Stand-alone Hybrid Energy System Research Articles

Optimal sizing of a proposed stand-alone hybrid energy system in a remote region of southwest Egypt applying different meta-heuristic algorithms

AbstractHybrid energy system (HES) is considered a solution to the energy supply issue, particularly in rural areas to achieve their sustainable development goals. The rise in energy consumption has increased the appeal of renewable resources, because of their potential to supply consumers with competitive, carbon-free electricity. This paper suggests strategies for managing energy and the most recently published optimizers for designing a stand-alone HES positioned in a remote region of southwest Egypt. This HES includes two green energy sources (wind and solar) and a storage system for energy (battery) as the first backup in addition to a second backup (diesel). The most recent sizing techniques employing the Chernobyl disaster optimizer, dynamic control cuckoo search (DCCS), and gold rush optimizer have been suggested to obtain the optimal design of the utilized HES. Furthermore, an in-depth evaluation of the applied optimization approaches has been achieved based on a comparative study. A detailed analysis of the studied algorithms aims to identify the optimum algorithm that provides the lowest possible cost at the highest level of reliability for the proposed HES. The simulation results verified that, the DCCS algorithm outperformed other algorithms, indicating its potential for achieving promising solutions.

Design and techno-economic assessment of a standalone photovoltaic-diesel-battery hybrid energy system for electrification of rural areas: A step towards sustainable development

The recent persistent power interruption in Nigeria has significantly disrupted commercial activities, resulting in a magnificent economic loss, supply chain ripples and revenue loss. As a result, harnessing renewable energy sources to generate electricity has become a popular choice for satisfying ever-increasing load demand and reducing apprehensions on global warming and reliance on depleted fossil fuels. The goal of this research is to determine whether powering a remote community with a hybrid energy system (HES) is technologically, financially and environmentally viable. The optimum design of a standalone HES with the diesel generator (DG), photovoltaic (PV) and battery storage system (BSS) is provided in this study to satisfy the electrical power needs of a farm settlement in Kura, Nigeria by considering generation constraints and load demand. This research work presents a genetic algorithm (GA) to minimize wearing cost of the system (WCS), minimize the land needed for the installation of the DG and PV system, minimize the total annual cost of the system (TAC) and maximize the benefit to cost ratio and revenue from electricity consumption. The findings of the research showed that PV/BSS/DG system is a prospective solution to satisfy the load requirements with least TAC of 67374 $/yr, annual maintenance cost (AMC) of 2808.2 $/yr, annual fuel cost (AFC) of 32300 $/yr and annual emission cost (AEC) of 774.2023 $/yr. The outcomes of the study show that a considerable TAC, AMC, AFC and AEC savings of 26766 $/yr (28.43 %), 2808.2 $/yr (53.09 %), 32300 $/yr (25.4 %) and 774.2023 $/yr (60.69 %) are recorded when compared with using DG alone. The control approach applied in this study has reduced the operational capacity of the DG and prevented about 41157 kg/yr, 419.19 kg/yr and 22.52 kg/yr of CO2, NOx and SO2 emissions from being injected into the atmosphere. The simulation outcomes of the research demonstrate that the developed model can significantly reduce cost of electricity in rural communities with the application of HES. Hence, a 45.36 % cost of energy saving has been accomplished through the energy management system introduced in the proposed HES. The study's outcomes can be used as benchmarks to help many countries to enhance access to electricity, raise their living standards and stimulate economic growth. The application of the proposed HES in remote communities can result in greater economic and environmental benefits to a general population of rural dwellers. The findings of the research work are beneficial to designers, independent power providers, investors, researchers and electricity consumers that are looking for a feasible power solution.

Using genetic algorithm for optimal sizing of stand-alone hybrid energy system

When planning a hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources—those that rely on fossil fuels—the primary considerations are the total cost of the system and the CO? emissions. In this paper, we will investigate the typical hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources involving a detailed simulation process that may require specific inputs, models, and data. Then, we employed dual optimization methods: genetic algorithm (GA) and particle swarm optimization (PSO). The consequences of GA and PSO execution in the bus timetabling problem depict that the GA algorithm is better at finding the optimal solution in terms of accuracy and iteration. Additionally, the GA algorithm is also superior to the straightforwardness of the techniques used. So, in this work, we employed a Genetic Algorithm Optimization (GA)–-based optimal sizing technique for HES configurations that include sustainability wind turbines (WTs), battery storage (BS), and diesel generators (DGs). HES improved power delivery to a rural community in the Wasit Province, Iraq, situated at 46° - 36° and 32° - 31° in the country's southeastern central region. Throughout the project's 25-year lifespan, the optimization primarily aims to minimize the total cost (CT) and total CO? emissions (ECO2T). The outcomes demonstrate that the GA algorithm may, with continuous electricity supply, minimize the objectives while meeting the load demand.

Optimal design and economic analysis of a stand-alone integrated solar hydrogen water desalination system case study agriculture farm in Kairouan Tunisia

In the contemporary global discourse on environmental and developmental issues, the dual challenges of sustainable green energy and water supply stand paramount. These elements are vitally intertwined with the socio-economic vitality of the world. Notably, regions plagued by freshwater scarcity are increasingly turning to desalination which consists of a reliable and unconventional water source. The intersection of renewable energy with desalination and water purification processes presents a compelling synergy. This approach is particularly pertinent in areas where freshwater shortages coexist with abundant solar energy availability. Additionally, these technologies boast the advantage of low operational and maintenance costs. This paper delves into the design, optimization and financial analysis of a novel, standalone hybrid energy system, integrating photovoltaic and fuel cell technologies, for an agriculture farm situated in Kairouan, Tunisia. Unlike conventional systems, this model foregoes battery storage in favour of hydrogen storage, generated through water electrolysis powered by solar energy. This system harnesses solar energy for direct electrical power generation and hydrogen gas production. A segment of the generated electricity is allocated to electrolysis for green hydrogen production. In times of solar unavailability, the stored hydrogen is reconverted to electricity via a fuel cell. An intriguing aspect of this system is the utilization of saline well water, which, due to its high salt content, necessitates purification through desalination to prevent damage to the electrolysis unit and to render it suitable for agricultural irrigation.

Multi-objective size optimization and economic analysis of a hydrogen-based standalone hybrid energy system for a health care center

The main contribution of this study is the multi-objective size optimization of a standalone hybrid energy system (HES) to supply the electricity demand of a health care center in Kerman province, south of Iran, in which fuel cell, photovoltaic, and diesel generator produces electricity, while the combination of electrolyzer and hydrogen tank is the storage system. The non-dominated sorting genetic algorithm II (NSGA-II) is applied to find the Pareto front of optimal solutions, where the loss of power supply probability (LPSP) and total net present cost (TNPC) are the objective functions. The results show that considering operating reserve and uncertainty, the TNPC increases 30.50% compared to the base load. Moreover, the fuel cell has a smaller share of energy production, which is due to the high cost of the storage system, while about 50% of the demand load is provided by DG in the cold seasons. The sensitivity analysis reveals that TNPC decreases by 8.93% for a 50% reduction of the storage system cost, while increases by 24.55% for a 50% increase in the fuel cost. Moreover, AHP/TOPSIS-based multi-criteria decision-making is implemented to find the best solution according to the opinions of three different managers/experts, which shows that the HES with LPSP = 0.2503% and TNPC = 2.1038 × 106 $ is the best solution in which uncertainties and operating reserve are also considered.

Effects of dispatch algorithms and fuel variation on techno-economic performance of hybrid energy system in remote island

A stand-alone hybrid energy system is needed to mitigate the growing demand for future energy and to reduce emissions generated by conventional fuel sources. This work shows and proposes an optimum hybrid energy system configuration with less environmental pollution for a coastal region of Bangladesh with a load demand of 292.20 kWh/d and a peak load of 41.14 kW. This research presents the cost of energy (COE) and net present cost (NPC) for a PV-wind hybrid system with five alternative fuel generator technologies. For each possible configuration, the effects of three alternative dispatch algorithms, load following (LF), cycle charging (CC), and combined dispatch (CD), are examined. All three algorithms were validated using a genetic algorithm (GA), Cuckoo search algorithm (CUSA), Constrained Particle Swarm Optimization (CPSO), Harmony search algorithm (HSA), and Non-dominated Sorting Genetic Algorithm (NSGA-II). Furthermore, a sensitivity analysis is also conducted by utilizing the gasoline price, discount rate, battery cost, PV cost, and inflation rate. The results show that the PV-wind-natural gas-based system provides the minimum COE (0.196 USD/kWh) and NPC (270,483 USD) when the CD algorithm is followed. For the same optimal hybrid energy system, the COE is 0.201 USD/kWh, 0.0998 USD/kWh, 0.101 USD/kWh, 0.101 USD/kWh, and 0.0987 USD/kWh respectively for GA, CUSA, CPSO, HSA, and NSGA-II. However, COE increases by 8 % (0.212 USD/kWh) and 15 % (0.225 USD/kWh) when the CC and LF algorithms are followed. In addition, a comparison of all configurations reveals that the PV-wind-biomass configuration with the CD algorithm excludes biomass generators to lower the COE, making the system emission-free.

Techno-economic optimization of standalone photovoltaic-wind turbine-battery energy storage system hybrid energy system considering the degradation of the components

The increasing demand for renewable energy sources has led to the development of HRES that combine multiple sources of renewable energy to provide a reliable and efficient energy supply. However, renewable energy sources typically come with higher costs than conventional energy production methods. Hence, the optimal sizing of HRES is essential to prevent the oversizing of the system while ensuring a reliable supply of load demand, accommodating variations in meteorological conditions and changes in power demand. Numerous research papers addressing the optimal sizing problem are available in the literature. However, none of the mentioned studies take into account the power degradation of all renewable sources. The degradation of renewable sources, such as PV and WT, can have a significant impact on the performance of HRES. The degradation of PV panels can result in reduced efficiency and output, leading to a decrease in the overall energy production of the HRES. Similarly, WT may experience wear and tear over time, leading to reduced performance and output. The reduction in the output of renewables in the standalone system causes an increase in the loss of power supply probability (LPSP). This paper analyzes the optimal sizing of the HRES, considering the degradation of the sources. Further, analysis has also been carried out based on the number of BESS to be added to HRES to meet the derived constraints and their impact on the cost of energy as well.

Techno-economic feasibility of stand-alone hybrid energy system with battery storage in educational buildings: A case study of Uttara University

Stand-alone hybrid energy systems (HES) have the potential to significantly reduce pollutant emissions and alleviate strain on the national grid. The selection and sizing of stand-alone HES for buildings can serve as a methodological approach toward establishing a resilient and clean electrical energy system in urban areas of developing countries. To explore this further, a case study was conducted using Hybrid Optimization of Multiple Energy Resources (HOMER) to assess the feasibility of implementing a HES at Uttara University in Dhaka, Bangladesh. This study examined the technical, economic, environmental, social, and reliability aspects of a stand-alone HES. The findings of this study suggested that the PV-WT-DG-BT is the most cost-effective solution for the University when compared to other hybrid configurations. Additionally, this HES benefits the surrounding communities by creating employment opportunities and contributing to human development. The sensitivity analysis showed that the COE and NPC of the optimal HES are sensitive to fuel price changes. A PV slope angle of 23.88° was cost-effective, and a 20-meter wind turbine hub height was optimal. It was observed that increased solar radiation decreases COE. Further, sensitivity analysis showed that fuel costs, CO2 emissions, and NPC will decrease if average daily load demand declines. It was also found that 1 kWh of Li-Ion-based HES performed the best compared to other batteries. Finally, the results of the genetic algorithm (GA), and grey wolf optimizer (GWO) showed that they provide the same optimum configuration as HOMER but with the lowest NPC. The findings of this study can serve as a foundational model for designing HESs in other large educational buildings located in low and middle-income countries with environmental conditions and socio-economic characteristics similar to Bangladesh.

Techno-economic analysis of a standalone hybrid energy system in Cambodia

This study aims to present an economically feasible and environmental-friendly hybrid energy system that does not connect to the grid. In Cambodia, many rural areas are facing insufficient power supply problems and need more electricity supply. So, the designed system in this research can supply electric power to a community with 30 households in Krong Kracheh, Kratie Province, Cambodia. Three different designs of hybrid systems are considered. The first design is a hybrid system with PV modules, a diesel generator, and a battery. The second design is a hybrid system including a wind turbine, PV modules, diesel generator, and battery, and finally, a hybrid system that contains a wind turbine, diesel generator, and battery as the third design. According to the simulation results, the first configuration is the best design compared to the other two scenarios as it is the most cost-effective. The Present Net Cost, Cost of Energy, and system operating cost is 46,866 $, 0.268 $/kWh, and 2,327 $/yr, respectively. Besides, it has a total of 4,496.29 kg/yr pollutants emitted, which is less than the third configuration but more than the second configuration. The production of electricity for the first configuration is 23,820 kWh/yr, with a renewable fraction of 65.2%.

Techno-economic assessment and optimal design of hybrid power generation-based renewable energy systems

This study presents a techno-economic analysis of five different hybrid energy systems (HES)-based renewable energy sources (RES) in the northern region of Saudi Arabia. It aims to provide valuable insights into the economic feasibility, technical compatibility, and environmental implications of these systems. To carry out this analysis, hybrid optimization of multiple energy resources (HOMER) software is used. Parameters such as total net price cost (TNPC), cost of energy (COE), initial capital cost (ICC), energy generation and consumption, excess and unmet energy, renewable energy (RE) fraction, and emissions were considered to assess the different HES configurations. The findings demonstrate that the grid-connected photovoltaic/wind turbines (PV/WT) system is the best option in terms of economic perspective with TNPC and COE of $213,099 and $0.0480/kWh, respectively followed by grid-connected PV/fuel cell (FC)/WT and stand-alone PV/diesel generator (DG)/WT/battery systems. The PV/battery and PV/FC/WT/battery green hybridization are the highest cost-effective due to their high initial and replacement battery costs. The grid-connected PV/WT and PV/DG/WT/battery systems are the most efficient in meeting load demand, while the PV/battery and PV/FC/WT/battery hybridization have the highest excess and unmet energy. From an environmental perspective, the stand-alone HES consisting solely of RESs, i.e., PV and batteries, has the lowest emissions, making it one of the most environmentally friendly options. Following closely is the PV/FC/WT/battery configuration, which also demonstrates low emissions. On the other hand, the grid-connected PV/WT system exhibits the highest total GHG emissions, rendering it the least environmentally friendly option. This research provides decision-makers, researchers, and stakeholders with valuable information for selecting the optimal hybrid energy systems, taking into account economic, technical, and environmental considerations.

Techno-economic Feasibility Analysis of Optimized Stand-alone PV and Hybrid Energy Systems for Rural Electrification in INDIA

Techno-economic Feasibility Analysis of Optimized Stand-alone PV and Hybrid Energy Systems for Rural Electrification in INDIA

Investigation of a reliable and sustainable stand-alone hybrid energy system for freshwater supply: a case study

ABSTRACT Hybrid renewable energy system-based reverse osmosis desalination has been identified as a reliable and sustainable solution for supplying potable water to the off-grid communities. In this respect, this study proposes a stand-alone hybrid energy system comprising solar PV, wind turbine, diesel generator, and a battery bank to power a reverse osmosis desalination plant. The proposed hybrid system is optimised using a novel metaheuristic optimisation technique named salp swarm algorithm (SSA) to minimise the three objective functions: levelised cost of energy (LCOE, $/kWh), life cycle emissions (LCE, CO2 kg-eq/yr.), and the excess energy (EE, kWh/yr.). Moreover, the performance of the novel algorithm is scrutinised using the benchmark solutions achieved from the widely utilised non-dominated sorting genetic algorithm II (NSGA-II) and particle swarm optimisation (PSO) techniques. In addition, the study also investigates the effects of water demand and the loss of power supply probability on the techno-economic performance. The results reveal that SSA outperforms NSGA-II and PSO algorithms towards achieving Pareto optimality hence provides financially rewarding solutions. The LCOE for the optimal HES is 0.179 $/kWh, and the LCE is 5921 CO2 kg-eq/yr. with an EE of 402 kWh/yr., whereas the cost of water for this system is 1.37 $/m3.

Combining green energy technologies to electrify rural community of Wollega, Western Ethiopia

Power shortages are a major problem in rural Ethiopia. Only about 45% of people living in around cities have access to the public power grid. The rest of the inhabitants lives in rural regions with limited access to grid-connected energy. To evaluate the potential of a standalone solar-wind hybrid energy system (HES) for a rural off-grid settlement in western Ethiopia, a feasibility study was performed. The electrical demand of a model household, comprising a school and health facility, was calculated. HOMER Pro is a tool for determining the viability of HES. When the software is executed, optimization results are obtained and sorted according to the lowest net present cost (NPC) and cost of Electricity (COE). The results reveal that the Photovoltaic (PV)/battery/converter combination is the most cost-effective, with the lowest NPC and COE. This setup's NPC is $9150, the COE is $0.173/kWh, and the renewable resource contribution is 100%. The study's findings can be used by interested parties, decision makers and investors to show the benefits of increasing renewable energy, modifying components, and reducing electricity bills.

Performance analysis of a stand-alone integrated solar hydrogen energy system for zero energy buildings

This study analyzes the optimal sizing design of a stand-alone solar hydrogen hybrid energy system for a house in Afyon, Turkey. The house is not connected to the grid, and the proposed hybrid system meets all its energy demands; therefore, it is considered a zero-energy building. The designed system guarantees uninterrupted and reliable power throughout the year. Since the reliability of the power supply is crucial for the house, optimal sizing of the components, photovoltaic (PV) panels, electrolyzer, storage tank, and fuel cell stack is critical. Determining the sufficient number of PV panels, suitable electrolyzer model and size, number of fuel cell stacks, and the minimum storage tank volume to use in the proposed system can guarantee an uninterrupted energy supply to the house. In this study, a stand-alone hybrid energy system is proposed. The system consists of PV panels, a proton exchange membrane (PEM) electrolyzer, a storage tank, and a PEM fuel cell stack. It can meet the continuous energy demand of the house is sized by using 10 min of averaged solar irradiation and temperature data of the site and consumption data of the house. Present results show that the size of each component in a solar hydrogen hybrid energy system in terms of power depends on the size of each other components to meet the efficiency requirement of the whole system. Choosing the nominal electrolyzer power is critical in such energy systems.

A novel assembly process guidance using augmented reality for a standalone hybrid energy system

A novel assembly process guidance using augmented reality for a standalone hybrid energy system

Performance analysis of autonomous green energy system based on multi and hybrid metaheuristic optimization approaches

The need for energy is constantly increasing worldwide. It is expected that renewable energy resources and fuel cells, solid wastes, and hydrogen energy technologies will play a significant role in energy generation and storage with their decreasing installation costs and increasing environmental concerns. Hydrogen is a potential fuel used in fuel cells that provides a carbon-free solution. The research is based on the techno-economics of off-grid wind (WT), solar (PV), biomass gasifier (BG), and fuel cell (FC) systems, which include storing excess wind and solar energy by converting it to hydrogen to provide fuel cell energy. It is critical from the standpoint of feasibility. In addition to electricity generation, energy storage integration, sizing methodologies, energy flow management, and the optimization algorithms that go with them are all covered. The annual cost system (ACS) is the primary goal function of the optimization process in this case. A robust rule-based energy management scheme is proposed to coordinate the power flow between various system components of a microgrid that will minimize the ACS and meet the energy demand reliably. The decision variables considered for this optimization process are PV panel power, WT power, and number of H2 tanks. The consumption and meteorological data of the year 2021 are used as the input of the system. The optimal size of each component is obtained by using the proposed Hybrid Firefly Genetic Algorithm (HFGA). To prove the superiority of the proposed optimization method in terms of accuracy and calculation time, it is compared to approaches that are used in similar applications such as Genetic Algorithms, the Firefly Algorithm, Sine-Cosine Algorithm and Cuckoo Search Algorithm. The optimum system configuration yielded 1094.68 KW WT, 2256.17 kW PV, and 775 H2 storage tanks when HFGA was used. The ACS of the system is $2921702.3, the total net present cost is $2.4639x107, while the leveled unit energy cost is $1.3416/kWh 'dir. The renewable energy fraction of the system is 100 % and consists of 51.8 % PV, 2.1 % WT, 11.8 % FC 34.3 % BG components. The results show that the proposed standalone hybrid (PV/WT/BG/FC) energy system is the most cost-effective option for the central campus of the university selected as the study area, and the proposed algorithm has excellent convergence capacity and provides high-quality outputs. The optimization algorithms are programmed using the MATLAB simulation package in this study.

Optimal renewable integrated rural energy planning for sustainable energy development

The renewable energy sources substitute traditional generation systems that can supply more reliable, environmentally friendly, and high-quality power. The off-grid electrification utilizing the integration of renewable energy systems is widely used to satisfy the energy need of remote rural areas. Due to intermittency in renewable production, energy storage balances the power demand against variable generation. The present study investigates the economic viability of a standalone hybrid energy system for a remote village in Uttarakhand (India). The suggested system consists of a Photovoltaic system, diesel generators, biogas generators, wind turbines, and batteries to meet the load demand of the area. The proposed microgrid utilized differential evolution (DE) to optimize the hybrid microgrid's sizing and economic analysis. The effectiveness of the proposed DE optimization results is compared with HOMER (Hybrid optimization of multi-energy resources), PSO (particle swarm optimization), and GA (Genetic algorithm). In addition, a sensitivity analysis is performed on the cost of energy for varying sensory inputs. The results indicate that DE can optimally size the system compared to its counterpart, HOMER, PSO, and GA. The decrement of 3.34%, 5.5%, and 7 % are achieved respectively in the total net present cost of the optimal configuration. However, it has been established that the suggested system is a more cost-effective and feasible system for rural area electrification.

Design and optimization of stand-alone hybrid energy system for rural areas

The main aim of this work to design and select the optimal photovoltaic based energy system that can meet the rural area irrigation and domestic load demand. The selection of optimal energy system configuration is based on modeling, economic and reliability analysis. Soft optimization computing tool (MATLAB & HOMER Pro) and Markov reliability method are used to identify optimal energy system configuration. The results show that COE of PV/battery is ₹6.87, PV/diesel/battery is ₹14.29, PV/DG is ₹30.25, DG/battery is ₹34.71 and DG is ₹36.12. Energy capacity shortage is higher in PV/battery (8%) and approx. zero in PV/DG/battery system. Reduction of fuel cost from diesel only system to hybrid PV/DG/battery energy system is 42.46%. PV/DG/battery failure rate (0.01101), EENS (0.080) and LOLP (0.00000725) are minimum as compared to another configuration. The obtained results concludes that hybrid PV/DG/battery energy system is cost-effective, sustainable and reliable system for rural areas in India.

Multiple design options for sizing off-grid microgrids: A novel single-objective approach to support multi-criteria decision making

When designing a microgrid, developers usually regard economic metrics, and occasionally consider reliability and environmental aspects. However, sociopolitical, supply chain, and geographical facets, among others, are often never included in project-design because they are really difficult to model, especially, in the context of developing countries. Traditional planning methodologies offer an optimal solution, disregarding solutions with similar profitability but different size of components, even when these second-best solutions can better fit the non-considered intangible developer needs. In this paper, we define the concept of Multiple Design Options (MDO) for a single-objective optimization. We propose a novel methodology (MDO-PSO) for sizing stand-alone hybrid energy systems that, by using Particle Swarm Optimization, identifies the optimal solution and post-processes the search history to select second-best options of interest. While searching for the traditional optimum, the proposed iterative algorithm stores all tried configurations. Moreover, a Pareto-like frontier, denoted as MDO-Pareto, is proposed to highlight the tradeoff between Net Present Cost (NPC) and CAPEX. The proposed Pareto-like frontier is also compared to a standard multi-objective optimization to illustrate how MDO-PSO successfully captures multiple goals. The numerical case study for a PV-battery-diesel-tank system in Uganda confirms that MDOs differing up to 32% in capacity can achieve NPC values within 2%–5% optimality with both load following and predictive MILP rolling-horizon operating strategies, thus suggesting important implications for business decision making.

Optimal Decision-Making on Hybrid Off-Grid Energy Systems for Rural and Remote Areas Electrification in the Northern Cameroon

Hybrid renewable energy systems are effective solutions to the problem of lack of electricity in many localities around the world. In this paper, a comparative study of ten different options of standalone hybrid energy systems is done. These systems are used for household energy supply in rural and remote areas. The three regions of the northern Cameroon have been chosen as study sites. HOMER optimization Pro software has been performed for the optimal sizing of the proposed systems. The system reliability, the cost of energy, the renewable energy penetration, and the carbon dioxide emissions are the main comparative indexes considered. For an energy demand of 46418.100 kWh/year and a lifetime project of 25 years, the best optimal system configuration for the sites considered based on economic analysis is the PV/DG/battery system with a cost of energy of 0.378 $/kWh in Garoua, 0.359 $/kWh in Maroua, and 0.394 $/kWh in Ngaoundéré. When considering the environmental criteria, the PV/Battery and the PV/wind/Battery are the best options with 0 kgCO2 emissions per year and 100% renewable energy penetration. The renewable energy penetration of the PV/DG/Battery system is 95.6% in Garoua, 96.3% in Maroua, and 95.1% in Ngaoundéré. Thus, when taking into account both economic and environmental aspects, the PV/DG/Battery could appear as the best optimal system for rural and remote areas electrification in the northern part of Cameroon. The sensitivity analysis revealed that the studied systems are more attractive when increasing the project lifetime (up to 50 years, the COE is 0.375 $/kWh, 0.356 $/kWh, and 0.391 $/kWh, respectively, in Garoua, Maroua, and Ngaoundéré). However, the studied systems are more attractive when reducing the fuel price and the discount rate. When reducing the fuel price to up to 0.01 $/l, the COE is 0.359 $/kWh in Garoua, 0.342 $/kWh in Maroua, and 0.371 $/kWh in Ngaoundéré. When reducing the discount rate to up to 1%, the values of the COE are 0.253 $/kWh, 0.240 $/kWh, and 0.264 $/kWh, respectively, in Garoua, Maroua, and Ngaoundéré.