plant is extremely difficult to operate and maintain. Operation of integrated power system is full of challenges and complications. To handle those complications and challenges, the GWO algorithm is suggested for solving the GS problem and thus obtain the optimal solution in integrated power systems by considering the reserve requirement, load balance, equality and inequality constraints. Originality/value The proposed system should be further tested on diverse test systems to evaluate its performance in solving a GS problem and the results should be compared. Computation results reveal that the proposed GWO method is efficient in attaining best solution in GS problem. Further, its performance is effectively established by comparing the result obtained by GWO with other traditional methods. Citation: International Journal of Energy Sector Management PubDate: 2018-10-16T02:00:01Z DOI: 10.1108/IJESM-07-2016-0001
First page: 696 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose Australia is one of the ten largest emitters of greenhouse gases but stands out from the others due to its economic growth without recession for 26 consecutive years. This paper aims to focus on the energy-growth nexus and the effects of energy consumption on the environment in Australia. Design/methodology/approach This analysis is performed using annual data from 1965 to 2015 and the autoregressive distributed lag model. Findings The paper finds empirical evidence of a trade-off between economic growth and carbon dioxide (CO2) intensity. The results show that increased gross domestic product (GDP) in Australia increased investment in renewable energy sources (RESs), although the renewable technology is limited and has no impact on reducing CO2 intensity in the long run. In contrast to investment in RES, fossil fuels, coal and oil, are decreased by GDP. However, oil consumption increased renewable energy consumption, and this reflects the pervading effect of the growing economy. Originality/value Overall, this paper contributes to the literature by analysing the behaviour of both energy consumption and the environment on the growing Australian economy. In addition, this paper goes further by studying the impact of economic growth on renewable and non-renewable energy consumption, as well as on CO2 emissions. The study is conducted on a single country for which literature is scarce, using a recent approach and a long time period. Citation: International Journal of Energy Sector Management PubDate: 2018-09-06T12:44:08Z DOI: 10.1108/IJESM-01-2018-0020
First page: 714 Abstract: International Journal of Energy Sector Management, Ahead of Print. Purpose The purpose of this paper is to study investments in renewable energy projects which are jointly operated with an energy storage system, with particular focus on risk-return characteristics from the perspective of private and institutional investors, taking into account resource risk, energy price risk, inflation risk and policy risk. Design/methodology/approach To this end, this paper presents a stochastic discounted cash flow model which is then applied to a wind farm with a pumped hydro storage system. Findings The results show that energy storage systems have the potential to increase the expected present value of future investment cash flows and to hedge (downside) risk. However, to realize this potential, storage systems have to be cost-effective in terms of fixed operation, maintenance, staffing and insurance costs. Also, several key factors are identified which have a considerable influence on the performance of the operation strategy. Originality/value The paper contributes to the literature by conducting an analysis of (downside) risk and return of renewable energy investments with a storage system taking into account stochastic policy, resource, inflation and energy price risk. Citation: International Journal of Energy Sector Management PubDate: 2018-10-02T12:55:49Z DOI: 10.1108/IJESM-02-2018-0009
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