scholarly journals Scenarios Analysis on Electric Power Planning Based on Multi-Scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8515
Author(s):  
Moussa Kanté ◽  
Yang Li ◽  
Shuai Deng
Keyword(s):  
Energy Demand ◽  
Electricity Demand ◽  
Reference Scenario ◽  
Annual Growth Rate ◽  
Investment Planning ◽  
Technological Parameters ◽  
Energy Agency ◽  
Promising Alternative ◽  
Sustainable Solutions

The increase in electricity demand is caused by population density, gross domestic product growth and technological conditions. A long-term forecast study on the electricity demand could be a promising alternative to the investment planning of power systems and distribution. In this study, the main aim is to forecast and understand the long-term electricity demand of the Taoussa area for the sustainable development of the regions of northern Mali, by using the Model for Analysis of Energy Demand (MAED) from the International Atomic Energy Agency. To fill such a knowledge gap, the long-term evolution of electricity demand is calculated separately for four consumption sectors: industry, transportation, service and household from 2020 to 2035. The demand for each end-use category of electricity is driven by one or several socioeconomic and technological parameters development of the country, which are given as part of the reference scenario (RS) and two alternative scenarios (Low and High). These scenarios were developed based on four groups of coherent hypotheses concerning demographic evolution, economic development, lifestyle change and technological change. The results showed that the annual growth rate of electricity demand in Taoussa area in all scenarios is expected to increase by only 8.13% (LS), 10.31% (RS) and 12.56% (HS). According to the seasonal variations of electricity demand, dry season electricity demand was higher than the demand in cool season during the study period. Such a conclusion demonstrates that the proposed long-term method and related results could provide powerful sustainable solutions to the electricity development challenges of Africa.

scholarly journals Scenarios Simulation and Analysis on Electric Power Planning Based on Multi-scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035

2021 ◽  
Author(s):  
Moussa Kanté ◽  
Yang Li ◽  
Shuai Deng
Keyword(s):  
Energy Demand ◽  
Average Rate ◽  
Peak Load ◽  
Electricity Demand ◽  
Reference Scenario ◽  
Analysis Tool ◽  
Planning Period ◽  
Peak Demand ◽  
Energy Agency ◽  
Scenarios Simulation

A long-term forecast study on the electricity demand of Taoussa of Mali is conducted in this paper, with various scenarios of socioeconomic and technological conditions. The analysis tool, which is applied in scenarios simulation, is the Model for Analysis of Energy Demand from the International Atomic Energy Agency. The analysis results are annual electricity demand and peak load forecast for the electrification from the period 2020 to 2035. During the planning period, the analysis results show that the electricity demand will increase to 49.40 MW (332.57 GWh) for the low scenario (LS), 66.46 MW (472.61 GWh) for the reference scenario (RS), and 89.47 MW (635 GWh) for the high scenario (HS). In addition, the total electricity demand increased at an average rate of 8.13% in the LS, 10.31% in the RS and 12.56% in the HS in all sectors. The electricity peak demand is expected to grow at 7.92%, 10.53% and 12.91% corresponding to the three scenarios; in this case, the system peak demand in 2035 will increase to 64.88 MW for the LS, 92.2 MW for the RS and 126.22 MW, the days of peak load are between 17th -23rd in May. The Industry sector will be the biggest electricity consumer of Taoussa area.

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.

Neither oil nor coal demand is likely to peak by 2040

2019 ◽  
Keyword(s):  
Energy Demand ◽  
Oil And Gas ◽  
International Energy Agency ◽  
Primary Energy ◽  
Energy Agency ◽  
Content Type ◽  
Primary Energy Demand ◽  
Term Energy ◽  
First Time

Subject Long-term energy markets outlook. Significance The International Energy Agency (IEA) has upgraded its forecast for total primary energy demand (TPED) to 2040 for the first time since it began projecting this far out in 2014. Impacts The IEA’s belief that the world is on an environmentally unsustainable path will bolster decarbonisation efforts nationally and globally. The IEA does not see oil demand peaking by 2040; this and gas’s growing share of global demand will help sustain oil and gas investment. China and India switching from coal to gas will reduce coal’s share of energy demand even though India’s official targets are optimistic.

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.

scholarly journals Pakistan’s Energy Demand Forecasting for Various Sector through Long Range Alternative Planning System

2021 ◽  
Vol 12 (1) ◽  
pp. 20
Author(s):  
Muhammad Mahboob ◽  
Muzaffar Ali ◽  
Tanzeel ur Rashid ◽  
Rabia Hassan
Keyword(s):  
Long Range ◽  
Policy Development ◽  
Energy Demand ◽  
Demand Forecasting ◽  
Planning System ◽  
Reference Scenario ◽  
Demand Forecast ◽  
Energy Forecasting ◽  
Energy Assets

Energy forecasting and policy development needs a detailed evaluation of energy assets and long-term demand estimation. The demand forecast of electricity is an essential portion of energy management, particularly in the formation of electricity. It is necessary to predict electricity needs to avoid the energy deficits or a destabilization between energy demand and supply. In this article, long-range energy alternative planning (LEAP) is used for the modeling of energy and various sectors in Pakistan as a case study. The simulated model comprises three different scenarios, a strong economy, a weak economy, and a medium economy as a reference scenario. The base year is 2015 and the outlook year is 2040. Electricity demands are almost more than four times those of the outlook year, increasing from 7.71 million tons of oil equivalent (MTOE) in 2015 to 29.77 MTOE by the end of 2040.

scholarly journals Interpretable Forecasting of Energy Demand in the Residential Sector

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6568
Author(s):  
Nikos Sakkas ◽  
Sofia Yfanti ◽  
Costas Daskalakis ◽  
Eduard Barbu ◽  
Marharyta Domnich
Keyword(s):  
Decision Support ◽  
Energy Demand ◽  
Demand Forecasting ◽  
Time Frame ◽  
Policy Support ◽  
Investment Planning ◽  
Explanatory Variables ◽  
Residential Sector ◽  
Time Frames

Energy demand forecasting is practiced in several time frames; different explanatory variables are used in each case to serve different decision support mandates. For example, in the short, daily, term building level, forecasting may serve as a performance baseline. On the other end, we have long-term, policy-oriented forecasting exercises. TIMES (an acronym for The Integrated Markal Efom System) allows us to model supply and anticipated technology shifts over a long-term horizon, often extending as far away in time as 2100. Between these two time frames, we also have a mid-term forecasting time frame, that of a few years ahead. Investigations here are aimed at policy support, although in a more mid-term horizon, we address issues such as investment planning and pricing. In this paper, we develop and evaluate statistical and neural network approaches for this mid-term forecasting of final energy and electricity for the residential sector in six EU countries (Germany, the Netherlands, Sweden, Spain, Portugal and Greece). Various possible approaches to model the explanatory variables used are presented, discussed, and assessed as to their suitability. Our end goal extends beyond model accuracy; we also include interpretability and counterfactual concepts and analysis, aiming at the development of a modelling approach that can provide decision support for strategies aimed at influencing energy demand.

scholarly journals Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

2021 ◽  
Vol 292 ◽  
pp. 116880
Author(s):  
Iris van Beuzekom ◽  
Bri-Mathias Hodge ◽  
Han Slootweg
Keyword(s):  
Energy Systems ◽  
Investment Planning ◽  
Urban Energy

scholarly journals MICRONUTRIENT CONTENTS IN THE PROFILE OF A RECOVERED SOIL WITH SEWAGE SLUDGE AND NATIVE SPECIES OF ATLANTIC FOREST

FLORESTA ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 485
Author(s):  
Lívia Mara Lima Goulart ◽  
Marianne Fidalgo de Faria ◽  
Grasiela Spada ◽  
Thiago Tássio de Souza Silva ◽  
Iraê Amaral Guerrini
Keyword(s):  
Sewage Sludge ◽  
Atlantic Forest ◽  
Soil Profile ◽  
Native Species ◽  
Control Treatment ◽  
Mineral Fertilization ◽  
Promising Alternative ◽  
Final Destination ◽  
Potassium Supplementation

The use of sewage sludge in agriculture and recovery of degraded areas has been shown as a promising alternative for its final destination. Studies on micronutrient levels after sludge application are necessary to avoid soil contamination at toxic levels. The objective of this work was to verify the micronutrient contents in the soil profile and pH, up to one-meter-deep, nine years after the application of sewage sludge and planting of native species of the Atlantic Forest. The experiment was implemented in a degraded Quartzeneic Neosol and conducted in randomized blocks with four replicates and eight treatments, consisting of six doses of sewage sludge (0, 2.5, 5, 10, 15 and 20 Mg ha-1, with supplementation of potassium due to low concentration in the residue), besides the control treatment, mineral fertilization and only potassium supplementation. After nine years, the contents of all micronutrients evaluated presented a significant response to the application of the treatments, and the application of sewage sludge provided an increase in their contents. Soil pH remained stable at sites receiving mineral fertilization and potassium supplementation. Only manganese and zinc showed mobility in the soil profile. The application of sewage sludge in degraded soil increases the micronutrient content and decreases its movement in the soil profile, and the application of the maximum dose of the residue does not provide toxic levels of these elements in the soil in the long term.

Low Alkaline Cement Used in the Construction of a Gallery in the Horonobe Underground Research Laboratory

2010 ◽  
Author(s):  
Masashi Nakayama ◽  
Haruo Sato ◽  
Yutaka Sugita ◽  
Seiji Ito ◽  
Masashi Minamide ◽  
...  
Keyword(s):  
Fly Ash ◽  
Research Laboratory ◽  
Concrete Lining ◽  
Energy Agency ◽  
Tunnel Support ◽  
Long Term Stability ◽  
Alkaline Conditions ◽  
High Level ◽  
Underground Research Laboratory

In Japan, any high level radioactive waste (HLW) repository is to be constructed at over 300 m depth below surface. Tunnel support is used for safety during the construction and operation, and shotcrete and concrete lining are used as the tunnel support. Concrete is a composite material comprised of aggregate, cement and various admixtures. Low alkaline cement has been developed for the long term stability of the barrier systems whose performance could be negatively affected by highly alkaline conditions arising due to cement used in a repository. Japan Atomic Energy Agency (JAEA) has developed a low alkaline cement, named as HFSC (Highly Fly-ash Contained Silicafume Cement), containing over 60 wt% of silica-fume (SF) and fly-ash (FA). HFSC was used experimentally as the shotcrete material in construction of part of the 140m deep gallery in the Horonobe Underground Research Laboratory (URL). The objective of this experiment was to assess the performance of HFSC shotcrete in terms of mechanics, workability, durability, and so on. HFSC used in this experiment is composed of 40 wt% OPC (Ordinary Portland Cement), 20 wt% SF, and 40 wt% FA. This composition was determined based on mechanical testing of various mixes of the above components. Because of the low OPC content, the strength of HFSC tends to be lower than that of OPC. The total length of tunnel using HFSC shotcrete is about 73 m and about 500 m3 of HFSC was used. The workability of HFSC shotcrete was confirmed in this experimental construction.

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