Electric power needs in developing countries: cogeneration and standardization

Author(s):  
R. Bollini ◽  
L.T. Youn
2019 ◽  
Vol 3 (2) ◽  
pp. 131
Author(s):  
Wildan Wildan

This study aims to determine the amount of electric power needs each year in South Sulawesi until 2025. This estimation aims to determine the large power needs of South Sulawesi until 2025 by using the DKL 3.02 method used to estimate the need for electric power in the future based on data the use of energy and electric power, population growth, and economic growth in South Sulawesi Province, namely the GDP of South Sulawesi Province from previous years before the estimated year. The estimated results of the total electricity demand for all sectors from 2015 amounted to 2,452,130,065 VA and up to the year 2025 amounted to 5,246,811,618 VA with an average growth of 7.48%.


1999 ◽  
Vol 38 (1) ◽  
pp. 69-84 ◽  
Author(s):  
Abdul Ghafoor ◽  
John Weiss

The electric power sector in Pakistan is growing faster (II percent) than the average growth rate of other developing countries (10 percent). However, the demand in Pakistan is growing even faster than the supply and therefore power shortage has become a serious problem. The problem is compounded by inefficiency of electric power sector. Moreover there is underpril:ing. subsidising, overstaffing and inadequate maintenance. Like many other developing countries, Pakistan has also opted for "privatisation" in the form of transfer of ownership as the first best solution. However, a wide range of literature argues that such type of privatisation in the case of electric power may not lead to miracles. The present a11icle attempts to analyse the past inefficiency of the electric power sector in Pakistan and performs a diagnostic analysis to identify sources and causes of inefficiencies. This analysis does not necessarily support a strict privatisation based reform. The article further discusses the salient feature of privatisation of electric power sector in Pakistan' and some important issu,es related to its feasibility. It is noted that the privatisation of electric power sector in Pakistan, as pursued now, may not resolve the problems of this sector. It may ease short-run financial constraints but it may also create a number of long-term problems such as inappropriate planning, greater energy dependence and insecurity. It is also noted that current problems stem primarily from institutional and organisational constraints faced by public sector power enterprises. The key issue may not be a choice between public or private ownership but to determine an appropriate reform package based on either public/private or a mixed ownership structure, that encourages greater private involvement and functions well in the specific environment of Pakistan.


2019 ◽  
Vol 9 (1) ◽  
pp. 67
Author(s):  
Xue Jiang

As one of the branch of English for Science and Technology, English for Electric Power bears the characteristic of professionalism in meaning and flexible in lexis. As key components in professional literatures, lexis of English for Electric Power needs to be paid enough attention and accurately identified in order to precisely comprehend professional reading materials. This paper focuses on solving the problem of identifying Electric English vocabulary precisely by analyzing the determination of the professional lexis from three aspects of morphological structure, reference relations and context. Distinguishing the meaning of Electric Power English vocabulary is a crucial part in the translation practice of Electric Power English, which  plays a vital role in ultimately understand and grasp the content of professional materials fully.


Energy Policy ◽  
1985 ◽  
Vol 13 (4) ◽  
pp. 320-325 ◽  
Author(s):  
Robert J. Saunders ◽  
Karl Jechoutek

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3154
Author(s):  
Yongguang Zhu ◽  
Deyi Xu ◽  
Saleem H. Ali ◽  
Ruiyang Ma ◽  
Jinhua Cheng

Nighttime light data are often used to estimate some socioeconomic indicators, such as energy consumption, GDP, population, etc. However, whether there is a causal relationship between them needs further study. In this paper, we propose a causal-effect inference method to test whether nighttime light data are suitable for estimating socioeconomic indicators. Data on electric power consumption and nighttime light intensity in 77 countries were used for the empirical research. The main conclusions are as follows: First, nighttime light data are more appropriate for estimating electric power consumption in developing countries, such as China, India, and others. Second, more latent factors need to be added into the model when estimating the power consumption of developed countries using nighttime light data. Third, the light spillover effect is relatively strong, which is not suitable for estimating socioeconomic indicators in the contiguous regions between developed countries and developing countries, such as Spain, Turkey, and others. Finally, we suggest that more attention should be paid in the future to the intrinsic logical relationship between nighttime light data and socioeconomic indicators.


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