scholarly journals Energy supply in Malawi: Options and issues

2017 ◽  
Vol 26 (2) ◽  
pp. 19 ◽  
Author(s):  
John L. Taulo ◽  
Kenneth Joseph Gondwe ◽  
Adoniya Ben Sebitosi
Keyword(s):  
Energy Supply ◽  
Energy Demand ◽  
Industrial Development ◽  
Current Status ◽  
Potential Contribution ◽  
Annual Growth Rate ◽  
Demand Forecast ◽  
Moderate Growth ◽  
Term Energy

Inadequate energy supply is one of the major problems confronting Malawi and limiting its social, economic and industrial development. This paper reviews the current status of energy supply and demand in Malawi; examines the major sources of energy, current exploitation status and their potential contribution to the electricity supply of the country; discusses key issues facing the energy sector; and identifies broad strategies to be implemented to tackle the energy supply challenges. Using secondary data for its critical analysis, the paper also presents modelling of long-term energy demand forecast in the economic sectors of Malawi using the Model for Analysis of Energy Demand (MAED) for a study period from 2008-2030. Three scenarios namely reference (REF), moderate growth (MGS) and accelerated growth (AGS) were formulated to simulate possible future long-term energy demand based on socio-economic and technological development with the base year of 2008. Results from all scenarios suggest an increased energy demand in consuming sectors with biomass being a dominant energy form in household and industry sectors in the study period. Forecast results reveal that energy demand will increase at an annual growth rate of 1.2% and reach 5160 ktoe in 2030 under REF scenario. The growth rates for MGS and AGS are projected at 1.5% each reaching 4639 ktoe and 5974 ktoe in 2030, respectively. The final electricity demand of about 105 ktoe in the base year will grow annually at average rates of 13.8%, 15.3% and 12.6% for REF, AGS and MGS, respectively. Over the study period 2008-2030 the annual electricity per capita will increase from about 111 kWh to 1062, 1418 and 844 kWh for the REF, AGS and MGS, respectively. The final energy intensity will decrease continuously from about 13.71 kWh/US$ in the base year to 3.88 kWh/US$, 2.98 kWh/US$ and 5.27 kWh/US$ for the REF, AGS and MGS, respectively in the year 2030. In conclusion, the paper outlines strategies that could be utilized to ensure adequate supply of modern energy which is a key ingredient for achieving sustainable social and economic growth.

Study and Application of the Mid-Long Term Energy early Warning System Based on SGM Model

2012 ◽  
Vol 512-515 ◽  
pp. 2519-2525
Author(s):  
Yi Xiang Deng ◽  
Si Qiang Wang
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Early Warning ◽  
Early Warning System ◽  
Energy Demand ◽  
Warning System ◽  
Living Standard ◽  
Demand Forecast ◽  
Term Energy

With the rapid economic development and improvement of the people’s living standard, the energy demand is increasing very fast in China. The national comprehensive energy early warning system is studied is this paper to adapt to the fundamental task of energy construction in China. On the energy demand forecast based on SGM model, the compreshensive energy warning system is built in this paper and put into the mid-long term enrgy early warning in China. For the BaU scenario, the comprehensive indices are dangerous both in 2020 and 2030; for the SD scenario, the comprehensive indices are attentive both in 2020 and 2030. So it can be concluded that the energy saving and sustainable development should be insisted to cope with the energy problems in China.

scholarly journals Long-term energy supply contracts in European competition policy: Fuzzy not crazy

Energy Policy ◽  
2009 ◽  
Vol 37 (12) ◽  
pp. 5399-5407 ◽  
Author(s):  
Adrien de Hauteclocque ◽  
Jean-Michel Glachant
Keyword(s):  
Competition Policy ◽  
Energy Supply ◽  
Supply Contracts ◽  
Term Energy

scholarly journals Long Term Household Electricity Demand Forecasting Based on RNN-GBRT Model and a Novel Energy Theft Detection Method

2021 ◽  
Vol 11 (18) ◽  
pp. 8612
Author(s):  
Santanu Kumar Dash ◽  
Michele Roccotelli ◽  
Rasmi Ranjan Khansama ◽  
Maria Pia Fanti ◽  
Agostino Marcello Mangini
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Sudden Change ◽  
Electricity Demand ◽  
Gradient Boosting ◽  
Forecasting Model ◽  
Demand Forecast ◽  
Daily Consumption ◽  
Energy Provider

The long-term electricity demand forecast of the consumer utilization is essential for the energy provider to analyze the future demand and for the accurate management of demand response. Forecasting the consumer electricity demand with efficient and accurate strategies will help the energy provider to optimally plan generation points, such as solar and wind, and produce energy accordingly to reduce the rate of depletion. Various demand forecasting models have been developed and implemented in the literature. However, an efficient and accurate forecasting model is required to study the daily consumption of the consumers from their historical data and forecast the necessary energy demand from the consumer’s side. The proposed recurrent neural network gradient boosting regression tree (RNN-GBRT) forecasting technique allows one to reduce the demand for electricity by studying the daily usage pattern of consumers, which would significantly help to cope with the accurate evaluation. The efficiency of the proposed forecasting model is compared with various conventional models. In addition, by the utilization of power consumption data, power theft detection in the distribution line is monitored to avoid financial losses by the utility provider. This paper also deals with the consumer’s energy analysis, useful in tracking the data consistency to detect any kind of abnormal and sudden change in the meter reading, thereby distinguishing the tampering of meters and power theft. Indeed, power theft is an important issue to be addressed particularly in developing and economically lagging countries, such as India. The results obtained by the proposed methodology have been analyzed and discussed to validate their efficacy.

scholarly journals A hybrid stochastic model based Bayesian approach for long term energy demand managements

2020 ◽  
Vol 28 ◽  
pp. 100462
Author(s):  
Somayeh Ahmadi ◽  
Amir hossien Fakehi ◽  
Ali vakili ◽  
Morteza Haddadi ◽  
Seyed Hossein Iranmanesh
Keyword(s):  
Stochastic Model ◽  
Bayesian Approach ◽  
Energy Demand ◽  
Model Based ◽  
Term Energy

LONG-TERM ENERGY SUPPLY AND DEMAND PROJECTIONS

OPEC Review ◽  
1977 ◽  
Vol 1 (6) ◽  
pp. 7-21
Author(s):  
Amir H. Maghen ◽  
Ivan Bejarano G.
Keyword(s):  
Energy Supply ◽  
Supply And Demand ◽  
Term Energy
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