International Journal of Energy Sector Management

Bishoge, Obadia Kyetuza; Zhang, Lingling; Mushi, Witness Gerald; Matomela, Nametso

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-11-2018-0003

This paper aims to analyze the context of community opinions and participation in the natural gas sector in developing countries, a case study of Tanzania. To achieve this purpose, the study pointed out six facts, namely, information on the natural gas sector; awareness of the natural gas-related policies; laws and regulations and the creation of employment opportunities; local experts in the natural gas sector; the use of natural gas revenues; and natural gas for poverty reduction and improvement of social well-being.Design/methodology/approachThe study is a systematic review of the literature on community participation based on the relevant studies published between 2010 and 2018. A comprehensive literature review was carried out following the seven-step model whereby relevant themes from different potential bibliographic databases such as Google Scholar were systematically selected, compiled and analyzed using descriptive methods.FindingsThe study revealed that despite the various efforts made by the governments and other stakeholders to promote community participation, there is an inadequate level of community participation in the natural gas sector in developing countries. There are limited local experts for natural gas operations and low transparency on natural gas contracts, agreements and revenues. Therefore, there is the need to raise awareness for a highly informed society with a clear sense of ownership of the natural gas wealth among the local communities. Moreover, transparency and accountability are recommended for the sustainable natural gas sector development.Originality/valueThis paper offers new and current cross-sectoral inclusion, opinions, hopes and concerns of the community on the natural gas sector management in developing countries.

Faccio, Maurizio; Nedaei, Mojtaba; Pilati, Francesco

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-11-2018-0005

The current study aims to propose a new analytical approach by considering energy consumption (EC), maximum tardiness and completion time as the primary objective functions to assess the performance of parallel, non-bottleneck and multitasking machines operating in dynamic job shops.Design/methodology/approachAn analytical and iterative method is presented to optimize a novel dynamic job shop under technical constraints. The machine’s performance is analyzed by considering the setup energy. An optimization model from initial processing until scheduling and planning is proposed, and data sets consisting of design parameters are fed into the model.FindingsSignificant variations of EC and tardiness are observed. The minimum EC was calculated to be 141.5 hp.s when the defined decision variables were constantly increasing. Analysis of the optimum completion time has shown that among all studied methods, first come first served (FCFS), earliest due date (EDD) and shortest processing time (SPT) have resulted in the least completion time with a value of 20 s.Originality/valueConsiderable amount of energy can be dissipated when parallel, non-bottleneck and multitasking machines operate in lower-power modes. Additionally, in a dynamic job shop, adjusting the trend and arrangement of decision variables plays a crucial role in enhancing the system’s reliability. Such issues have never caught the attention of scientists for addressing the aforementioned problems. Therefore, with these underlying goals, this paper presents a new approach for evaluating and optimizing the system’s performance, considering different objective functions and technical constraints.

Jain, Achala; Huddar, Anupama P.

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-07-2018-0015

The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units.Design/methodology/approachThe proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique.FindingsThe proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization.Originality/valueTo validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.

Jahangoshai Rezaee, Mustafa; Dadkhah, Mojtaba; Falahinia, Masoud

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-09-2018-0015

This study aims to short-therm forecasting of power generation output for this purpose, an adaptive neuro-fuzzy inference system (ANFIS) is designed to forecast the output power of power plant based on climate factors considering wind speed and wind direction simultaneously.Design/methodology/approachSeveral methods and algorithms have been proposed for systems forecasting in various fields. One of the strongest methods for modeling complex systems is neuro-fuzzy that refers to combinations of artificial neural network and fuzzy logic. When the system becomes more complex, the conventional algorithms may fail for network training. In this paper, an integrated approach, including ANFIS and metaheuristic algorithms, is used for increasing forecast accuracy.FindingsPower generation in power plants is dependent on various factors, especially climate factors. Operating power plant in Iran is very much influenced because of climate variation, including from tropical to subpolar, and severely varying temperature, humidity and air pressure for each region and each season. On the other hands, when wind speed and wind direction are used simultaneously, the training process does not converge, and the forecasting process is unreliable. The real case study is mentioned to show the ability of the proposed approach to remove the limitations.Originality/valueFirst, ANFIS is applied for forecasting based on climate factors, including wind speed and wind direction, that have rarely been used simultaneously in previous studies. Second, the well-known and more widely used metaheuristic algorithms are applied to improve the learning process for forecasting output power and compare the results.

A. Kassem, Mukhtar; Khoiry, Muhamad Azry; Hamzah, Noraini

2019 International Journal of Energy Sector Management

doi: 10.1108/IJESM-11-2018-0002

PurposeThis study aims to investigate the risk factors in construction projects in oil and gas processing facilities in Yemen and serves as a case study for developing countries.Design/methodology/approachBy using a questionnaire, data were collected from 201 project managers and engineers employed in different sectors in the oil and gas industry in Yemen.FindingsThe survey analysis based on Kruskal–Wallis test method shows a high degree of agreement on the perceptions of risk factors depending on categories of companies. In other words, the tested risk factors exist in all sectors of oil companies in Yemen and are valid as a measure of risk factors in construction projects in oil and gas organizations in general. Although no evidence suggests that the risk factors differ significantly according to job title, the result of identifiable risk factors according to experience shows a statistically significant difference among participants in terms of their experience. The relative importance of the ranking of risk factors was obtained by the statistical analysis of responses on the impact and likelihood of occurrence of these risks. Findings show that internal risks are the greatest influential factors in construction projects in the oil and gas sector, followed by changes during construction project, government instability, incorrect project cost estimation, government delay in decision making, incorrect project schedule estimation, and political situation and war in the country.Originality/valueThese findings are valuable to organizations that are planning to conduct construction projects for oil and gas processing facilities in Yemen and other nations with similar environments, such as developing countries.

Krömer, Sarah

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-10-2018-0010

The purpose of this paper is to assess model risk with regard to wind energy output in monthly cash flow models for the purpose of valuation and risk assessment of wind farm investments, where only a few approaches exist in the literature.Design/methodology/approachThis paper focuses on the risk-return characteristics of this investment from the perspective of private and institutional investors and takes into account several risks, in particular the resource risk related to the uncertainty of the monthly wind energy produced. To this end, this paper presents different approaches for modeling monthly wind power output and assesses the impact of three selected models with different properties on the investment’s risk-return characteristics by means of a stochastic discounted cash flow model. In addition, the model considers the possibility of a joint operation of the wind farm with a pumped hydro storage system to reduce risk and improve profits.FindingsThe results show that the (non-)consideration of seasonality of the monthly wind energy produced considerably influences the risk-return characteristics, but that principal developments dependent on input parameters and model variables remain similar.Originality/valueThis paper contributes to the literature by presenting different approaches for modeling the monthly wind energy produced based on direct models of the wind energy output, which are rare in the existing literature. Further, their impact on risk-return characteristics of a wind farm investment is analyzed, and thus, related model risk is assessed.

Soon, Kok Yew; Chua, Kein Huat; Lim, Yun Seng; Wang, Li

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-02-2018-0010

This paper aims to propose a comprehensive methodology for setting up rural electrifications for indigenous villages with minimum budgets and the lowest possible cost of electricity (COE). The electricity accessibility of rural area in Malaysia is not fully covered and the cost of extending the grid to these areas can be high as RM 2.7m per km. Lack of vigorous policies and economic attraction of the rural areas are also the main barriers to rural electrification. Electricity is an essential element of economic activities and the lack of electricity exacerbates poverty and contributes to its perpetuation. Therefore, a hybrid standalone power system can be an alternative solution for the rural electrification. A hybrid standalone power system is studied to investigate the potential of the implementation and the budget required.Design/methodology/approachA site survey has been carried out in a village in Peninsular Malaysia, namely, Kampung Ulu Lawin Selatan. A standalone hybrid system is modeled in HOMER Pro software and the data collected from the selected site are used to obtain the system configuration with the lowest COE. The load following and cycle charging energy dispatch methods are compared to identify the optimal system configuration that yields the lowest COE. The diesel generator-only system is chosen as a benchmark for comparisons.FindingsThe results show that the hybrid system constituted from the diesel generator, photovoltaic (PV), micro-hydro and energy storage using the load following energy dispatch method yields the lowest COE of RM 0.519 per kWh. The COE of the hybrid system is 378 per cent lower than that of the diesel generator-only system. The lead-acid energy storage system (ESS) is able to reduce 40 per cent of COE as compared to the system without ESS.Originality/valueThe results indicate that the COE of the diesel-micro hydro-PV-ESS system with load following dispatch strategy is RM 0.519 per kWh, and this value is 35 per cent higher than the average electricity price in Malaysia. However, it is important to note that the costs of extending the grid to the rural area are not taken into account. If this cost is considered into the electricity price, then the standalone hybrid power system proposed by this study is still a competitive alternative for rural electrification.

Kengne Signe, Elie Bertrand; Kanmogne, Abraham; Emmanuel, Guemene D.; Meva’a, Lucien

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-07-2018-0014

The purpose of this paper is contribution to estimate the potential of wind energy in Douala in Cameroon, by modeling and predicting the regime of wind. The paper deals with the analysis and comparison of seven numerical methods for the assessment of effectiveness in determining the parameters for the Weibull distribution, using wind speed data collected at Douala International Airport in Cameroon, in the period from September 2011 to May 2013, obtained by meteorological equipment belonging to the Laboratory of Energy Research of the Institute of Geological and Mining Research.Design/methodology/approachBy using ANOVA, root mean square error and chi-square tests to compare the proposed methods, this study aims to determine which methods are effective in determining the parameters of the Weibull distribution for the available data, in an attempt to establish acceptable criteria for better usage of wind power in Douala, which is the economic capital and ought to have prominence in the use of renewable sources for electricity generation in Cameroon.FindingsThe study helps to determine that moment, empirical and energy pattern factor methods used to determine the shape parameter k and the scale parameter c of the Weibull distribution present a better curve fit with the histogram of the wind speed. This fact is clearly validated by means of the statistical tests. But, all the seven methods gave excellent performance. Then, k reaching levels ranging from 3.5 to 5.5 and c range from 1.7 to 2.4.Originality/valueThen as far as we are concerned, for a significant contribution, it could be more effective to have a model for prediction of wind characteristics using wind data collected per hour, one at least three years. A comparison of results obtained from lots of other methods (seven in this case) is necessary before an efficient discussion. Standard deviations and errors between measured and predicted data must also be presented.

Pandey, Ajay Kumar; Ghodke, Manjushree

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-10-2018-0006

The purpose of this paper is to develop an interpretive structural modeling (ISM) of barriers related to viability of Power Distribution Companies (discoms) in India.Design/methodology/approachFeedback from the Experts of Indian power sector has been taken as the basis to develop the model for barriers to viability of discoms, where major barriers have been identified through extent review of literature and through discussions with experts in the power sector keeping the viability of discoms in focus, and the hierarchical structure of barriers has been developed using ISM.FindingsAn interpretive structural model has been developed for discom-related factors (barriers) affecting its viability. The hierarchical structure portrays the impeding factors of viability and showcases that lack of regulatory effectiveness, inadequate tariffs and lack of government’s expenditures on power sector are the key barriers.Research limitations/implicationsThis paper has implications for both practitioners and academics. For practitioners, it provides an indicative list of major barriers affecting the viability of Indian discoms. For academics, the methodology used provides a mechanism to conduct an exploratory study by identifying the key variables of interest and emphasizing their interactions through hierarchical structures.Originality/valueThe proposed model for barriers to viability of discoms developed through qualitative modeling technique is a pioneering effort altogether in the context of power distribution companies in India. Understanding contextual relationships among key barriers to viability of discom’s is neglected in existing literature, and this paper makes a contribution in this regard.

Goswami, Kishor; Choudhury, Hari K.; Hazarika, Atanu; Tripathi, Rohit

2019 International Journal of Energy Sector Management

doi: 10.1108/ijesm-11-2018-0009

This paper aims to analyze the economic viability of jatropha plantation in North East India.Design/methodology/approachEconomic viability is measured through the net present value and the benefit–cost ratio (BCR) at four different production standards along with four different prices of jatropha seed.FindingsAt a very low price and small production, jatropha plantation is economically not feasible. However, when the price of seed increases from INR 5 to 8, BCRs become greater than 1, provided that the discount rate is less than equal to 8 per cent. The minimum threshold of BCR indicates that the threshold of 1.5 BCR at a production level of 1.5 tons/ha can be achieved with a combination of seed price of INR 10 per kg and a discount rate of 1 to 3 per cent. Thus, jatropha cultivation is economically viable but not highly profitable.Research limitations/implicationsPresent study analyzes the economic viability of jatropha plantation from purely financial point of view. Social cost and benefit of energy crop plantation is not included in the study. This suggests to adopt social cost–benefit analysis to evaluate the overall feasibility of plantation crops in future studies.Originality/valueThis paper contributes to the academic literature of economic viability of energy plantation crops. Economic viability of jatropha plantation is shown in different cost and revenue conditions with statistical evidences.