Backup diesel generator (DG) systems continue to be a heavily polluting and costly solution for institutions with unreliable grid connections. These systems slow economic growth and accelerate climate change. Photovoltaic (PV), energy storage (ES), grid connected, DG – Hybrid Energy Systems (HESs) or, PV-HESs, can alleviate overwhelming costs and harmful emissions incurred from traditional back-up DG systems and improve the reliability of power supply. However, from project conception to end of lifetime, PV-HESs face significant barriers of uncertainty and variable operating conditions. The fit-and-forget solution previously applied to backup DG systems should not be adopted for PV-HESs. To maximize cost and emission reductions, PV-HESs must be adapted to their boundary conditions for example, irradiance, temperature, and demand. These conditions can be defined and monitored using measurement equipment. From this, an opportunity for performance optimization can be established. The method demonstrated in this study is a techno-economic and environmental approach to improving the performance of PV-HESs. The method has been applied to a case study of an existing PV-HES in Kenya. A combination of both analytical and numerical analyses has been conducted. The analytical analysis has been carried out in Microsoft Excel with the intent of being easily repeatable and practical in a business environment. Simulation analysis has been conducted in improved Hybrid Optimization by Genetic Algorithms (iHOGA), which is a commercially available software for simulating HESs. Using six months of measurement data, the method presented identifies performance inefficiencies and explores corrective interventions. The proposed interventions are evaluated, by simulation analyses, using a set of techno-economic and environment key performance indicators, namely: Net Present Cost (NPC), generator runtime, fuel consumption, total system emissions, and renewable fraction. Five corrective interventions are proposed, and predictions indicate that if these are implemented fuel consumption can be reduced by 70 % and battery lifetime can be extended by 28 %, net present cost can be reduced by 30 % and emissions fall by 42 %. This method has only been applied to a single PV-HES; however, the impact this method could have on sub-Saharan Africa as well as similar regions with unreliable grid connections is found to be significant. In the future, in sub-Saharan Africa alone, over $500 million dollars (USD) and 1.7 billion kgCO2 emissions could be saved annually if only 25 % of the fuel savings identified in this study were realized. The method proposed here could be improved with additional measurement data and refined simulation models. Furthermore, this method could potentially be fully automated, which could allow it to be implemented more frequently and at lower cost.