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Abstract This paper explores scenarios for powering rural areas in Gaita Selassie with renewable energy plants, aiming to reduce system costs by optimizing component numbers to meet energy demands. Various scenarios, such as combining solar photovoltaic (PV) with pumped hydro-energy storage (PHES), utilizing wind energy with PHES, and integrating a hybrid system of PV, wind, and PHES, have been evaluated based on diverse criteria, encompassing financial aspects and reliability. To achieve the results, meta-heuristics such as the Multiobjective Gray wolf optimization algorithm (MOGWO) and Multiobjective Grasshopper optimization algorithm (MOGOA) were applied using MATLAB software. Moreover, optimal component sizing has been investigated utilizing real-time assessment data and meteorological data from Gaita Sillasie, Ethiopia. Metaheuristic optimization techniques were employed to pinpoint the most favorable loss of power supply probability (LPSP) with the least cost of energy (COE) and total life cycle cost (TLCC) for the hybrid system, all while meeting operational requirements in various scenarios. The Multi-Objective Grey Wolf Optimization (MOGWO) technique outperformed the Multi-Objective Grasshopper Optimization Algorithm (MOGOA) in optimizing the problem, as suggested by the results. Furthermore, based on MOGWO findings, the hybrid solar PV-Wind-PHES system demonstrated the lowest COE (0.126€/kWh) and TLCC (€6,897,300), along with optimal satisfaction of the village's energy demand and LPSP value. In the PV-Wind-PHSS scenario, the TLCC and COE are 38%, 18%, 2%, and 1.5% lower than those for the Wind-PHS and PV-PHSS scenarios at LPSP 0%, according to MOGWO results. Overall, this research contributes valuable insights into the design and implementation of sustainable energy solutions for remote communities, paving the way for enhanced energy access and environmental sustainability.

Abstract Economic development relies on access to electrical energy, which is crucial for society’s growth. However, power shortages are challenging due to non-renewable energy depletion, unregulated use, and a lack of new energy sources. Ethiopia’s Debre Markos distribution network experiences over 800 h of power outages annually, causing financial losses and resource waste on diesel generators (DGs) for backup use. To tackle these concerns, the present study suggests a hybrid power generation system, which combines solar and biogas resources, and integrates Superconducting Magnetic Energy Storage (SMES) and Pumped Hydro Energy Storage (PHES) technologies into the system. The study also thoroughly analyzes the current and anticipated demand connected to the distribution network using a backward/forward sweep load flow analysis method. The results indicate that the total power loss has reached its absolute maximum, and the voltage profiles of the networks have dropped below the minimal numerical values recommended by the Institute of Electrical and Electronics Engineers (IEEE) standards (i.e., 0.95–1.025 p.u.). After reviewing the current distribution network’s operation, additional steps were taken to improve its effectiveness, using metaheuristic optimization techniques to account for various objective functions and constraints. In the results section, it is demonstrated that the whale optimization algorithm (WOA) outperforms other metaheuristic optimization techniques across three important objective functions: financial, reliability, and greenhouse gas (GHG) emissions. This comparison is based on the capability of the natural selection whale optimization algorithm (NSWOA) to achieve the best possible values for four significant metrics: Cost of Energy (COE), Net Present Cost (NPC), Loss of Power Supply Probability (LPSP), and GHG Emissions. The NSWOA achieved optimal values for these metrics, namely 0.0812 €/kWh, 3.0017 × 106 €, 0.00875, and 7.3679 × 106 kg reduced, respectively. This is attributable to their thorough economic, reliability, and environmental evaluation. Finally, the forward/backward sweep load flow analysis employed during the proposed system’s integration significantly reduced the impact of new energy resources on the distribution network. This was evident in the reduction of total power losses from 470.78 to 18.54 kW and voltage deviation from 6.95 to 0.35 p.u., as well as the voltage profile of the distribution system being swung between 1 and 1.0234 p.u., which now comply with the standards set by the IEEE. Besides, a comparison of the cost and GHG emission efficiency of the proposed hybrid system with existing (grid + DGs) and alternative (only DGs) scenarios was done. The findings showed that, among the scenarios examined, the proposed system is the most economical and produces the least amount of GHG emissions.

Abstract The impacts of climate change, combined with the depletion of fossil fuel reserves, are forcing human civilizations to reconsider the design of electricity generation systems to gradually and extensively incorporate renewable energies. This study aims to investigate the technical and economic aspects of replacing all heavy fuel oil (HFO) and light fuel oil (LFO) thermal power plants connected to the electricity grid in southern Cameroon. The proposed renewable energy system consists of a solar photovoltaic (PV) field, a pumped hydroelectric energy storage (PHES) system, and an ultra-capacitor energy storage system. The economic and technical performance of the new renewable energy system was assessed using metrics such as total annualized project cost (TAC), loss of load probability (LOLP), and loss of power supply probability (LPSP). The Multi-Objective Bonobo Optimizer (MOBO) was used to both size the components of the new renewable energy system and choose the best location for the solar PV array. The results achieved using MOBO were superior to those obtained from other known optimization techniques. Using metaheuristics for renewable energy system sizing necessitated the creation of mathematical models of renewable energy system components and techno-economic decision criteria under MATLAB software. Based on the results for the deficit rate (LPSP) of zero, the installation of the photovoltaic field in Bafoussam had the lowest TAC of around 52.78 × 106€ when compared to the results for Yaoundé, Bamenda, Douala, and Limbe. Finally, the project profitability analysis determined that the project is financially viable when the energy produced by the renewable energy systems is sold at an average price of 0.12 €/kWh.

Access to clean, cost-effective, and available energy is essential for the sustainable development of a country. Nowadays, the production of energy from fossil fuels has environmental and economic disadvantages. In this context, this work proposes to study the technical and economic aspects of the replacement of a 20 MW Light Fuel Oil (LFO) thermal power plant by a hybrid Photovoltaic Pumped Hydro Storage System (PV-PHSS) power plant in northern Cameroon. The objective is to minimize the total life cycle cost (TLCC) of the proposed hybrid system with a loss of power supply probability (LPSP) below a defined limit. To obtain optimal results, several meta-heuristics such as Artificial Bee Colony (ABC), Water Cycle Algorithm (WCA), Grey Wolf Optimizer (GWO), and African Vulture Optimization Algorithm (AVOA) have been used. Moreover, the optimal sizing of the hybrid system components was performed under MATLAB software using real-time information and meteorological data from the selected site. All the algorithms achieved good results. However, the WCA algorithm delivered a slightly better result than the other algorithms.

In order to improve on system reliability, utilities conduct contingency scenarios to determine the impact of component outages to the network. It is usually challenging to conduct this analysis due to the complex grid structure. However, the huge consequences of an equipment outage on the grid and the connected loads are compelling enough for researchers to find ways to mitigate these events. Several blackouts have occurred in various parts of the Southern Interconnected Grid (SIG) of Cameroon due to the transient state of the power system. The most recent was the blackout that kept a greater part of the country's political capital, Yaounde, for several days with no electricity. The paper analyses 44 single line (N-1) contingency scenarios in the SIG using ETAP in order to evaluate the impact of line outage events on grid stability. A combined performance index was calculated from the bus voltage security index (PIV/Vsp), real power flow index (PIΔP), reactive power flow index (PIΔQ) and the branch overloading security index (PIS/Ssp). The results showed that the Mangombe - Oyomabang line outage (scenario 22) was the most severe with the load flow failing to converge, followed by the Oyomabang - Ngousso line 1 (scenario 36) with combined performance indices of 992.6191 and 79.74415 respectively. Other scenarios showed overloaded lines, overloaded transformers, high power losses and under/over bus voltages. This study has identified lines with high vulnerability and should be used by utility operators to enhance the reliability of the transmission network and minimize its susceptibility to cascaded power outages.

A decentralized intelligent droop-based control strategy is proposed in this paper for the enhancement of equal active and reactive power sharing in an islanded inverter-based microgrid. Droop control is mostly preferred because it does not need communication facilities for its implementation. However, the presence of different feeder impedances for the different distributed generators (DGs) in a microgrid make reactive power sharing inaccurate. Furthermore, as a result of considerable load changes and different droop characteristics for the DGs, the inverter's output voltage and frequency are altered and these in turn alter the reactive and active power sharing respectively. With these conditions, the generalized droop control (GDC) strategy fails to effectively share load reactive and active power among the DGs. In order to extenuate these challenges, this paper presents a nonlinear autoregressive exogenous neural network droop-based control (NARX-NN DBC) strategy which does not depend on the varying line impedances, droop gains for the different DGs and is less affected by fluctuating loads in the grid. A microgrid, made up of two DGs and a load is modelled in MATLAB/Simulink environment and validation of the proposed control strategy is done through many simulations. Within the simulation runtime, NARX-NN DBC yielded a maximum frequency percentage deviation of 0.46% from the nominal value of 50 Hz whereas GDC yielded 0.62%. Regarding the voltage, NARX-NN DBC gave maximum deviation of 0.026% meanwhile GDC gave 0.079% from the nominal value for 380 V. In addition, during 0.57–0.64 s with load active power demand of 4.6 kW, NARX-NN DBC registered 0.43% power sharing error whereas GDC registered 6.5%. On the other hand, during 0.57–0.64 s, with 5kVAr load power demand, NARX-NN DBC registered 0.2% whereas, GDC registered 2%. These obtained results clearly show that NARX-NN DBC strategy has a better performance compared to GDC strategy with respect to power sharing in an autonomous microgrid.

The power system is a network of components having specific operational limits such that any violation of these limits during their operation could lead to more damage in the grid. The grid in Cameroon has been facing several undesired loading events at some sections of the network and the utility company has over the years, employed measures to mitigate these issues. This study has used the ETAP software to conduct a contingency analysis on the largest independent grid in Cameroon, supplying 6 regions in Cameroon. Seventeen transformer outage events in the network were used to conduct the N-1 scenario-based contingency, so that the vulnerability of the network can be evaluated. The fast decoupled power flow method was continuously applied on the network, and the different contingency scenarios were ranked using a combination of 4 performance indices. These four performance indices gave information on the impact of the various transformer outage scenarios on the grid. The four indices were added to give a combined value, and the outages were ranked in order of severity based on this combined index. A major contribution of this paper is the use of four scalar indices to classify the critical elements in the grid of a developing country. The initial load flow simulation of the network showed that 12 nodes had under voltages, while 3 transformers and one transmission line were overloaded. The Ngousso corridor suffered one of the worst under voltage situation during the initial power flow study. This is an indication that the utility company needs to undertake intensive network upgrade and implore measures to increase power generation to support the growing loads. It was observed that all the contingency scenarios experienced convergence. The Oyomabang transformer 1 had the highest combined index of 71.20, showing a huge negative impact on the network as a result of the outage of the transformer. This was followed by the Oyomabang transformer 2 with a combined index of 48.63. The results will be very useful to utility operators in prioritizing transformers in the network with high risk of causing huge impact on the network in case of an outage.

AbstractThe Cameroon power sector is currently undergoing a period of transition with government setting ambitions to increase the generation of clean electricity to meet the rapidly growing demand. A significant aspect of this transition is the phasing out of some thermal plants and supporting power generation with renewables. This can be achieved through the heavy exploitation of the renewable energy resources in the country. In line with this goal, the study assesses the feasibility of a 211.75 MW solar PV power plant in Yaounde, Cameroon using RETScreen Expert. The simulation showed an annual electricity production of 304,668.191 MWh with arrays mounted on a fixed axis. The model considered a debt ratio of 40%, debt interest rate of 12%, PV cost per kW of $1371 and a total system initial cost of $291,791,500. The annual revenue from exporting power to the grid was $36,560,183 and a capacity factor of 16.4%. The solar PV project was economically viable with a cost of energy (COE) of $75.43/MWh or $0.075/kWh and a gross annual GHG emission reduction potential of 61,004.5 tCO2 corresponding to 141,870.9 barrels of crude oil not used throughout the project life time. The benefit-cost ratio obtained in the simulation was 4.5 which implies that the project is profitable (ratio is greater than 1). The project break-even point of equity payback was 9.2 years while the simple payback was 8.9 years. The PV system had an IRR-assets of 7.4%, which was below the debt interest rate of Cameroonian financial institutions hence, the project will be attractive to investors. Also, the project risk and sensitivity analysis showed that a reduction in the project’s initial cost had a significant effect on the net present value (NPV) and the cost of energy production. Similarly, a rise in the grid electricity export reduced the cost of energy production when the confidence level was set to 90%.

The state of the Ghana Power System reflects a story of progress, challenges, and future potential. Ghana has experienced significant milestones and achievements in its power system, including the development of major infrastructure projects such as the Akosombo Dam and initiatives to expand access to electricity. The country has also made strides in diversifying its energy mix by embracing renewable energy sources. However, challenges exist, including the need to address system reliability, aging infrastructure, financial viability, and rural electrification. The integration of emerging technologies, such as smart grid solutions, energy storage systems, and regional power interconnections, offers opportunities for a sustainable and reliable power system. Recommendations for Ghana's power sector focus on diversification, grid flexibility, infrastructure upgrades, energy efficiency, institutional strengthening, and regional cooperation. Implementing these recommendations holds the promise of building a resilient, affordable, and environmentally sustainable power system for Ghana's future.

Nowadays, renewable energy generation has gained a lot of attention in the global electrical energy production. This has led to an increased integration of distributed generators into the traditional electrical grid, standalone generations as well as the formation of microgrids. The continuous increase in microgrid penetration has resulted in the microgrids becoming neighbours to one another, thus, favouring the interconnection of these microgrids to form the multi-microgrids. The multi-microgrids infrastructure has the potential to improve energy availability, reliability and reduction in the net cost of energy through sharing of resources. The notion of unidirectional power flow that normally applies to the traditional electrical grid is no longer applicable in this context. This paper investigates the advantages of several microgrids’ interconnection on the system reliability within the town of Goma in the Democratic Republic of the Congo (DRC) using the Homer Grid software for optimal sizing of components considering technical and economic aspects. From the potential assessment of this case study, it is realized that the methane gas present in Kivu Lake and solar PV are potential distributed sources that can be used. In addition, it was observed that when connected to the Virunga private grid, the system with PV can be sold to the grid with a payback period of about seven years. The system made of Generator, PV and battery was found to be the most reliable. This led to the conclusion that, the interconnection of several microgrids produces a more stable and reliable system, especially when different sources of energy are used.

Cameroon’s electricity mix is dominated by hydropower sources despite the huge potentials of other sources like solar. The over-dependence on hydropower has led to frequent load shedding especially in the dry season as a result of low water levels. Interestingly, the government plans to diversify her power mix and provide sustainable energy to Cameroonians. It is in this framework that this study evaluates the integration of solar PV into the Southern Interconnected Grid of Cameroon using dynamic analysis. The ETAP tool was used in developing the model. A power loss assessment was done through successive injection of solar PV into the candidate busbars while monitoring the active power losses in the grid. Then, a transient stability analysis was conducted so as to assess the grid’s response to induced instability after the penetration of large-scale solar PV. The study showed that the use of static performance indices to evaluate the solar PV hosting capacity do not safeguard the grid’s technical robustness. The results indicated an optimum solar PV penetration level of 30% (211.8 MW) at the Ngousso 93 kV busbar. The findings will be useful to system operators and regulators in developing low-carbon pathways in the electricity network in Cameroon.

The Intergovernmental Panel on Climate Change (IPCC) 2021 report has noted the perceived rise in severe weather phenomena such as heat radiations, hurricanes, flooding, and droughts and the rising scientific evidence attributing these events to anthropogenic sources of climate change. Cameroon as a nation is equally exposed to these climate vulnerabilities, and contributing to global climate efforts is imperative. She has earmarked the integration of 25% renewables in its electricity production mix and a 32% emission reduction, all as part of her commitment to global climate action. The fresh commitments coupled with a rapidly growing power demand have paved the way for a revolutionized approach to electricity generation in Cameroon. However, the imminent changes, as well as their implications, remain uncertain. This study explores how these emission reduction targets can be achieved through the adoption of a more sustainable power transition, which provides realistic solutions for emission reduction, escaping high carbon pathways. The assessment of the level at which long-term electricity generation scenarios in Cameroon could be renewable energy intensive was done using the Low Emissions Analysis Platform (LEAP) tool following a backcasting approach. The study noted that there is an implementation gap between earmarked policy ambitions and existing measures. The study recommended several opportunities in aspects, such as suitable share of technologies, administrative reforms, and required adjustments within the Nationally Determined Contributions (NDCs), which the government could exploit in the electricity sector to sail across the challenging trade-offs needed to become a sustainable economy in a carbon-constrained world. It equally examines actions that could help close the gap between earmarked policy ambitions and existing pathways and proposes cost-effective methods that were identified as priorities.

Renewable energy solutions are appropriate for on-grid and off-grid applications, acting as a supporter for the utility network or rural locations without the need to develop or extend costly and difficult grid infrastructure. As a result, hybrid renewable energy sources have become a popular option for grid-connected or standalone systems. This paper examines hybrid renewable energy power production systems with a focus on energy sustainability, reliability due to irregularities, techno-economic feasibility, and being environmentally friendly. In attaining a reliable, clean, and cost-effective system, sizing optimal hybrid renewable energy sources (HRES) is a crucial challenge. The presenters went further to outline the best sizing approach that can be used in HRES, taking into consideration the key components, parameters, methods, and data. Moreover, the goal functions, constraints from design, system components, optimization software tools, and meta-heuristic algorithm methodologies were highlighted for the available studies in this timely synopsis of the state of the art. Additionally, current issues resulting from scaling HRES were also identified and discussed. The latest trends and advances in planning problems were thoroughly addressed. Finally, this paper provides suggestions for further research into the appropriate component sizing in HRES.

The manufacturing process of renewable energy components involves some conventional energy at different steps. It is then clear that the fabrication of the components of a renewable energy system will emit an amount of greenhouse gas(GHG). The work carried out in this paper is based on investigating a sample of 1m2 solar panel and analyzing the energy involved in its complete fabrication process as well as the amount of GHG emitted. The energy generated by the sample during its useful lifetime is evaluated and the prevented amount of carbon dioxide (CO2 recovered) computed; that CO2 recovered is the amount of GHG which could have been emitted if the conventional energy sources were to be used to generate that same amount of lifetime energy. The greenness percentage with regards to renewable energy material (photovoltaic) is then defined as a ratio of GHG emission (CO2-eq.) during fabrication and GHG prevented (CO2 recovered) as a result of had been using the panel throughout its entire lifetime. It appears that if manufactured in china and installed in Cameroon, the 1m2 module exhibits a greenness percentage of 49.14% in Bamenda and 29% in Ngaoundéré. The same photovoltaic sample is 98.43% green if manufactured in Cameroon and installed in China. Thus, a solar panel installed in china, if manufactured in Cameroon will need only about 0.44 years to compensate the amount of GHG emitted during manufacturing in Cameroon which is equivalent to a gain of more than 29 years of pollution free period out of the 30 years of expected average lifetime of a photovoltaic module. Keywords: Renewable energy, Silicon solar cell, Manufacturing process, Green energy, Carbon footprint, Pollution, Greenness percentage, Lifetime, Conventional energy, Sunshine

Power system operators are in search of proven solutions to improve the penetration levels of distributed generators (DGs) in the grid while minimizing cost. This transition is driven, among others, by global climate concerns, the growing power demand, the need for greater flexibility, the ageing grid infrastructure and the need to diversify sources of energy production. Distributed renewables would not easily substitute the conventional electric grid system, perhaps because the latter is a well-established technology and it would not be prudent to abandon it, while the new distributed renewable energy technologies are generally not adequately developed to support the total load. Thus, it is becoming increasingly necessary to consider sustainable options such as integrating renewable energy sources into the existing power grid. This study is a review that is mainly hinged on distributed generation (DG) classification, the challenges of DG to grid integration, practical options used in DG integration, lessons learned from some countries with successful DG to grid integration, push factors in the growth of DGs and the merits of DG to grid integration. These standpoints of DG to grid interconnection are critical in conducting grid planning and operational studies, which should be conducted in strict observance of aspects such as optimal technology selection, optimal capacity and a suitable connection point of DGs in the network. Therefore, the perspectives highlighted regarding DG can assist power system engineers, developers of DG plants and policymakers in developing a power network that is stable, efficient and reliable.

The Fifth Generation (5G) Network will bring different use-case services like eMBB, mMTC, and uRLLC. As more devices connect to the 5G network, each user device request for data capacity will continue to grow. The increase in the number of devices and capacity request for each device will require an increase in network capacity, which will also need an increase in the number of Base Stations in the network. More Base Stations will increase the Mobile Network Operator’s capital investment and operation costs. However, this increase in CAPEX and OPEX will not increase the Average Revenue Per User (ARPU) as users tend to be less willing to pay more as their capacity request increases. Mobile Vendors and Mobile Network Operators will face the challenge of providing higher capacity for the same or less ARPU for their customers to maintain their customer base and business profitability. C-RAN was identified as a new and promising paradigm to help Mobile Network Operators reduce their CAPEX and OPEX while delivering higher capacity to their customers and maintaining business profitability. How C-RAN resources are allocated and managed within the 5G network will determine how efficient and profitable this optimization process will be. This article provides a high-level review of the main enabling 5G Technologies and an exhaustive study of C-RAN resource allocation algorithms for 5G networks emphasizing resource allocation metrics/parameters. The main resource allocation metrics considered in this work include BBU computational/processing resource, capacity, Power/ energy consumption, wavelength, UE-RRH mapping, and RRH-BBU mapping. Energy Harvesting in 5G C-RAN, including its architecture, categorized taxonomy, and requirements, are also discussed. Lastly, future research directions and open research issues for efficient C-RAN resource allocation are highlighted. [ABSTRACT FROM AUTHOR]