A Survey of AI-Powered Mini-Grid Solutions for a Sustainable Future in Rural Communities
This paper presents a comprehensive survey of AI-driven mini-grid solutions aimed at enhancing sustainable energy access. It emphasises the potential of mini-grids, which can operate independently or in conjunction with national power grids, to provide reliable and affordable electricity to remote communities. Given the inherent unpredictability of renewable energy sources such as solar and wind, the necessity for accurate energy forecasting and management is discussed, highlighting the role of advanced AI techniques in forecasting energy supply and demand, optimising grid operations, and ensuring sustainable energy distribution. This paper reviews various forecasting models, including statistical methods, machine learning algorithms, and hybrid approaches, evaluating their effectiveness for both short-term and long-term predictions. Additionally, it explores public datasets and tools such as Prophet, NeuralProphet, and N-BEATS for model implementation and validation. The survey concludes with recommendations for future research, addressing challenges in model adaptation and optimisation for real-world applications.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementSurveySimilar Papers 제목 키워드 기반
Smart Grids: A Comprehensive Survey of Challenges, Industry Applications, and Future Trends
With the increased energy demands of the 21st century, there is a clear need for developing a more sustainable method of energy generation, distribution, and transmission. The popularity of Smart Grid continues to grow a…
Artificial intelligence for sustainable wine industry: AI-driven management in viticulture, wine production and enotourism
This study examines the role of Artificial Intelligence (AI) in enhancing sustainability and efficiency within the wine industry. It focuses on AI-driven intelligent management in viticulture, wine production, and enotou…
Recommendation SystemsSmart Grid Architecture with High Proportion of Energy Utilization
DC power generation is an emerging trend and has been preferred due to its low cost and low in system power losses within local distribution grid. The theme of this paper is the indigenous design of a DC standalone micro…
ManagementVocal Bursts Intensity PredictionReinforcement Learning for Sustainable Energy: A Survey
The transition to sustainable energy is a key challenge of our time, requiring modifications in the entire pipeline of energy production, storage, transmission, and consumption. At every stage, new sequential decision-ma…
Decision Makingreinforcement-learningReinforcement LearningSafe Reinforcement Learning+3An Evolutionary Approach for Optimal Citing and Sizing of Micro-Grid in Radial Distribution Systems
This Paper presents the methodology of penetration of Micro-Grids (MG) in the radial distribution system (RDS). The aim of this paper is to minimize a total real power loss that descends the performance of the radial dis…