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Pumped hydro-energy storage (PHES) development involves heavy investment with stringent environmental and social requirements. Therefore, selecting the best site is a key influencer of the plant's ability to sustainably provide the expected benefits throughout its whole lifecycle. An important contribution could be provided by developing specific tools for improving decision accuracy while addressing the issue of sustainability through the decision-making process. In this view, this study aims to propose a decision-making model for selecting the best alternative from a number of predetermined PHES candidate sites, in a perspective of sustainable development. The approach is based on the identification of decision factors and criteria, and the use of multi-criteria decision-making (MCDM) techniques such as the analytic hierarchy process (AHP), rating scales and fuzzy logic-based scoring systems, and the ELimination and Choice Expressing REality (ELECTRE) III. These methods are comprehensively selected and combined to deal with the heterogeneity of the information and the vagueness of human preference and, to operationalise the concept of strong sustainability. Its practicality and efficiency was successfully tested on a set of eleven PHES candidate sites in Western Cameroon. As result the five best alternatives to be considered in the framework of the country's sustainable power generation policy were suggested in descending order of priority: (1)-Enep, (2)-Mbatu-dam, (3)-Benakuma, (4)-Bamendjin, (5)-Mentchum. • A decision-making model based on multiple criteria analysis for pumped hydro-energy storage plant site selection is provided. • Sustainability is a key issue to address when planning pumped hydro-energy storage. • The foremost ranking of some pumped hydro-energy storage opportunities in Cameroon is proposed. [ABSTRACT FROM AUTHOR]

Abstract Energy access in Sub-Saharan Africa (SSA) remains a challenging issue at the midway point to the United Nations' development goals. From the perspective of energy efficiency and diversification of power-generation sources, this paper investigates the capacity of the wood-processing industry to contribute to the decentralised power generation by performing a techno-economic analysis of the use of wood residues for cogeneration. Using a survey performed in Cameroon as a case study, a biomass-fuelled cogeneration scheme and a model analysing its viability are proposed for the specific context of SSA. A sensitivity analysis indicates for a given process efficiency of the industry, the attractiveness of cogeneration as the processing capacity and feed-in tariffs of electricity increase. More specifically, the threshold of feed-in tariffs ensuring the economic viability of CHP in the sub-region is estimated at $0.15 per kWh for mills where the output capacities of sawn timber products are of 5000 cubic metre per annum and more. The power-generation potential from the primary processing of timbers in the sub-region is about 388 kWh per cubic metre of sawn wood, while the energy intensity of the sawing process is estimated at 132 kWh per cubic metre. Therefore, the industry can generate up to 2472 GWh of electricity in the three sub-regions of East, West and Central Africa if a total of US$ 2.5 billion is invested, allowing a substantial increase of 1% of the current electricity-generation capacity for the geographic location which has the most important forestry resources on the continent. Highlights • Wood-processing residues can contribute significantly to the distributed power generation in African forestry regions. • Energy patterns and the biomass feedstocks from wood-processing industries in Sub-Saharan Africa is comprehensively analysed. • The condensing-extraction steam turbine appears to be the most suitable technology for wood-fired CHP in Sub-Saharan Africa. • A model analysing the viability of industrial wood-fired CHP in the particular context of Sub-Saharan Africa is provided. • Key barriers to the development of waste-wood-fuelled CHP in Sub-Saharan Africa are identified. [ABSTRACT FROM AUTHOR]

• Carbon dioxide recharge and limnic eruption processes in deep lakes are reviewed. • Novel system associating pumped-hydro storage and deep lakes degassing is analysed. • The proposed system gives way to sustainable and useful gas removal from deep lakes. • Technical arrangements for pumped-hydro storage at natural deep lakes is provided. • The levelised cost of storage for the proposed system is analysed. Nowadays, pumped-hydro storage is the most established large-scale energy storage technology, but its implementation is seriously constrained by the availability of favourable sites. The geographical symbiosis between mountainous areas and deep lakes offers good prospects for the detection of such sites. In these areas, the generally meromictic structure of such lakes causes carbon dioxide saturation in the deep waters and, in order to mitigate the risk of lethal limnic eruptions as the world has already experienced, the gas-lift technique is being applied although it has a serious environmental drawback. This paper proposes an innovative and sustainable symbiotic match between pumped-hydro energy storage with the ideal deep lake degassing solution, providing removal of toxic gases from deep layers without polluting the surface waters of the lake. Considering the two Cameroonian "killer lakes" Nyos and Monoun taken as cases studies, the feasibility of the proposed system is analysed as well as conditions for participation in the local power market. As a result, the threat posed by these two hazardous water bodies is transformed into an opportunity to store about 756 MWh of electrical energy. In terms of installed capacity, this can achieve as much as 80 MW available for harnessing variable renewable energy and contributing to peak power supply. Finally, thanks to the number and distribution of deep lakes around the world, the proposed system shows capability to significantly contribute to the global energy storage potential in a context marked by an ever increasing need for flexibility in power systems. [ABSTRACT FROM AUTHOR]

Poor access to electricity remains a major hindrance to the economic development in Central Africa sub-region. To address this issue the Central African Power Pool (CAPP) has been established with the vision to create and manage a regional cross-borders exchange of electricity based on the development of the sub-region's enormous hydropower potential. However, the implementation of this vision is struggling with poor visibility on information related to the potential and the state-of-the-art of the development of hydropower in the member states. The objective of this work is to review the literature and data pertaining to the potential of hydropower and state of development in Cameroon, in the perspective of full access to energy in Central Africa as targeted by CAPP. The reviewed documents include both research articles and reports of investigative works carried out in the field of hydropower by various technical commissions since 1970s. This encompasses conventional hydropower at large and small schemes, storage dams and, pumped-storage for which a comprehensive synthesis of the available data and information appears crucial. A better understanding of the current state of hydropower in the country is provided as well some policy recommendations for a hydro-based development of the power sector in the whole sub-region. It is hoped that this paper contributes to synthesising the various assessments of Cameroon's hydropower potential, so as to address the issue of lack of visibility on data and information in the sector, as this has hitherto been a handicap to the fulfilment of the pool's vision. • The present situation and upcoming development of Central Africa Power Pool is discussed. • The pivotal role of Cameroon in achieving Central Africa Power Pool's objective is highlighted. • Many large hydropower and storage plants in Cameroon might feed the Inga-Calabar power highway. • Small-hydropower and pumped-storage are showing good prospects for electrifying many remote areas in Cameroon. • A few hydropower projects are under construction while most of them are still awaiting financing. [ABSTRACT FROM AUTHOR]

The effectiveness of a photovoltaic (PV) system can be increased by using maximum power point tracking (MPPT). The literature has suggested a number of methods for tracking the maximum power point (MPP). However, this number of methods most often presents a high convergence speed in reaching the MPP, complexity under their implementation, power fluctuations, overshoots, and great difficulty in reaching the MPP under fast-changing atmospheric conditions, thus influencing the efficiency of PV systems. Intending to improve the performance of PV systems under rapid changes in the atmosphere, this paper proposes model reference adaptive control (MRAC) as a technique for tracking the MPP based on the employ of reference models such as optimal voltage and current at the MPP ( V MPP and I MPP ). The MATLAB/Simulink environment is used to produce the simulation results; the Kyocera Solar KC 130 GT module is used here as a photovoltaic power plant, connected to a boost converter, supplying a resistive load. The Lyapunov theory was used to demonstrate the stability of the system. The simulation outcomes obtained using the suggested method are compared with those obtained by techniques such as perturb and observe (P&O), incremental conductance (INC), variable step incremental conductance (VSINC), particle swarm optimization (PSO), and grey wolf optimization (GWO), thus showing a very large improvement under standard test and fast-changing atmospheric conditions of the technique proposed on the other techniques in terms of convergence speed and tracking efficiency. The simulation results prove that the suggested method has great tracking effectiveness (>99.88%), less time for convergence (<0.01 s), and simple implementation complexity under fast-changing atmospheric conditions without both transient and steady-state power oscillations, overshoots, and chattering effects, thus causing a great minimization of energy losses, and the proposed technique reaches exactly the MPP under fast-changing atmospheric conditions. [ABSTRACT FROM AUTHOR]

Electricity as an energy carrier par excellence has a vital role in economic development. However, even with the transformation of power systems that follows technological development, mastering the electricity consumption dynamics remains a challenge task. Therefore, in order to be able to develop effective energy policies based on accurate projections, the search for better consumption modelling options is nowadays the focus of many researchers. Given the emerging use of quantile regression, decision tree and artificial neural network models for prediction, this study tries to address the issue of their performances in assessing electricity consumption drivers. A sample of data from a household's electricity consumption survey in Cameroon was used as the empirical context for application of these three models through a comparative analysis. Factors related to equipment and their use, household income level, housing structure, residential living, energy-saving behaviour and weather conditions showed a significant influence on electricity consumption. Artificial neural network model proved to be more efficient than quantile regression and decision tree, with root mean square error (RMSE), mean absolute error (MAE), and mean absolute error percentage (MAPE) lower values and a higher determination coefficient (R2) value. It is expected that these results serve as a reference for making a decision when selecting the most accurate approach for better understanding of those drivers that have the greatest impact on energy demand. • Divers of households electricity consumption are questioned. • Quantile regression, Decision Tree en Artificial Neural Network is used for estimate drivers of energy demand. • Artificial neural network model proved to be more efficient than others approaches. • Appliances, household income, housing structure and weather conditions showed greatest impact on energy demand. [ABSTRACT FROM AUTHOR]

Promoting cost-effective energy efficiency actions is an important objective for many countries, as this appears to be one of the ultimate and effective strategies to ensure reliable access to energy while reducing greenhouse gas emissions. As this is a key challenge facing developing countries, assessing the potential for energy savings in households appears as a crucial action to be considered by local policymakers, given the growing importance of residential electricity demand and the difficulties they face in managing the supply/demand balance of electricity. The literature review reveals a shortage of knowledge on residential electricity consumption behaviours in sub-African developing countries. Noting this gap, an energy demand frontier function is used to assess the potential for electricity savings in the residential sector in Cameroon, taking as a case study. The result showed that: households have an average efficiency of 62.4% with a range of 71%, which implies a significant potential for reducing electricity consumption. Rural households emerged more efficient than urban households. The study also clarify the potential for demand management at the household level which confirms that the efficiency level varies according to technical and social standards. This assessment is the very first of its kind in Cameroon. • Electricity savings potential in Cameroonian households are questioned. • Energy demand frontier function model is used for estimate efficiency index. • Rural households are more efficient than urban households. • Cameroonian households have an average efficiency of 62.4% with a range of 71%. [ABSTRACT FROM AUTHOR]