Hybrid renewable energy for agriculture: Review of optimising power dispatch and reliability analysis

Abstract

• A comprehensive analysis of hybrid renewable energy solutions for agriculture. • The study investigates optimal power dispatch and reliability analysis in CHP-PV-wind-grid systems. • Synthesises 45 research papers (2015-2025) using systematic and bibliometric methodologies. • Evaluates optimisation approaches: deterministic, metaheuristic, and AI-based models • Analyses the Monte Carlo, stochastic-robust, and hybrid reliability assessment models. • Highlights gaps in CHP integration, reliability indices, and hybrid storage modelling. • Examines machine learning and metaheuristic methods used in adaptive control systems. • Recommends robust, cost-effective multi-objective frameworks for rural applications. • Outlines potential directions for merging digital twins with reinforcement learning. This paper presents a complete overview of optimal power dispatch algorithms and reliability analysis methods for hybrid energy systems incorporating combined heat and power (CHP), photovoltaic (PV), wind energy and grid connections in agriculture applications. Agriculture presents particular energy issues due to seasonal needs, isolated locations, and varying power requirements. Hybrid systems provide intriguing solutions by combining complementary energy sources, but require advanced techniques for power dispatch and reliability enhancement. This review was carried out using a systematic methodology, with a structured search across the Web of Science Core Collection, Scopus, IEEE Xplore Digital Library, and ScienceDirect databases. The search terms were ‘hybrid renewable energy,” “CHP integration,” or ‘reliability analysis’. Studies were included if they focused on hybrid renewable energy systems involving CHP, photovoltaic, wind or grid integration, addressed optimisation, dispatch, or reliability analysis, and were published between 2015 and 2025 in peer-reviewed journals or conference proceedings. The exclusion criteria excluded simply theoretical works without validation, research not related to agricultural uses, and articles that lacked quantitative assessment. In total, 45 relevant studies were synthesised. Multi-objective optimisation frameworks, advanced reliability evaluation methodologies, technology advances in energy storage and system integration, and economic-environmental sustainability concerns are all critical areas of study. Research gaps are identified, such as a lack of integration of CHP with renewable energy in agricultural contexts, insufficient dependability measurement for critical agricultural activities, and inadequate frameworks for comprehensively resolving economic-environmental-reliability trade-offs. Future research directions will focus on standardised but adaptable system designs, improved integration of thermal and electrical needs, and complete modelling approaches that consider social and regulatory factors. This synthesis contributes to the development of more efficient, reliable, and sustainable agricultural energy solutions.