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

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.