The northern part of the globe is dominated by industrialisation and is well-developed. For many years, the southern part of the world (South Asia, Africa etc.) has been a target of research concentrating on access to energy (mainly electricity) in rural regions. However, the Central Asian region has not been a focus of energy research compared to South East Asia and Africa. Despite plentiful domestically available energy resources, the energy supply in Central Asia is very unevenly distributed between urban and rural areas. Almost half of the total population of Central Asia lives in rural areas and there is a lack of access to modern energy services to meet primary needs. To analyse the energy situation (i.e., electricity, heating, hot water consumption, cooking, etc.) in rural Central Asia, this paper reviews residential energy consumption trends in rural Central Asian regions as compared to urban areas. Furthermore, the paper illustrates the potential of renewable energies in Central Asia. To perform the study, a qualitative comparative analysis was conducted based on a literature review, data, and statistical information. In summary, the presented article discusses the rural energy situation analytically and provides in-depth insights of Central Asian energy infrastructure.

This paper proposes a home energy management system able to achieve optimized load scheduling for the operation of appliances within a given household. The system, based on the genetic algorithm, provides recommendations for the user to improve the way the energy needs of the home are handled. These recommendations not only take into account the dynamic pricing of electricity, but also the optimization for solar energy usage as well as user comfort. Historical data regarding the times at which the appliances have been used is leveraged through a statistical method to integrate the user’s preference into the algorithm. Based on real life appliance consumption data collected from a household in Morocco, three scenarios are established to assess the performance of the proposed system with each scenario having different parameters. Running the scenarios on the developed MATLAB script shows a cost saving of up to 63.48% as compared to a base scenario for a specific day. These results demonstrate that significant cost saving can be achieved while maintaining user comfort. The addition of supplementary shiftable loads (i.e., an electric vehicle) to the household as well as the limitations of such home energy management systems are discussed. The main contribution of this paper is the real data and including the user comfort as a metric in in the home energy management scheme.

The escalating demand for water, energy, and food, coupled with the imperative for sustainable development, necessitates innovative solutions to address the complex interdependencies within the water–energy–food nexus. In this context, agriculture and photovoltaics (Agri-PV or Agri–voltaics) systems have emerged as a promising approach to promoting sustainable agricultural practices while enhancing energy efficiency and food production. However, limited research, especially on the technical aspects of Agri-PV, has resulted in a knowledge gap regarding how to model and determine the suitability of Agri-PV for different crops based on local conditions. This study presents a novel approach to modeling and simulating Agri-PV systems for various major crops in developing countries, using Uzbekistan as a case study. It provides a blueprint for selecting suitable Agri-PV systems. The research investigates the technical feasibility of Agri-PV technology tailored to Uzbekistan’s agricultural landscape, with broader implications for Central Asia. Employing a systematic methodology, the study begins by selecting appropriate sites and crops for Agri-PV system testing, ensuring the relevance and applicability of the research findings to the local context. Using advanced software tools such as PVSyst, the study accurately calculates photosynthetically active radiation (PAR) values specific to selected crops, bridging a significant knowledge gap and providing empirical data essential for informed decision making. The methodology further incorporates an in-depth analysis of economic and technical considerations in selecting PV modules and inverters, enhancing the scientific accuracy of the study. By strategically modeling Agri-PV systems based on parameters like row density, module distance, and tilt angle, this research aims to optimize the integration of photovoltaic technology with agricultural practices in Uzbekistan. Moreover, this study helps to understand the impact of Agri-PV systems on the water–energy–food nexus, providing valuable insights into the potential benefits and challenges specific to the region. The study identifies the positive impact of Agri-PV on major crops and provides a suitable design and modeling approach for sustainable farming practices.

Sub-Saharan Africa, especially its rural areas, faces significant challenges in achieving universal electrification despite its abundant renewable energy resources. The region has the highest population without access to electricity, largely due to economic, infrastructural, and geographical barriers. Energy poverty is a critical issue that hinders sustainable development and exacerbates inequalities. Namibia’s sustainable energy policy aligns with the global Sustainable Development Goals (SDGs), particularly SDG 7, which aims to provide affordable and reliable modern energy access for all. The policy emphasizes mini-grids and decentralized power systems as key strategies for rural electrification. However, despite increased deployment of mini-grids, these solutions often struggle with long-term sustainability. This research explores cost-effective electrification strategies through scenario-based modeling to reduce energy poverty and expand energy access in Namibia’s rural communities, focusing on the existing mini-grids in Tsumkwe and Gam. Using a comprehensive methodology that incorporates HOMER Pro for mini-grid capacity expansion and MS Excel for evaluating main-grid extensions, this study aims to identify the most feasible and economical electrification solutions. The analysis compares electricity supply, total net present cost, and the levelized cost of electricity across these systems. The findings will offer insights into addressing energy poverty in Namibia and provide recommendations for sustainable and scalable rural electrification across Sub-Saharan Africa.

The urgent pursuit of climate-resilient agriculture and clean energy systems, central to the Energy–Agriculture Nexus and the UN Sustainable Development Goals, has accelerated global interest in agrivoltaic (Agri-PV) technologies. This paper presents a global systematic review and meta-analysis of 160 peer-reviewed studies, structured through a five-stage thematic synthesis: (1) mapping global and regional Agri-PV deployment and potential, (2) analyzing system design and modeling methodologies, (3) evaluating crop suitability under partial shading, (4) reviewing enabling policies and regulatory frameworks, and (5) assessing techno-economic feasibility and investment barriers. Results reveal that Europe and Asia lead Agri-PV development, driven by incentive-based policies and national tenders, while limited regulatory clarity and high capital costs constrain wider adoption. Despite technological progress, no integrated model fully captures the coupled energy, water, and crop dynamics essential for holistic assessment. Strengthening economic valuation, policy coherence, and standardized modeling approaches will be critical to scale Agri-PV systems as a cornerstone of sustainable and climate-resilient land use.

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment.