Hydropower plants are among the most efficient and reliable renewable energy systems in the world as far as electricity production is concerned. Run-of-river hydropower plants seem more attractive than conventional hydroelectric plants since they can be a cheaper and environmentally friendly alternative. However, their expected energy production pattern heavily depends on several construction variables that need an appropriate design using specific models. This paper analyzes several existing models used for the calculation of the diameter and thickness of a penstock, the optimal selection and implantation (admissible suction head) of a turbine, to estimate the energy produced and expected cost of small hydropower projects for grid-connected and off-grid/micro-grid applications. This review particularly brings out the specificities of each of the models to suggest the most appropriate model according to the context of study and proposes methods to use them more efficiently. This review can be used as a guide in the design and simulation of run-of-river hydropower plants, thus helping in the assessment of the economic feasibility of projects that usually requires a high level of experience and expertise.

Wind potential estimation is generally evaluated using two-parameter (k, c) Weibull distribution. Root Mean Square Error (RMSE), Coefficient of Determination (R²) and Relative Error (RE) are computed in order to comparatively analyse fourteen methods of determining Weibull parameters. They are the Graphical Method, the Standard Deviation Method, the Empirical Method of Justus, the Empirical Method of Lysen, the Energy Pattern Factor Method, the Maximum Likelihood Method, the Modified Maximum Likelihood Method, the Alternative Maximum Likelihood Method, the Least Square Method, the Weighted Least squares Method, the Curve Fitting Method, the Wind Variability Method, the Moroccan Method and the Median and Quartile Method. These methods have been applied on three different windy sites (slightly, moderately and very windy sites) with hourly wind data over a period of 10 years (2005–2014), measured at 10 m height. As a result, compared to the other methods, Energy Pattern Factor method is the more suitable method applicable to assess the Weibull parameters for all wind speeds. However, the values obtained from RMSE, R² and RE tests revealed that the WVM and MoroM methods are not suitable while all other methods are acceptable for the estimation of k and c. parameters. The determination of the wind power density and the gap between the predicted standard deviation by each method and the measured standard deviation for all the sites highlighted the relevance of EPFM method and the others methods. Moreover, this work reveals that the Weibull shape factor k decrease with height above ground level, while that of the scale factor c increase with height.

Run-of-river hydropower plants are a cost-efficient technology that produce a power output proportional to the instantaneous flow of water diverted from the exploited stream by exploiting several mechanical, hydraulic, and electric devices. However, as no storage is available, its design and operation is tailored according to the unpredictability of its power generation. Hence, the modelling of this type of power plants is a necessity for the promotion of its development. Accordingly, based on models from the literature, this study proposes a comprehensive methodology for optimally designed small run-of-river hydropower plants based on a levelized cost of energy (LCOE). The proposed methodology aims at facilitating a faster design for more cost-effective and energy-efficient small hydropower plants. Depending on the average daily flow rates and the gross head of a given site, the model proposed in this study calculates the diameter, thickness, and length of a penstock; it also suggests the optimal selection of a turbine, determines the admissible suction head of a turbine for its optimal implementation, and determines the optimal number of turbines, all in order to minimize the LCOE of the proposed project. The model is tested to design a small run-of-river hydropower plant with a capacity of 6.32 MW exploiting the river Nyong in Mbalmayo. The results confirm the profitability of the investment with an LCOE of around 0.05 USD/kWh, which is the lowest limit value of the LCOE range for small hydropower plants, as presented in the IPCC (Intergovernmental Panel on Climate Change) report, assuming a project lifespan of 50 years and a discount rate of 12.5%. These results also show that it may be worth to provide the energy sector with a small hydropower design tool with a graphical interface. In addition, it would be appropriate to use a similar method in an off-grid context where a hydropower plant, with or without storage, is combined with another source to meet the electrical needs of a given population.

Peer-to-peer (P2P) energy trading using blockchain is presented as a great innovative potential to promote rural electrification. Opportunities and challenges assessment for the implementation of this technology in Sub-Saharan Africa shows that it is only at its embryonic stage in the region. The decreasing cost of stand-alone solar technology and the expansion of investment in mini-grid sector are among the opportunities. However, the considerable restriction of private participation in the mini-grid sector, the difficulty of the regulatory process and licensing requirements, the issues with tariff framework, and the uncertainty of the regulation about the future grid integration are among the main challenges. This chapter proposes a policy and regulation framework for the promotion of P2P energy trading using blockchain in Sub-Saharan Africa. Request access from your librarian to read this chapter's full text.

Sub-Saharan African power systems face persistent access and reliability constraints under high financing costs, making the viability of capital-intensive firm low-carbon generation highly dependent on de-risking. Small Modular Reactors (SMRs) are increasingly proposed for medium-sized grids, yet decision-relevant evidence remains limited because nuclear is rarely included in cross-country financing datasets and many assessments use stylized discount rates. This paper addresses these gaps through a two-stage financial modelling approach. First, a peer-reviewed cost-of-capital framework is extended to derive country-level costs of capital for nuclear and SMRs across Africa, yielding continent-wide averages of 14.5% (mature large nuclear) and 15.4% (FOAK SMRs). Second, these financing conditions are translated into project-finance outcomes for Cameroon using a FINPLAN cash-flow appraisal of a FOAK 420 MW SMR, benchmarked against firm hydropower anchored on the 420 MW Nachtigal project. At a reference tariff of 65 €/MWh and 15% discounting, the SMR is strongly unviable (project NPV −951 M€; IRR 7.1%; DSCR_min 0.59) and implies an affordability gap (LCOE=170 €/MWh). Sensitivities show SMR deployability requires either single-digit effective WACC (NPV > 0 only below 7%) or a much higher tariff (176 €/MWh at 15%), alongside major FOAK CAPEX reduction and strict schedule/IDC risk control. Hydropower remains near the affordability frontier, supporting hydro-led transition pathways in Cameroon.