P. A. Adeoye, Joseph Babatola Ayodele, Fomonyuy Shinyuy, Clement Dossou-Yovo · 6 authors
Nigeria faces one of Sub-Saharan Africa’s most severe energy poverty crises, with over 85 million people lacking electricity access, a challenge that disproportionately affects more than 2.5 million Internally Displaced Persons (IDPs) in conflict-affected North-East Nigeria. Despite national electrification efforts, humanitarian settlements remain largely excluded from reliable power infrastructure. This study evaluates the technical feasibility, spatial energy gaps, and policy barriers associated with deploying decentralized solar and hybrid solar–wind systems in IDP settlements across six North-Eastern states. A mixed-method geospatial framework was applied, integrating Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data, Geo-Referenced Infrastructure and Demographic Data for Development (GRID<sup>3</sup>) infrastructure datasets, and Distributed Renewable Energy (DRE) demand data using Python and Quantum Geographic Information System (QGIS). Nighttime light intensity was classified into no-access (≤100 nW/cm²/sr), limited-access (101–1000 nW/cm²/sr), and full-access (>1000 nW/cm²/sr) categories. Results identified 670 IDP camps across 112 Local Government Areas (LGAs), with high concentrations in Bauchi (264 camps), Borno (194), and Gombe (140), predominantly located within limited-access zones. Solar resource assessment shows strong regional potential (4.2–4.6 kWh/m²/day Global Horizontal Irradiation (GHI)), while average wind speeds of 2–4 m/s support small-scale hybrid applications. A representative camp load analysis (3.72 kWh/day) demonstrates that a 0.99 kWp solar array combined with a 3.2 kWh battery and a 300 W vertical-axis wind turbine can reliably meet basic household energy needs, reducing approximately 25.88 kgCO<sub>2</sub>e per household annually. Key barriers include high upfront costs, limited financing mechanisms, weak humanitarian energy policy integration, and security-related operational risks. The study provides empirical evidence for integrating decentralized renewable energy into national electrification strategies through risk-informed planning and tailored financing models to enhance resilience, sustainability, and dignity in displacement settings.
Predicting future demand for distributed energy sources is difficult because of the energy generations is unpredictability. We proposed an auto executable blockchain-based peer-to-peer energy transaction market with Long ShortTerm Memory (LSTM) neural network for energy trading and predictions. Our proposed energy transaction market and trading strategy are built via smart contracts inside the blockchain. The energy trading process in the market is auto executable and does not need a long waiting time as in the conventional bidding strategy. LSTM is integrated into the market for predicting future energy usage. Experimental results show that the proposed blockchain-based peer-to-peer energy transaction market can earn more profit than the traditional method.
Mariela Tapia, Leonard Ramos, Detlev Heinemann, Edwin Zondervan
Abstract Solar energy plays a crucial role in helping cities to decentralize energy production and thus decarbonize the energy mix. Reliable resource assessments are needed to support the deployment of solar power systems, especially in cities of developing countries where large solar potential remains untapped. The aim of this work is to assess the potential of rooftop solar photovoltaic (PV) in three populated cities in Ecuador’s mainland (Quito, Guayaquil and Cuenca) and in the Galapagos Islands. The assessment involves (i) the estimation of the available rooftop area based on geographic information system data, (ii) the calculation of energy yield based on hourly satellite-derived irradiance and meteorological data, and (iii) the economic feasibility assessment in terms of levelized cost of electricity (LCOE) compared to representative electricity tariffs. In addition, a sensitivity analysis is carried out to assess the variability of the estimated technical and economic potential with respect to changes in the input parameters. The results reveal a total available rooftop area of about 144 km 2 , mainly concentrated in urban parishes. The estimated energy yield is 16.94 ± 3.38 TWh/a, which could cover almost twice the annual energy consumption in 2019 of the study areas. The economic assessment shows that the LCOE ranges between 7.65 and 21.12 USD cents/kWh. However, the comparison of LCOE against representative residential tariff suggests that rooftop PV technology is not cost-competitive under most of the financial scenarios. The findings from this study will be of interest for local authorities and other decision makers to design policies and financing strategies to increase the penetration of rooftop PV and thus exploiting the large potential assessed in the study areas. The described methodology can be used for assessing the potential in other regions of Ecuador and thereby support the diversification and decarbonization of the energy mix in the country.
S. Ramesh, J. Seetha, G. Ramkumar, Satyajeet Sahoo · 9 authors
The functioning of a solar hybrid power system is investigated in this research using a unique fuzzy control method. Turbines, solar photovoltaics, diesel engines, fuel cells, aqua-electrolyzes, and other autonomous generation products are used in the hybrid renewable energy system. Further energy storage components of the system include the batteries, turbine, and ultracapacitor. This research incorporates a supercapacitor hybrid energy storage system (HESS) into a solar hybrid power generating system, allowing the consumption and energy storage space and power output to be significantly increased. This study’s approach incorporates a decentralized power generation system with a HESS while increasing electrical output in phases utilizing a dynamic reactive power compensation scheme and a conductance-fuzzy dual-mode control strategy. Due to a nonlinear behavior of photovoltaic (PV) devices’ power output, maximum power point tracking (MPPT) methods must be used to create the greatest power. Infrequently developing atmospheric circumstances, traditional MPPT algorithms do not work adequately. Modeling is used to determine the microgrid’s power output to the photovoltaic hybrid power generating organization, as well as the optimization method for each device in the network. The dynamic power factor correction scheme and also the conductance-fuzzy dual-mode control approach are primarily used in this study to optimize the solar hybrid renewable energy system.
The main drivers of the third industrial revolution era were the internet technologies and rise of renewable and distributed energy technologies. Transition to green and decentralized energy resources and digital transformation of the existing industrial infrastructure had been the biggest achievements of the third industrial revolution. The main drivers of the fourth era will be artificial intelligence (AI), quantum computing, advanced biotechnology, internet of things, additive manufacturing, and most importantly, distributed ledger technology (DLT). Energy forecasting such as wind and solar power forecasting models are the most common energy AI-based informatics applications in the energy sector. In addition, use of DLT is expected to be an industrial standard in various industrial sectors including energy business in the coming decade. This chapter emphasizes description of energy forecasting using AI and energy DLT and future developments and solutions to overcome challenges that are associated with standardization of the energy DLT applications.
The decoupling of energy prices from fossil fuel is slowly making its way as investment is poured into renewable energy sources. Small Island Developing States are gaining in both stability and cost from this momentum but face threat from the same unsustainable centralization practices. A decentralized framework is proposed for Small Island Developing States aimed at achieving grid stability and in attracting independent financing mechanisms. This framework is applied from a Wind perspective and to ensure replicability on all types of terrains, and the model is analysed through three case studies: high-rise buildings, flat terrains and Gaussian terrains. This study provides a novel framework and a general solution for Wind farming over different terrain layouts including forbidden regions and complex topography.
L. V. Nefedova, Alexander Alexsvitch Solovyev, Olena Popova
The prospects of increasing access to electricity for the population of rural areas of Africa are considered. The main international funds and organizations aimed at sustainable energy development in Africa are described. An analysis of the state and possible options for using renewable energy sources for this purpose in decentralized energy supply through the creation of mini-grids or stand-alone systems is given. The risks by developing renewable energy sources in rural areas and modern mechanisms for financing in solar energy are presented.