Demand-Supply Forecasting based on Deep Learning for Electricity Balance in Cameroon

Mbasso, Wulfran Fendzi; Molu, Reagan Jean Jacques; Naoussi, Serge Raoul Dzondé; Kenfack, Saatong

doi:10.32479/ijeep.13092

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…It is a fundamental requirement for the economy of a country and the most important condition for the continuity of civilization [1]. The global population is continuously growing, leading to ever-growing energy demand [2]. In developing countries, energy is a vital resource for the development of remote areas [3].…”

Section: A Background Motivation and Literature Reviewmentioning

confidence: 99%

Optimizing Technical and Economic Aspects of Off-Grid Hybrid Renewable Systems: A Case Study of Manoka Island, Cameroon

Jacques Molu,

Naoussi,

Wira

et al. 2023

IEEE Access

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The lack of accessible and reliable electrical energy in Cameroon has become a pervasive obstacle to the nation's progress, with energy availability, quality, and cost identified as key hindrances to development over the past 15 years. Conventional solutions that rely on combustion engines and electrochemical storage systems have proven to be cost-prohibitive, limited in power output, and constrained in capacity. The dependence on traditional diesel generators has perpetuated maintenance challenges and a continuous demand for fuel supply, while the accompanying noise and pollution have restricted their use in residential areas. Recognizing the imperative of reducing dependence on fossil fuels and curbing greenhouse gas emissions, the need for clean and sustainable energy sources has emerged as a critical concern for the advancement of civilization. Against this backdrop, this research endeavors to identify the most cost-effective and efficient blend of renewable energy sources capable of meeting the power requirements of three small communities on Manoka Island, a district of Douala, Cameroon. Through a comprehensive technical, environmental, and economic analysis, this study addresses the substantial energy needs of 334 households, with an average daily power consumption of 1082.90 kWh and a peak electrical load of 183.99 kW. Leveraging the Hybrid Optimization Model for Electric Renewables (HOMER) program, this investigation assesses the feasibility of implementing Hybrid Renewable Energy Systems (HRES) to meet the region's energy demands. The research highlights the most optimal scenario integrating solar panels, wind turbines, battery cells, fuel cell generators, biogas, and an electrolyzer within an off-grid HRES system. Notably, the study demonstrated an absence of idle load, resulting in remarkably low unit energy costs of $0.1981 and a compelling net present value of $2,209,741. The cost-effective arrangement featured 201 batteries, yielding a project profit of $57,387, with an impressive Internal Rate of Return (IRR) of 9.09%, Return on Investment (ROI) of 6.19%, and a payback period of 8.76 years over a 25-year term. In essence, the insights gleaned from this exploration of hybrid energy systems represent a pioneering case study in sustainable electricity provision. This research significantly contributes to the knowledge base on renewable energy within the nation, underscoring its tremendous potential for sustainable development and energy security. INDEX TERMSHybrid Renewable Energy, Off grid, Optimization, Techno-economic Nomenclature A Rotor swept area (m 2 ) 𝑨 𝒈 Fuel consumption coefficient (l/kW) 𝑩 𝒈 Fuel consumption coefficient (l/kW) 𝑪 𝒂𝒏𝒏,𝒕𝒐𝒕

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Section: A Background Motivation and Literature Reviewmentioning

confidence: 99%

Optimizing Technical and Economic Aspects of Off-Grid Hybrid Renewable Systems: A Case Study of Manoka Island, Cameroon

Jacques Molu,

Naoussi,

Wira

et al. 2023

IEEE Access

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A case study of a neighborhood in Douala examining the technical feasibility of a hybrid renewable energy system connected to the grid for energy and oxygen production in the fight against respiratory diseases

Wulfran,

Raoul,

Jacques

et al. 2023

Solar Compass

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Oil and gas well repair analysis technique based on data mining in management

Нургалиева,

Латыпова

2022

Моделирование, Оптимизация И Информационные Технологии

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Одним из важнейших шагов для увеличения прибыли в нефтедобыче, наряду с инвестициями в оборудование, поиском и открытием новых месторождений, является аналитика. Эффективность добычи нефти и газа на существующих месторождениях можно повысить с помощью комплексного анализа существующего потока данных. Мониторинг добычи нефти и газа и профилактический ремонт скважин предполагают сбор и обработку данных о функционировании скважин. Этих данных не всегда достаточно для принятия точных решений по управлению ремонтами скважин. Ряд проблем нельзя выявить из-за скудности информации, в связи с чем снижается эффективность принимаемых решений. Мониторинг ремонта скважин с использованием интеллектуального анализа данных выполняет ряд функций. Во-первых, он определяет состояние критических условий ремонта скважины, для которых будет разработан план действий. Во-вторых, он предоставляет руководству обратную связь, определяя причины прошлых положительных и отрицательных результатов. В статье предлагается методика анализа ремонта нефтегазовых скважин при управлении на основе интеллектуального анализа данных с использованием поиска последовательных шаблонов ремонта. Методика апробирована в нефтегазовой компании ПАО «Газпром нефть» на данных по ремонту скважин месторождений сообщества «Газпромнефть-Ноябрьскнефтегаз». One of the most important steps to increase profits in oil production is not only investment in equipment, exploration and discovery of new fields, but also analytics. The efficiency of oil and gas production in existing fields can be improved through a comprehensive analysis of the existing data stream. Monitoring of oil and gas production and preventive maintenance of wells involve the collecting and processing of data on the functioning of wells. Such data are not always sufficient for making accurate decisions on well repair management. A number of problems cannot be identified due to the scarcity of information, and therefore the efficiency of the decisions is reduced. Well repair monitoring using data mining performs a number of functions. Firstly, it determines the status of critical well repair conditions for which an action plan will be developed. Secondly, it provides management with feedback by identifying the causes of past positive and negative results. The article proposes an oil and gas well repair analysis technique based on data mining with the aid of repair sequential pattern mining in management. The technique was tested in the oil and gas company Gazpromneft on oil and gas well repair data of Gazpromneft-Noyabrskneftegaz community field.

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Demand-Supply Forecasting based on Deep Learning for Electricity Balance in Cameroon

Cited by 3 publications

References 16 publications

Optimizing Technical and Economic Aspects of Off-Grid Hybrid Renewable Systems: A Case Study of Manoka Island, Cameroon

Optimizing Technical and Economic Aspects of Off-Grid Hybrid Renewable Systems: A Case Study of Manoka Island, Cameroon

A case study of a neighborhood in Douala examining the technical feasibility of a hybrid renewable energy system connected to the grid for energy and oxygen production in the fight against respiratory diseases

Oil and gas well repair analysis technique based on data mining in management

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