scholarly journals Assessment of Long-Term Sustainable End-Use Energy Demand in Romania

10.1596/31272 ◽  
2019 ◽  
Author(s):  
Sunil Malla ◽  
Govinda R. Timilsina
Keyword(s):  
Energy Demand ◽  
End Use

Assessment of long-term sustainable end-use energy demand in Romania

2018 ◽  
Vol 38 (3) ◽  
pp. 253-275
Author(s):  
Sunil Malla ◽  
Govinda R. Timilsina
Keyword(s):  
Energy Demand ◽  
End Use

Study on Dynamic Relationship between Economic Growth and Energy Consumption in Chongqing - Based on 1980-2011 Data

2013 ◽  
Vol 448-453 ◽  
pp. 4319-4324
Author(s):  
Sheng Wang ◽  
Chun Yan Dai ◽  
En Chuang Wang ◽  
Chun Yan Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Energy Consumption ◽  
Energy Demand ◽  
Industrial Structure ◽  
Impulse Response Function ◽  
Improve Energy Efficiency ◽  
Dynamic Relationship ◽  
Equilibrium Relationship

Analyzed the dynamic interaction characteristics of Chongqing Economic growth and energy consumption between 1980-2011 based on vector auto regression model, impulse response function. The results showed that: 1 Between the Chongqing's economic growth and energy consumption exist the positive long-term stable equilibrium relationship, Chongqing's economic development depending on energy consumption is too high, to keep the economy in Chongqing's rapid economic development, energy relatively insufficient supply sustainable development must rely on the energy market, which will restrict the development of Chongqing's economy. 2At this stage, Chongqing continuing emphasis on optimizing the industrial structure to improve energy efficiency at the same time, the key is to establish and improve the energy consumption intensity and total energy demand "dual control" under the security system, weakening the energy bottleneck effect on economic growth.

Long-Term Electricity Demand Forecast Using Multivariate Regression and End-Use Method: A Study Case of Maluku-Papua Electricity System

2021 ◽  
Author(s):  
Tumiran Tumiran ◽  
Sarjiya Sarjiya ◽  
Lesnanto Multa Putranto ◽  
Edwin Nugraha Putra ◽  
Rizki Firmansyah Setya Budi ◽  
...  
Keyword(s):  
Multivariate Regression ◽  
Electricity Demand ◽  
Demand Forecast ◽  
Electricity System ◽  
Study Case ◽  
End Use

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 Abatement cost for selectivity negative emissions technology in power plant Indonesia with aim/end-use model

2021 ◽  
Vol 894 (1) ◽  
pp. 012011
Author(s):  
Z D Nurfajrin ◽  
B Satiyawira
Keyword(s):  
Emission Reduction ◽  
Energy Demand ◽  
Reduction Potential ◽  
Abatement Cost ◽  
Energy Sector ◽  
Cost Curve ◽  
Baseline Scenario ◽  
Low Carbon ◽  
Ghg Emission ◽  
End Use

Abstract The Indonesian government has followed up the Paris Agreement with Law No. 16 of 2016 by setting an ambitious emission reduction target of 29% by 2030, and this figure could even increase to 41% if supported by international assistance. In line with this, mitigation efforts are carried out in the energy sector. Especially in the energy sector, it can have a significant impact when compared to other sectors due to an increase in energy demand, rapid economic growth, and an increase in living standards that will push the rate of emission growth in the energy sector up to 6. 7% per year. The bottom-up AIM/end-use energy model can select the technologies in the energy sector that are optimal in reducing emissions and costs as a long-term strategy in developing national low-carbon technology. This model can use the Marginal Abatement Cost (MAC) approach to evaluate the potential for GHG emission reductions by adding a certain amount of costs for each selected technology in the target year compared to the reference technology in the baseline scenario. In this study, three scenarios were used as mitigation actions, namely CM1, CM2, CM3. The Abatement Cost Curve tools with an assumed optimum tax value of 100 USD/ton CO2eq, in the highest GHG emission reduction potential, are in the CM3 scenario, which has the most significant reduction potential, and the mitigation costs are not much different from other scenarios. For example, PLTU – supercritical, which can reduce a significant GHG of 37.39 Mtoe CO2eq with an emission reduction cost of -23.66 $/Mtoe CO2eq.

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