Explore the vast range of titles available.

Renewable energy sources offer a promising future, backed by mature technologies and a viable pathway toward sustainable energy systems. However, careful planning is necessary to efficiently utilize these resources, especially during site selection. Many rural areas lack access to grid electricity, making off-grid hybrid wind-solar power an attractive solution. In the Tigray region of Ethiopia, no such research has been conducted before. This study aims to identify suitable sites for hybrid wind-solar power for rural electrification using Geographic Information System (GIS), Analytic Hierarchy Process, and Monte Carlo simulation. The criteria fall into three categories: Climate, Topography, and Infrastructure, prioritized through pairwise comparisons by thirteen experts from five organizations engaged in renewable energy research, planning, and operations. Monte Carlo simulation was used for sensitivity analysis to address uncertainties in expert judgments and validate the rankings. The spatial analysis reveals 6470 km2 as highly suitable for off-grid solar, 76 km2 for off-grid wind with predominant easterly winds, and 177 km2 as most favorable for hybrid generation. Areas of good suitability measure 447 km2 for wind, 44,128 km2 for solar, and 16,695 km2 for hybrid systems. Based on this assessment, techno-economic analysis quantified the Levelized Cost of Energy (LCOE) under varying solar–wind shares and battery autonomy days. The analysis shows a minimum LCOE of$0.23/kWh with one-day storage and $ 0.58/kWh with three-day storage, indicating shorter autonomy is more cost-effective while longer autonomy enhances reliability. Sensitivity analysis shows financial parameters, particularly discount rate and battery capital cost, dominate system economics.

The current electrification status in West African countries presents rural electrification rates below 40%, national grid losses above 39% with frequent disruptions, and electricity prices averaging$0.35/kWh, up to national values of $ 0.66/kWh. With this, off-grid systems have gained great attention during the last decade as energy solutions; especially solar home systems (SHS) and mini grids. Nowadays, 385 mini grids with a power of near 30 MW are operating in West Africa, with 95% based on PV. Since 2019, result-based tenders with international aid funding—more effective than previous competitive tenders—seek to install at least 317 new mini grids in Togo, 250 in Nigeria, 100 in Burkina Faso, and two in Mali. Besides, the market for mini-grid energy access start-ups grew from$19 million in 2013 to $ 339 million in 2018. Despite this recent development in West Africa, research and data for mini grids in this region is scarce, and it is mostly approached from the technological side, with a striking lack of information regarding the social impact. This work tries to describe the present status of research and current operating installations, as well as the main challenges for future development of off grid mini grids in West Africa, which pose as the missing link between SHS and grid extension.

This study proposes a comprehensive framework for developing a multi-energy off-grid microgrid with the decoupled flow of thermal and electrical energies in a rural setting. A carbon-neutral microgrid with a hybrid generation system constituting a photovoltaic unit and a biofuel generator is proposed. In order to enhance the fuel utilisation efficiency, the biofuel generator is operated in combined cooling, heating, and power mode, and the recovered thermal energy forms the heat distribution network in the microgrid. The flexibility of system operation is improved by suitable multi-energy (electrical and thermal) storage. Firstly, an optimal sizing framework has been developed for the system as a mixed integer linear programming model. Secondly, a coordinated multi-energy management system (MEMS) has been developed for combined optimal dispatch of multiple generation and storage resources. The MEMS has been developed as a mixed integer non-linear programming model, which minimises system operational cost while considering minimum battery degradation to prolong its lifetime. Finally, a detailed economic analysis of the proposed system has been presented, highlighting the levellised cost of energy and net present value. Extensive case studies and simulation results depict the effectiveness and suitability of the proposed MEMS for the rural off-grid microgrid.

Under the Sustainable Development Goals (SDGs), the world has pledged to “leaving no one behind”. Responding to goal No. 7 on the agenda, efforts to provide modern energy to all the world population must be pushed forward. This is important because electrification in the rural area can indirectly support opportunities for social and economic development resulting in an acceleration of the eradication of poverty. The research goal of this study is to contribute insights about the scale of energy demand in unelectrified villages in the Southeast Asian countries and to discuss some factors that might influence the energy demand growth. This is done by making projections based on surveys and interviews, including a time-use survey, in three off-grid villages located in Myanmar, Indonesia, and Laos. Our analysis presented the living condition, highlight the types of energy sources, how, and in what rhythms people use energy on a daily basis in those villages. The demands in each case study villages were then projected based on several constructed scenarios. It was found that the factors of household size, proximity to the city, climate, and topography may influence the present and future growth of energy demands in the villages. The estimated energy demand may be useful for project managers to design a pilot off-grid energy system project in a similar environment and pointed out important factors to consider when formulating off-grid energy policies in the region.

Rural electrification is a crucial component of meeting sustainable development goals. In Pakistan, load shedding and power outages are frequent. According to the current data, Pakistan is experiencing a shortfall of power between 6000 and 6500 MW. Microgrid technology has the potential to provide a solution to this problem in an efficient and low‐cost manner. This paper proposes the development of a hybrid microgrid system (HMGS) for rural communities. For that purpose, a technological analysis of the HMGS system for rural electrification is performed. Solar photovoltaic (PV) and wind resource‐based renewable energy systems are considered in this work for the electrification of rural areas of Pakistan. A hybrid PV/wind system is designed using MATLAB software. Simulation results show that a 230‐V sinusoidal output voltage has been produced by the proposed model. The advantage of this model is that it minimizes the impact of transients and provides a sinusoidal output waveform.

Moving toward sustainable energy in small-scale dairies is an indispensable requirement and a significant challenge in developing countries. This study investigates a solar-powered refrigeration system with heat recovery designed to address the energy challenges faced by small-scale dairy farmers in off-grid areas of developing nations. It presents a novel solar-powered refrigeration system with integrated heat recovery, experimentally optimized to simultaneously deliver heating and cooling while valorizing waste heat and synergistically integrating solar energy to establish a decentralized and energy-autonomous milk preservation system for off-grid applications. The proposed system successfully recovers an average of 55% of the heat rejected by the condenser, thereby delivering more than 1000 W of usable thermal energy necessary for milk pasteurization. The experimental findings showed a coefficient of performance of 4.7, representing a 43% improvement over conventional systems, and achieved a Carnot efficiency of 42%. In addition, the system yields an annual energy savings of 3650 kWh and reduces carbon emissions by 971 kg per year for a 50 L unit. These findings underscore the system’s substantial potential to enhance energy efficiency, promote sustainability, reduce spoilage, improve incomes, mitigate carbon emissions, and enhance local milk preservation capabilities within small-scale dairy operations, minimizing reliance on diesel or firewood, particularly in regions that are distant from access to grid energy.

A coprime array is capable of achieving more degrees-of-freedom for direction-of-arrival (DOA) estimation than a uniform linear array when utilizing the same number of sensors. However, existing algorithms exploiting coprime array usually adopt predefined spatial sampling grids for optimization problem design or include spectrum peak search process for DOA estimation, resulting in the contradiction between estimation performance and computational complexity. To address this problem, we introduce the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) to the coprime coarray domain, and propose a novel coarray ESPRIT-based DOA estimation algorithm to efficiently retrieve the off-grid DOAs. Specifically, the coprime coarray statistics are derived according to the received signals from a coprime array to ensure the degrees-of-freedom (DOF) superiority, where a pair of shift invariant uniform linear subarrays is extracted. The rotational invariance of the signal subspaces corresponding to the underlying subarrays is then investigated based on the coprime coarray covariance matrix, and the incorporation of ESPRIT in the coarray domain makes it feasible to formulate the closed-form solution for DOA estimation. Theoretical analyses and simulation results verify the efficiency and the effectiveness of the proposed DOA estimation algorithm.

Photovoltaic (PV) is a highly promising energy source because of its environment friendly property. However, there is an uncertainty present in the modeling of PV modules owing to varying irradiance and temperature. To solve such uncertainty, the fuzzy logic control-based intelligent maximum power point tracking (MPPT) method is observed to be more suitable as compared with conventional algorithms in PV systems. In this paper, an isolated PV system using a push pull converter with the fuzzy logic-based MPPT algorithm is presented. The proposed methodology optimizes the output power of PV modules and achieves isolation with high DC gain. The DC gain is inverted into a single phase AC through a closed loop fuzzy logic inverter with a low pass filter to reduce the total harmonic distortion (THD). Dynamic simulations are developed in Matlab/Simulink by MathWorks under linear loads. The results show that the fuzzy logic algorithms of the proposed system efficiently track the MPPT and present reduced THD.

Several families in India live in remote places with no access to grid-connected power supply due to their remoteness. The study area chosen from the Indian state of Odisha does not have an electrical power supply due to its distant location. As a result, this study analyzed the electrification process using Renewable Energy (RE) resources available in the locality. However, these RE resources are limited by their dependency on weather conditions and time. So, a robust battery storage system is needed for a continuous power supply. Hence, the Nickel Iron (Ni-Fe), Lithium-Ion (Li-Ion) and Lead Acid (LA) battery technologies have been analyzed to identify a battery technology that is both technologically and economically viable. Using the available RE resources in the study area, such as photovoltaic and biomass energy resources, as well as the various battery technologies, three configurations have been modelled, such as Photovoltaic Panels (PVP)/Biomass Generator(BIOMG)/BATTERY(Ni-Fe), PV/BIOMG/BATTERY(Li-Ion) and PVP/BMG/BATTERY(LA). These three configurations have been examined using nine prominent metaheuristic algorithms, in which the PVP/BIOMG/BATTERY(Ni-Fe) configuration provided the optimal Life Cycle Cost value of 367,586 USD. Among the all metaheuristic algorithms, the dynamic differential annealed optimization algorithm was given the best Life Cycle Cost values for all of the three configurations.

A fundamental aspect of fish farms is their energy consumption, which is essential for various activities like water supply, pool aeration, thermal conditioning, lighting, filtration, and recirculation systems. Due to volatile prices and rising energy use, costs have surged, requiring energy-optimization solutions for economic viability and pollution reduction. In this context, this study aims to evaluate renewable energy integration in these installations based on real data, assessing current operations, proposing renewable energy optimization, and exploring hydrogen systems for energy needs, using HOMER PRO® to analyze different scenarios. For this purpose, it targets a rainbow trout farm in Estonia, and by simulating the various hybrid configurations proposed, it aims to optimize its energy production and storage, ensuring feasibility and technical integration. The results of the simulations primarily demonstrate the potential for using the byproduct of electrolysis to cover the oxygen demand in these types of processes, reducing the demand for raw materials. Additionally, it is observed that storage enhances performance in isolated systems; however, the economically viable integration of hydrogen technology requires three assumptions: a regulatory framework allowing surplus energy sales to the grid, an existing infrastructure for hydrogen trading, and high energy purchase prices.